They often need more help than their seasoned colleagues, but overlook DMOs because they’re starting the planning process elsewhere (here’s looking at you, ChatGPT).

Many destination organizations provide complimentary services that directly support meeting success, such as venue sourcing, site-visit coordination, and local vendor connections. But if those services are buried under broad “meetings services” language or hidden behind a general contact form, planners may never realize how much help is available to them.

You don’t need to attempt to convince Gen Z and novice planners to stop using social media, AI tools, or sourcing platforms. You need to make your DMO visible and feel like one of the most useful tools in their meetings and business event planning process.

Go Fish Tourism + Business Events, along with our clients, is conducting proprietary research on Next Gen and Gen Z Meeting Planners.

Our team is continually reviewing the research needed to support our clients’ future needs. If there’s something you’re looking to research deeper, let’s have a chat!

How Gen Z Meeting Planners Research Destinations

Gen Z planners and younger industry professionals are entering business events with a digital-first playbook. They’re accustomed to finding information instantly, comparing options independently, and validating decisions through multiple sources before ever reaching out to a human.

This planning behavior reflects a larger shift in how audiences search for information. Sprout Social’s Q2 2025 Pulse Survey found that 41% of Gen Z turns to social platforms first when looking for information, ahead of traditional search engines at 32%.

Younger business event planners are also incorporating AI into the planning process. A recent PCMA survey found that more than 90% of meeting planners surveyed were using AI in some way to plan events, including for content, destination summarization, logistics, marketing, data analysis, and attendee communication. 

For DMOs, that means your first impression may not happen in a sales conversation. It may happen through a Google result, an AI-generated answer, a LinkedIn post, a short-form video, a planner resource page, or a recommendation from a peer. If your DMO’s value is not clear in those first-impression moments, planners may assume they can move faster on their own (and they will).

How DMOs Can Increase Visibility Before the RFP Stage

The reality that younger planners are starting in new spaces makes early visibility essential. If they’re building shortlists before speaking with destination representatives, DMO marketing has to show up before the RFP stage, not just once the planner is ready to submit an inquiry.

So, how can you meet them where they’re at? Your value should appear across the digital spaces where younger planners research. That includes:

And the content itself needs not just to promote the destination but also to help the planner make progress. 

Think value-adds like a “New to Working With a DMO?” resource, a complimentary services landing page (cross-promoted on social or via email), a downloadable site-visit planning checklist, or a short video explaining how RFP support works with the DMO.

The content should be easy to scan, clear, and specific about what the planner receives. The less a planner has to infer, the more likely they are to see the DMO as useful.

How DMOs Can Better Support Meeting Planners

Traditional destination marketing often leads with features: walkability, hotel inventory, convention space, off-site venues, dining, accessibility, and attractions. Those details still matter, but younger planners also need to understand how the DMO helps them use those assets to create successful outcomes (there’s the shift).

A walkable district is not just a destination feature. It reduces transportation complexity. 

A strong vendor network is not just a local advantage. It helps planners move faster and source more confidently. 

Destination collateral is not just a marketing asset. It helps drive attendance and makes the event easier to promote with less lift on the planner.

These outcomes are important because Gen Z and novice planners may not be evaluating the destination only on what exists. They’re also evaluating the level of support they will receive.

Show them how your destination team can reduce friction, clarify options, and help bring a stronger recommendation to their stakeholders.

Why Local Expertise Still Matters in Event Planning

AI and self-service tools can help planners gather information quickly, but they cannot replace the local insights and judgment of a destination team.

A planner can use AI to generate a list of venues. A DMO can explain which venues actually fit the meeting program’s group type, room block, flow, attendee profile, and transportation needs. Similarly, a planner can search for restaurants. A DMO can recommend reliable local partners for a specific group size, budget, sustainability, or accessibility requirements. A planner can compare hotels. A DMO can help interpret compression dates, district dynamics, and real-time availability.

That human advantage should be more visible in DMO marketing. Younger planners may be digital experts, but that does not mean they want a faceless process.

In fact, Freeman’s 2025 Gen Z research found that 91% of Gen Z respondents consider in-person events one of the best ways to build social and interpersonal skills. That finding is essential for DMOs because it shows younger professionals still crave human connection. The key? Making that connection accessible, useful, and worth the planner’s time.

What Younger Event Planners Expect from Destinations

Younger planners are entering the industry at a time when events are expected to do more than fill rooms. Attendees, sponsors, boards, and internal stakeholders increasingly want programs that feel connected to the host destination, are aligned with organizational values, and are mindful of community and environmental impact.

Skift Meetings’ 2025 Megatrends report identified several shifts shaping business events, including AI-powered event technology, authenticity over aesthetics, sustainability in action, mental health as a priority, multigenerational audience strategies, and local inspiration. 

The alignment happens naturally with the DMO’s role. A destination organization can help planners identify community-based venues, diverse-owned vendors, CSR opportunities, local speakers, neighborhood experiences, cultural institutions, accessibility resources, and sustainability programs. Plus, young planners will appreciate that working with the DMO itself means directly utilizing local resources.

This service story is especially relevant for younger planners who may be responsible for creating events that feel more purposeful and locally grounded.

How Destination Marketing Must Adapt for Gen Z Planners

If younger planners are underutilizing DMO services, the answer is not simply more promotion. It’s clearer positioning across the full planning journey—and knowing where to show up.

Make the DMO easier to understand, easier to trust, and easier to engage by:

A younger planner should not have to understand the DMO model already to benefit from it.

How to Make DMO Services More Visible to Meeting Planners

For Gen Z planners, the DMO should not feel like an extra step (or a forgotten puzzle piece). It should feel like a magical shortcut.

DMOs already provide many of the services planners need most. The next step is making those services impossible to miss.

At Go Fish Tourism + Business Events, we help destination organizations clarify the value of their meetings, build planner-first content strategies, and strengthen their visibility before the RFP stage. If your DMO offers strong support but planners aren’t seeing it, contact us to learn how to build a business events strategy around how young planners actually search, learn, and decide.

Knowing how to create content that ranks in AI search means understanding what those systems are selecting for: extractability, clarity, depth, and demonstrated trustworthiness. This article breaks down how AI search engines work, what signals they evaluate, and the specific tactics that give your content the best chance of being cited.

What It Means to “Rank” in AI Search (And Why It’s Different)

In traditional search, ranking means your page appears as a blue link on a results page. In AI search, ranking means being selected as a source that feeds a generated answer. This shift is one reason many traditional SEO KPIs are becoming less reliable indicators of actual visibility and performance.

The distinction matters because you can rank highly in traditional search and still be invisible in an AI-generated response, and increasingly, that generated response is what users engage with first.

This shift has given rise to Generative Engine Optimization (GEO): the practice of structuring and writing content so that AI systems can extract, evaluate, and reuse it effectively. GEO is not a replacement for SEO; it is an extension of it, applied to a new layer of how search works. For teams looking to operationalize GEO, tools like Fan-Out Queries, Page Optimization, and ORM Configuration can help uncover content gaps, optimize pages, and monitor brand visibility in AI search.

The core difference between the two disciplines comes down to the unit of competition. Traditional SEO optimizes entire pages to rank for specific keywords. AI search evaluates individual passages within pages and pulls from multiple sources to construct a single answer. Your goal is not to be the top result; it is to be one of the trusted contributors whose content earns a place in the assembled response.

How AI Search Engines Work and Choose Content

To optimize for AI search, you need a working model of what happens between a user query and a generated answer. The process is simplified here, but the underlying logic is consistent across platforms.

AI search systems start by crawling web content and breaking it into smaller sections, often called passages or chunks. Each chunk is evaluated independently for relevance to a query, which means a single well-written section of your page can be selected even if the rest of the page is not especially strong for that topic. This is why structure and clarity at the paragraph level matters as much as the overall quality of a page.

Once relevant passages are identified, the system assembles an answer by drawing from multiple sources. The signals that determine whether your content makes the cut include:

The concept worth internalizing here is “citation-worthy content”: a passage so complete and credible that it could stand alone as a reliable answer to the question, even stripped of the surrounding page. That is the standard AI systems are effectively applying when they select content to cite.

If you’re looking for practical frameworks to make content more extractable and citation-worthy, download our guide to AI prompts that help content get picked up in AI-generated answers.

Core Principles of Content That Gets Cited in AI Search

No single tactic produces AI search visibility. What does work is a consistent combination of clarity, depth, and trust built into every piece of content you publish. The following principles are drawn from how AI systems extract and evaluate content — not from speculation, but from the observable patterns in how AI-generated answers are assembled.

