• The TikTok sale is complete. TikTok USDS Joint Venture LLC closed on January 22, 2026, placing majority control in the hands of American investors Oracle, Silver Lake, and MGX. The ad infrastructure and auction mechanics are still running. 
• User deletions spiked nearly 150 percent post-announcement, but active usage held flat. Sentiment and platform health are two different things. 
• Governance shifts hit auction dynamics before they touch the product. Watch CPM and conversion rate week over week, not month over month. 
• Pulling budget reactively during platform transitions destroys learning phase momentum and costs more to rebuild than staying in. 
• Platform governance is now a media planning variable. The TikTok sale set a precedent that extends to every major platform in your media mix.

On January 22, 2026, TikTok USDS Joint Venture LLC officially purchased TikTok’s U.S. operations from ByteDance, transferring control to an American-led investor group anchored by the tech giant, Oracle, and investment groups Silver Lake and MGX.

What does this mean for advertisers on the platform?

The app isn’t shutting down. This is a governance restructuring, and TikTok’s ad products and auction mechanics are still running for its 170 million U.S. users. That said, regulatory shifts like this create real volatility risks that deserve a structured response.

This guide breaks down what did and didn’t change, and how to protect your performance without abandoning one of the most powerful paid channels in your media mix.

What the TikTok U.S. Sale Actually Changes

After the sale, TikTok USDS Joint Venture LLC now owns the U.S. aspects of the platform. ByteDance still owns a 20 percent stake, but the governing majority is now American.

Here’s what that means in practical terms.

What changed

Data governance is the biggest structural shift. U.S. user data is now stored and managed under American oversight, with Oracle handling cloud infrastructure. The new joint venture is also retraining TikTok’s recommendation algorithm on U.S. user data exclusively, to keep the content feed free from outside manipulation. Users won’t notice that change immediately, but it’s significant.

The American-owned entity now sets content moderation. The transition introduced additional compliance review processes for ad targeting parameters and audience segments, requiring some targeting options to be re-approved as the platform rebuilt its ad infrastructure. 

What didn’t change

The TikTok ads infrastructure is intact. TikTok Ads Manager, Smart+, TopView, and In-Feed formats are all still live. At the 2026 NewFronts, TikTok unveiled new ad formats, including Logo Takeovers and Prime Time placements, showing that new ownership isn’t slowing down on advertising anytime soon.

Creator monetization is also unchanged. The TikTok algorithm still powers discovery through the For You Page, so its rules are still critical for anyone trying to make money on the app. Per TikTok CEO Shou Chew’s internal memo, ByteDance’s global entity continues to manage the platform’s e-commerce operations and broader marketing functions on the new U.S. platform.

Early User Signals: Noise or Real Risk?

According to Sensor Tower data shared with CNBC, the daily average of U.S. users deleting TikTok jumped nearly 150 percent in the five days following the joint venture announcement, compared with the previous three months.

A drop that sharp could raise serious concerns for advertisers, but it deserves some context before we decide whether it signals real risk.

Three things fueled the spike, and none of them signal structural collapse:

• A data center power outage caused failed uploads and For You feed irregularities, which TikTok publicly acknowledged.
• An updated privacy policy prompted in-app backlash, though the flagged language was present in an archived August 2024 version of the same policy. 
• Uncertainty around the new ownership’s content moderation approach prompted some creators to hedge their distribution across other platforms.

Competing platforms saw temporary bumps. U.S. downloads for UpScrolled increased more than tenfold, and platforms like Skylight Social and Rednote climbed 919 and 53 percent week over week, respectively.

Monitor trends like these. A sustained shift in creator behavior matters far more to your campaigns than a short-term uninstall spike driven by a data center outage and a misread privacy policy.

The Real Paid Media Variable: Auction Volatility

Here’s what most advertisers miss during a major platform transition: governance changes hit auction dynamics before they touch the product.

TikTok operates on an auction system where costs fluctuate based on competition, targeting choices, and ad quality. Your cost per mille (CPM) isn’t a fixed rate. It moves with how many advertisers are competing for the same audience at any given time, which makes the post-sale period worth watching closely.

Two forces are working in opposite directions right now.

The first is upward CPM pressure from the algorithm retraining cycle. The new joint venture is retraining TikTok’s recommendation algorithm on U.S. user data exclusively. As that process plays out, ad delivery patterns can shift mid-campaign. Campaigns optimized against the previous algorithm’s behavior may see performance move before any creative or targeting change explains it.

The second force is a temporary drop in auction competition. Some marketers were already planning to scale back spending heading into the transition. That window won’t stay open long. As advertiser confidence returns and paused budgets resume, CPM pressure will rise again.

Three things to monitor right now:

• Watch your week-over-week CPM movement. Any sustained spike signals a shift in auction dynamics, not just creative underperformance.
• Monitor conversion rates independently of volume, since algorithm retraining can compress efficiency without changing impression counts.
• Track creative fatigue aggressively. TikTok’s auction dynamics and creative decay rates punish advertisers who let assets run too long without refreshing. 

Why Overreacting Hurts Performance

Pulling budget in response to platform uncertainty feels like risk management, but it’s often the riskiest move you can make in practice.

TikTok’s algorithm depends on a learning phase to optimize ad delivery. During this window, it tests bidding by evaluating your audience and creative to identify who is most likely to convert. Full optimization stability is generally reached around 50 conversions per ad group.  

Any significant change, like pausing campaigns or cutting budgets sharply, pushes an ad group back into the learning phase, resetting the optimization progress already built.

The cost of underfunding is equally concrete. Campaigns that don’t meet effective spending thresholds show CPMs 40 to 60 percent higher than properly funded ones, because the algorithm cannot optimize without sufficient data volume.

The post-sale period sharpens this dynamic considerably. With the algorithm retrained on U.S. data, cost per acquisition may increase 20 to 40 percent before stabilizing. Pausing during this window causes the algorithm to stop learning from your account entirely. Advertisers who read that temporary cost-per-action (CPA) spike as a signal to exit will reset their learning phase mid-cycle, compounding the problem they were trying to solve.

There’s also a competitive angle worth considering. Brands that maintained their presence through the transition period emerged with stronger relative positioning as competitors pulled back. When auction competition drops, CPMs follow. Advertisers who stayed in captured that efficiency. Those who paused paid higher costs to re-enter a recovering auction.

Volatility creates both inefficiency and opportunity. Which one you experience depends on whether you plan for it or react to it.

How to Protect Performance Without Abandoning TikTok

Here’s the operating model to build so you can capitalize on TikTok’s volatility now, or another platform’s in the future.

1. Pre-Approve Budget Flex Scenarios

Making significant budget changes reactively can ruin campaign performance. Deciding your triggers now means you respond with a plan instead of scrambling.

Don’t wait for a performance drop to decide how you’ll respond. Define your thresholds in advance, like a sustained CPM increase of 20 percent or more week-over-week or a conversion rate drop held across two consecutive weeks.

2. Keep Meta and YouTube Shorts Warm

A channel you haven’t run in months is a cold channel. Meta and YouTube Shorts require the same data runway as TikTok to reach full optimization stability, roughly 50 conversion events per ad group. Maintain enough spend on both to keep your audiences warm and your algorithms learning, so you’re never rebuilding from zero.

3. Increase Creative Velocity

On TikTok, creative has a short shelf life. Volatile auctions accelerate that decay further. Volatile auctions accelerate that decay. Have new creative variations ready to deploy before you need them, not after performance has already dropped.

4. Tighten Weekly Reporting Cadence

Temporarily shift from monthly to weekly performance reviews. CPM movement and conversion rate shifts during algorithm retraining happen fast. Catching them early gives you time to adjust bids before small inefficiencies compound.

5. Audit Platform Dependency

You want to ensure you’re spending enough to gain traction, but not so much that one platform can make or break your marketing success. Roughly 13 percent of agencies’ social spend over the past 12 months has gone to TikTok. If TikTok represents more than 30 percent of your paid social budget, you have concentration risk that deserves a contingency plan. 

Zooming Out: Governance Is Now a Media Planning Variable

The TikTok case underscores a growing tension between digital privacy and free speech in the government’s approach to technology platforms. As apps collect vast amounts of user data, governments will likely continue scrutinizing foreign-owned platforms.

 Source: Metricool

That scrutiny isn’t going away, and it won’t stay limited to TikTok. If another foreign-owned platform gains popularity, Congress may revisit this model of ownership-based restrictions. The legal and regulatory architecture built around TikTok is now a template.

Meanwhile, data sovereignty pressures are intensifying globally. Governments worldwide are restricting cross-border transfers and asserting jurisdiction over data within their borders, possibly touching every major platform operating at scale in the U.S. market.

Platform risk is no longer purely a performance question. Ownership structure and data governance now belong in the same due diligence conversation as CPM benchmarks and audience sizing. A channel that delivers strong return on ad spend (ROAS) today can face structural disruption tomorrow for reasons unrelated to its ad product.

FAQs

Conclusion

TikTok remains a Tier 1 paid media channel. The U.S. market accounts for roughly 38 percent of TikTok’s entire global advertising income, a concentration that reflects genuine advertiser confidence. That doesn’t change because of a governance restructuring.

What does change is how you should think about it. Tier 1 status doesn’t mean risk-free. The TikTok sale established a precedent for how governments can intervene in platform ownership, and that precedent applies beyond TikTok. Every major platform you rely on now carries some version of this risk.

The smart move is better planning.

Stay active on TikTok while the auction competition is still recovering. Build a paid media strategy that lets you flex budgets quickly when conditions shift. Define your thresholds now so you don’t make reactive decisions under pressure, and keep your creative velocity high. Short-form content gives you a low-cost way to keep creative cycling regardless of what’s happening at the platform level.

The platforms that attract 170 million users don’t disappear overnight. Build your strategy around that reality.

• LinkedIn articles are long-form content published natively on LinkedIn. They live on your profile, get indexed by Google, and surface in LinkedIn search results long after you publish them.
• Feed posts drive reach. Articles build the kind of credibility that makes someone want to hire you, work with you, or trust your expertise.
• The strongest use case for articles is distribution, not creation. Adapt existing content rather than starting from scratch.
• Performance starts with the headline. Specific, opinionated titles outperform vague ones every time.
• Articles are increasingly picked up by AI-generated search answers, making them a quiet but growing visibility channel outside LinkedIn itself.

Most brands still treat LinkedIn like a feed-first platform. Post a thought, collect some likes, move on. That works well enough for reach. It does almost nothing for credibility.

The shift worth paying attention to is not about posting frequency. LinkedIn now surfaces content through search and AI-generated answers that reach well beyond your first-degree connections. The professionals and brands showing up in those spaces are not the ones with the most followers. They are the ones publishing LinkedIn articles.

LinkedIn articles are one of the most underused assets in organic LinkedIn marketing right now. I’ll cover what makes them different from feed posts, how to use them as a distribution channel, and how to write them in a way that actually gets read.

LinkedIn Articles Aren’t New, But Their Role Has Changed

LinkedIn launched its publishing platform more than a decade ago under the name Pulse. Most marketers filed it under “things we should probably use” and forgot about it. The format has since been rebranded simply as LinkedIn Articles, and the ones paying attention to what it has become now have a real head start.

What changed is how LinkedIn itself handles content discovery. The platform acts more like a search engine than it used to. Older articles get resurfaced to relevant audiences. Search queries on LinkedIn increasingly pull from published articles, not just profiles. And because LinkedIn articles are public and hosted on a high-authority domain, Google indexes them. A well-written piece can appear in organic search results for months after publication, reaching people who have never heard of your brand.

Most marketers make one of two mistakes here. They either ignore articles entirely, or they copy-paste from their company blog and treat it as done. Neither approach takes advantage of what the format uniquely offers. It is worth noting that articles are available to both individual profiles and company LinkedIn pages, which means the opportunity exists at every level of your presence on the platform.

The deeper issue is that articles require a different strategic mindset than feed content. They are not built for the scroll. Discoverability on LinkedIn works differently than most marketers assume, and that distinction is worth understanding before you publish your first piece.

Why Articles Play a Different Role Than Feed Posts

Feed posts are built for speed. A sharp observation, a quick take. They generate engagement quickly and lose most of it within 48 hours. That is not a flaw, just the format doing what it was designed to do.

Articles operate differently. They are not competing for attention in a scroll. A reader who finds your article through LinkedIn search or a Google result is already in a different mode. They are not skimming a feed but are likely looking for something specific, and are willing to spend time with it.

That behavioral difference is what makes articles valuable for credibility in a way feed posts aren’t. Publishing a well-structured argument on a topic you have real expertise in signals something that likes and comments cannot. It shows you can develop an idea past a single take. The people making decisions about who to hire or work with notice that and they are very much not counting your impressions.

There is also a practical career and business case that rarely gets discussed. The people who evaluate you before a hiring decision or a pitch are not reading your feed. They are searching your name. A LinkedIn profile with published articles on relevant topics sends a different signal than one without. It is the difference between someone who has opinions and someone who has a body of work.

The Real Opportunity: Articles as a Distribution Channel

The framing that kills most LinkedIn article strategies is boiling it down to: “We need to create more content.” More is not the problem. Distribution is.

Most marketing teams are already producing content that never reaches its full potential audience. Blog posts with strong insights get two weeks of traffic and fade. Bylined pieces in trade publications get shared once, then disappear. Presentations from industry events are often never seen again outside the room where they were given.

LinkedIn articles give that content a second life. Take a blog post, extract its central argument, and adapt it for LinkedIn’s format and audience. The original piece stays on your site. The article links back to it and drives qualified traffic from readers who found the piece through LinkedIn search or Google. This extends the shelf life of work you already did without doubling the workload.

The same logic applies at the individual level. An executive’s byline in an industry publication reaches that outlet’s audience once. The same argument published as a LinkedIn article reaches their network, their followers, and anyone searching that topic on the platform for months afterward.

This is the reframe that makes articles sustainable: they are a distribution layer, not a content creation obligation. If your team treats every article as a net-new piece, it will always feel like too much. If they treat it as an adaptation of something that already exists, the lift is manageable and the compounding visibility adds up over time.

How to Write LinkedIn Articles That Actually Perform

Performance starts before the first sentence. Your LinkedIn headline is the only thing most readers will see before deciding whether to click. Vague titles get scrolled past while specific, opinionated ones get clicked. “Thoughts on the Future of B2B Marketing” is invisible. “Why Most B2B Content Strategies Stall at the Awareness Stage” signals a real argument and a reason to keep reading.

Once someone is in, lead with the insight. Most articles lose readers in the first two paragraphs because the writer is still warming up, providing background, explaining what they are about to say. Skip that. Start with the argument. The context can come later (if it is needed at all) structure matters more on LinkedIn than on a traditional blog also, since readers on the platform skim before they commit. Short paragraphs and clear transitions help them orient quickly. The occasional subheading does not hurt either. A reader who skims and grasps the structure is far more likely to slow down and read closely than one who hits a wall of text and bounces.

Tone is the variable most writers underestimate. LinkedIn articles perform better when they sound like a person who has a real position, not a brand running a content calendar. Opinionated works. Specific works better. “Here is what we have seen hold up across dozens of campaigns” lands differently than “Here is what the research suggests.” Readers can tell the difference between lived experience and summarized consensus and respond accordingly.

One practical tip: write the headline last. Draft the piece, find the sharpest sentence in the whole thing, and ask whether it belongs at the top of the article or in the headline. The answer is usually both.

Close with a soft call to action. The article should be valuable on its own, but it can still point somewhere. A forward-looking question to spark discussion, a brief observation that invites a reply, or a link to a related resource all work. Hard sells do not belong here. The goal is to earn the next click, not demand it.

One step most people skip: after publishing, go into the Manage tab and set a custom title and description for your article. These fields are what search engines use in place of your on-page headline, so taking two minutes to optimize them for a target keyword meaningfully improves how the piece gets found off-platform.

Where LinkedIn Articles Fit in a Modern Content Strategy

Most content strategies have a gap between awareness and action. Social content gets attention. Your website converts it. What sits in between is often nothing, and that gap is where brands lose the consideration battle to whoever showed up with more substance.

LinkedIn articles fill that gap. They are where a reader who already knows you exist decides whether your thinking is worth trusting. That is a different job than a feed post or a homepage. It is the consideration stage, and most brands leave it completely unaddressed.

Think about how buying decisions actually get made in B2B. Someone sees a post, looks up the author, skims the profile, and then either moves on or goes deeper. Articles are what “going deeper” looks like. A series of well-argued pieces on a specific topic does more to establish authority than any amount of engagement metrics on short-form content. It is proof of thought, not just presence.

Your owned content still handles the conversion. An article should not be trying to close a deal. It should be building enough confidence that a reader wants to take the next step on their own.

The brands doing this well rarely talk about it as a content strategy. They talk about it as a sales and trust-building motion. That reframe is worth borrowing.

The Missed Opportunity: LinkedIn Articles and AI/Search Visibility

Here is something most LinkedIn content guides do not mention: your articles can show up in Google before your company website does.