Lead With the Answer, Then Expand

AI systems are looking for the answer to the user’s question. If your content buries the key point after three introductory sentences, the system may move on before reaching it. The better approach is to state the direct answer at the top of each section, then follow it with supporting context, examples, or nuance.

This is also better for users. Most readers scanning an article want to confirm quickly that a section contains the information they need before committing to reading all of it. Leading with the answer serves both audiences: the AI extracting a passage and the human deciding whether to keep reading.

Make Content Easy to Extract and Reuse

AI systems process content in sections. A page with clear heading hierarchy, short paragraphs, and well-defined subsections gives those systems more obvious entry points for extraction. A page built around long, undifferentiated prose makes that job harder, and the content is less likely to be selected as a result.

Each section of your content should be self-contained enough to make sense without requiring the reader to have consumed everything that came before it. If understanding your H3 requires memory of a specific sentence from three paragraphs earlier, the section is not as extractable as it could be. Write each major section as if it might be the only part someone reads.

Go Deep on Topics (Not Just Keywords)

Thin content, such as a short page that answers only the surface-level question, performs poorly in AI search because it cannot address the follow-up questions that users frequently have. A page on “what is anchor text” that stops at the definition will lose to a page that also explains how anchor text affects ranking, how to write it well, and what to avoid.

This does not mean writing longer for its own sake. Depth means covering the full logical scope of a topic: the definition, the mechanism, the application, the common mistakes, and the relationship to adjacent concepts.

This approach can have a significant impact on visibility. For example, when we helped MoneyGeek reorganize more than 4,000 pages around stronger topical alignment, clearer entity relationships, and deeper subject coverage, the site saw a 75% increase in clicks and more than 26 million impressions.

Build Trust Signals Into the Content

AI systems draw on E-E-A-T signals when evaluating whether content is citation-worthy. In practice, this means content that makes claims without support is less likely to be selected than content that backs those claims with data, references credible sources, or demonstrates firsthand knowledge of the subject.

Clear authorship helps too. A byline with a brief author bio, a named brand with a documented track record in its field, and content that cites verifiable sources all contribute to the trust signals that make a page more likely to earn a place in a generated answer. Accuracy matters especially for topics that change. Outdated claims undermine the trust signals that freshness and fact-checking reinforce.

Reinforce Context With Entities and Relationships

In SEO and GEO, entities are the specific people, places, tools, organizations, and concepts that populate a topic. When you reference them by name and explain how they relate to each other, you give AI systems a richer map of what your content is actually about beyond just the keywords present on the page.

A page about content strategy that references tools like Google Search Console and Semrush, concepts like topical authority and search intent, and platforms like Google and Bing is more contextually grounded than one that uses only generic language. This is not about name-dropping; it is about writing with precision. The more clearly your content situates itself within the actual ecosystem of a topic, the more confidently AI systems can match it to relevant queries.

Structuring Content for AI Search Visibility

Structure is not just a readability concern; it directly determines whether AI systems can identify and extract the relevant portions of your content. A page that buries its best answers inside undifferentiated paragraphs will underperform a page with identical information that is cleanly organized.

The most effective structural choices for AI search visibility are the same ones that make content easier for humans to scan: question-based headings that match how users actually phrase queries, short sections focused on a single idea, and clear visual separation between distinct points. When each section answers one question completely, the AI system has an obvious, self-contained passage to extract.

Consider the difference in extractability between these two approaches to the same information:

The second version gives an AI system everything it needs to cite your content for that specific query. Lists and definitions work especially well here because they are easy to extract with context intact. Consistent formatting across your site also helps. When your pages follow predictable patterns, AI systems learn to find the answer-bearing sections faster.

Matching Content to Conversational Search Intent

Traditional keyword targeting optimizes for short, often fragmented queries: “meta description length” or “best CMS for SEO.” AI search changes that pattern. Users ask AI tools full questions: “What should my meta descriptions say to improve click-through rates?” or “What’s the difference between a technical SEO audit and a content audit, and which one should I do first?” The specificity is higher, the phrasing is more natural, and often multiple sub-questions are embedded in a single prompt.

Content that performs in this environment is content written for the actual question behind the query, not just the keywords in it. The most reliable way to identify those questions is to look at the sources where they naturally appear: autocomplete suggestions and “People also ask” boxes in Google, internal site search logs, customer support ticket summaries, and sales call notes. These surfaces reveal the language your actual audience uses when they are genuinely trying to solve a problem.

Once you have a clear primary question, map out the follow-up questions that naturally arise from it and address them within the same piece of content. A guide to creating a content calendar should anticipate questions about frequency, format, team workflow, and tool selection — not because those are separate keyword opportunities, but because they are the next logical things a reader will want to know. Satisfying that full arc of intent in a single piece of content makes it more likely to be the definitive source an AI system reaches for.

Using Schema and Technical SEO to Support GEO

Schema markup is metadata embedded in a page’s code that tells AI systems and search engines what kind of content they are looking at and how its parts relate to each other. It does not guarantee inclusion in a generated answer, but it reduces the ambiguity AI systems face when interpreting your content, and less ambiguity means a higher likelihood of correct extraction and citation.

The schema types most relevant for AI search visibility are:

JSON-LD is the preferred implementation method. It lives in a script tag in the page’s head and does not require changes to the visible HTML structure. It is readable by AI systems without affecting how the page renders for users, which makes it the least disruptive way to add structured data to existing content.

Beyond schema, the technical fundamentals still matter. AI systems cannot index what they cannot crawl. Content that lives inside JavaScript-rendered components, behind login walls, or in PDFs without HTML equivalents is less accessible than standard HTML pages. Fast load times and mobile-friendly design contribute to crawlability and quality signals. Clean URL structures and logical site architecture help AI systems understand how your content is organized and which pages carry the most authority. 

Building Authority Across Your Site and the Web

AI systems do not select sources randomly from the pool of pages that could answer a query. They weight toward sources that are widely recognized, frequently cited, and consistently accurate across a topic area. That is an authority problem as much as a content problem, which means the off-page and structural work that builds domain authority in traditional SEO also builds citation likelihood in AI search.

On your own site, the primary lever is topical depth: a cluster of well-linked pages covering a subject from multiple angles signals to AI systems that your domain has genuine expertise in that area, not just a single page optimized for a popular keyword. 

This approach doesn’t just improve traditional search visibility. It also helps AI systems better understand the relationships between topics and recognize expertise at the entity level. For example, our work with Murphy & Prachthauser combined content optimization, semantic alignment, and authority-building efforts to significantly increase visibility and strengthen recognition across search and AI-driven discovery experiences.

Internal linking connects those pages into a coherent topic structure, which helps AI systems map the relationship between your content and the broader subject it covers.

Off your site, the signals are backlinks and brand mentions from credible, relevant sources. A mention in an industry publication, a citation in a research roundup, or a feature in a respected newsletter all contribute to the web of corroboration that AI systems use to validate sources. This takes time to build, and it compounds: a site with a strong backlink profile from authoritative sources becomes progressively more likely to be cited, because the citation itself reinforces the signals that prompted the original selection.

Keeping Content Fresh and Measuring AI Search Impact

AI-generated answers carry an implicit promise of accuracy. When a user asks ChatGPT or Google AI Overviews a question, they expect the answer to reflect current information.

Content that was accurate two years ago but no longer is creates a liability: it may still be cited, but it damages the credibility of the source when the answer turns out to be wrong. Keeping high-priority content current is part of earning and maintaining AI search visibility.

The practical approach is a tiered content maintenance schedule: identify the pages most likely to be cited in AI answers — typically your highest-traffic pages, your most linked-to pages, and your pages targeting time-sensitive topics — and build a quarterly or semi-annual review cycle around them. Adding a clearly visible “last updated” date to those pages also reinforces the freshness signal for both AI systems and users.

Measuring AI search visibility directly is still limited. Most platforms do not yet expose clean data about when your content was cited in a generated answer. The best available proxies are:

As measurement tools mature, these proxies will be supplemented by more direct signals. For now, combining traffic analysis with regular manual checks gives you the clearest picture of where you stand.

This is one of the key challenges uncovered during an AI search readiness audit, where teams evaluate how well their content aligns with AI retrieval and citation systems.

How AI Search Changes SEO (But Doesn’t Replace It)

The fundamentals of SEO, like producing accurate, useful content that earns trust and authority over time, are exactly what AI search systems reward. The core discipline has not changed. What has changed is the emphasis placed on certain elements within that discipline.

Structure and clarity matter more than they did when ranking algorithms evaluated pages primarily as whole documents. Answering questions directly matters more than constructing content around keyword density. The ability to satisfy a full arc of user intent in a single piece of content matters more than optimizing individual pages for isolated queries. None of these are new ideas in SEO, but AI search makes them more consequential.