LinkedIn’s domain authority is among the highest on the internet. When you publish an article there, you are borrowing that authority. A well-structured piece on a specific professional topic can surface in Google organic results, featured snippets, and AI Overviews faster than a comparable post on a newer company blog that is still building its own search presence.

 For brands that are early in their SEO journey, that is a meaningful shortcut. And the opportunity is only growing: LinkedIn is now the second most cited source in AI-generated answers, trailing only Reddit.

Source: Semrush

Most marketers measure LinkedIn articles by what happens on LinkedIn. Reach and engagement matter, but they miss the larger picture. A piece that generates modest engagement on the platform can quietly pull in search traffic for months. The people finding it that way were never in your feed. They were looking for an answer, and your article was there.

AI-generated answers tend to pull from sources that are credible and publicly accessible. LinkedIn articles are both. If you are not publishing them, you are not in that conversation at all.

FAQs

Conclusion

LinkedIn articles are not a volume play. The teams getting real results from them are not publishing more often. They are being more deliberate, using articles to deepen ideas that already have an audience and extend content that is already doing work elsewhere.

The format rewards a genuine point of view backed by specific experience. If you have content worth publishing, you have content worth adapting. Start with one strong piece, sharpen the argument for a LinkedIn audience, and publish it with a headline that earns the click. The discoverability of that article, both on and off the platform, will depend on how well you understand LinkedIn SEO, so that is worth getting right from the start.

• SEO fundamentals don’t require a lot of technical expertise. Even beginners can get results by starting with keyword research, then building content quality and site structure around what they find. 
• Strong SEO and AI visibility are built on the same principles. Authoritative content and a clear site structure help you rank in traditional search and get cited in AI-generated answers. 
• User experience directly affects SEO. Page speed, mobile optimization, and easy navigation are confirmed Google ranking factors.
• Links from high-authority sites signal trust to search engines and AI systems alike. Quality always beats quantity when building your backlink profile. 

Search engine optimization (SEO) remains one of the most reliable ways to drive consistent, targeted traffic to your site. 

That hasn’t changed. 

What has changed, though, is the environment in which it operates.

The difference now is that strong SEO doesn’t just help you rank on Google. It positions your content to be cited by the AI systems that increasingly shape what users see first.

This guide covers the SEO basics you need to build a foundation that holds up in both traditional and AI-driven search. If you’re new to SEO or tightening up an existing strategy, this is the right place to start.

SEO stands for search engine optimization. It’s how you get your website to show up when people search for what you offer. 

More specifically, it’s the process of improving your site’s performance, authority, and structure to rank higher in search engine results pages (SERPs), including the AI Overviews (AIOs) that now sit at the top of many results pages.

Google gets more than 80 billion visits every month. That’s a lot of potential customers, but modern digital marketers have to consider more than Google alone.

Social SEO’s potential to reach new customers is off the charts, too. Nearly half of consumers use TikTok as a search engine, and more and more people (Gen Zers, in particular) use social platforms like YouTube and Instagram to find content that answers their questions.

Visibility on those platforms (and in AI systems) follows many of the same principles of traditional SEO: authoritative content, clear structure, and direct relevance to what people are actually asking. 

The same is true for AI systems. Well-structured, credible content is what earns citations in AI Overviews and social search alike.

Why Is SEO Important?

AI taking up more SERP real estate doesn’t change the fundamentals of your marketing strategy. 

The best way to reach and convert your target audience is to focus on the keywords they’re most likely to search for and the intent behind those searches. Those fundamentals hold true across both traditional blue links and AI-generated answers citing your content.

According to seoClarity’s analysis of 432,000 keywords, 97 percent of AI Overviews cite at least one source from the top 20 organic results, proving ranking well is a reliable path to AI visibility. 

If that tells us anything, it’s that ranking well in traditional search and earning visibility in AI-generated answers are built on the same foundation. 

That foundation is helpful content built around Google’s experience, expertise, authoritativeness, and trust (E-E-A-T) framework. It applies just as directly to AI visibility as it does to traditional rankings.

The businesses writing off SEO as dead are the ones that will fall behind. 

How AI SEO Works

AI SEO shares the same foundation as traditional SEO, but they serve different purposes. 

Traditional SEO earns you visibility in organic SERP links. AI SEO earns you citations inside the AI-generated answers that now sit above them. 

Here’s how the two compare at a high level:

Strong SEO basics build the infrastructure that AI systems draw on when deciding what to cite. 

Nail the basics, and you’re not just competing for blue links. You’re competing for the answer, too.

Setting Yourself Up for SEO Success

Before getting into the SEO basics, make sure you have the right foundations in place.

Your domain name matters more than people think. Something straightforward and related to your business will perform better in search. A .com extension is the gold standard, but .net and .co are solid alternatives.

Your hosting platform is equally important. Choose one that prioritizes security and facilitates fast page loading. Page speed is a confirmed Google ranking factor, and a slow site hurts both your rankings and your users.

A logical site structure helps search engines find and index your pages. It also helps visitors quickly and intuitively navigate to whatever they’re looking for.

You’ll notice Kim’s Restaurant (above) as an example. 

The homepage branches into four main category pages: Menu, Locations, Catering, and About. Only one of those categories (Locations) goes a level deeper, with a dedicated page for each neighborhood. Every page has a clear parent, and the structure mirrors how a real user would navigate the site.

None of this needs to be perfect on day one. Jonathan Hoffer, SEO Manager at NP Digital, puts it well: 

“Often, when starting an SEO program, perfection is the enemy of starting. Zeroing in on your audience and what they’re searching for can help. The path to the top of the SERPs begins with a single article being published.”

Common SEO Myths

Before going further, it’s worth clearing up a few common SEO misconceptions that tend to trip people up:

• SEO produces instant results. It doesn’t. Most strategies take three to six months before you see meaningful movement in rankings.
• More keywords mean better rankings. Keyword stuffing actually hurts your rankings. Google rewards relevance and context, not repetition.
• You only need to do SEO once. Search is a moving target. Algorithms are always being updated, and competitors are constantly adapting their strategies.
• AI has made SEO obsolete. As we covered above, strong SEO is still the most reliable path to both organic and AI visibility.

SEO Subtypes

SEO breaks down into several subtypes. Depending on your target audience and your goals, certain types of SEO will matter more than others. Here’s a quick breakdown:

• On-page SEO optimizes the content and HTML elements on individual pages, including keywords, title tags, meta descriptions, and headings. These are foundational elements in ranking for the right queries.
• Off-page SEO builds your site’s authority through external signals, primarily backlinks from credible websites. More trust from other sites means more trust from search engines. 
• Technical SEO optimizes your site’s infrastructure so search engines can crawl and index your content correctly. This covers site speed, mobile-friendliness, HTTPS, and structured data.
• Local SEO improves your visibility in location-based searches. It’s critical for brick-and-mortar businesses and service providers targeting customers in specific areas.
• International SEO optimizes for audiences in different countries and languages. It’s particularly relevant for brands looking to grow beyond their domestic market.
• Social SEO optimizes your presence on social platforms like TikTok and YouTube, which increasingly function as search engines in their own right.

SEO, GEO, and LLMO

AI-powered search tools like ChatGPT and Google’s AI Mode have sparked the creation of two more SEO subtypes: generative engine optimization (GEO) and large language model optimization (LLMO). 

GEO focuses on structuring your content so generative AI systems pull from it when composing answers. 

LLMO goes a step further, optimizing your brand’s presence across the large language models that power those systems.

The underlying principles closely mirror conventional SEO. Traditional ranking signals like strong E-E-A-T and clean site structure carry weight in GEO and LLMO, just as they do in traditional search. 

SEO Basics #1: Keyword Research

Keyword research is the process of identifying the specific words and phrases people use when looking for information on search engines.

For example, a vegan restaurant could use keywords like “vegan restaurant near me” and “best vegan burgers” in its website copy and blog posts to help it rank on the first page of Google. 

Good keyword research can reveal:

• How many people are searching for a specific keyword or phrase.
• The search intent behind those queries. Are people looking for information, or are they ready to buy?
• How relevant a keyword is for your target audience and content.
• How competitive a keyword is based on what other sites are ranking for it.
• Long-tail keywords that surface your audience’s pain points and suggest content topics.

Start by brainstorming relevant topics for your business, then run them through a keyword research tool like Ubersuggest or Semrush. Use what you find to shape your content strategy. 

Here’s a look at the keyword opportunities our friends at the vegan burger restaurant might have:

Source: https://app.neilpatel.com/en/ubersuggest/keyword_ideas/

Also, remember that search results are always changing. Be sure to revisit your strategy regularly as algorithms and competitors evolve.

Quick Tips for Keyword Research

• Brainstorm seed keywords. Start with basic terms relevant to your business and industry, and use those as the foundation for deeper research. 
• Understand your audience. Identify the exact words and phrases potential customers type when searching for your product or service. 
• Target long-tail keywords. More specific phrases people use when they’re closer to a buying decision tend to have less competition and higher conversion rates. 
• Analyze competitor keywords. Look at what your competitors rank for to find gaps and opportunities worth targeting. 
• Explore related keywords. Identifying terms closely related to your primary keywords helps you avoid keyword cannibalization. 
• Consider search intent. There are four types: informational (question-based queries), navigational (website- or webpage-specific queries), transactional (product or service queries), and commercial (research-based queries featuring words like “best” or “review”).

SEO Basics #2: Create Effective, Optimized Content

Good content is fundamental to SEO.

Useful content, from articles and infographics to videos and e-books, earns links from other websites. Prospective customers will also see you as a reliable, credible source of information.

Here’s what my colleague Matthew Santos, Chief Product Officer at NP Accel, has to say about content marketing:

“Over the past 20 years, we have seen so many new features come out from Google that have caused SEOs to adopt new tactics, but one constant we have never seen Google move away from is the importance of high-quality content. As we have continued to double down on high-quality content, we have seen thousands of customers over the last five years survive every single one of the major core algorithm updates.”

Regularly creating informative, relevant, and optimized content is one of the primary ways to grow your organic presence. It’s not a guarantee, but it stacks the deck in your favor alongside other SEO best practices.

Add your keywords where they feel natural and relevant. Stuffing keywords into your copy can make it unreadable and much less effective, causing your pages to drop in the rankings.

It also helps to add a key takeaways section at the top and an FAQ section at the bottom of your blogs. Both improve readability for human visitors and make your content significantly easier for LLMs to parse and cite. 

Here’s what each looks like in practice:

Source: https://neilpatel.com/blog/keyword-cannibalization/

Quick Tips for Content Creation

• Brainstorm content ideas based on audience needs. Use your target keywords to generate topics. A plumbing business targeting “how do I fix a sink” could turn that into an article explaining why hiring a professional is better than DIY. 
• Write clearly and concisely. Provide helpful information and cut the fluff. Use headings, bullet points, and formatting to improve readability and make content skimmable. 
• Implement E-E-A-T. Write well-researched and accurate content supported by expert quotes. Cite your sources, and build author bio pages that showcase each contributor’s credentials, demonstrating their status as subject-matter experts (SMEs). 
• Incorporate relevant keywords. Include your target keywords to optimize content for SEO, but always prioritize natural, readable prose over keyword density. 
• Use proprietary data. First-party statistics and unique insights give AI systems and readers something they can’t find anywhere else. 
• Try different content formats. Different formats serve different purposes. Infographics, for example, work well for data and case studies build authority, while blog posts drive ongoing organic traffic.
• Repurpose and refresh old content. Repurposing your old content is one of the best ways to get the most value from it. For example, long-form content could be compiled into an e-book or published as a newsletter series. Updating dated references, stats, and facts keeps older posts relevant and valuable over time.

SEO Basics #3: Optimize Your Title Tags and Meta Descriptions

Title tags and meta descriptions tell search engines what your site is about, helping them match your pages to the right search queries.

Optimizing them drives more traffic to your site and gives searchers a clearer picture of what you offer. They also directly influence your click-through rate, the percentage of users who see your listing in a SERP and decide to click it.

Title tags signal to visitors what they can expect to read. They should spark curiosity and encourage your audience to go deeper into your content.

Think of meta descriptions as a quick sales pitch. They’re your chance to attract and engage your audience right from the search results page, before they ever reach your site.

Urtopia’s meta description above tells e-bike shoppers exactly what they’ll find before they click. It provides a clear signal that pulls in the right audience and filters out the wrong one.

Quick Tips for Crafting Title Tags and Meta Descriptions

• Include relevant keywords. Keywords in title tags and meta descriptions boost your content’s visibility in search results, just as they do in body copy. 
• Place keywords close to the beginning. Search engines prioritize the most relevant content. Front-loading your keywords sends a clear signal about what the page covers. 
• Keep them focused and concise. Aim for 150–160 characters in a meta description that conveys the main benefit or unique selling proposition. 
• Use action-oriented language. Words like “now” and “today” create urgency, while action verbs like “discover” and “learn” can draw readers in. 
• Test variations. Try different keywords and sentence constructions to see which drives the highest click-through rates.

SEO Basics #4: Focus on User Experience (UX)

User experience (UX) refers to how easily people can use your website and find what they need. It’s one of the most overlooked areas of basic SEO for a website, as it’s consequential for rankings.

A user comes to your site to find a product or information. Your design and visuals can add real value, but they can’t compensate for a slow, confusing, or inaccessible site. 

Google knows this. 

Page speed and mobile-friendliness are confirmed ranking factors, and ease of navigation sends strong signals about usability, too. A site that frustrates users sends negative signals to search engines, while one that keeps visitors engaged sends positive ones.

According to Google, 53 percent of mobile users will abandon a site that takes longer than three seconds to load, confirming that mobile-friendliness and page speed are non-negotiable UX factors.

A positive user experience keeps visitors on your site longer and encourages them to explore multiple pages. Engaged visitors are also more likely to sign up for a newsletter or download a resource, leaving behind the engagement signals that tell search engines your site is useful.

Quick Tips for Improving UX

• Increase site speed. Page speed is one of the most important ranking factors. Compressing images and removing unused plugins or third-party widgets can meaningfully improve load times.
• Simplify navigation. Your main menu should be logical and easy to understand. Use submenus or drop-down menus to organize additional pages rather than overwhelming visitors with too many options at once. 
• Reduce clutter. Too many ads and pop-ups are distracting, particularly on mobile devices. 
• Provide clear calls to action. Don’t make visitors hunt for a way to schedule an appointment or view a demo. Most won’t stick around long enough to find it. 
• Make your website accessible. An accessible website means everyone can use it and keeps you compliant with the Americans with Disabilities Act (ADA).

SEO Basics #5: Prioritize Mobile Experience

Mobile devices now account for more than 62 percent of global website traffic, and that number keeps climbing. Catering to mobile users is a must if you want your content to rank.

Google uses a mobile-first approach to indexing, meaning it crawls the mobile version of your website to understand and rank your pages.

A mobile-responsive website is essential. That means designing and coding your site so it automatically adjusts based on the device being used.

One of the best ways to test your mobile performance is Google’s Lighthouse tool for Chrome. It generates a detailed report like the one below, and tells you exactly what to fix.

Quick Tips for Improving Mobile Experience

• Design for touch interaction. Larger buttons and clickable elements make it significantly easier to navigate on a small screen. 
• Keep content concise and scannable. Users reading on phones move fast. Short paragraphs, clear headings, and bullet points help them find what they need quickly. 
• Streamline forms and checkout processes. Minimize the number of fields and make error messages clear and easy to see on a small screen. 
• Optimize images for mobile. Large, uncompressed images are among the most common culprits of slow mobile load times. Compress them and use responsive image sizing. 
• Test across devices. Your site may look fine on one phone and break on another. Regular cross-device testing catches issues before your users do.

SEO Basics #6: Build Links

Backlinks from high-authority, relevant sites send a trust signal to Google. It’s like having somebody vouch for you. The more credible sites that link to yours, the more likely you are to rank well in the SERPs.

For example, here’s the Ubersuggest backlinks report for my own site. I’ve got a strong spread of backlinks across a range of sites, which signals to search engines that my website is a reliable and trustworthy source of information.

Source: https://app.neilpatel.com/en/seo_analyzer/backlinks?domain=neilpatel.com&lang=en&locId=2840&mode=domain

AI systems like Google’s AI Overviews and ChatGPT increasingly favor sources with strong third-party credibility. Brand mentions and citations across the web all signal that your content is worth referencing. 

Quick Tips for Building Links

• Create valuable, educational resources. Original research, comprehensive guides, and data-driven content are the types of assets other sites naturally want to reference and link to. 
• Fix broken links. Use tools like Ubersuggest’s Site Audit feature to identify broken links on high-authority sites in your niche, then reach out and offer your content as a replacement. 
• Pursue media requests. Platforms like Connectively (formerly HARO) connect you with journalists looking for expert sources. A single mention in a major publication can earn a high-authority backlink and boost your AI visibility at the same time. 
• Run a competitive analysis. Identify which sites are linking to your competitors but not to you. Those are warm prospects. If your content is stronger, you have a compelling reason to reach out.

SEO Basics #7: Don’t Neglect Technical SEO

Good content won’t perform if your site has technical issues preventing search engines from finding and understanding it. 

Technical SEO is the foundation that makes everything else work.

Without it, even your best content may never get indexed or ranked. Addressing the technical side of your site makes sure search engines can interpret your content and serve it to the right audience.

Tips for Improving Technical SEO

• Optimize your site structure. Create a logical, hierarchical structure for your website. This helps both users and search engines navigate easily. 
• Improve site speed. Use tools like Google PageSpeed Insights to identify and fix issues slowing your site down. Compressing images and leveraging browser caching are good starting points. 
• Implement SSL. Secure your site with HTTPS. It protects user data and is a confirmed Google ranking factor. 
• Create and submit a sitemap. Generate an XML sitemap and submit it through Google Search Console. This helps search engines discover and index your pages more efficiently. 
• Fix broken links. Regularly check for and repair broken links. Tools like Ubersuggest or Screaming Frog can help identify them quickly. 
• Manage duplicate content. Use canonical tags to indicate the preferred version of a page when similar content exists across multiple URLs. 
• Optimize your robots.txt file. Make sure to configure your robots.txt file correctly to guide crawlers on which parts of your site to index and which to ignore. 
• Monitor crawl errors. Check Google Search Console regularly for crawl errors and address them promptly to keep your important pages indexed.

SEO Basics #8: Measure Your Results

Monitoring your SEO strategy’s performance over time lets you make data-driven decisions to improve it and boost your rankings.

Analyzing SEO metrics helps you spot opportunities to replicate high-performing content and catch technical issues that drag your content down. 

It also helps you adjust your strategy to ensure you’re producing relevant, keyword-optimized content that targets the right audience. That’s what leads to higher organic traffic and better business outcomes that demonstrate SEO’s value to stakeholders.

With the rise of AI visibility, measurement now goes beyond rankings and clicks. So, you’ll need to monitor your presence in AI systems, too.

Tools like Semrush’s AI Visibility Toolkit and Otterly.ai let you track how often your brand is cited across AI-generated answers on platforms like ChatGPT and Google AI Overviews. 

Source: https://www.tryprofound.com/blog/semrush-ai-visibility-toolkit-review

As AI search continues to grow, brands that measure both traditional SEO performance and AIO or GEO results will have a clearer picture of where they actually stand in search.

Quick Tips for Measuring Results

• Define clear key performance indicators (KPIs). Choose the KPIs most relevant to your business that you can act on and improve, including traditional metrics like rankings and CTR, as well as AI visibility signals like citation frequency and share of voice. 
• Use analytics tools. Good tools to get started include Google Analytics, Google Search Console, and Ubersuggest for traditional SEO. For tracking AI visibility, platforms like Ahrefs Brand Radar and Semrush’s AI Visibility Toolkit are helpful. 
• Create a regular tracking cadence. Consistent monitoring helps you identify performance changes and uncover new optimization opportunities. 
• Benchmark your performance. Compare your results against industry standards and competitors to understand where you stand in both traditional search and AI-generated results. 
• Conduct A/B testing. Test different content variations, keyword approaches, and structural changes to see what performs best across both search and AI platforms. 
• Act on your results. Tracking your KPIs only matters if you take steps to resolve issues and build on what’s working.

FAQs

Conclusion

Modern-day digital marketing is often like trying to fire an arrow at a moving target. Learning the SEO basics makes it much easier to hit the mark, and there’s a lot you can do to boost your rankings, even with limited technical skills.

Start by reviewing your existing content. What can you do to add value to your pages and make it easier for visitors to find what they need? 

In today’s SERPs, hitting the mark means more than ranking on page one. It also means producing authoritative, well-structured content that also earns visibility in AI-generated answers.

Think of your audience and the search engines when working on your site. 
As your strategy matures, explore advanced SEO techniques and study the latest search engine trends to stay ahead of the curve.

• Backlinks are links from other websites to yours, and they still matter because they help search engines evaluate how authoritative and trustworthy your site is. 

• Not all backlinks are equal. A few relevant, high-quality links from authoritative sites are usually more valuable than many weak or spammy ones. 

• Backlinks support AI visibility because generative engines and language models favor content from authoritative, trustworthy sources, and backlinks are one of the clearest signals of that authority. 

• Tracking backlinks means monitoring quality and growth. Pay attention to referring domains, anchor text distribution, and link stability over time. 

• The best way to build backlinks is to earn them through useful content and targeted outreach. You will need to keep refining your approach based on what works. 

AI is reshaping search, but one traditional SEO practice has held its ground: backlinks.

A backlink in SEO is a link from another website that points to yours. These mentions across different websites help search engines understand how you fit into the overall picture of your industry, and sites that reference you repeatedly signal authority and trust to Google. That authority also carries weight in AI-driven search experiences, where AI platforms favor content from sources they consider trustworthy.

Backlinks still matter, and the case for them has only grown stronger as AI reshapes how search works.

So, What Exactly Are Backlinks?

A backlink forms when another site links to your page, signaling to search engines that your content is worth referencing. You may also hear them called inbound links or incoming links.

The screenshot below shows what a backlink looks like in practice, with one site linking directly to another as a reference.

Source: https://plausible.io/blog/backlinks-seo-guide

Nikki Brandemarte, Senior SEO Strategist and Local SEO Team Lead at NP Digital, explains it well: “Getting backlinks from reputable sources can demonstrate to Google that you have expertise on the topics you cover. I like to think of quality backlinks as a ‘vote of confidence’ that you know what you’re talking about.” 

Backlinks help search engines understand which pages other websites find useful and authoritative enough to mention. That same authority can also support visibility in AI search experiences, even if backlinks are not the main ranking factor there.

I’ll go into what makes a “good” and “bad” backlink later in this article. For now, the key thing to know is that backlinks are one of the clearest ways authority gets passed around the web.

Backlink Examples/Types

Dofollow backlinks are the standard links most site owners want. They allow search engine bots to crawl and index your site, passing authority signals that typically have the biggest SEO impact. These are the links worth prioritizing in your outreach and content efforts.

Dofollow HTML example: <a href=”https://example.com/”>anchor text</a>

Nofollow backlinks work differently. They carry a special HTML attribute that tells search engines not to pass authority, but they still drive referral traffic and keep your link profile looking natural. You’ll commonly find them on social media, forums, and sponsored content. Since 2019, Google has treated nofollow links as hints rather than strict directives, meaning some may still carry indirect value.

Nofollow HTML example: <a href=”https://example.com/” rel=”nofollow”>anchor text</a>

A healthy backlink profile includes both. Pursuing only dofollow links can signal to search engines that your links are artificially built rather than earned, which can work against you.

Why Are Backlinks Important For SEO?

Even as search has changed, backlinks still help search engines understand when other websites see your content as worth referencing. Authority and trust still influence rankings, especially for competitive topics.

Backlinks serve as a seal of approval from one site to another. They strengthen your site’s credibility and make it easier for search engines to surface your content in results. They’re also critical for driving targeted, quality traffic to your site. When someone clicks through from a relevant site, they arrive already interested in what you offer.

Backlinks also play a bigger role in the broader visibility ecosystem around search. Strong mentions and links earned through strategies like digital PR can support your presence across traditional and AI search.

Backlinks require ongoing attention, though. They aren’t “set it and forget it” things. A strong backlink profile is built over time and needs regular review. It’s an investment in your site’s long-term success and one of the clearest ways to build durable SEO authority.

Source: https://neilpatel.com/blog/free-backlink-tool/

Why Quality Backlinks Matter

Quality beats quantity when it comes to backlinks. 

A single backlink from a high-authority, relevant site can do more for your SEO than dozens of low-quality links. High-quality backlinks strengthen your site’s authority and can push your rankings higher in search results.

Going after links without caring about their quality is a recipe for trouble. It’s like inviting a bunch of strangers to your party without checking if they vibe with your crowd. This approach can tarnish your site’s reputation and lower its ranking.

High-quality backlinks share a few common traits:

• Relevancy: A link from a site in a related or complementary field helps Google see your link as more valuable.
• Domain or page authority: When authoritative sites link to yours, Google assumes your site is more trustworthy as well.
• Dofollow links: These pass authority signals to your site and are worth prioritizing in your outreach efforts. That said, a healthy backlink profile includes nofollow links too, since an all-dofollow profile can signal to search engines that you built your links artificially.
• Anchor text: Relevant anchor text can provide an even bigger potential boost to rankings.

What counts as a quality backlink can also vary by industry and competition level. In more competitive spaces, you may need stronger, more relevant links to stand out. That’s especially true for ecommerce link building, where product and category pages aren’t naturally linkable and quality links are harder to earn.

Low-quality backlinks typically come from sites unrelated to your niche, sites with questionable content, or known spam sources. Paying for links or accepting them indiscriminately puts your SEO at risk, regardless of how tempting a shortcut it may seem. 

Are Backlinks Important For AI?

Backlinks are still important in AI-driven search, though not as a direct ranking factor. Google has confirmed that the same core SEO guidance applies to AI features like AI Overviews and AI Mode, and backlinks are part of that foundation.

Backlinks support visibility across generative engine optimization (GEO), large language model optimization (LLMO), and answer engine optimization (AEO), the three major AI optimization frameworks shaping modern search. In GEO, which focuses on getting your content cited in generative summaries, backlinks signal the depth and authority generative engines favor. In LLMO, which shapes how language models understand and reference your brand, backlinks reinforce the consistent authority signals models rely on. Even AEO, which targets direct answer boxes and featured snippets, stronger backlink profiles help pages earn those placements more easily.

AI platforms tend to surface content from sites they consider authoritative. Semrush analyzed 1,000 unique domains and found a strong positive relationship between authority score, which reflects backlink quality, and how often a domain appears in AI-generated answers. The Pearson correlation of 0.65 and Spearman correlation of 0.57 from the study indicate a strong relationship, meaning sites with stronger backlink profiles show up in AI search results more consistently.

Publishing crawlable, useful content remains the priority, but backlinks across reputable sites reinforce that you are a trusted source worth surfacing.

Microsoft’s guidance on AI search visibility reinforces the same point, noting that traditional SEO fundamentals, including crawlability, backlinks, and content authority, remain central to whether content gets surfaced in AI-generated answers.

The chart below shows how different backlink metrics correlate with AI visibility across 1,000 unique domains. Authority Score, which reflects overall link quality, shows the strongest relationship by a significant margin.

Source: https://www.semrush.com/blog/backlinks-ai-search-study/

For AI search, backlinks are one signal among many, but they remain a meaningful one.

How to Track Your Backlinks

Tracking your backlinks is just as important as building them. Backlink analysis tools show you which sites link to yours and help you catch problems before they affect your rankings.

A backlink analysis tool like my free backlink checker lets you:

• Examine the quality of your backlinks.
• Spot any links that could be dragging your rankings down, such as links from spammy or irrelevant sites.
• Identify opportunities for higher-quality or more links.

You also want to understand which sites are linking to you, whether those sites are relevant to your niche, what anchor text they’re using, and whether your referring domains are growing over time. My backlink checker surfaces all of this in one place, giving you a clearer picture of whether your backlink profile is getting stronger or just getting bigger.

The tool also makes competitive analysis straightforward. Enter a competitor’s URL and you can see everyone linking to them but not to you, turning that gap into a list of actionable link-building opportunities. Advanced filtering lets you narrow results by region, anchor text, domain score, page score, and URL, and you can choose to view only dofollow or nofollow links. Once you’ve refined your results, you can export them to CSV for further analysis.

As you get more backlinks, monitoring them manually takes too much time and effort. The right backlink analysis tools make maintaining them much easier and help you make smarter link-building decisions and catch problems early.

Backlink Building Best Practices

You’re ready to start building backlinks, but you can’t just fire off pitches to every publisher with a major name. Here’s what Kimberly Deese, Director of Digital PR at NP Digital, has to say about it:

“Two factors that impact building high-quality backlinks are the target page you are trying to build links to and the number of opportunities that currently exist that are relevant to that target page. Personalize content to personas and specific use cases to create more opportunities to reach out and build that personalization into your pitch and call to action.”

The biggest best practice is relevance. Start creating content that’s valuable and relevant to your niche. Focus on content people want to cite, like original research or genuinely helpful guides.

You should also look for broken-link opportunities. When a site in your space points to an outdated resource, you can suggest your content as a replacement.

Media requests are another strong play. Journalists and editors regularly need expert quotes, and a strong response earns you authoritative links and mentions.

It also helps to study what’s already working. Competitive backlink analysis can show you which sites, formats, and outreach angles are earning links in your niche.
These are some core moves, but backlink building rewards consistency. Check out our full guide on how to build backlinks for a deeper look at execution.

FAQs

Conclusion

Backlinks are one of the most important parts of a solid SEO strategy. They build credibility and authority, and search engines notice. That same authority carries into AI-driven search, where platforms consistently favor content from sources they trust.

The work is ongoing. You need to track what you have, pursue broken link opportunities, cut what’s hurting you, and keep earning better links over time. When you approach backlinks correctly, the payoff compounds. Stronger links mean stronger rankings, and stronger rankings mean more of the right people finding your content.

• CTV advertising delivers video ads within streaming content on internet-connected TV devices, with targeting and measurement precision that linear TV never had.
• Streaming accounted for 45.6 percent of all ad-supported TV viewing in Q4 2025, while only 36 percent of U.S. adults still subscribe to cable or satellite.
• Inventory is expanding fast. Amazon has repositioned its demand-side platform (DSP) as a cross-screen programmatic platform, and Pinterest’s acquisition of tvScientific has brought discovery-based audience data into the CTV mix.
• CTV advertising rewards intentional spend. Set clear outcome goals, keep frequency under control, and track metrics that connect to real business results rather than just impressions.
• Not every business is a natural fit for CTV advertising, but self-serve buying tools have lowered the barrier significantly, making meaningful tests possible without a traditional TV budget.

According to Pew Research, 83 percent of U.S. adults watch streaming services, while only 36 percent subscribe to cable or satellite TV at home. In Q4 2025, 74.2 percent of all TV viewing was ad-supported, with streaming accounting for 45.6 percent of that share, the largest of any category, per Nielsen. 

Ad dollars are following the audience. According to IAB, CTV ad spend grew 16 percent year over year in 2024, and digital video surpassed linear TV (traditional scheduled television delivered via cable or satellite) for the first time that year, capturing 51 percent of total TV and video ad spend.

Here is what you need to know about CTV advertising to reach the right viewers on the biggest screen in the house.

What is Connected TV?

Connected TV (CTV) is exactly what it sounds like; televisions that connect to the internet. But it’s so much more than just smart TVs. CTV encompasses any device that allows you to stream content on your TV screen—think Roku, Amazon Fire Stick, and gaming consoles as well.

The shift towards CTV has been dramatic. In 2023, cable TV subscribers dropped to 72.2 million from 98.7 million in 2016. Why? Because 82% of American adults say streaming entertains them more than cable TV. It’s not just about cutting the cord—it’s about gaining control over what, when, and how we watch.

What Is CTV Advertising?

CTV refers to internet-connected devices that enable viewers to stream video content on a TV screen. This includes smart TVs like LG and Samsung, streaming sticks like Roku and Amazon Fire TV, and video game consoles like Xbox or PlayStation. 

CTV advertising is a form of digital advertising that delivers video ads within that TV streaming content. Ads can appear across ad-supported tiers of streaming services like Hulu and Peacock, free ad-supported streaming TV (FAST) channels like Pluto TV and Tubi, and apps on streaming devices.

CTV ads give you the full-screen, lean-back viewing experience of traditional TV ads, with the reporting and optimization of paid digital. Google Display & Video 360 (DV360), for example, lets advertisers layer CTV-specific audience segments on top of first- and third-party data, going well beyond the demographic filters available in standard Google Ads campaigns. 

The screenshots below show the difference in targeting controls between the two platforms. Google Ads operates within Google’s own data signals, while DV360 lets you bring in your own customer relationship manager (CRM) lists and third-party data on top of that.

Source: https://improvado.io/blog/dv360-vs-google-ads

That kind of targeting sophistication is becoming the standard across the industry, and the major players have taken notice. Amazon has repositioned itself not just as a streaming platform but as a full-funnel, cross-screen programmatic ecosystem, reflective of broader trends in paid media. 

Through Amazon’s DSP, advertisers can now access inventory across its own distribution channels and third-party platforms like Netflix and Disney. Layering Amazon’s first-party shopper data on top of that inventory creates targeting and attribution capabilities that go well beyond standard streaming buys.

CTV advertising’s reach is expanding just as quickly as its targeting capabilities. Netflix’s ad tier generated $1.5 billion in revenue in 2025 and is expected to nearly double to roughly $3 billion in 2026. CTV ads on LinkedIn have also entered the mix, enabling B2B advertisers to reach professional audiences on connected TV screens through partners like Roku, Samsung, and NBCUniversal.