GEO is best understood as an additional lens applied to content strategy, not a separate practice that competes with SEO. A page optimized for traditional search is well-structured, authoritative, thorough, and technically sound, and is also well-positioned for AI search. The investment compounds across both channels.

How Go Fish Digital Helps Brands Win in AI Search

Most brands are not losing ground in AI search because their content is bad. They are losing ground because their content is not structured, cited, or authoritative enough to compete in an environment where AI systems are making the selection decisions. That is a solvable problem, but it requires working across content strategy, technical SEO, and authority building simultaneously.

Go Fish Digital works with brands at each of those layers. On the content side, that means auditing existing pages for extractability and E-E-A-T gaps, building topic cluster structures that signal deep subject expertise, and producing content designed to satisfy full user intent rather than isolated queries. On the technical side, it means implementing the structured data that helps AI systems interpret your content accurately, ensuring crawlability, and maintaining the site architecture that supports authority signals.

Authority building is where the long-term competitive gap gets created. Earning coverage in relevant publications, securing citations from credible sources in your industry, and building the off-site corroboration that AI systems use to validate sources — this is the work that compounds over time and makes your content progressively harder to displace in generated answers.

If your team is navigating the shift to AI search and wants a clear picture of where your current content stands, what gaps exist, and what to prioritize, that is exactly the kind of work we do. Reach out through our contact form and we’ll dig into the specifics with you.

Key Takeaways

Creating content that ranks in AI search requires a shift in focus from keyword rankings to citation potential. AI systems don’t evaluate pages the same way traditional search engines do; they evaluate passages, extract answers, and assemble responses from multiple sources.

To improve your chances of being included:

The fundamentals of good SEO still matter, but AI search rewards content that is clear, complete, trustworthy, and easy to reuse. Brands that optimize for both search engines and AI systems will be better positioned to earn visibility, citations, and conversions as search continues to evolve.

Building content that performs in AI search requires more than publishing new pages. It requires understanding how AI systems retrieve, evaluate, and cite information. If you’re looking for help improving visibility, strengthening topical authority, or building an AI search strategy, the team at Go Fish Digital can help.

Frequently Asked Questions About Ranking in AI Search

What is Generative Engine Optimization (GEO)?

GEO is the practice of optimizing content for inclusion in AI-generated search results — structuring, writing, and positioning content so that AI systems are more likely to extract and cite it in their answers. It builds on traditional SEO by adding specific attention to extractability, conversational intent, and the trust signals that AI systems weight most heavily. GEO is not a separate discipline from SEO; it is SEO extended to account for how AI-powered search works.

Can you optimize website content specifically for AI tools like ChatGPT?

Optimization is not platform-specific. The signals that lead to citation in ChatGPT, such as clear structure, direct answers, strong E-E-A-T, and topic depth, are largely the same signals that lead to citation in Google AI Overviews and Perplexity. Content optimized for these principles performs better across AI tools broadly, rather than requiring separate strategies for each platform.

What types of content perform best in AI search?

FAQs, how-to guides, definitions, and structured explanations consistently perform well because they are built around discrete questions with clear answers; exactly the format AI systems find easiest to extract and reuse. That said, format matters less than whether the content directly answers the question being asked. A well-structured narrative explanation can outperform a poorly written FAQ if it answers the query more completely.

How do you measure visibility in AI-generated results?

Direct tracking is still limited. The most reliable approach combines monitoring organic traffic trends and click-through rates for signs of AI Overview cannibalization, tracking referral traffic from AI tools that pass it (such as Perplexity), and manually testing your target queries in major AI platforms to see whether your content is being cited. As platforms develop better attribution tools, more direct measurement will become available.

eCommerce category page SEO is probably the most overlooked strategy when it comes to search engine optimization for companies that sell products online. 

Companies hyper-focus on their product pages or pouring resources into blog content, while their category pages are hardly given a second thought — no content, weak title tags, zero internal linking strategy. 

As a result, many expensive and time-consuming SEO initiatives fail to reach their full potential.

With search continuing to evolve in 2026, category pages remain one of the most important levers for driving qualified organic traffic. The good news is that many of the highest-impact improvements are relatively straightforward to implement. If that sounds familiar, let’s talk about why category pages deserve to be your top SEO priority in 2026 and what you can actually do to fix them.

What Are Category Pages?

Category pages — often referred to as Product Listing Pages (PLPs) — are pages on an eCommerce website that organize products into specific categories. Using Solly Baby as an example, categories include collections such as Wraps, Soft Buckle Carriers, Nursing Covers, and Sleep Sets.

Within those broader categories, products may be further organized into more specific groupings. For example, a Sleep Sets category could contain separate collections for Women’s Sleep Sets, Baby Sleep Sets, and Toddler Sleep Sets. This structure helps customers navigate the catalog while also creating opportunities to target more specific search intent.

At the other end of the site hierarchy are product pages, often called Product Detail Pages (PDPs). These pages are dedicated to a single product, such as a specific Solly Wrap colorway or a particular Soft Buckle Carrier design.

To simplify:

This distinction is important because it reflects how most eCommerce websites are structured.

From an SEO perspective, category pages generally fall into two groups:

Category Listing Pages (CLPs) — Broader pages that primarily link to other categories rather than individual products. Using Solly Baby as an example, a “Shop All” page or a high-level collection hub that directs users to Wraps, Carriers, Nursing Covers, and other collections would function as a CLP.

Product Listing Pages (PLPs) — Pages that display products within a specific category. For example, the Wraps collection page would be considered a PLP because it contains individual products available for purchase.

Understanding which type of page you’re optimizing is important because it influences content strategy, internal linking, site architecture, and keyword targeting.

Why Category Pages Dominate eCommerce SEO

Understanding how to categorize your store’s products is essential for SEO because they typically have more traffic potential than any other page type on your site.

While homepages often generate the highest volume of traffic, much of that traffic is branded. Users searching for your company name are already familiar with your brand, making homepage traffic a less reliable indicator of SEO performance.

Blog content can generate significant traffic as well, but it often attracts users earlier in the buying journey. Someone searching for “how to choose running shoes” is typically less purchase-ready than someone searching for “men’s trail running shoes.”

This is where category pages stand apart.

Category pages target high-volume, transactional queries from users who already know what type of product they want and are actively evaluating options.

Despite this, many eCommerce SEO strategies focus heavily on blog content because of its traffic potential or product pages because of their conversion potential. Category pages often receive far less attention, even though they frequently represent the largest opportunity to drive qualified organic traffic and revenue.

For many eCommerce sites, category pages are the most valuable pages to optimize—and one of the most underutilized.

9 Ways to Improve Your eCommerce Category Pages for SEO

Before getting into tactics, a quick note on keyword research: every piece of category page optimization starts with knowing what your customers are actually searching for. 

Not what you call your products internally, not what sounds logical to you — what people type into Google.

This tends to happen more often with B2B keywords where terminology may be out-of-fashion with newer generations of buyers or terms that get used at tradeshows and conventions don’t necessarily represent what typical customers use.

Before you optimize a single title tag or write a single word of category content, use a keyword research tool — Ahrefs, Google Search Console, or even Google’s autocomplete — to confirm you’re targeting the phrases people actually search. Then build everything below around those terms.

1. Optimize Title Tags — Including the Parts Most People Get Wrong

Title tags are one of the most important on-page SEO factors, and on category pages, they’re even more critical because the stakes are so much higher.  A well-optimized title tag on a strong category page can be responsible for thousands of visits per month.

Here’s what actually matters:

Put Your Primary Keywords First

Don’t bury it after your brand name. If someone is searching “men’s trail running shoes,” your title tag should lead with that phrase, not with your company name. Again, your website shouldn’t have any problem ranking for its own branded terms, so those should never take top billing (aside from your homepage – maybe).

Consider Dropping Your Brand Name Entirely

If your category page only sells your own brand’s products, your brand name in the title tag is probably wasted characters. 

Google is unlikely to rank a competitor over you for your own branded category, so you’re not winning anything by including it — and you’re losing space you could use for another keyword.

And if your category page isn’t dedicated to your brand’s own products, there’s even less point to adding your brand name. 

Use those extra characters for other important keywords or terms that will help your clickthrough rate (i.e., “guaranteed”, “free shipping”, “two-day delivery”, etc.).

Test Modifiers

Speaking of your extra characters, check to see which modifiers seem to work best for your competitors.

Words like “Cheap,” “Shop,” and “Buy” can attract different search intents. 

In the past, title tags that used words like “Best” and “Top” were exclusively the domain (no pun intended) of blog posts, but that’s not always the case anymore. Do your due diligence to see if certain modifiers may be the necessary ingredient for higher traffic.