Metro Vein Centers is a good illustration of what CTV advertising precision looks like in practice. The clinic used CTV’s geotargeting to reach women in specific demographic groups near its physical locations, layering in a retargeting campaign to re-engage previous site visitors. The result was an 85 percent reduction in cost per site visitor.

How Does CTV Advertising Work?

Here’s how the CTV advertising process works from the moment a viewer hits play:

1. Viewer Initiates: A viewer selects content to watch on their connected device. This could be anything from a Netflix show on a smart TV to a YouTube video on a gaming console.
2. Publisher Transmits Data: The publisher (like Hulu or Roku) sends available viewer information to an ad exchange. This data might include device type, content genre, and any known viewer demographics.
3. Auction Begins: An automated bidding process, known as real-time bidding (RTB), starts for this specific ad opportunity. This happens in milliseconds, before the content even begins to load.
4. Platforms Share Information: Supply-side platforms (SSPs) provide more detailed information to potential buyers. This could include the viewer’s approximate location, the time of day, and the type of content being watched.
5. DSPs Bid: DSPs with matching criteria automatically bid for the ad slot. If you’ve set up a campaign to target, say, sports fans in Chicago, your DSP will bid on this opportunity if it matches.
6. Exchange Selects Winner: The highest-bidding DSP wins, and their ad is placed. If that’s your ad, it’s then served to the viewer as part of their streaming experience.

This entire programmatic advertising process happens in less than a second, across millions of devices simultaneously, matching your ad to the right viewer before content even loads.

There are three main ways to buy CTV ads:

1. Open auction or RTB: Prices are determined during a real-time auction.

Source: https://www.getpublica.com/blog/dont-chase-cookies-learn-how-ctv-targeting-really-works-the-state-of-ctv-targeting-1-2

2. Private marketplace (PMP): An invite-only version of an open auction.
3. Programmatic direct: Direct sales at a fixed price, bypassing the auction.

Source: https://www.getpublica.com/blog/dont-chase-cookies-learn-how-ctv-targeting-really-works-the-state-of-ctv-targeting-1-2

The key players in this process are:

• DSPs: Advertisers use them to manage bids and targeting. 
• SSPs: Publishers use them to make inventory available to buyers. 
• Ad exchanges: These are the digital marketplaces where SSPs and DSPs transact.

The buying process is getting smarter, too. NBCUniversal teamed up with agency RPA and ad server FreeWheel to test agentic AI systems that handle campaign planning, activation, and execution across both linear TV and streaming, including live sports. The goal is to let AI handle the operational grunt work so teams can focus on strategy.

Benefits of CTV Advertising

Here’s what CTV advertising can do for your marketing:

• Precise targeting: You can reach specific audiences based on interests, behaviors, and locations. 
• Real-time measurement: You’ll see who watched your ad, for how long, and what they did afterward. This instant feedback tells you what to change and when.
• Reach expansion: CTV advertising lets you connect with viewers who’ve switched to streaming. 
• Higher completion rates: CTV advertising’s targeting means your message is more likely to resonate, keeping viewers engaged to the end.
• Agile campaigns: Unlike traditional TV, you can adjust CTV ads quickly. Spot an underperforming element? Change it immediately and see the impact.

You’ll need enough budget to generate meaningful signal, creative built for a full-size screen, and a clear sense of your target outcome. Self-serve buying tools have made entry more accessible than ever, but you still need enough spend to generate data worth acting on.

How to Plan and Execute a Connected TV Campaign

A strong CTV campaign doesn’t happen by accident. Here is what the CTV advertising planning and execution process looks like step by step:

• Develop your strategy.
• Choose the right platform.
• Create compelling content.
• Set your budget and bidding strategy.
• Monitor and optimize your campaign.

1. Develop Your Strategy

Before you spend a dime, you need a clear plan:

• Define your objectives: Are you aiming for brand awareness, lead generation, or direct sales? Be specific.
• Identify your target audience: Who are you trying to reach? Provide as much detail as possible about your target audience’s demographics, interests, and viewing habits.
• Set clear KPIs: Decide how you’ll measure success. It could be:
  • Impressions: Tracks how many times your ad is displayed.
  • Completion Rate: Measures the percentage of viewers who watch your entire ad.
  • Cost Per Completed View (CPCV): Tracks the cost for each viewer who watches your ad through to the end.
  • Brand Lift: Measures changes in brand awareness, perception, or purchase intent after viewing your ad.
  • Reach and Frequency: Tracks how many unique viewers saw your ad and how often.
  • Website Visits: Measures traffic to your website after running the CTV campaign.
  • Conversion Rate: Tracks the percentage of viewers who take a desired action after seeing your ad.
  • Return on Ad Spend (ROAS): Measures the revenue generated relative to your ad spend.
  • Foot Traffic: Tracks increases in in-store visits attributed to your CTV campaign for brick-and-mortar businesses.
• Align with other marketing efforts: CTV works best when it reinforces messaging across your other paid and organic channels. If you’re running paid search or paid social, make sure your CTV creative is telling the same story.

2. Choose the Right Platform

Source: https://about.ads.microsoft.com/en/blog/post/june-2024/making-ctv-accessible-to-everyone

Once your strategy is set, the next decision is where to run your ads. Here are your main options:

• Smart TV manufacturers: These are TV brands, like VIZIO and Samsung, that have built-in streaming capabilities. They offer ad inventory across their native apps and sometimes partner channels. 
• Streaming devices: These are external devices that connect to TVs to enable streaming. Roku, Apple TV, and Amazon Fire TV are a few choices, though Roku and Amazon also manufacture their own smart TVs. They provide ad opportunities across their platforms and partner apps.
• Video streaming services: These content providers stream content directly to viewers and offer ad inventory within their programming streams. Hulu and YouTube are a couple of major players when it comes to CTV, but other apps like Netflix and Disney+ also offer advertising options. 
• DSPs: These technology platforms enable you to buy ad inventory across multiple CTV sources, offering broader reach and more advanced targeting options. Amazon’s DSP and DV360 are two examples. 
• Over-the-top (OTT) aggregators: OTT refers to video content delivered over the internet, bypassing traditional cable or satellite providers. CTV is the device used to view that content, like a smart TV or game console. In short, OTT is the delivery method, while CTV is the screen. Platforms like FreeWheel and Magnite aggregate ad inventory from multiple streaming services and devices, giving buyers a single point of access to diverse CTV inventory. Unlike DSPs, which operate on the demand side, aggregators work on the supply side, connecting publishers to potential buyers across multiple platforms.
• FAST platforms: Free ad-supported services like Tubi, Pluto TV, and The Roku Channel have expanded rapidly into mainstream viewing. Tubi is already reaching more than 100 million monthly viewers, offering broad reach at competitive CPMs.
• Social platforms: Social media platforms are increasingly entering the CTV space, extending their audience data and ad products to the television screen. Pinterest, for example, announced the acquisition of tvScientific, connecting its discovery-based audience data to TV reach. The platform’s first original CTV series, “Bring My Pinterest to Life,” launched on Roku in March 2026, giving brands a shoppable format that bridges upper-funnel inspiration with connected TV exposure.

Each platform type has its strengths, and the right choice depends on your campaign goals, audience, and budget. Smart TVs and streaming devices give you direct access to viewers, while DSPs and aggregators offer broader reach and more granular targeting. FAST platforms and newer entrants like Pinterest add scale and audience data that didn’t exist in CTV a few years ago. Most advertisers find that a mix works better than any single path.

3. Create Compelling Content

Good CTV creative has one job. It must earn attention on a screen where the viewer did not invite it in. A few principles separate the ads that work from the ones that get ignored.

• Hook fast, stay clear. You have seconds before a viewer mentally checks out. Lead with the problem, the product, or a visual that demands attention. The message should land cleanly, even if speakers are muted.
• Design for one takeaway. CTV is a lean-back environment. Viewers are not scrolling past your ad, but they are not taking notes, either. Pick one thing you want them to remember and build everything around it.
• Give viewers somewhere to go. A QR code, a branded search term, or a simple URL gives engaged viewers a direct path to act. According to Innovid, interactive ads earn an average of 71 additional seconds of viewer time over standard pre-roll, suggesting that engagement formats are worth the extra production effort.
• Match the creative to the audience. CTV targeting is precise enough to serve different messages to different household segments. A generic spot wastes that advantage. Tailor the message to those watching.
• Think beyond the 30-second spot. Pause ads, overlay formats, and shoppable units are all part of the modern CTV creative toolkit.
  • Overlay formats appear during content and let viewers scan a QR code or click through to take an action like visiting a site or making a purchase.
  • Pause ads appear when a viewer pauses content and can include QR codes or direct response prompts.
  • Shoppable units let viewers buy directly from their TV when their retail accounts, such as Walmart or Amazon, are linked to their device.

Sources:https://www.sabioctv.com/blog/top-8-ctv-ad-creative-units-to-boost-engagement, https://strikesocial.com/blog/getting-started-with-youtube-pause-ads-what-you-need-to-know/, https://www.collectivemeasures.com/insights/ctv-and-the-addition-of-shoppable-ads

Examples worth studying

Lexus used dynamic countdown creatives paired with a home screen roadblock on LG Smart TVs during the U.S. Open, reaching viewers the moment they launched the app before content even began. The campaign drove a 64 percent lift in brand perception, which is a strong illustration of how matching creative format to a high-attention moment can move brand metrics in a way a standard pre-roll spot cannot.

Another automotive brand used Vizio’s Inscape platform to target households identified as “auto intenders” on CTV, running seven campaigns across six models over three months. The campaign resulted in more than 2,600 vehicle purchases and delivered an average ROAS of $31.91, showing that CTV can drive high-value conversions when targeting is built around purchase intent rather than broad demographics.

Both cases illustrate what separates effective CTV from wasted spend. One shows how matching creative format to a high-attention moment moves brand metrics, while the other shows how building targeting around purchase intent drives measurable conversions. 

4. Set Your Budget and Bidding Strategy

CTV advertising rewards intentional spending over volume.

• Start with a test budget, not your full commitment. Give the campaign enough room to generate real traction across audiences and placements before scaling. Industry guidance generally points to dedicating 15 to 30 percent of your digital video budget to CTV advertising as a starting point for meaningful testing.
• Understand how CTV advertising is priced. Most CTV inventory is bought on a cost per mille (CPM) basis, with rates for most U.S. campaigns ranging from $20 to $40 per thousand impressions and many settling around $25 CPM, depending on targeting depth, content type, and inventory quality. Premium direct deals, such as those on Netflix, can push rates significantly higher. Cost per acquisition (CPA) is better thought of as an outcome goal than a bidding model, or something you optimize toward rather than bid on directly.
• Allocate budget across platforms based on performance. If you are running across multiple publishers or buying paths, let delivery data drive where the money goes. Do not set it and walk away.
• Set frequency caps. This prevents ad fatigue and stops you from burning budget on viewers who have already seen your ad enough times. Research suggests three to seven exposures optimize impact, while more than 10 can reduce purchase intent.

Spend less time chasing the lowest CPM and more time making sure your budget is working against the right audiences in the right environment.

5. Monitor and Optimize Your Campaign

CTV advertising gives you real-time performance data that most traditional TV buys never could. Here’s how to use it:

• Track key metrics. Monitor impressions, completion rates, and conversions to understand whether the campaign is delivering and whether viewers are watching through to the end.
• Analyze viewer behavior. Look at engagement patterns and drop-off points to understand where creative is losing attention and where it is holding it.
• Adjust in real-time. Many platforms enable you to optimize campaigns while they’re running, rotating creative, or tightening targeting based on what the data is telling you.
• Test and learn. Try different creative versions or bid strategies. Small tests compound into meaningful performance gains over time.
• Connect online and offline data. Use attribution tools to understand how CTV exposure influences actions taken on other devices or in physical locations.

Run incrementality tests. Platform-reported metrics often undercount CTV’s true contribution. Comparing exposed households against a control group gives you a cleaner read on whether your campaign is changing behavior, not just reaching people who were already going to convert.

FAQs

Conclusion

CTV has earned its place as a core part of any modern media mix. The brands winning on CTV right now are the ones applying the same discipline to testing and measurement that they bring to search and paid media. 

If CTV is not yet part of your 2026 media mix, start by defining your audience and picking a platform that fits your buying model. Strong video creative that holds attention on the biggest screen in the house will do the rest.

• The Ubersuggest Chrome Extension surfaces keyword data like volume, CPC, and competition scores directly on Google, YouTube, and Amazon search results pages without leaving your browser. 

• The extension works on both Windows and Mac, and activates automatically once installed. 

• YouTube and Amazon support expands your keyword research beyond Google, covering video and ecommerce search behavior in one tool. 

• The extension connects to the full Ubersuggest platform, where AI visibility features help you track how your brand and content appear in AI-generated search results. 

• Traditional organic rankings are no longer the whole picture. Ubersuggest helps you monitor visibility across both classic search and the AI-powered results shaping where traffic goes next. 

The Ubersuggest Chrome Extension has seen some significant updates over the years, and the latest version is the most useful one yet. 

You can download it here and install it in seconds. 

The improvements go well beyond a simple refresh. Keyword research is faster, more intuitive, and built around how SEO professionals actually work. This post breaks down what the extension does, what’s changed, and how to get the most out of it. 

Here’s what Ubersuggest Chrome can do for you…

The Ubersuggest Chrome Extension brings SEO data directly into your browser, so you’re not jumping between tabs or tools to get the numbers you need. 

Once installed, the extension activates automatically whenever you run a Google search. Right there on the results page, you’ll see keyword data layered in: monthly search volume, cost-per-click (CPC), and competition scores for your search term. No extra steps required. 

Here’s how to put it to work across a few common use cases: 

Researching keywords: Search any term on Google and the extension surfaces volume and difficulty data instantly. Use that to qualify whether a keyword is worth targeting before you invest time in content. 

Scoping out the competition: Click into any organic result directly from the SERP and the extension pulls up domain-level authority data. It’s a fast way to size up who you’re up against. For a deeper look, pair it with a full competitor analysis to understand where gaps exist. 

Finding related keywords: The extension also surfaces keyword suggestions tied to your search. These are useful for building out topic clusters or identifying secondary terms to work into existing content. 

It works the same way whether you’re on Windows or Mac, as long as you’re running Chrome. The experience is consistent across both operating systems, so the workflow above applies regardless of your setup. 

Keyword research beyond Google

Google isn’t the only place people search. YouTube is the second-largest search engine in the world, and Amazon drives more product searches than Google does in the ecommerce space. The Ubersuggest Chrome Extension works across both platforms, giving you keyword data wherever your audience is actually searching. 

On YouTube, the extension surfaces keyword data directly as you type. Search any term and you’ll see volume and competition data on suggested keywords in real time. 

Click “view all” next to the search bar for a deeper breakdown. You’ll see monthly search volume trends over the past 12 months, seasonal patterns, competition scores, CPC data, click rates, and audience age ranges. The extension also shows whether a keyword skews toward mobile or desktop searches, which matters for conversion strategy. Desktop searches tend to convert at higher rates, so prioritizing those terms can sharpen your targeting. 

The right-hand side of any YouTube results page also surfaces related keyword suggestions, giving you additional terms to evaluate without leaving the page. 

Amazon works a little differently. Rather than overlaying data on the results page, the extension surfaces keyword information directly on search suggestions, keeping the shopping experience intact while still giving you the data you need for ecommerce keyword research. 

Think of the extension as your on-ramp to smarter research across the open web. The data it surfaces on Google, YouTube, and Amazon is just the starting point. The full Ubersuggest platform goes deeper, with features like AI visibility tracking and AI-powered keyword overviews that help you understand not just where you rank, but how AI search surfaces your brand. Those capabilities live in the platform, and the extension is the fastest way to get there. 

What does that mean for you?

Search has changed. Google’s AI Overviews now answer questions directly on the results page, and platforms like TikTok, YouTube, and Amazon have become legitimate search destinations in their own right. Ranking on Google alone no longer guarantees visibility. 

That’s where Ubersuggest’s newer AI-focused features become relevant. The platform can show you how your brand and content are surfacing across AI-generated results, not just traditional organic rankings. That kind of insight is hard to get anywhere else, and it’s increasingly necessary for staying competitive. 

The Chrome Extension is your entry point into all of it. It gives you real-time keyword data as you browse, and connects directly to the Ubersuggest platform where the deeper AI visibility analysis lives. Together, they give you a clearer picture of where you stand across both traditional and AI-powered search. 

In short: the extension makes everyday research faster, and the platform helps you think bigger about where search is headed. 

But wait, There’s more…

There is also one other important change made to the extension that you may have already noticed if you use Google on a regular basis. 

When you search on Google, there is now traffic estimations under each URL. 

This traffic estimation is for organic search traffic and it is done on a domain level. Eventually, we will tweak it to be page-based and even show you the other keywords each page ranks for… but for now, we are providing you with organic traffic estimates for each domain. 

And if you are more of a visual person, in the right-hand sidebar you can also see the traffic estimation for any result in the top 10. 

FAQs

Conclusion

Already using the Ubersuggest Chrome extension? It’s still a great way to get quick insights as you browse. 

But here’s the real play: use it as your entry point into the full platform. 

When you click through, you’ll unlock deeper keyword data, competitor insights, and our newer AI features that help you generate content ideas, analyze pages, and move faster without guessing. 

Don’t have the extension yet? Install it here and start turning everyday browsing into real SEO opportunities. 

• Knowing how to measure marketing ROI requires moving beyond credit assignment toward causal proof. Attribution shows what happened; incrementality shows what marketing actually caused.
• Marketing leaders face structural visibility gaps from walled gardens, cross-device behavior, offline conversions, and AI-mediated discovery that no single tool can fully account for.
• Marketing investment ROI looks different at different funnel stages. Lower-funnel channels support high statistical confidence. Upper-funnel activity requires directional signals and longer evaluation windows.
• The payback curve problem means short reporting cycles systematically under-value brand and upper-funnel investment, even when those channels drive the most long-term growth.
• Learning velocity matters as much as measurement precision. A confident direction pursued quickly outperforms a perfect answer that arrives too late.

The Real Measurement Challenge CMOs Face

The core challenge in figuring out how to measure marketing ROI is not a lack of data. Most marketing teams have more data than they can act on. The challenge is that the data they have mostly reflects activity, not impact. And the visibility gaps that matter most are structural, not fixable with a better dashboard or a new marketing measurement plan.

Consider what falls outside standard analytics. Walled garden platforms like Google, Meta, and Amazon run their own measurement systems optimized to report performance favorably within their ecosystems. Cross-device behavior means a buyer who saw an ad on mobile and converted on desktop may never be connected in a single attribution path. Offline conversions, from phone calls to in-store visits to deals closed in a CRM, are underrepresented or missing entirely. Private sharing channels, where recommendations travel through direct messages and group chats, show up as direct traffic if they register at all. And AI-mediated discovery, where a buyer forms a view of a brand through an AI-generated answer before ever visiting a website, leaves no footprint in standard reporting.

NP Digital research found that the average customer journey grew from 8.5 touchpoints in 2021 to 11.1 touchpoints in 2025. The interactions most likely to have shaped a purchase decision are the ones least likely to appear in a marketing report.

Marketing leaders who understand this stop expecting their measurement stack to show a complete picture. Instead they ask which signals are reliable enough to act on, which decisions require stronger proof, and where directional confidence is sufficient to move forward.

Why Attribution Doesn’t Answer Leadership Questions

Attribution modeling remains one of the most widely used marketing measurement tools available, and it has a genuine role to play in day-to-day campaign management. The problem is that when it gets used to answer questions it was not built to answer.

Attribution shows which touchpoints preceded a conversion. It does not show whether those touchpoints caused the conversion. That distinction sounds subtle, but it has significant implications for budget decisions. When Airbnb paused its performance marketing budget, bookings did not drop. When Uber cut spend in certain channels, rider acquisition was largely unaffected. In both cases, the attribution system had been crediting spend for outcomes that would have occurred regardless. The marketing was capturing demand, not creating it.

The questions leadership most often asks are precisely the ones attribution cannot answer reliably. Did this campaign generate new demand, or intercept demand that already existed? Would revenue have changed if this activity had not run? Which channels are actually changing the economics of the business? These are questions about causality. Attribution is built around correlation.

According to NP Digital research, nearly 47 percent of marketers lack confidence in their current attribution model. Yet most organizations still use attribution reports as the primary input for strategic budget decisions. Understanding where attribution blind spots appear is the first step toward building a marketing measurement plan that can support those decisions more reliably.

The Four Questions Modern Marketing Measurement Must Answer

Rather than starting with a dashboard, high-growth marketing organizations start with a set of diagnostic questions. These questions function as decision filters, helping leaders separate marketing activity from actual business impact. They come directly from how to measure marketing ROI in a way that connects to causal outcomes rather than credited touchpoints.

What is the incremental conversion lift? This asks not how many conversions occurred, but how many would not have occurred without the marketing spend. The gap between attributed conversions and incremental ones reveals how much of reported performance reflects demand capture rather than demand creation.

What is the incremental search impact? If branded search volume rises following a campaign, what created that lift? Upstream video, social, or content investment often generates the demand that search later captures. Understanding this connection changes how upper-funnel spend gets evaluated.

What attribution redistribution is occurring? Referral traffic spikes or conversion rate improvements in one channel sometimes reflect credit shifting between paths rather than genuine growth. Identifying redistribution separates real gains from accounting changes.

Where is attributed alienation occurring? At what point does frequency, promotional dependency, or margin compression start producing negative incremental lift? Channels that look efficient in aggregate can be actively eroding value at the margin.

These questions are not new KPIs to add to a dashboard. They are the lens through which marketing investment ROI gets evaluated honestly. For teams building this capability from scratch, tracking content marketing ROI using incremental rather than attributed signals is a practical place to start, since content often influences conversions across multiple subsequent touchpoints.

Matching Measurement Standards to Funnel Position

One of the most common errors in building a marketing measurement plan is applying the same standards of statistical rigor to every channel, regardless of where it sits in the funnel. Lower-funnel and upper-funnel activity operate on fundamentally different timescales and produce fundamentally different signal quality.

Lower-funnel channels, including branded search, retargeting, and conversion-focused paid campaigns, generate fast, measurable feedback. Requiring 95 percent statistical confidence before acting on their results is appropriate. The signal is clear, the data is abundant, and underperformance should be addressed quickly.

Upper-funnel channels work differently. Video, brand campaigns, content, and influencer partnerships create future demand. Their effects develop gradually, often appearing as increased branded search volume, improved conversion rates, or lower customer acquisition costs weeks or months later. Requiring the same level of statistical certainty from channels with 8- to 12-week lag times means cutting potentially effective strategies before they can prove themselves.

This creates a pattern NP Digital research consistently surfaces: teams reduce upper-funnel investment because it lacks immediate proof, then experience declining lower-funnel efficiency as the demand pipeline weakens. SEO ROI follows a similar curve. Organic search investment can take months to produce measurable returns, but teams that cut it during that window often see compounding downstream effects on paid efficiency.

The practical approach is tiered standards matched to funnel position. Lower-funnel channels require high confidence before spending continues or scales. Upper-funnel channels can be evaluated at 50 to 60 percent directional confidence, supported by leading indicators like branded search lift, engagement rate trends, and downstream conversion rate improvements.

The Payback Curve Problem

A related challenge in knowing how to measure marketing ROI is what happens when budgets shift toward channels with longer payback periods. Most organizations evaluate all marketing activity on the same weekly or monthly reporting cadence, regardless of how long each channel takes to deliver its full value. This creates a systematic bias against the investments that often produce the most long-term growth.

Direct-response channels like paid search and retargeting deliver 80 to 90 percent of their value within the first week. Email and owned media deliver 60 to 70 percent within the first two weeks. Paid social and display activity produces 50 to 60 percent of its value in the first three weeks, with a long tail extending to 8 to 12 weeks. Video and brand investment delivers only 30 to 40 percent of its value in the first month, with the majority accruing over three to six months.

When marketing spend shifts toward longer-payback channels, weekly performance declines by design. The scrutiny does not. Teams that understand their channel-level payback curves can model expected performance rather than reacting to short-term dips. Teams that do not understand them tend to cut upper-funnel investment at exactly the point where it would have begun producing downstream returns.

Building a dual-view reporting approach helps address this directly. Reporting what happened this week alongside what the model projects based on payback curves gives leadership the context to evaluate performance honestly. This is a core component of unified marketing measurement, where multiple methods and timeframes are combined into a single coherent view of marketing performance rather than a collection of disconnected channel reports.

Why Directional Confidence Often Beats Perfect Precision

Waiting for certainty before acting is one of the most reliable ways to lose ground in modern marketing. How to measure marketing ROI is partly a question of marketing investment ROI, but it is equally a question of decision speed. A model with 60 percent directional confidence, acted on quickly and iterated frequently, consistently outperforms a perfect answer that arrives a quarter too late.

Incrementality testing and geo experiments are the most reliable ways to build directional confidence without waiting for statistical perfection. A well-designed geo holdout can validate whether a channel is generating causal lift within a matter of weeks. The result may not be 95 percent certain, but it is far more useful for a budget decision than months of attribution reporting that cannot establish causality at all.

Rapid iteration compounds this advantage. Organizations that run frequent, smaller experiments build measurement capability faster than those waiting to design the perfect study. Each test produces a documented methodology that makes the next one cheaper and faster. Over 12 to 18 months, this creates a meaningful gap in decision quality between organizations that have built this muscle and those still relying primarily on attribution.

Learning velocity, the rate at which an organization converts experiments into better decisions, matters as much as the precision of any individual measurement. The teams gaining ground are the ones that have made experimentation a routine part of how they allocate budget, not a special project triggered by a performance crisis.

What This Means for Modern Marketing Leaders

The shift in how to measure marketing ROI comes down to three practical changes in how marketing leaders operate. Each one moves measurement closer to the capital allocation decisions that actually matter.

First, prioritize causal insight over attribution reports for strategic decisions. Attribution has a role in day-to-day optimization, but it should not be the primary input when deciding where to increase or decrease investment at a channel level. Incrementality testing and marketing measurement tools that surface marginal returns give a more reliable picture of where the next dollar will produce incremental growth.

Second, allocate budget based on marginal impact rather than blended performance. A channel running at strong average ROAS may be saturated at the margin. A channel with weaker blended numbers may have significant headroom. Understanding where diminishing returns begin is what separates organizations optimizing toward real growth from those optimizing toward the appearance of it. This is the core of unified marketing measurement: combining MMM, incrementality, and attribution signals to see the full picture rather than any single view in isolation.

Third, build experimentation into the operating rhythm rather than treating it as a special project. Weekly budget decisions based on directional evidence outperform quarterly reallocations based on attribution. Organizations that run incrementality tests regularly, document the results, and apply those learnings to subsequent decisions accumulate a structural advantage that compounds over time.

FAQs

Conclusion

Knowing how to measure marketing ROI has always required judgment alongside data. What has changed is that the data itself has become less reliable as a standalone guide. Attribution models over-credit demand capture. Platform dashboards optimize within closed ecosystems. Blended ROAS hides where spending stops working. And the channels doing the most to build future demand are often the ones that look weakest in a standard report.

The organizations closing this gap are building unified marketing measurement approaches that combine causal proof with directional confidence, match standards to funnel position, and make budget decisions at a cadence that reflects how fast markets actually move. 

If you are building this capability, start with the questions before the tools. Identifying which decisions your current stack cannot support is more valuable than adopting new marketing measurement tools before you know what gaps they need to fill. And for teams beginning with organic and content investment, this breakdown of content marketing ROI applies the same incremental thinking to channels that are often the hardest to measure and the most underfunded as a result.

• Copywriting is persuasive writing designed to drive a specific action. It differs from content writing, which builds awareness over time. 
• Good copy starts with a deep understanding of your audience’s pain points. It goes deeper than just listing your product’s features. 
• AI can assist with drafting and scaling copy, but human strategy and judgment are what make it convert. 
• Craft fundamentals like tone and storytelling remain the backbone of effective copy. 
• Copy that demonstrates genuine expertise and cites original data is more likely to show up in AI visibility.

AI can write copy in seconds. So why does human-generated content still pull in 5.44 times more traffic than AI-generated content?

Copywriting is about getting people to act. That’s a skill that still demands a human touch.

Copywriting is different from content writing. Whereas content writing builds awareness over time, copywriting is built for one thing: conversions. Every word is focused on driving visitors to sign up or buy.

That distinction matters more than ever as AI floods the internet with generic output every day. The brands that cut through the noise are the ones treating AI like a tool, using it strategically to craft copy that speaks to real human motivations.

This guide covers what copywriting is, why it still matters in 2026, and which strategies work.

What Is Copywriting?

Copywriting is the practice of writing persuasive text to get readers to take a specific action, such as signing up for a newsletter or making a purchase. It includes everything from ads and landing pages to emails and product descriptions.

Good copy communicates your value clearly and motivates the reader to act. Features, benefits, pricing, and social proof all serve the message, but copy is what determines how those elements land with the reader.

In other words, your product or service is the offer, and your copywriting is the pitch. No matter how strong the offer is, a weak pitch won’t convert your target audience.

How Does Copywriting Differ from Content Marketing?

Many people get tripped up by the difference between copywriting and content writing. Some use the terms interchangeably, but they serve different purposes.

Content writing is the craft behind content marketing. It focuses on indirect goals, such as educating your audience or building brand awareness. Assets like blog posts and webinars fall into this category. Their aim is to bring readers in and keep them coming back.

Copywriting is more direct. Its job is to get the reader to take a specific action, right now. You see it in ads, calls to action (CTAs), and product descriptions, but it shows up everywhere decisions get made.

My own blog is a good example of both working together. The article you’re reading right now is content marketing. Its goal is to inform you about copywriting. 

However, the page also contains distinct copy elements, each doing a specific job: 

• The headline, “Comprehensive Guide to Copywriting: 2026 Update,” gets you to click. 
• The banner ad above drives traffic to our Ads Grader. 
• The CTA below, which also shows up in the sidebar of my site, nudges you to get a free SEO analysis and potentially work with our agency. 

All appear on the same page, but each has a different objective. 

Is Copywriting Still Important?

AI can generate copy at scale. So, the question many marketers are asking right now is: Do you even need a human copywriter anymore?

The short answer is yes. Here’s why.

Copywriting has always been about more than stringing words together. It’s about understanding what motivates your audience and building a message that moves them to act. AI can draft and iterate quickly, but it can’t replace the strategic thinking that makes copy convert.

There’s also a trust problem. According to Accenture’s Life Trends report, 62 percent of consumers say trust is an important factor when choosing to engage with a brand. 

At the same time, AI-generated content is flooding every channel. Audiences are getting better at spotting generic copy and tuning it out, and their eyes are sharpening quickly. Data from CivicScience shows 36 percent of consumers can spot AI in a brand’s marketing and won’t do business with them when they do. That number has gone up 4 percent in less than six months. 

This data illustrates exactly why copywriting is so important. A well-crafted headline or an email that sounds human still requires a writer who understands the nuance behind the words. 

AI is a powerful tool in the writing process, but the judgment and the strategy behind effective copy still require a person. Neglecting that human element means you could be missing out on over five times as much traffic, as we mentioned in the intro to this guide. 

Types of Copywriting

Copywriting strategies vary depending on your goals. Here’s a look at how brands can apply each of the types of copywriting.

Brand Copywriting

Brand copywriting defines how a brand displays its values and personality, creating an emotional connection with its customers. It shows up in landing pages and anywhere else a brand needs to interact with its audience.

Many people picture brand copywriting as the big, flashy stuff, like what you see in Pepsi commercials and on Nike billboards. Those are some of the most visible examples, but the goal is the same no matter the scale: to create an emotional connection with your audience.

That connection drives real business results. Analysis of over 1,400 advertising case studies in the Institute of Practitioners in Advertising (IPA) dataBANK finds that purely emotional campaigns outperform those using rational content alone, generating almost double the profitability. 

Take the ad below from Apple as an example. It doesn’t mention product specs or features. It’s designed to make the viewer feel they’re getting the coolest products with the best technology when they buy from Apple. 

Brand copywriting is about making people emotionally connected to your brand. Done well, it turns a transaction into a lasting relationship.

Social Media Copywriting

Social media copywriting is about grabbing users’ attention as they scroll and then converting it. Every platform has its own rules, so your approach needs to adapt accordingly. Copy that works on LinkedIn, for example, won’t land the same way on X or TikTok.

That said, the goal’s the same across platforms: to get people to act. Recent data shows 89 percent of consumers say a brand’s social media impacts their purchasing decisions. That kind of conversion requires copy that’s platform-native and strongly guides viewers to a clear CTA.

While there are some nuances to creating native copy, here are a few principles that apply across channels:

• Use strong, active verbs and keep sentences short.
• Write in a tone that feels human, not corporate.
• Lead with your hook and always include a clear CTA.
• Mix it up. Rotate between educational, entertaining, and conversational content.
• Use hashtags strategically to extend your reach

SEO Copywriting

SEO copywriting is the practice of writing content that ranks well in search engines and provides value to the reader. It’s about creating copy that satisfies search intent and compels the right audience to take action.

For years, the formula was straightforward: Research keywords and build high-quality content around them. That formula still holds, but the game has changed.

AI is now answering questions directly on the search engine results page (SERP), which means traffic that once flowed to well-ranked content is shrinking. 

Recent data shows that the organic click-through rate (CTR) for queries featuring Google AI Overviews has dropped 61 percent (as seen in the graph below). Users are getting the information they need quickly and moving on without clicking through to your site. 

Source: https://www.seerinteractive.com/insights/aio-impact-on-google-ctr-september-2025-update

The right response is to make your SEO copywriting better. 

Copy that answers questions with depth and specificity, earning citations in AI Overviews, will outperform generic, keyword-stuffed content. According to the same study, websites cited in AI Overviews are seeing a 35 percent higher organic CTR than those without citations. 