And if you don’t see any of your competitors adding these kinds of modifiers to their category pages, get busy doing some tests. You could discover a competitive edge that unlocks your eCommerce site’s full SEO potential. 

2. Go as Granular as Your Product Catalog Allows

One of the biggest traffic opportunities in eCommerce SEO is creating subcategory pages that target the specific, longer search queries your customers actually use.

Broad category pages such as “Women’s Clothing” often face intense competition from major retailers, marketplaces, and established fashion brands. More specific searches, however, are typically less competitive and often reflect stronger purchase intent. A query like “black flare jeans” or “high-waisted flare jeans” may attract less search volume, but it also creates an opportunity to compete for highly qualified traffic that larger competitors may not be targeting as directly.

The best way to uncover these opportunities is to look at how customers already navigate your inventory. Filters based on size, color, style, material, or other product attributes can often reveal subcategories that deserve dedicated landing pages. In the Willow Boutique example below, shoppers can filter products by attributes such as size and color.

While not every filter should become an indexable page, these navigation options often mirror the same product attributes customers use when searching online. The key question is whether users are actively searching for that specific product grouping and whether there is enough demand to support a standalone page.

Many successful eCommerce brands take a highly granular approach to category architecture. Rather than relying solely on broad category pages, they create indexable subcategory pages around popular product types and attributes that align with real search behavior. In many cases, your existing site filters can serve as a roadmap for identifying these opportunities.

Another useful method is to review the queries that already generate impressions for your category pages but fail to earn clicks. If Google is showing a page for a specific search term, it has already established some level of relevance. For example, if a general jeans category consistently receives impressions for “black flare jeans” but attracts little traffic from that query, it may indicate that searchers would be better served by a dedicated category page optimized around that intent.

That’s a very easy opportunity to create a page and optimize it for a valuable long-tail keyword.

3. Add Content — But Know When to Stop

Even in 2026, I think on-page content still remains one of the biggest missed opportunities for eCommerce companies. Many websites don’t have any at all. They have a Title Tag, an H1, and a list of products, that’s it. 

Unfortunately, that doesn’t give Google a lot to work with. No wonder so many eCommerce companies go years without seeing any traffic on these all-important pages.

Here’s what Google’s John Mueller actually said about category pages with no content:

“When the eCommerce category pages don’t have any other content at all, other than links to the products, it’s really hard for us to rank those pages.”

That being said, Mueller also warned about taking things too far by creating 1,000-word walls of text that get stuffed below the product grid on category pages across the web:

“Our algorithms sometimes get confused when they have a list of products on top and essentially a giant article on the bottom, when our algorithms have to figure out the intent of this page.”

So what’s the right amount? 

A short introductory paragraph — 50 to 100 words — above the product grid is a good opportunity to work in any keywords that may help Google better understand the page.

I also recommend taking this opportunity to add any copy that might encourage a customer to continue shopping. This is another chance to let them know about your shipping policy, guarantees/warranties, or anything else you know your market values (i.e., “made in America”, “family-owned”, etc.).

 However, I also recommend adding plenty of copy beneath the product grid, too. Keeping in mind Mueller’s warnings against going overboard, a text block at the very bottom of the page is a great place to include keyword-optimized content without interrupting the user experience. 

Amongst other things, this is an easy place to include an FAQ that covers popular questions and can even link out to blogs – especially content hubs that could use the boost – that elaborate on the topic in more detail.

Again, the point is not to create a whole blog post down there. This is only going to confuse Google about the point of the page. Stick to relevant content.

If you want a shortcut to figuring out what these FAQs are – and other types of content that would work for a category page – we recently made our own proprietary SEO tool, Barracuda, open to the public. It can do a whole host of important SEO analysis tasks, including helping you optimize the content for your category pages.

4. Be Strategic About How Categories Link to Products

The main job of a category page is to connect customers to products. But how you do that linking has real SEO consequences.

Prioritize Your Most Popular Products

For large stores—say, 50,000+ SKUs—trying to surface every product through a category page dilutes the PageRank that category page could be passing to your best-performing products. Instead of linking to everything through endless pagination, feature your most popular and most searched products prominently on the main category page and use subcategories to organize the rest.

This isn’t just an SEO consideration. A well-organized category page also creates a better user experience. Most shoppers do not want to scroll through hundreds of products to find what they need when a curated selection can help them reach the right products faster. In many cases, improvements to usability and site organization benefit both SEO performance and conversions.

Point Product Links to Canonical URLs

I know this sounds obvious, but it’s a common issue (especially on Shopify sites): product links from category pages can point to URL variants rather than the canonical product page, splitting ranking signals. 

Always double-check that your product grid links go to the right destination. 

Link to the Last Page of the Series

If a category page contains a large inventory, search engines may not efficiently discover every paginated URL by following only the sequential pagination links at the bottom of the page. In many cases, pagination only exposes links to the next few pages in the series, requiring crawlers to move through multiple layers before reaching deeper pages.

This can create crawl inefficiencies on large category pages. For example, if a category contains 20 pages of products, Googlebot may need to navigate through numerous intermediate pages before discovering the final pages in the series.

One way to improve crawlability is to include a link from the first page directly to the last page in the paginated sequence. This allows search engines to access deeper pages more quickly and discover products throughout the series with fewer crawl steps.

This video demonstrates how REI uses this approach to improve the crawlability of large category pages.

Many large eCommerce retailers, including Home Depot and Best Buy, use similar pagination structures to help search engines discover inventory more efficiently.

It’s also important to avoid placing noindex tags across an entire paginated series. Doing so can prevent search engines from discovering products that exist on deeper pages and limit the visibility of those URLs.

5. Build an Internal Linking Strategy Around Category Pages

Internal linking is the most underrated tactic in all of eCommerce SEO, and category pages are where it pays off most. The concept is straightforward: every internal link to a page tells Google that page is relevant and authoritative for its topic. You have more control over internal links than you do over external backlinks, so use that control deliberately.

In general, there are two caveats:

Link From Blog Content to Product Pages

This is actually the main SEO reason I’d argue for maintaining an eCommerce blog. Not because blogs convert (they usually don’t), but because a well-ranked blog post can pass authority to the category pages that do – where conversions usually start.

Write posts that answer questions your customers ask:

And link from each of those posts to your relevant category pages using descriptive anchor text.

Here’s how the Vitamin Shoppe does this to help its category page rank for competitor search terms. They created blogs on the left around oral healthcare to link to their category page that sells oral health products:

Link Between Category and Subcategory Pages

Your broad category pages should link to their subcategories, and where it makes sense, subcategory pages should link to related subcategories. This creates the pyramid structure that Google uses to understand your site’s topical authority.

Of course, your CMS probably does this automatically from the filtering options. (Pic here)

However, I’d still take it a step further and link to some of your subcategory pages in the content under your product grid with optimized anchor text.

Link From High-Performing Product Pages to Relevant Category Pages

You don’t want to give a customer who’s ready to buy a reason to navigate away from your product page. 

But a carefully placed link — at the bottom of the page, or in a “Browse more” section — can pass meaningful authority. Tag these links and monitor whether they’re actually getting clicked, and whether clicks correlate with lost conversions. If they do, remove them.

6. Consider Where Category Pages Live in Your Navigation Bar

Every link in your site’s main navigation bar appears on every page of your website. That means your navigation links receive a massive amount of internal link equity — arguably more than any other links on your site. 

How you allocate that equity matters a lot.

If your navigation includes links to 80 different category and subcategory pages, you’re essentially telling Google “all of these pages are equally important and you need to crawl each of them every time you crawl a page with the navigation bar on it” – which, again, would be every single page. 

That means your highest-priority category pages — the ones competing against strong rivals for high-volume keywords — are receiving the same internal authority boost as subcategory pages that face almost no competition at all.

So, be selective. 

Feature your most competitive, highest-opportunity categories in the top-level navigation. 

Pages that are easy to rank — niche subcategories with low competition — can live deeper in the site and still get found through subcategory links, blog posts, and faceted navigation. They don’t need the SEO boost that comes from a nav link on every page of your site.

Check for 301s

Check that every link in your menu points to the actual destination URL, not a URL that 301 redirects to the real page.

It sounds like a minor technical issue, but when the same redirecting link appears on every page of a 10,000-page site, that’s Google’s crawler wasting significant resources re-following the same unnecessary redirect over and over. Switch the navigation links to point directly to the final destination.

7. Use Canonical Tags Effectively 

Most eCommerce category pages include filters that allow customers to sort products by attributes such as color, size, price range, material, or rating. While these filters improve usability and help shoppers find relevant products more quickly, they can create significant SEO challenges.