Thought Leadership Copywriting

Thought leadership copywriting positions your brand as a trusted authority in your industry. The goal is to deliver expert perspectives and original thinking that earns credibility with the people who matter most. 

My team and I already implement this strategy through thought leadership pieces like this one on social ranking strategies from our Digital PR Director, Kimberly Deese:

This approach works well with experienced, senior audiences. 

According to the recent Edelman-LinkedIn B2B Thought Leadership Impact Report, the majority of decision-makers and C-suite executives spend an hour or more each week consuming thought leadership content. And 73 percent say an organization’s thought leadership is one of the best ways to evaluate the caliber of work it’s likely to deliver to clients.

Thought leadership content takes many forms: expert interviews, research reports, essays, podcasts, and branded publications. 

Nutanix is a strong example. Its online magazine, The Forecast, takes a broad look at enterprise cloud computing through expert content, and builds authority without ever leading with a product pitch.

Email Copywriting

Email copywriting is one of the most direct forms of copy you’ll write. You’re landing in someone’s personal inbox, and you have seconds to make an impression before they scroll past or hit delete.

The opportunity is worth the effort. Email marketing generates a higher return on investment (ROI) than virtually any other marketing channel, averaging $10 to $36 for every $1 spent.

What makes email copywriting distinct is the relationship it assumes. Unlike a social ad or a search result, an email speaks directly to someone who has already opted in. That trust needs to be respected. 

Strong email copy starts with a subject line that earns opens and delivers value quickly, then asks the reader to take action with your CTA. Personalization and relevance are the baseline.

Tools for Copywriters

AI writing tools aren’t going away, and that’s a good thing for copywriters. They can sharpen your output when you use them strategically. Without applying your own judgment along the way, though, they can flatten it. 

Here are four tools that can make your writing more efficient and impactful if you use them right.

1. Anyword

Anyword is a data-driven AI copywriting platform built specifically for marketers. Its standout feature is a predictive performance score that forecasts how well your copy will convert before you publish, based on a dataset of millions of real-world A/B-tested ad campaigns.

Anyword gives you multiple variations ranked by predicted performance. You pick the winner before spending a dollar on distribution.

It works best for performance-driven copy like paid ads. If you’re running campaigns where conversion rates directly impact revenue, Anyword’s ability to cut the guesswork makes it worth the investment.

2. Grammarly

Grammarly has been a popular copywriting tool for years. It integrates directly into the apps you already use, catching spelling and grammar mistakes and flagging tone mismatches.

In late 2025, Grammarly’s parent company rebranded to Superhuman, uniting Grammarly with productivity tools Coda and Superhuman Mail under one platform. The Grammarly writing tool itself remains unchanged. It’s just now part of a broader AI productivity suite that includes a new AI assistant called Superhuman Go.

For copywriters, the core value proposition hasn’t shifted. Grammarly is still one of the most reliable tools for catching errors and refining tone before your copy goes live.

3. Wordtune

Wordtune is an AI-powered rewriting tool built around one core idea: Your meaning is there, but the words aren’t landing yet. Paste in your copy, and Wordtune suggests alternative phrasings that preserve your meaning while improving clarity and flow.

Unlike tools focused on grammar correction, Wordtune is about expression. You can toggle between formal and casual tones and choose from multiple rewrite options for the same passage. It integrates directly into most major platforms, working wherever you write.

For copywriters, it’s most useful during the editing phase when you need to sharpen individual sentences without losing your voice. Think of it as a sounding board for your ideas.

4. Writesonic

Writesonic is a full-scale AI content platform built for marketers and content teams that need to produce high volumes of quality copy across multiple formats. Where tools like Wordtune focus on refining what you’ve already written, Writesonic is built for content generation.

Recently, the platform has grown beyond its content-generation engine roots to include SEO tools and AI visibility tracking, showing brands how they appear on platforms like ChatGPT and Perplexity. For copywriters working on search-driven content, that’s an advantage over tools that rely solely on static training data.

Writesonic is best suited for small or large teams that need to produce high-quality content and track its performance in today’s search everywhere environment. 

As with any AI writing tool, of course, the output still requires human editing and strategic oversight, but it significantly reduces the time from a blank page to a working draft.

How to Copywrite: Copywriting Strategies

Tools can make you faster. Strategy is what makes you effective. Here are 10 basics of copywriting that turn good writing into copy that drives action.

1. Before You Start, Get to Know Your Audience

Great copy speaks directly to your reader. Before you write a word, you need a clear picture of who that person is.

According to Attentive’s Consumer Trends Report, 81 percent of consumers ignore irrelevant marketing messages. The fix is knowing your audience well enough that your copy never feels generic to them.

Start by building a buyer persona: a detailed profile of your ideal customer, like the one below. Pull from your actual customer data rather than assumptions. Look at who your highest-value customers are and what they have in common.

Source: https://xtensio.com/user-persona-template/

Once you have that profile, let it shape every copy decision. How does this person speak? What objections do they have to your brand? The more specifically you can answer those questions, the more directly your copy will speak to them.

Another simple tactic that works every time is writing to “you,” not “them.” Copy that addresses the reader directly, and not your audience as a group, converts better because it feels personal.

HubSpot proved this with a study of 330,000 CTAs over a six-month period. The resulting data showed that personalized CTAs performed 202 percent better than more generic CTA copy.  

2. Use the Right Tone

Tone is what makes copy feel right or wrong for a given audience. It’s the attitude behind your words that signals whether your brand is playful, authoritative, empathetic, or direct. Get it wrong, and even accurate, well-written copy can push people away.

Consider two versions of copy for a fictional sales software company:

“Understand your customers better using state-of-the-art software designed to take your business from zero to hero.”

“Gain a deeper understanding of your customers using our AI-powered sales software. SellingPlus helps streamline your sales funnel and drive revenue.”

The first is approachable and slightly playful, a good fit for a scrappy startup audience. The second is polished and precise, better suited for a C-suite buyer evaluating enterprise solutions.

Using the right tone will resonate more with the person you identified in your buyer persona. When tone matches the audience, readers feel like the copy was written specifically for them. 

3. Stress Your Unique Value Proposition (UVP)

U.S. e-commerce sales exceeded $1.5 trillion in 2025, according to Digital Commerce 360’s data analysis.

Source: https://www.digitalcommerce360.com/article/us-ecommerce-sales/

In a market of that size, the brands that win are the ones that are crystal clear about what they offer that their competitors don’t.

That clarity is your unique value proposition (UVP): a concise statement of what you do and why you’re the right choice over the competition.

Strong UVP copy is specific. “We help small businesses manage their finances” is a generic example. 

On the other hand, “Cloud accounting software built for small business owners who hate spreadsheets” tells someone exactly whether they’re in the right place.

Brands shouldn’t try to be perfect for everyone. 

A small business owner shopping on a tight budget has different needs than an enterprise CFO. A free-range egg farmer needs different tools than a factory operation. 

The more precisely your copy speaks to your actual audience, the more effectively it’ll convert. Stop trying to appeal to everyone and own your unique niche clearly.

4. Use Storytelling

“Facts tell, stories sell,” is one of the oldest sayings in sales and marketing, proving that storytelling is one of the most powerful tools in a copywriter’s toolkit.

A good story is more entertaining than a list of features and far more likely to be passed along. Most importantly, it puts the reader inside an experience rather than outside looking at a product.

Allbirds does storytelling well. The footwear brand leads with a story about why its shoes exist, giving customers a sense of pride when buying from them. By the time you get to a product page, you’re already invested.

Source: https://www.allbirds.com/pages/our-story

You can see from the above example that you don’t need a lengthy origin story to use this approach. Even a single sentence of narrative context can shift how copy lands. In this case, the copy tells you that the brand is about “creating better things in a better way.” 

That’s a strong ethos statement that people will feel compelled to support with their wallets. 

5. Solve Pain Points

Copy that leads with features tells people what you built. Copy that leads with pain points tells people you understand their problem. 

The second approach tends to convert at a higher rate because it meets the reader where they actually are. And that’s a big deal given that more than 80 percent of customers ignore irrelevant marketing messages.

Take Ubersuggest. When someone considers using my keyword research tool, they’re not thinking about features. They want to outrank their competitors and show up where it counts: on Google and in AI search results. The Ubersuggest landing page copy speaks directly to that ambition.

There’s no feature list or product description. Just the outcome the audience cares about.

That focus is intentional. Your copy can’t solve every problem, and it shouldn’t try to. 

Identify the most common pain points your audience faces and build your message around the one you solve best. Customer interviews and support ticket trends are all reliable ways to surface what really matters to your audience.

6. Leverage Social Proof

Consumers do their homework before they buy. 

According to recent data from BrightLocal, 41 percent of consumers “always” read reviews when browsing for businesses, a significant jump from 29 percent the year before (2025). 

If your copy doesn’t include social proof, then you could be leaving customers on the table.

The reason it works is that people trust other people more than they trust brands. A stranger’s review carries more weight than your best marketing copy, because it comes without a motive to sell.

There are two smart ways to use social proof in your copywriting. 

First, let it inform your messaging. Reviews and customer surveys reveal exactly what language your audience uses to describe the problems and benefits they care about most. 

Second, place it strategically on landing pages and homepages where buying decisions are made.

Social proof can apply to B2B brands, too. For example, Slack lets other businesses know they’ll be joining “the most innovative companies” by using their service:

Source: https://slack.com/

That single phrase tells a prospective customer that the decision has already been made by people like them. 

Case studies, testimonials, star ratings, and media mentions all establish trust before your copy even has to ask for the sale.

7. Avoid Fluff and AI Tells

In the age of AI-generated content, copy that reads like it came off an assembly line can erode trust in your brand.

AI tools can be incredibly useful, but you still need to edit like a human. That means cutting the filler phrases that weaken your message and replacing predictability with personality.

Here are some of the most common AI tells to eliminate from your copy. The fix is often as simple as deleting or reordering a few words.

• “When it comes to…”
  • The tell: When it comes to marketing, copywriting is a must-have skill.
  • The fix: Copywriting is a must-have marketing skill.

• “It’s important to know/remember…”
  • The tell: It’s important to remember to track your marketing campaign metrics.
  • The fix: Remember to track your marketing campaign.

• “By doing X, you can do Y”
  • The tell: By tracking campaign metrics, you can optimize the success of your marketing.
  • The fix: Tracking campaign metrics helps you optimize the success of your marketing.

• “Ever-evolving landscape of…”
  • The tell: AI tools are essential to survival in the ever-evolving landscape of copywriting.
  • The fix: AI tools are essential to your survival as a copywriter.

• “Whether you do X or Y…”
  • The tell: Whether you post blogs or record videos, your storytelling skills are important.
  • The fix: Strong storytelling resonates regardless of the format you choose.

• “ABC isn’t X—it’s Y”
  • The tell: Marketing isn’t about listing features, it’s about telling stories.
  • The fix: Marketing is about telling stories that move people to act.

• “ABC does more than X — they Y”
  • The tell: Marketers do more than advertise products, they provide solutions.
  • The fix: Marketers connect people with solutions to real problems.

• Predictable lists of three (“X, Y, and Z”)
  • The tell: Strong copy requires clarity, brevity, and a compelling call to action.
  • The fix: Strong copy is clear and concise, with every word earning its place, including the CTA.

If a phrase delays you getting to your point or creates a robotic cadence, cut it. 

A good rule of thumb is to read your copy out loud. If it sounds like something a machine would write, it needs another pass.

8. Test Your Copywriting

What resonates with your audience today might fall flat in six months. The only way to know what’s actually working is to test it.

A/B testing web copy means running two versions of the same element against each other to see which drives more action. According to a recent benchmark report from Unbounce, the median landing page conversion rate across 41,000 pages is just 6.6 percent.

That number leaves a lot of room for improvement, and systematic testing is how you close the gap.

The key is to test one variable at a time. If you change too many things at once, you won’t know what actually moved the needle. 

Focus your tests on:

• Headlines: Test different angles, benefit statements, or emotional hooks. 
• CTAs: Try variations in wording and placement to find what drives the most clicks. 
• Point of view: Compare second-person options like “you can save” against direct imperatives like “save now.” 
• Button copy: Make small wording shifts and measure the impact on conversions.

Testing is how you stay current with what the market wants. Audience expectations shift over time, and copy that converts well in January may need to be adjusted by Q4 as seasonal priorities change. 

Building testing into your process as a habit is the best way to stay ahead of the curve.

9. Use Engaging Data and SME Proof

With AI becoming widely adopted, it’s easy for just about anyone to produce content at scale. However, the question becomes: Is it effective, high-quality content?

Today, facts and data backed by subject matter expert (SME) proof are essential for your copy’s credibility and visibility.

According to the Content Marketing Institute’s B2B Content Marketing Report, only 4 percent of B2B marketers report a high level of trust in generative AI content output. 

Audiences are skeptical of AI-generated copy for good reason, but one of its biggest crimes is that it often makes assertions without evidence. The way for copywriters to stand out is to be someone who actually backs their claims.

This is what Google’s framework, experience, expertise, authoritativeness, and trustworthiness (E-E-A-T), looks like in practice. And it’s a ranking signal for traditional search and AI systems.

Content that demonstrates genuine expertise through proprietary data and named expert quotes is significantly more likely to earn citations in both traditional and AI-powered search.

For copywriters, the practical takeaway is to replace vague assertions with specific figures whenever possible. Swap anonymous claims for named expert quotes. Commission original research so your brand owns the data, as my team did with our AI hallucinations study:

If you can’t do that, the next best option is to source data from original, credible sources. Track data all the way back to the original organization or company that researched it. 

Another best practice is to use only data points from highly credible sites. Publications such as peer-reviewed academic journals and case studies are great places to look.

Implementing these copy improvements will result in strong copy that signals to both readers and AI systems that your content is worth citing.

10. Build Your Call to Action

Potential customers who visit your website need a clear path to follow. A CTA gives them that, telling them exactly what to do next. The goal is to remove any hesitation about taking that step.

Specific language like “Get your free report” outperforms generic phrasing like “Submit.” Specificity reduces friction and makes the value clear to the customer before they click.

CTAs are even more important on landing and product pages built around a single conversion goal. 

A few principles worth keeping in mind for CTA success:

• Use action-oriented verbs.
• Keep CTA language short.
• Align the CTA messaging with the copy above it.

You can take things a step further by A/B testing your CTAs. It should be a regular part of your process, since even the smallest wording changes can drive meaningful lifts in conversion. 

Copywriting for AI Visibility: What to Do

AI visibility is whether your brand gets cited or recommended by large language models (LLMs). It’s becoming as important to track as your search rankings. If your brand isn’t showing up as the answer to your audience’s queries on AI platforms, you risk being left out of the conversation entirely.

McKinsey’s AI Discovery Survey says half of consumers now intentionally seek out AI-powered search engines, and a majority say AI is the top digital source they use to make buying decisions. The good news is that many of the principles that make copy effective for humans also make it more likely to be cited by AI.

A few strategies that can help:

• Lead with clear, direct answers. AI systems favor content that gets to the point.
• Use specific data and named sources. Vague claims get skipped, while cited stats get repeated.
• Structure content with descriptive headers. Well-organized copy is easier for AI systems to parse and extract answers from.
• Include expert quotes with credentials. Named authority signals are weighted heavily as they establish credibility.
• Keep your copy current. AI systems favor recently published, frequently updated content.

How to Use AI for Copywriting (the Right Way)

AI writing tools are most useful when you treat them as a first-draft engine. Editing is important, but the output is only as good as the direction and input you give it up front.

The way you design your prompts is critical in making the most out of AI-generated content. Vague requests produce vague copy. The more context you give the tool, the more useful the output will be. 

Compare these two prompts:

• Weak: “Write a headline for my email marketing tool.”
• Strong: “Write five headline options for a landing page promoting an email marketing tool for e-commerce brands. The tone should be direct and confident. The main benefit is saving time through automation. The CTA is ‘Start your free trial.’”

The second prompt gives the AI something to work with. The first gives it practically nothing.

A strong copywriting prompt includes:

• Your target audience
• The goal of the piece
• The tone you want
• Any key points to hit

Once you have a draft, that’s where your work begins. Read it aloud and ask whether the cadence sounds or feels robotic. Does it sound like your brand? Does it lead with the right pain point and have a strong CTA?

AI can draft, but only you can judge whether it converts. Think of it as a collaboration where AI gives you the basic building blocks, and you turn it into something worthwhile.

FAQs

Conclusion

AI can generate copy at scale, but scale without strategy produces noise. The brands that stand out are the ones investing in copy that’s human and built around a real understanding of their audience. That’s a skill no tool can fully replicate.

The strategies in this guide give you a framework to start with. As you put them into practice, dig into the psychology behind why copy converts. Understanding what motivates your reader at a deeper level is what separates good copy from great copy. 

When you feel confident with the copywriting basics, you can focus on more targeted copywriting strategies that move the conversion needle.

• Keyword research is the process of finding and analyzing the search terms your audience uses to determine which ones are worth targeting and why.
• Search intent, keyword difficulty, search volume, and topical authority are the core variables that determine whether a keyword is a viable target for your site.
• AI Overviews now appear in a significant share of searches and measurably reduce click-through rates. 
• Long-tail keywords carry more weight than ever. They convey highly specific intent and mirror the natural language patterns behind voice and LLM queries.
• Prompt research is a discipline that sits alongside traditional keyword research. It accounts for how people interact with AI tools, where query structure and user intent differ meaningfully from traditional search.

Have you been tracking your target keywords, only to watch rankings hold steady while organic traffic falls? 

You’re not imagining it. 

According to SEOClarity, AI Overviews (AIOs) appear for 30 percent of U.S. desktop searches, and according to Ahrefs, that presence alone reduces organic click-through rate (CTR) for position-one results by 58 percent.

You might think that makes keyword research for SEO less important now, but that couldn’t be further from the truth. 

Your research still matters. What’s changed is the goal. High-volume terms alone won’t cut it anymore. 

You need to identify which keywords still drive clicks and understand how large language models (LLM) prompts are reshaping the demand signals you rely on.

This guide covers the full research process, updated for how search works today.

What Is Keyword Research?

Keyword research is the process of identifying and analyzing the search terms your target audience types into search engines and LLMs. The goal is to determine which terms are worth targeting based on factors like the intent behind a user’s query.

Intent is the why behind what people search, and it’s an area many teams underinvest in.

Finding a high-volume keyword is easy enough. The harder part is understanding the true intent behind the keyword. That’s the key to making sure your content satisfies that intent better than what’s already ranking.

Why Is Keyword Research Important for SEO?

Creating content without keyword research is a gamble. 

Sure, you might produce something useful. However, without confirming what people are actually searching for and that you have a realistic shot at ranking, you’re spending resources on content that may never be found.

Keyword research solves for three variables that determine whether a keyword is worth pursuing:

• Search volume tells you how many people are looking for a term each month. A keyword with zero volume isn’t worth a dedicated page. Search volume alone doesn’t close the case, though. The vast majority (94.74 percent) of keywords receive 10 or fewer monthly searches, proving low-volume, high-relevance terms can still drive traffic that converts.

• Keyword difficulty tells you how competitive a keyword is based on the authority of the pages currently ranking for it. This is where many teams misjudge their opportunities. A keyword with a high difficulty score might be within reach for a high-authority domain but completely out of scope for a site with limited backlink equity. Targeting beyond your domain’s current authority just adds to your backlog.

• Topical authority has become increasingly important over the past two years. Google has gotten a lot better at evaluating whether a domain demonstrates depth and consistency within a topic area. Keyword research should inform a content strategy that builds clusters of related content rather than targeting disconnected terms.

There’s also the AI layer. 

AIOs now appear in a significant share of searches and reshape the value of a keyword depending on whether one shows up. 

Research from Seer Interactive tracking 3,119 informational queries finds that organic CTR dropped 61 percent for queries with AIOs compared to queries without them.

Notice how a more semantic long-tail keyword for the same subject produces a Google AIO versus a product-based search:

Source: Google.com

Source: Google.com

See how small differences in keywords can drastically change your results? This is why doing proper keyword research is important.

Long-tail keywords are more likely to trigger AIOs, which means users get their answer without clicking through. 

That’s worth knowing, but it’s not a reason to abandon those keywords. Flag them during analysis and see where they fit in your broader strategy.

Why Search Intent Is Important for Keyword Research

Search intent is the underlying goal behind a query. 

Google organizes intent into four broad categories: 

• Informational (users want to learn something)
• Navigational (users are looking for a specific site or brand)
• Commercial (users are comparing options before a purchase)
• Transactional (users are ready to buy or act)

Intent type is a big deal because Google matches results to intent. 

An e-commerce product page won’t rank for a query that Google interprets as informational. A how-to article won’t win for a transactional query where users want a product listing. 

No amount of optimization compensates for a content-to-intent mismatch.

Use keyword research for SEO to verify intent before you commit to a content format. The fastest way to do this is to run the keyword in Google and see what’s ranking. 

If listicles dominate page one, that’s what Google thinks the searcher wants. If product pages own the top positions, a blog post isn’t going to break through.

“What sort of things do they search for during the awareness, research, and transaction phases of their buying journey? Target each of these clearly in different areas of the website by bucketing groups of terms into these different intent groups,” explains William Kammer, Vice President of SEO at NP Accel.

Bucketing your keyword list by intent before mapping keywords to pages is one of the most practical things you can do to make sure your SEO efforts match how your audience actually moves through the funnel.

Prompt Research and AI Visibility

Traditional keyword research focuses on what people type into Google. 

Prompt research focuses on how people interact with AI tools like ChatGPT, Perplexity, and Gemini. The patterns across them are quite different.

When someone searches Google for “email marketing tools,” they enter that short phrase (or a close variant) and scan a list of results. 

When someone asks ChatGPT the same question, the query looks more like this: “I run a small e-commerce business, and I’m looking for an email marketing tool that integrates with Shopify and has automation features. What would you recommend?”

The intent might be the same, but the structure and the specificity are completely different.

LLMs take these longer queries and break them down into three key components:

• Persona: Defines who the user is and helps the LLM tailor the response to them
• Context: Identifies the user’s specific needs and narrows the scope of the answer
• Question: The actual “ask” contained within the query defines the LLM’s output

Source: Claude.ai

This structural difference affects your content strategy. 

LLMs synthesize information from multiple sources to generate a response. They evaluate content for credibility and depth. 

A page optimized around a head keyword might rank well in Google but never appear in an LLM response if it doesn’t fully answer the underlying question a user would actually ask.

Prompt research is the practice of identifying the underlying questions within the full, natural-language queries people use when interacting with AI tools and the keyword-related topic clusters those queries reveal.

Think of it as keyword research for a different interface. LLMs use a process called query fan-out, breaking out a single user prompt into multiple sub-queries to retrieve information. That means your content needs to answer not just the surface question but the related ones surrounding it.

A quarter of search volume has already shifted toward AI-driven chatbots and answer engines, according to Gartner. 

That shift is gradual, but it’s not stopping. Get ahead of it now by building prompt research into your workflow alongside traditional keyword research.

How to Do Keyword Research

Good keyword research starts with the same core process regardless of where you’re starting. Here’s how to work through it, whether you’re building a content strategy from scratch or auditing an existing one.

1. Revisit Your SEO Goals

Before you open a keyword tool, get clear on what you’re trying to accomplish. Your keyword strategy should follow from your business goals, not the other way around.

A site prioritizing revenue will have a different keyword mix than one focused on growing organic traffic volume. A brand building topical authority in a new vertical needs different content targets than one trying to hang on to existing rankings. 

Your objectives will dictate the metrics you optimize for and which parts of the keyword funnel you invest in first.

Three common goal types shape keyword priorities:

• Conversion-focused goals call for commercial and transactional keywords. These terms sit at the bottom of the funnel and carry strong purchase or sign-up intent. They also tend to have higher keyword difficulty. That means traffic volumes are often lower, but the quality is high.

• Traffic-growth goals point toward informational keywords with higher search volumes. These terms attract users earlier in the funnel and are generally easier to rank for, though they convert at lower rates.

• Topical authority goals are where keyword clusters shine. These are groups of semantically related terms that together signal depth of expertise to Google. The cluster approach is a longer-term play, but it’s often the only sustainable way to rank for the high-difficulty terms in competitive verticals.

Keep your competition in mind as you match keywords to goals, too. 

If a transactional keyword is out of reach for your domain right now, targeting it could hurt your conversion goals and waste resources. A smarter move is finding long-tail keywords around the same seed and intent as a backdoor into that topic.

2. Keyword Discovery

Keyword discovery is where you build a broad list of potential targets before narrowing it down during analysis. A lot of teams spend too much time here without a clear method. Here’s one that works.

Start by mapping your core topic areas from your audience’s perspective. Consider their pain points and the industry terminology they naturally use. These become your seed keywords,  the starting points you’ll expand through tools.

From there, enter your seed keywords into a keyword tool. 

My SEO tool, Ubersuggest, has a Keyword Ideas feature that gives you dozens of variations to shape the focal point of your content. 

Here’s what it delivers for the seed keyword “hiking boots”:

Source: https://app.neilpatel.com/en/ubersuggest/keyword_ideas/

Run enough seed keywords through the tool to build a list of hundreds of candidates before you start cutting.

Your competitors are a valuable third-party source, too. Pull competitor domains into Ubersuggest’s Keywords by Traffic feature to see which keywords are driving traffic to their pages. This surfaces real gaps in your strategy rather than theoretical ones.

Here’s what you get when you search my domain, neilpatel.com.

One caveat to note is that tools may not yet have reliable volume data for trending or emerging topics. 

Jonathan Hoffer, SEO Manager at NP Digital, notes that “in the case of new trends, they might not appear in a tool, so you’ll have to check social media or forums to see if something is trending.”

Long-Tail Keywords

Long-tail keywords are search phrases of three or more words. They carry lower search volumes than head terms, but they’re more specific. That means they face less competition and tend to attract users with clearer intent, which often translates to higher conversion rates.

“Hiking boots skechers” illustrates the point well. The difficulty score is lower than our seed keyword phrase, meaning it’s easier to rank for. 

As you can see below, Ubersuggest rates “hiking boots” 39 in SEO difficulty vs. 27 for “hiking boots skechers.”

That keyword is still valuable, though, because someone typing “hiking boots skechers” probably knows exactly what they want to buy. That means the odds are good that they’re close to a purchasing decision. 

A page that directly addresses that particular brand is far more likely to rank and convert than a generic “hiking boots” page ever would for that searcher.

The value of long-tail keywords goes beyond traditional SEO.

For starters, voice search queries are naturally long-tail. They’re phrased the way people speak in real life rather than in typed shorthand.

Someone typing might enter “hiking boots waterproof.” The same person using voice search asks, “What are the best waterproof hiking boots for wide feet?”

LLM prompts follow the same conversational pattern. A user asking an AI assistant a question phrases it the way they’d phrase it to a knowledgeable colleague. 

Targeting long-tail keywords in these cases gives you the best shot at matching how your audience searches.

Local Keywords

Local keyword research follows the same core process as broader keyword research. There’s one important distinction, though: Potential competitors and search intent are filtered through geography. 

Someone searching “pizza delivery” in Santa Monica isn’t looking for the same results as someone searching the same term in Chicago. Both are looking to get pizza delivered, yes, but the keyword effectively becomes a different target once location comes into play.

Don’t limit yourself to a single location modifier. 

A pizzeria in Santa Monica can target “pizza delivery Santa Monica” and neighborhood-level variants like “pizza near the pier.” Service-specific combinations like “late night pizza delivery Santa Monica” work, too.

Each geographic variation is a keyword opportunity in its own right.

Local keywords tend to have lower difficulty than non-local ones, but that doesn’t make them uniformly easy. 

Local rankings don’t run on content alone. Your Google Business Profile and the consistency of your name, address, and phone number (NAP) across the web factor in, too.

3. Keyword Analysis

By the end of discovery, you’ll have a long list of potential keywords. Keyword analysis is how you cut it down to a working set.

The primary metrics to evaluate are search volume, keyword difficulty, and search intent alignment.

A tool like Ubersuggest lets you organize all your candidates in a Keywords List and sort by these variables simultaneously, which is faster than evaluating them one at a time.

The right search volume floor depends on your goals. Don’t automatically filter out low-volume keywords. A term with 50 monthly searches and clear commercial intent can be worth more than a 5,000-volume informational keyword with no realistic conversion path.

For keyword difficulty, calibrate your threshold to your domain authority. 

Sites with limited backlink equity are usually better off focusing on terms with difficulty scores under 40. Higher-authority domains have more room to compete for scores of 50 and above. What counts as realistic is site-specific.

After sorting by the numbers, run a Google search on each shortlisted keyword and analyze the search engine results page (SERP) directly. Your goal is to answer two questions:

• Does the content format match what you can produce? If every top-ranking result is a detailed comparison guide and you’re planning a product page, that’s an intent mismatch.

• Does your domain belong in this conversation? Look at who’s ranking. If the top results are all major publications with significantly more backlink equity than your site has, be realistic about your timeline and consider adjusting your target keyword.

You should also consider whether your target keyword generates an AIO. A keyword where an AIO is present doesn’t make it a bad target, but it does change how you measure success. For those terms, landing an AIO citation matters as much as ranking position.

Nikki Brandemarte, Sr. SEO Strategist and Local SEO Team Lead at NP Digital, offers this guidance: “Pay attention to content coverage for specific topic areas. For example, are your SERP competitors publishing multiple blogs that explain the basics of a topic, or a single comprehensive guide? This can help pinpoint gaps in topical authority.”

By the end of analysis, every keyword on your shortlist should clear these bars:

• Measurable search volume
• Relevant to your brand or industry
• A difficulty score your domain can realistically compete for
• Clear search intent alignment
• A content format your site can actually produce

4. Keyword Targeting

Once you have a refined keyword list, you need to decide which keywords to pursue first and which URLs to target them with. 

For prioritization, start with keywords that combine low difficulty with reasonable volume. These are your highest-probability wins. They won’t always be the most valuable keywords on your list, but early traction validates the strategy and gives you ranking data to learn from.

From there, move to high-intent commercial keywords. These carry more difficulty but have the most direct line to revenue. A few hundred visitors from a well-targeted commercial keyword can generate more return than thousands of visits from an informational term.

Finally, layer in top-of-funnel, high-volume informational terms. These are the awareness plays. They’re hard to rank for and have longer time horizons, but they’re important for building topical authority over time.

When assigning keywords to pages, be deliberate about avoiding keyword cannibalization. 

Cannibalization happens when two or more pages on your site target the same or nearly identical keywords. This splits ranking signals, creating competition between your own content. 

It’s one of the more common structural problems in mature content programs. Audit for it before you start mapping new keywords to existing pages. If you find two pages competing for the same term, consolidate, redirect, or clearly differentiate the content before adding more.

5. Keyword Optimization

With your keyword targets set, optimization is how you signal relevance to search engines without sacrificing content quality. Here’s a rundown of what current best practices look like.

• Title tag and H1: Your primary keyword belongs in both. This remains one of the most consistent on-page ranking signals. According to Rankability, 93.5 percent of page-one results use their target keyword in the title or H1.
• URL slug: Use a clean, keyword-inclusive URL. Research shows that URLs that include the target keyword see up to 45 percent higher click-through rates than those without.
• Meta description: Your meta descriptions don’t directly influence rankings, but they do influence clicks. The goal is to include the keyword naturally and give searchers a clear reason to click.
• Body copy: Use your keyword and related semantic terms throughout, but write it for the reader first. Resist the urge to stuff keywords. Density has declined as a ranking factor. Pages in the top 10 today have significantly lower keyword density than those that ranked well even a few years ago. 
• Image alt text: Include your keyword in at least one image’s alt attribute on the page. Alt text serves accessibility and SEO purposes.
• Structured data: Schema markup helps search engines and AI systems understand the content type and context of your page. For competitive keywords, structured data improves your eligibility for featured snippets and AIO citations.
• Content completeness: For any keyword you’re seriously targeting, your content needs to address the topic more thoroughly than what’s currently ranking. That doesn’t mean longer for its own sake. Your piece can be shorter and still outrank what’s currently there if yours is more helpful.

For highly competitive keywords, link building to the specific page will almost certainly be part of the equation. Rankings alone won’t hold in a tough vertical without external authority pointing at the page.

6. Keyword Tracking

Systematically tracking your keyword research is what separates good SEO results from great SEO. 

Rankings change, and competitor or algorithm adjustments can swiftly change the playing field. A tracking system catches those changes before they become problems.

Typically, keyword research tools include a rank-tracking feature that monitors your keyword positions daily and displays ranking distribution or visibility trends across your tracked keyword set. 

Here’s what Ubersuggest’s Rank Tracking feature looks like:

You can track performance separately by desktop and mobile, which is a big plus given how differently Google’s SERPs behave across devices.

The core metrics to monitor are:

• Ranking position
• Organic impressions via Google Search Console
• CTR

CTR is especially worth watching for any keywords where AIOs are present. 

A stable ranking alongside a declining CTR is a signal that an AIO has entered the picture, but don’t panic. This is less a traffic problem and more an opportunity for content optimization. You may be able to go back and refresh that page with long-tail keywords that more properly align with AI search.

For broader keyword programs, tracking AI citation frequency is increasingly worth adding to your reporting stack. Brands cited in AIOs earn 35 percent more organic clicks and 91 percent more paid clicks than brands that aren’t cited on the same queries, according to Seer Interactive. 

Citation is now a meaningful key performance indicator (KPI) alongside position.

The Prompt Research Process: Is It Any Different?

The short answer is yes. Prompt research differs somewhat from traditional keyword research, but the fundamentals overlap.

Prompt and keyword research share the same goal, though: to understand what your audience is looking for and create content that satisfies that need. 