Every filter combination has the potential to generate a unique URL. On a large eCommerce site, a category page with multiple filter options can produce thousands—or even millions—of URL variations, many of which contain substantially similar content. Search engines may still attempt to crawl these pages, consuming crawl budget on URLs that provide little unique value and do not need to be indexed.

The right approach depends on the type of filtered page and whether it represents meaningful search demand:

8. Implement Structured Data

Structured data tells Google exactly what your category page contains, which increases the chance of enhanced search results that stand out in SERPs.

As a result, your category page will likely have a higher clickthrough rate. For category pages specifically, three schema types are worth implementing: 

BreadcrumbList: Breadcrumbs reinforce your site hierarchy in Google’s index and can display as breadcrumb trails directly in search results. It helps users understand where the page sits in your navigation and can improve click-through rates. It’s such a simpl —yet extremely effective—site feature that going without it is unacceptable in 2026.

ItemList: This tells Google your page contains a list of products. Combined with the CollectionPage schema type, it signals that the primary purpose of the page is a product collection, not an article or a blog post. This disambiguation matters.

Product schema on featured items: If your category page prominently features specific products (bestsellers, new arrivals, sale items), Product schema on those individual listings can pull review stars and price information into search results.

One important note: don’t add AggregateRating schema to the category page itself. 

Google’s structured data guidelines explicitly say not to apply review markup when the page is a category listing rather than a specific product. Getting this wrong doesn’t just fail to help — it can trigger a manual penalty.

9. Optimize How Your Products Appear on the Page

The product listings inside your category pages are what users actually interact with. 

If those listings don’t give customers enough information to feel confident about clicking through, your bounce rate climbs, Google notices, and, of course, your conversions will suffer.

Here are some easy tips to avoid those consequences:

A High-Quality Product Image

Product images are often the first element shoppers evaluate before deciding whether to engage with a listing. Blurry, low-resolution, inconsistent, or missing images can undermine trust before a customer even reads the product title.

Consistency matters as well. Using a standardized image format—including the same background, angle, and scale—creates a cleaner category grid and makes products easier to compare at a glance.

Where possible, consider displaying multiple product images directly within the category page. Retailers like TaylorMade allow users to preview alternate product images by hovering over a listing, providing additional context without requiring a click-through.

An Accurate, Descriptive Product Title

Product titles should clearly communicate what the item is and highlight the attributes most important to shoppers.

Avoid relying solely on internal product names or SKUs. Instead, use terminology customers recognize and front-load key details whenever possible. For example, “Men’s Waterproof Trail Running Shoes” communicates significantly more information than “Trail Shoe M WP 2.0.”

Dick’s Sporting Goods provides several strong examples of descriptive product titles that quickly communicate product type and key features within category listings.

Star Ratings and Review Count

Displaying ratings and review counts directly within category pages provides immediate social proof and helps customers evaluate products without additional clicks.

A product with 4.7 stars and hundreds of reviews signals credibility before a shopper ever reaches the product page. Making this information visible at the category level can improve engagement and help users make faster purchase decisions.

Price — and Sale Pricing When It Applies

Pricing should be clearly visible within category listings, including both the original and discounted price when a product is on sale.

Prominent sale pricing helps products stand out within the category grid and can encourage additional clicks. If an entire category is discounted, consider using promotional messaging or banners to make that offer immediately visible.

Availability and Shipping Signals

Availability and shipping information can play a significant role in purchase decisions, particularly for shoppers with specific delivery expectations.

Badges such as “In Stock,” “Ships in 2 Days,” or “Free Shipping” provide useful context and reduce friction during the shopping experience.

Variant Previews Where Relevant

For products available in multiple colors, finishes, or variations, previewing those options directly within the category page can improve usability and reduce unnecessary clicks.

Simple visual indicators, such as color swatches, help shoppers quickly determine whether a product is available in their preferred variation before visiting the product page.

Standardizing these elements across category pages creates a more consistent shopping experience. Inconsistent listings—some with reviews, some without; some with complete imagery, others with placeholders—can create friction for users and reduce trust throughout the buying journey.

An “Add to Cart” button on each listing

If a customer already knows what they want, requiring them to visit a product page before adding an item to their cart can introduce unnecessary friction.

Every additional step between product discovery and checkout creates another opportunity for shoppers to abandon the purchase. That’s why many eCommerce retailers now surface “Add to Cart” or “Quick Add” functionality directly within category page listings, allowing ready-to-buy customers to move straight to checkout without an extra click.

As shown in the example below, some retailers make this functionality highly visible with a dedicated “Quick Add” button, while others use a more compact icon-based approach. Both methods help reduce friction and create a faster path to purchase.

This approach is particularly effective for products where customers already know what they want and require little additional evaluation, such as supplements, consumables, replenishment purchases, or frequently purchased products.

When appropriate for the product category, reducing the number of steps between discovery and checkout can improve both user experience and conversion performance.

Treat Category Pages as Your Top Priority in 2026

Category pages are often the most valuable organic assets on an eCommerce website. They target high-intent, transactional searches, connect customers directly to products, and can drive qualified traffic at a scale that product pages and blog content rarely match.

Yet despite their importance, category pages remain one of the most under-optimized areas of many eCommerce SEO strategies.

The good news is that many of the highest-impact improvements are relatively straightforward to implement. Optimizing title tags, improving category page content, strengthening internal linking, refining navigation, and creating more targeted subcategory pages can all contribute to stronger organic visibility and a better user experience.

As search engines continue to prioritize relevance, site architecture, and user intent, category pages will remain a critical component of sustainable eCommerce growth. Brands that invest in these pages today will be better positioned to capture qualified traffic, support conversions, and compete more effectively in organic search.

If you’re looking to improve category page performance, uncover new organic growth opportunities, or build a scalable eCommerce SEO strategy, the Go Fish Digital team can help evaluate your current approach and identify the highest-impact opportunities.

A scalable multi-location SEO strategy creates a repeatable framework for organizing locations, building useful local pages, managing business listings, targeting localized keywords, and tracking results by market.

As search engines place greater emphasis on proximity, business data, and local intent, these fundamentals play an increasingly important role in local visibility and customer acquisition.

Key Takeaways

How Search Engines Understand Multi-Location Businesses

Search engines evaluate individual pages, but they also look at how those pages connect to the larger business. For multi-location brands, that means each location page needs to support a clear relationship between the main brand, the services or products offered, and the specific market that location serves.

Site architecture, internal linking, and consistent business data help reinforce those relationships. Together, they show search engines which pages represent the overall brand, which pages explain core offerings, and which pages are tied to specific locations.

Key signals search engines use to understand multi-location businesses include:

Recommended Site Structure for Multi-Location Businesses

For businesses with multiple physical locations, a hub-and-spoke structure is usually the most scalable approach. The hierarchy may vary based on how many locations the business has and how concentrated they are in certain regions, but the goal is the same: create a clear path from broad location discovery to specific local destination pages.

The Locations Hub Page

The locations hub is the top-level discovery page for the brand’s local footprint. This is typically a page like “Our Locations” or “Find a Location,” and it should help users quickly find the right office, store, clinic, or branch. For search engines, this page creates a central place to understand that the business serves multiple markets.

This page also plays an important internal linking role. Because it links down to state, regional, city, or individual location pages, it can help distribute authority throughout the location structure and make deeper local pages easier to crawl. As users move through the hierarchy, the content becomes more specific, helping them navigate from a broad locations overview to the exact office, store, or branch they need.

For example, Extra Space Storage’s location finder demonstrates this approach by helping users narrow from a broader market search into individual city-area storage facilities and their corresponding location pages. For businesses with a larger geographic footprint, additional layers such as state, regional, or city-level index pages can further organize these locations and provide more context for both users and search engines.

A strong locations hub page should include:

State or Regional Index Pages

Speaking of state or regional index pages, these are useful when a business has enough locations that one main locations page becomes too broad. They create an intermediate layer between the main locations hub and more specific city or location pages.

These pages help organize the site by geography and give search engines more context about how the business scales across different markets. They can also support broader state- or region-level searches when there is enough demand.

A state or regional index page should include:

Example structure:

This structure keeps the hierarchy organized and gives each geographic layer a clear role.

City-Level Index Pages

City-level index pages are helpful in dense markets where a business has multiple locations within the same city or metro area. They give users a single place to compare nearby options and help search engines understand how locations are clustered within a specific market.

These pages can also reduce confusion when several nearby locations serve similar searches. Instead of forcing every location page to compete for the same city-level terms, the city page can act as the broader market page while individual location pages target more specific neighborhoods, addresses, or service areas.

A city-level index page should include:

For example, a business with multiple Atlanta locations may use a city-level page for Atlanta and individual pages for Buckhead, Decatur, Midtown, or other nearby areas.