The difference is the interface.

LLM users don’t type compressed keyword strings. They ask full questions and often include specific constraints. 

The prompt below breaks down how each component works together. Notice how far it goes beyond a simple keyword search:

Source: https://www.thevccorner.com/p/guide-writing-powerful-ai-prompts

These added layers change what a good target keyword looks like.

Here’s a practical approach to building prompt research into your workflow:

• Start with your existing keyword list. Take your top commercial and informational keywords and expand them into full-sentence questions. “Email marketing tools” becomes “What’s the best email marketing tool for a small business that already uses Shopify?” 

• Mine community forums and Q&A platforms. Reddit threads and Quora discussions show you the actual language your audience uses when asking for help. These tend to be longer and more detailed than keyword tool data, and that specificity is precisely what LLM prompts look like.

• Use your keywords in LLMs directly. Type your target topics into ChatGPT or Perplexity and observe their results and how they phrase follow-up questions. Those follow-up questions represent the sub-queries the model identified as relevant, which are also the content gaps your pages can fill.

• Monitor brand mention prompts. Tools like Profound track which prompts lead AI engines to mention your brand or your competitors, and how those mentions change over time. This is the closest thing to rank tracking for LLM visibility.

The content strategy implication is to prioritize completeness. 

Content scoring highly on semantic completeness appears in AI-generated answers at a rate 340 percent higher than content that scores lower, according to recent AIO research data. 

LLMs reward content that fully addresses a topic, which is the same thing Google has been rewarding since the Helpful Content updates. The convergence is not coincidental.

Bonus: More Ways to Find Keywords

As your skills grow or you take on more competitive keywords, the tools below are worth adding to your stack to spot opportunities you might otherwise miss. You’ve already seen a little of what Ubersuggest can do, so let’s start there.

Ubersuggest

One sometimes-overlooked part of Ubersuggest is the Keyword Ideas feature’s ability to filter keyword results by suggestions, related terms, questions, prepositions, and comparisons. 

Each filter uncovers a different angle on how people search for your topic (as shown in our hiking boots example).

The Questions modifier is particularly useful for content planning.

The Questions filter alone gives you 120 variations for “hiking boots.” They range from informational queries like “how long do hiking boots last” to commercial ones like “where to buy hiking boots near me.” 

Each has a potential content angle with its own intent and difficulty profile.

It shows you exactly what people are asking about a keyword, giving you ready-made content angles and FAQ targets. 

Ahrefs and Semrush

Ahrefs’ Keywords Explorer provides full SERP analysis in one dashboard. 

One feature worth highlighting is the AI visibility filter in Ahrefs’ Site Explorer, which shows exactly which of your ranking keywords are currently triggering AIOs. That filter turns AIO exposure into a specific, actionable list of keywords you can monitor more closely.

Semrush has integrated AI-specific research tools into its platform, too. 

Its tracking functionality enables you to monitor your brand’s performance across ChatGPT, Perplexity, and Google’s search generative experience (SGE) simultaneously. Plus, its AI sentiment feature tells whether AI-generated responses mention your brand positively or negatively. 

For teams building out an AEO strategy alongside traditional SEO, that cross-platform visibility is difficult to replicate manually.

Many experienced SEOs use multiple tools in parallel, cross-referencing data from Ubersuggest, Ahrefs, and Semrush to build a more complete picture. Because volume figures are estimates and can vary by platform, using multiple tools reduces the risk of making targeting decisions based solely on a single platform’s data.

AnswerThePublic

AnswerThePublic generates question-based keyword ideas from a seed keyword. Enter a topic, and the tool maps the questions people are asking about it, organized by preposition and question type.

The output is useful for building FAQ sections and identifying informational content angles that pure volume-based tools can’t see. 

For example, if you search for “social media marketing,” AnswerThePublic returns questions like “what are the best social media marketing strategies?” and “how to measure ROI in social media marketing?”

Both are strong long-tail targets with real search demand.

LLMs and AI Tools

AI tools have become genuinely useful for scaling keyword research, particularly in the brainstorming and clustering phases.

Take Claude or ChatGPT. You can rapidly expand a seed keyword into related angles and intent clusters. Use the persona component of your prompt to make them think like your target audience.

For example, you might ask an LLM to generate the questions a small business owner would ask before buying a product. Or you might dig into the objections they’d have at each stage of the purchase process. 

LLM output isn’t a replacement for tool-based volume data, but it’s a fast way to surface angles you wouldn’t have thought to search for.

Here’s a sample query I ran in Claude: “What questions would someone ask before buying email marketing software?”

Source: Claude.ai

This is just a small snippet of what it returned. The LLM returned questions across a variety of categories, covering the entire buying journey someone might go through when purchasing email marketing software. 

Doing the same could provide you with long-tail keyword opportunities to reach every segment of your target audience exactly where they are. 

Semrush’s AI-powered keyword clustering tools take this further by grouping related keywords by semantic meaning and search intent. Running your keyword list through clustering before mapping keywords to pages can reveal topical gaps and consolidation opportunities that spreadsheet-based sorting misses.

Of course, you need to keep these tools’ limitations in mind. They’re strong at synthesis and pattern recognition but weaker at providing reliable volume and difficulty data. Use them alongside your keyword tools, not instead of them.

Search Suggestions

Search engines themselves are a free, always-up-to-date resource for keyword research. Google autocomplete, the People Also Ask box, and the related searches section at the bottom of the SERP all surface real query patterns from real users.

Google autocomplete is particularly useful for long-tail discovery. Enter your seed keyword and add a letter:

Source: Google.com

Google will suggest several popular phrases, each of which is a data point about what people search with that keyword as a root. 

People Also Ask (People also search for) displays related questions that Google considers topically connected to your query, often revealing adjacent content opportunities worth targeting independently.

Source: Google.com

FAQs

Conclusion

Keyword research has always been the foundation of SEO. 

What’s changed is the complexity of the environment you’re researching. AIOs have changed how clicks are distributed. LLMs have introduced a layer of search behavior that operates under different rules entirely. And topical authority now matters as much as optimizing individual keywords.

The teams navigating this well aren’t researching keywords in isolation anymore. 

They’re combining traditional keyword analysis with prompt research and monitoring AI citation alongside ranking position. They then use that research to build content strategies around topic clusters rather than individual terms.

The process I’ve outlined here covers all that. If you want to go deeper on implementation, my complete SEO checklist walks through how keyword research connects to the rest of your optimization program. 

If you’d rather have an expert team handle the execution, NP Digital’s SEO consulting services are built for exactly this kind of work and dive into keyword research for your site using the process above.

1. AI Overviews can reduce paid search click-through rates by more than 50 percent for affected queries, making impression share a critical visibility metric.
2. Informational queries are most vulnerable. AI answers resolve research intent directly in the SERP, reducing the number of users who scroll to ads.
3. Transactional and brand queries hold up better. Teams reallocating budget toward high-intent searches see more consistent engagement.
4. Measurement frameworks need to expand. Click-through rate alone no longer tells the full story when impressions rise but clicks fall.
5. Search is no longer a single channel. Brands that extend paid strategy to YouTube, Pmax, Demand Gen, Reddit, TikTok, and AI platforms capture demand earlier and across more touchpoints.

Your impression numbers look healthy. Your click-through rate tells a different story.

For many paid search teams, this is the new reality. AI Overviews now appear at the top of Google search results for millions of queries, answering user questions before they ever reach the ads. Impressions hold steady or climb. Clicks get harder to come by.

Research from Seer Interactive found that when AI Overviews appeared in search results, paid click-through rate dropped to 9.87 percent compared to 21.27 percent on the same queries without an overview. That translates to a 53.6 percent reduction in traffic.

Let’s look into why certain query types are more exposed than others and what paid search teams are doing right now to adapt their strategy, targeting, and measurement.

AI Overviews Are Reshaping the Search Results Page

When Google introduced AI Overviews, it fundamentally changed the architecture of the SERP. The AI-generated summary now occupies the most visible real estate at the top of many search results, answering the user’s question before they interact with anything else on the page.

For paid search, the implications are significant. Ads that once appeared near the top of the page now often appear below the AI summary. Users scroll past a detailed AI-generated answer before they encounter a paid result.

This is not just a visual shift. Seer Interactive’s research found that the presence of an AI Overview correlates with a 12 percentage point decrease in paid click-through rate. Across a full dataset, that translated to a 53.6 percent reduction in traffic compared to searches where no AI Overview was shown.

The core issue: paid search visibility is no longer the same as paid search attention. An impression in a SERP dominated by an AI Overview does not carry the same weight as an impression on a traditional results page.

If teams assume all impressions carry equal value, their performance data will remain difficult to interpret. Impressions go up. Clicks stay flat. Revenue and ad costs become harder to predict.

Understanding this requires analyzing which query types most frequently trigger AI Overviews and the resulting implications for budget allocation.

Why Informational Queries Are Becoming Less Valuable for Paid Search

Not all queries are equally at risk. AI Overviews appear far more often on informational queries than on high-intent queries, and that distinction matters for budget allocation. This is closely tied to the broader trend of zero-click searches, where users get what they need from the SERP itself and never click through to a website.

Now the AI summary answers the question on the spot. The research phase that once sent users scrolling through several pages of results has been compressed into a single AI-generated box. Users read the answer, get what they need, and move on without clicking.

Transactional queries tell a different story. Searches with clear purchase intent, such as pricing inquiries, product comparisons, and demo requests, are less likely to trigger an AI Overview. When they do, ads still perform reasonably well. According to the same Seer research, brand queries with AI Overviews present still generated a 16.36 percent click-through rate, well above the average for informational query types.

The practical implication: budget allocated to queries that consistently trigger AI Overviews is at higher risk of generating impressions without clicks. Identifying which queries in your account fall into that category is a practical first step toward protecting performance.

10 Paid Search Pivots Teams Are Making Right Now

Paid search teams are not waiting for Google to solve this. The following pivots reflect what practitioners are already doing to protect performance and adapt to a more competitive SERP.

Shift Budget Toward Transactional Queries

Informational searches increasingly resolve in the SERP. Queries like “what is a CRM” or “how does ROAS work” are prime territory for AI Overviews, which means fewer users scroll to ads.

Transactional searches behave differently. “Best CRM for small business,” “Salesforce pricing,” and “schedule a demo” queries still generate strong ad engagement. Auditing your campaigns for intent and moving spend away from informational keywords toward conversion-ready queries is one of the most direct ways to protect revenue.

Structure Campaigns Around Intent, Not Just Keywords

Traditional keyword groupings by topic are giving way to segmentation by intent stage. Organizing campaigns into informational, commercial, and transactional buckets allows teams to allocate budget with more precision and adjust quickly as AI Overview coverage expands.

When informational campaigns are isolated from high-intent traffic, reducing or pausing them becomes a cleaner decision. You can act without disrupting the campaigns that are still driving results.

Defend and Expand Brand Search

Brand queries are among the most resilient in an AI-driven search environment. Users searching for your company by name carry strong purchase intent, and brand ads still convert at high rates even when AI Overviews appear.

Without an active brand campaign, competitors can bid on your brand terms and capture that traffic directly. Protecting brand terms is a baseline priority that pays off consistently.

Make Ads More Visually Competitive

Ads appearing below an AI summary need to work harder to earn attention. Every available asset matters. Sitelinks add navigation options. Callouts reinforce value propositions. Structured snippets give product category detail. Pricing extensions answer a buyer’s primary question before they click.

A well-extended ad standing out below an AI Overview will consistently outperform a barebones text ad in the same position.

Write Ad Copy That Moves the Decision Forward

The user who sees your ad has likely already read an AI-generated summary of the topic. Ad copy should not repeat what the AI already covered. It should move the decision forward.

“Get a free audit” does more work than “Learn more about SEO.” Specificity converts when users are already past the information-gathering stage. Copy focused on differentiation, pricing clarity, or a clear next action earns the click that a generic brand message will not.

Expand Competitor Conquesting

AI Overviews frequently name specific products and brands when summarizing a category. After reading a summary that lists top CRM tools, a user often searches immediately for a specific brand’s alternatives or pricing. That is a conquesting opportunity.

Bidding on “[Competitor] alternative” and “[Competitor] vs [Your Brand]” queries reaches users at the moment they are actively comparing options. These searches happen right after the AI Overview has done the initial filtering for them.

Invest More in Remarketing and Audience Targeting

AI Overviews compress the research phase, but they rarely close the decision entirely. Many users read the summary, step away, and return to search again before converting. Remarketing lets you reconnect with those users in that return window.

First-party data becomes more valuable here. Building audience segments from site visitors, email lists, and CRM data gives teams the targeting precision that broad keyword bidding alone cannot provide.

Use Broader Match to Capture Conversational Queries

AI-influenced searches tend to be longer and more natural in phrasing. Users accustomed to conversational AI tools bring that style to their search queries. Exact match lists built for shorter, traditional keyword patterns will miss a growing share of that traffic. Revisiting your paid search bidding strategies with this in mind is worth the time.

Performance Max campaigns and broader match types help capture the longer, less predictable queries that are becoming more common. The trade-off is less control, which makes ongoing performance monitoring more important.

Rethink How You Measure Search Performance

Click-through rate dropping while impressions hold is not necessarily a failure. In an AI Overview environment, it is often an expected outcome. The mistake is treating CTR as the primary health indicator when the SERP environment has fundamentally changed.

Teams shifting their measurement frameworks are tracking impression share, top-of-page visibility rate, branded search volume growth, and assisted conversions alongside traditional metrics. Together, those signals give a fuller picture of what search is actually contributing to business outcomes.

Source: The Media Captain

Diversify Beyond Search Ads

Zero-click trends reduce the available inventory of high-quality search clicks. As explored in the zero-click future of search, search still matters, but it cannot carry the same weight alone that it once did.

Demand Gen campaigns, YouTube, Display, and paid social all help reach users earlier in the funnel before they arrive at Google ready to buy. Search then becomes the capture mechanism for demand built elsewhere. The full paid media mix has to work together more tightly than before.

Paid Search Measurement Is Changing

The instinct to look at click-through rate when paid performance dips is understandable. It is one of the most visible metrics in any search account. In an AI Overview environment, though, it is an incomplete signal.

Rising impression counts with declining click-through rate is not always a campaign failure. It often reflects a change in SERP composition. Search Engine Land’s analysis of paid search teams confirms that AI Overviews are lowering CTR and raising CPCs simultaneously, compressing the buyer journey and requiring a measurement evolution rather than just a performance fix.

Source: Adthena

Impression share tracks how often ads appear for eligible queries. A high impression share with low CTR confirms visibility is strong but engagement is soft. That is a different problem than an impression share problem, and it calls for a different solution.

Branded search volume is a proxy for overall demand. If awareness campaigns and upper-funnel efforts are working, brand search volume should rise over time. It is one of the cleaner ways to confirm whether broader marketing spend is translating into search intent.

Assisted conversions show how search contributes to outcomes that close on a different channel or in a later session. Search often does awareness and consideration work that surfaces in the last-click data of another touchpoint entirely.

Top-of-page rate tracks the share of impressions appearing in the highest-visibility positions above organic results. In an AI Overview environment, that position matters more than it ever has. Semrush’s AI Overviews study found that AI Overview prevalence varies significantly by industry, which means teams with niche-specific data will have an advantage in calibrating how aggressively to adjust their measurement benchmarks.

Source: Semrush

The Bigger Shift: Search Is Becoming an Ecosystem

Google is still the dominant search platform. But as AI SEO continues to reshape how content gets discovered, search as a behavior now happens across a much wider set of surfaces.

Users looking for product reviews turn to Reddit. Short-form how-to content lives on YouTube and TikTok. AI tools like Perplexity and ChatGPT answer research queries directly. Younger audiences often bypass Google for discovery entirely, using social platforms as their primary search interface.

Source: Yewx

For paid teams, search advertising strategy has expanded to match. Visibility on Google still matters. So does presence on the platforms where users form opinions and compare options before they ever open a search bar.

Paid search budgets are increasingly being redistributed to reflect this. Teams that once concentrated the majority of digital spend in Google search are now testing YouTube, PMax, Demand Gen, Reddit Ads, and TikTok in parallel. The goal is not to abandon search but to meet demand at every point it forms.

FAQs

Conclusion

The teams that adapt their targeting, measurement, and channel strategy will find that paid search still delivers. The approach that worked in 2022 or 2024 just needs a serious audit.

AI Overviews have compressed the research phase, shifted where attention falls on the SERP, and exposed the limitations of click-through rate as a standalone KPI. Marketers who recognize those shifts early and adjust accordingly will stay competitive as Google’s search experience continues to evolve.

Search is not disappearing, but the way people use it is. The paid media strategies built for that evolution will outperform those still built for a world where clicking through to a website was the default outcome of every query.

For a deeper look at how paid and organic strategies work together in this environment, explore the complete guide to Google Ads and the SEO strategy guide to see how these channels can reinforce each other. Our Google Ads Grader will also help make sure the ads you do make are best positioned to succeed.