Individual Location Pages

Individual location pages are the primary destination pages for local intent. Each page should give users the information they need to choose that specific location and give search engines enough detail to understand its relevance, proximity, and relationship to the broader brand.

These individual pages should also reflect the actual offerings of that location. If one office offers a specific service, amenity, practitioner, menu item, or appointment type that another does not, that distinction should appear on the page. These details help users make decisions and give search engines more location-specific context.

Lowe’s provides a good example of this approach.

Within the same market, individual store pages highlight details that help users choose the most appropriate location. In the example above, the S.W. Charlotte Lowe’s page includes store-specific information such as address, hours of operation, contact numbers, available services, and nearby store alternatives. The page also highlights services available at that location, including installation services and in-store or curbside pickup.

These location-specific details help users determine which store best meets their needs while giving search engines clearer signals about the location’s relevance, offerings, and relationship to nearby stores within the same brand network.

Every individual location page should include:

A strong location page supports both ranking and conversion. It should align with the corresponding Google Business Profile and other local listings, including the same NAP details, business category, hours, and destination URL. This consistency helps reinforce trust across the local search ecosystem.

Keyword Localization for Multi-Location SEO

Once your location hierarchy is in place, keyword localization helps align each page with the searches happening in that market. Multi-location businesses typically target four types of local searches:

These keyword groups should map directly to the location structure you’ve established. Individual location pages typically target the most specific local searches, while city and regional pages can support broader geographic terms.

Location-modified and service + location keywords are often the clearest indicators of local intent because they tell search engines both what the user needs and where they want to find it. Searches such as “storage units in Austin,” “physical therapy Buckhead,” or “dentist in Raleigh” typically align with:

When targeting these terms:

For businesses with multiple locations in the same market, more granular targeting can help reduce keyword overlap. For example, a business with several Atlanta-area locations may target neighborhoods such as Buckhead, Decatur, or Midtown rather than having every location compete for the same Atlanta keywords.

Not every local search includes a city name. Queries like “storage units,” “coffee shop,” or “dentist near me” are heavily influenced by proximity and local relevance signals. These searches are not optimized through exact-match keyword usage alone.

Strong performance for implicit local and near me searches is often supported by:

Near me visibility is ultimately a product of local relevance and entity alignment, not just keyword placement.

Listings Management for Multi-Location Businesses

Your location architecture doesn’t stop at your website.

Search engines also use business listings across the web to validate location information and confirm that each office, store, or branch is a legitimate local entity. Consistent information across these platforms reinforces the location structure you’ve built on-site and helps strengthen trust, relevance, and visibility in local search results.

For most multi-location businesses, the highest-priority listings include:

These platforms act as reference points across the local search ecosystem. When business information is consistent across listings and location pages, search engines have greater confidence in the accuracy of that data.

As the number of locations grows, listings management becomes less of a setup task and more of a governance function. Maintaining hundreds or thousands of listings requires standardized processes to ensure information remains accurate and aligned across every platform.

Some key best practices include:

The larger the business footprint, the more important governance becomes. Small inconsistencies can quickly multiply across dozens of locations, making it harder for search engines to trust location data and harder for customers to find accurate information.

How to Set Up Keyword Tracking and Location Monitoring at Scale

Once your multi-location SEO strategy is in place, tracking and reporting help validate whether it’s working. Local rankings can vary significantly based on a searcher’s location, device, and search history, so rank tracking should be viewed as a directional measure of visibility rather than an exact science.

The goal is to identify trends, compare performance across markets, and uncover opportunities for improvement.

Setting Up Keyword Tracking

Keyword tracking should reflect how customers search in each market. At a minimum, businesses should track rankings at the city level, with ZIP-code tracking layered into priority markets where proximity plays a larger role in visibility.

Tracking should also be segmented by device, particularly mobile versus desktop, since local search behavior often differs between the two.

To keep reporting organized, consider tagging keywords by:

Additional best practices include:

Rankings should be monitored at the city level whenever possible. Our location-based search study found significant ranking variation between state-level and city-level searches, reinforcing the need for market-specific tracking rather than relying on a single national or regional ranking.

How to Monitor Near Me Performance

Near me searches behave differently than traditional local keywords because rankings can change dramatically based on where the search takes place. A business may rank highly for a query in one part of a city and much lower just a few miles away.

To better understand these shifts, track near me keyword variations explicitly and monitor rankings from multiple locations within the same metro area. Mobile tracking should be prioritized since near me behavior is heavily mobile-driven and often tied to immediate action.

To validate whether visibility is translating into engagement, pair rank tracking with Google Business Profile performance data such as:

Near me tracking should be treated as a visibility trendline rather than a fixed-rank exercise.

Market and Location-Level Reporting

Multi-location SEO performance should be evaluated at the market and location level, not just at the domain level. This makes it easier to identify which locations are improving, which locations need attention, and where future investment may have the greatest impact.

Key reporting layers often include:

To improve location-level attribution, use UTM parameters on all Google Business Profile links, including website, appointment, and menu URLs. Each location should use a unique campaign parameter so traffic and engagement can be segmented accurately within GA4.

Reporting should ultimately help answer questions such as:

Common Multi-Location SEO Mistakes That Break Scale 

A multi-location SEO strategy is only as strong as the systems supporting it. As the number of locations grows, small issues can quickly compound into larger visibility, reporting, and management challenges.

Some of the most common mistakes include:

These issues can make it harder for search engines to understand the business footprint, connect users to the right location, and accurately measure performance by market. Establishing clear processes for site architecture, listings management, internal linking, and reporting helps create a framework that can scale alongside the business.

Final Takeaways

Scalable multi-location SEO is ultimately about building a system that helps search engines understand where your business operates, what each location offers, and which location is most relevant to a user’s search.

That process starts with a strong location structure, followed by clear contextualization through location pages, internal linking, and business listings. From there, keyword localization helps align pages with local search demand, while ongoing tracking and reporting provide the insights needed to refine performance over time.

Businesses that succeed with multi-location SEO rarely do so because they have the most pages. They succeed because they have a repeatable framework for managing locations, maintaining accurate business data, and creating useful local experiences at scale. The stronger the foundation, the easier it becomes to expand into new markets while maintaining visibility across existing ones.

Building and maintaining a scalable multi-location SEO strategy requires more than creating additional location pages. It requires a framework that connects site architecture, local content, business listings, and reporting into a system that can grow alongside the business.

If you’re evaluating your current location strategy or planning an expansion into new markets, the Go Fish Digital team can help identify opportunities to improve local visibility at scale.

This article is a practitioner’s problem–solution guide for marketing leaders who are under pressure to make social a growth lever. We’ll unpack the eight issues that actually block results — and show how to overcome them in ways that connect to pipeline, revenue, and brand differentiation. No channel-by-channel tutorials or generic tips — just the challenges you face, and what to do about them.

Key Takeaways  

Why B2B Social Media Feels Broken (Even When You’re “Doing Everything Right”)

B2B operates at smaller scale and higher complexity than B2C. Your total addressable audience is measured in thousands, not millions. Buying decisions span quarters, not minutes. And they’re made by committees, not individuals. That combination makes linear cause-and-effect between any one post and closed revenue almost impossible to see in a dashboard.

So you follow the playbook — publish consistently, polish visuals, test formats — and still struggle to trace activity to pipeline. Likes trickle in, followers grow slowly, executives ask for direct attribution, and your team spends more time proving value than creating it. The problem isn’t the posts; it’s misaligned expectations and measurement built for simpler journeys.

Progress starts with diagnosing the real obstacles: reaching a small, specific audience; creating content senior decision-makers respect; standing out on crowded platforms; balancing organic and paid; and, above all, measuring impact across long, multi-touch journeys while running lean. Solve these, and social becomes a force multiplier for demand, brand, and sales.

Challenge #1: Reaching the Right Audience in a Small, Niche Market  

Most B2B brands don’t need millions of followers; they need consistent visibility with a few thousand right-fit buyers across a defined set of accounts. Follower growth and broad reach look good in slides, but they’re weak proxies for influence over specific opportunities and buying groups that matter to revenue.

Account-based realities complicate reach. You’re not just aiming at one title — you’re trying to connect with a web of evaluators, influencers, users, procurement, and executives. Organic reach to that group is naturally limited, and paid targeting only works if your audience definition and offer are precise.

Shift the goal from breadth to depth. Treat social as an always-on channel to stay present with key accounts and roles, not as a public scoreboard. Your platform choices, employee advocacy, executive profiles, and paid filters should all map to the same concentrated audience definition.

Challenge #2: Creating Content Decision-Makers Actually Care About  

Executives don’t log in to be sold features; they’re scanning for sharp points of view that help them make or defend decisions. Most brand feeds default to product updates, light tips, and promotional cycles that feel safe — but not useful to senior buyers managing risk, budget, and change.

Real thought leadership isn’t a slogan; it’s earned by publishing expert takes on real problems, sharing how you solve them, and backing it with customer stories and data. Subject matter experts (founders, product leaders, consultants, architects) carry credibility algorithms can’t fake. Bring their voice to the surface and make it repeatable.

Brand safety often blunts the message. Content that wins with decision-makers is specific, opinionated, and willing to take a stand on trade-offs. If your POV could appear on any competitor’s page, it won’t earn attention in a crowded feed.

Anchor every post to a business problem your buyers actually have: how to reduce implementation risk, accelerate time-to-value, navigate compliance, or capture an emerging opportunity. Use social to model the conversations your sales team wants to have, not to summarize your feature set.

Challenge #3: Standing Out in Crowded Feeds (Especially on LinkedIn)  

LinkedIn is the default B2B arena, and it’s saturated. The same carousels, recycled templates, and generic “growth hacks” crowd feeds. Add a wave of AI-generated sameness and audiences grow numb. More volume just adds to the noise unless your voice is unmistakable.

Differentiation comes from narrative cl  and a recognizable leadership voice, not from chasing every format trend. Decide the three or four themes you want to own for the next year and commit. Build a writing and design style that’s identifiable in two seconds. Make your leaders’ profiles extensions of the brand—not corporate parrots.

When a post could only have come from your company because it reflects your worldview, language, and proof, you’re playing a different game. Consistency of perspective — not posting cadence — is what trains the algorithm and your audience to pay attention.

Challenge #4: Balancing Organic and Paid Social in B2B  

Organic reach is structurally limited for most B2B pages. Without a memorable leadership voice and engaged employee advocates, your content won’t reliably reach the buying groups that matter. But going all-in on paid without a clear ICP, compelling offers, and measurement beyond clicks invites wasted spend and low-quality leads.

Paid begins to make sense when you can precisely define accounts and roles, articulate a problem-solution narrative, and measure outcomes in your CRM, not just ad dashboards. It’s the engine for controlled distribution and controlled learning, especially when paired with strong creative rooted in SME credibility.

Think of organic as trust and narrative infrastructure, and paid as precision distribution. Together, they form a portfolio: organic establishes who you are and what you stand for; paid ensures the right people actually see it when it counts.

Once you’ve established a clear audience and messaging strategy, paid social can help extend reach within key accounts. These LinkedIn Ads best practices cover tactics for improving targeting and campaign performance.

Challenge #5: Measuring ROI Across Long, Complex Sales Cycles  

In B2B, social influence often happens far upstream: a CFO sees your perspective in a leader’s post, a practitioner saves a framework, a VP hears your customer’s story at the right moment. Those touches shape perception but rarely show up as last click. When the opportunity finally appears, the dashboard credits search or direct, social is invisible.

Last-click reporting and channel-isolated dashboards undercount social because they’re built for linear journeys. Real buyers bounce between social, email, events, peers, and search over months. Assisted conversions, view-through influence, and multi-touch attribution attempt to capture this, but none provide perfect certainty — only better approximations.

Instead of forcing social into binary sourced/not-sourced buckets, use tiered KPIs. Track leading indicators that precede opportunities (executive follows, shares within named accounts, content saves), middle-funnel signals (high-intent content consumption, form fills from paid retargeting), and revenue metrics (opportunity creation, pipeline influenced, win rates).

Tie this reporting to the sales cycle length in your category. If your median cycle is 120 days, weekly ROI updates are theater. Report momentum: coverage within buying groups, progression rates, and repeat exposure among target accounts. That’s how social’s real contribution becomes legible to the business.

Marketing impact exists even when measurement is imperfect. Attribution is a model, not a verdict; your job is to reduce uncertainty, not eliminate it.

Challenge #6: Connecting Social Media to Pipeline and Revenue  

Executives don’t buy engagement; they buy outcomes. Likes, comments, and impressions are useful for optimization, but the board cares about pipeline created, pipeline influenced, win rates, deal velocity, and ACV. The shift is from counting reactions to explaining how social moves deals forward.

Integrate social data with your CRM and opportunity records. Map UTM parameters, capture sourced inquiries from paid and organic, and tag contacts who engaged with executive content. Then analyze opportunity creation and progression: how many deals included social touches, did those deals move faster, and did they close at higher rates?

Prioritize lead quality over lead volume. Sales feedback loops — on conversation quality, problem–solution fit, and deal stage progression—will tell you more than raw MQL counts. Build reporting that highlights social-sourced opportunities and social-influenced opportunities with clear narratives your CRO can validate.

Use social as a catalyst across the journey: executive posts to break through at target accounts, paid distribution to expose buying groups to a customer proof point, and retargeting to accelerate consensus. Report the stories behind the numbers so revenue leaders recognize the linkage.

Many marketing teams are shifting away from engagement-focused reporting and toward revenue-centric measurement frameworks that better connect marketing activity to business outcomes.

Challenge #7: Doing More With Limited Resources  

Many B2B social programs live with a familiar constraint: a lean team expected to handle strategy, content, design, distribution, and reporting—often while chasing approvals and SME time. The result is a lot of activity, too little altitude, and creeping burnout.

Budgets restrict creative experimentation, paid amplification, and tooling. Meanwhile, executives still expect coverage across multiple platforms, steady content volume, and airtight reporting. Without ruthless prioritization, the engine stalls or becomes noise.

The fix isn’t hustle; it’s focus. Concentrate effort where your niche is reachable, build repeatable formats that showcase SME credibility, and repurpose anchor assets across channels and levels of the funnel. Collaboration with sales and product turns scarce access into high-signal content.

Challenge #8: Keeping Up With Constant Platform and Algorithm Change  

Playbooks age quickly. Algorithm updates, new formats, and shifting user behaviors can invalidate tactics that worked six months ago. Chasing every tweak burns cycles and leads to erratic results that are hard to explain internally.

AI-driven discovery and recommendation systems are increasing the premium on cl , distinctiveness, and watchable/skim-friendly content. For B2B, this means your ideas and proof matter more than polish. It also means distribution can spike or dip unexpectedly as systems learn what your audience engages with.

AI is already reshaping how content is surfaced, consumed, and evaluated. Explore how social content and strategy are evolving in our brief on AI’s impact on social media.

Compete on adaptability, not checklists. Build flexible pillars and hypotheses, ship small tests, and keep feedback loops tight between marketing, sales, and customer success. Measure learning speed: how quickly you identify a new pattern, adjust the narrative, and scale what works. That resilience beats any single tactic.

Conclusion

Many of the biggest B2B social media challenges stem from audience targeting, content strategy, measurement, and platform alignment. If you’re unsure whether your current approach is helping or hurting performance, a Social Commerce Audit can uncover opportunities across paid social, organic social, audience targeting, creative, and conversion paths.

Request a free Social Commerce Audit to see where your social strategy is falling short and where the biggest growth opportunities exist.

Frequently Asked Questions  

What content should B2B brands publish to engage senior decision-makers?

Content rooted in subject-matter expertise with a clear point of view on real business problems: customer stories with decision criteria and outcomes, evidence-backed industry insights, and practical frameworks that help executives make or defend choices. Keep it specific, opinionated, and concise.

How should B2B leaders balance organic and paid social to drive results?

Use organic to establish narrative and trust via leadership and SME voices, and deploy paid once your ICP and offers are clear and your CRM is set up for beyond-click measurement. Treat them as a portfolio: organic builds credibility; paid delivers precision reach and controlled learning.

How can B2B marketing teams prove social media’s impact on pipeline and revenue?

Integrate social data with your CRM to track social-sourced and social-influenced opportunities, analyze deal progression and win rates, and report tiered KPIs: leading indicators, mid-funnel behaviors, and revenue outcomes. Prioritize lead quality and sales-validated stories over raw volume.

Why is B2B social media harder than B2C social media?

B2B social media is more challenging than B2C because marketers must influence smaller audiences, longer buying cycles, and buying committees rather than individual consumers. Social media teams are also expected to create content that resonates with decision-makers while proving business impact across complex, multi-touch customer journeys. As a result, success depends less on generating viral engagement and more on building credibility, reaching the right stakeholders, and contributing to pipeline and revenue growth.

With Pride Month underway and a new season of All Stars bringing fans back to the runway, we wanted to see which queens Americans can’t stop searching for.

Using Google Trends data from the past 12 months, Go Fish analyzed search interest for winners of RuPaul’s Drag Race and RuPaul’s Drag Race All Stars to determine each state’s favorite champion. Read on to discover which queens are still winners, baby!

U.S. Map of Each State’s Favorite RuPaul’s Drag Race Winner

Trixie Mattel popularized the adage, “The real race begins after Drag Race”, and after her seasons, she’s still leading the pack. She is the most-searched Drag Race winner overall, claiming the top spot in eight states. Her popularity stretched from New England to the Mountain West, with states like Maine, Vermont, Utah, and Oklahoma searching for the Season 7 fan favorite and All Stars 3 winner more than any other champion.

Bianca Del Rio wasn’t far behind, leading seven states. More than a decade after winning Season 6, the comedian continues to draw attention across the country, especially in her home state of Louisiana. Meanwhile, reigning Season 16 champion Nymphia Wind proved that newer winners can compete with franchise legends. Nymphia was the most-searched winner in six states, including California, New York, Oregon, and Washington.

Season 3 legend Raja Gemini rounded out the top four, leading five states. One of the All Stars Season 4 ‘twinners’, Trinity The Tuck, and our current reigning queen, Myki Meeks, each claimed four states, including their home states of Alabama and Florida, respectively.

A few other hometown heroes stood out. Hawaii’s most-searched winner is hometown queen Sasha Colby. Georgia residents searched for Angeria Paris VanMicheals more than any other champion, giving the Peach State a hometown favorite of its own. Yvie Oddley is Colorado’s favorite winner (she’s native to Denver), and Aquaria is the top-searched winner in her home state of Pennsylvania. Ohio’s favorite queen is Onya Nurve, who’s from Canton, Ohio. 

Lastly, a few more interesting callouts. Hilariously, All Stars Season 2 winner Alaska was the top-searched in the state of Alaska. BeBe Zahara Benet, the franchise’s very first winner, is the most popular in Minnesota. Finally, D.C.’s favorite queen is the legendary Jinkx Monsoon, the only queen to be crowned twice. 

Whether your personal favorite is a comedy queen, fashion icon, pageant legend, or lip-sync assassin, the results show that fans across the country are still keeping up with the winners long after the crowns were handed out.

Closing Thoughts

No matter which drag queen is your favorite, whether a winner of RuPaul’s Drag Race, another contestant of the show, or a fabulous queen local to your LGBTQ+ community, we hope you have enough energy to show them all love! From the Go Fish family to yours, happy Pride! 

At Go Fish, Google Trends is one of our favorite tools for crafting Digital PR campaigns. One of the things we love most about search data is its ability to reveal the topics Americans are obsessed with. By pairing publicly available data with a timely cultural conversation, we help brands create content that’s engaging, shareable, and newsworthy. Check out Go Fish’s Digital PR offerings and request a proposal to build your backlink profile! 

Methodology

Go Fish Digital analyzed Google Trends search data for winners of RuPaul’s Drag Race and RuPaul’s Drag Race All Stars over a 12-month period ending in May 2026.

For each state and the District of Columbia, we compared relative search interest among all winners and identified the queen with the highest Google Trends score. Google Trends data measures relative search popularity rather than total search volume, with a score of 100 representing peak popularity for a given search term within a specific location and time period. 

Only queens who won a season of RuPaul’s Drag Race or RuPaul’s Drag Race All Stars were included in this study.

Fair Use

You are welcome to use, reference, and share non-commercial excerpts of this study with proper attribution. If you cite or cover our findings, please link back to this page so readers can view the full methodology, charts, and context.

And while planners remain critical, they are not the only—or even the primary—driver of whether meetings happen in the first place.

If destinations want to grow their meetings and group business, the path forward isn’t doubling down on what worked in the past. It’s a broader, more intentional approach to B2B that influences the full business travel ecosystem.

The B2B Blind Spot: Why Destination Marketing Is Missing the Real Decision Makers

The decision to host a meeting is shaped by a myriad of influential voices. By executives. By finance. By business leaders asking a different question altogether: “Is this meeting worth having?”

But most destination marketing strategies are still built around influencing planners after the decision-making process has already started.

1. We’re Entering the Conversation Too Late

Most DMOs have built their entire meetings strategy around a singular focus: generate RFPs from planners. The challenge is that by the time an RFP is issued, the most important decision has already been made.

The meeting is already approved.
The budget is already allocated.
The destination shortlist is already forming.

If you’re only showing up at that stage, you’re not influencing the decision; you’re competing in it, often with the odds stacked against you. And in that environment, the conversation defaults to what it always has:

That’s a race to the middle.

2. The Real Trigger for Consideration Is Growth

At a recent U.S. Travel Group Travel Network meeting, one insight stood out: The #1 trigger for meetings consideration among executives is new growth opportunities.

That insight aligns with something we’re seeing across our client work: executives don’t “buy” the financial ROI narrative the industry has relied on for years. But they do respond to what we call human ROI:

These are harder to quantify but far more influential in the decision to meet. And they are only realized in one environment: in person.

Why the Business Travel Ecosystem Matters

The demand is there. According to U.S. Travel, group travel as a whole generates $319 billion in annual economic impact and more than 3 million jobs—and business events alone account for $126 billion.

As rapid technology advancement renews the importance of in-person engagement, the category is expanding. But the growth isn’t happening the way it used to. It’s not just about large conventions or citywide events. It’s happening across:

The opportunity is broader and more fragmented than ever. Which means destinations can no longer rely on planner-focused marketing alone to drive growth. The business travel ecosystem now extends well beyond the planner audience, and destination marketing strategies need to evolve with it.

The Industry Misalignment

This is where the industry disconnect becomes visible.

I had the opportunity to speak at the Destinations International 2026 CEO Summit in Newport Beach with more than 65 destination leaders in the room.

We talked about a challenge that every single one of them recognized immediately: the midweek gap. And more importantly, what’s causing it.

For years, we’ve seen a persistent misalignment—but not in the way most people think.

Both sales and marketing are ultimately focused on the same audience: the meeting planner.

Sales is focused there because planners are the ones sending RFPs. Marketing is focused there because they are hoping the marketing will lead to more RFPs, which it doesn’t. So both teams are optimizing for the same moment: when the RFP is already in market.

The result? We’re not influencing the decision to meet. We’re only responding once it’s already been made.

Which means the broader business travel ecosystem—corporate transient, executive decision-makers, and the attendees themselves—never gets the same level of strategic attention. Not the same investment. Not the same innovation. Not the same energy.

And after 15 years of building and running what’s evolved into Go Fish Tourism + Business Events, I can say this clearly: We still haven’t solved it, but we are working on it.

How to Expand Your B2B Approach

Expanding the B2B approach means expanding who destination marketing is built to influence.

That means expanding beyond planners to engage the full business travel ecosystem:

Because each of these audiences plays a role in the final outcome. And right now, most destinations are only actively engaging one of them.

Leverage Leisure to Shape Perception

Engaging the full business travel ecosystem and its distinct audiences is more important than ever, as the lines between leisure and group travel are crossing. 

At Go Fish Tourism + Business Events, we say: Leisure shapes perception. Perception drives consideration. Consideration fuels group business.

Business leaders and executive decision-makers are also leisure travelers. Instead of making the first introduction cold through a business message, consider that leisure messaging helps create a warmer and more qualified B2B prospect pool. 

While some responses to this shifting tide are to separate leisure and business marketing more aggressively, to silo their approaches and philosophies, we see an opportunity to strategically link them.

From Transactions to Influence

The destinations that will lead in the next phase of meetings growth are not the ones that:

They are the ones that influence decisions earlier. That build visibility and relevance before the meeting is even approved. That leverage their leisure marketing for B2B and strategically link them. That position meetings not as logistical events but as business catalysts. That align sales and marketing around shared audiences, shared visibility, and shared outcomes. That’s the shift from marketing to planners to influencing the full business travel ecosystem.

The Bottom Line for Destination Organizations

In-person meetings aren’t going away. If anything, they’re becoming more valuable. Not because of what they cost, but because of what they unlock.

The question for destination leaders isn’t whether to invest in meetings and group business. It’s whether they’re investing in the right strategy to capture it.

Because if we continue to market meetings the way we always have, we’ll continue to compete the way we always have. And that’s not where the opportunity is.

If you’re ready to reach a broader audience and capture more midweek business opportunities, reach out to us today to learn how to get started.

Something changes on your site, and you don’t notice it right away. Then a few days later, performance starts to shift, and now you’re trying to figure out what happened. That’s a pattern most teams run into at some point, especially once a site reaches a certain level of complexity.

The challenge isn’t that changes are happening. It’s that they’re happening constantly, and not always in a way that’s easy to track or connect back to performance. So when something moves, whether it’s traffic, rankings, or conversions, you’re left piecing together what might have caused it after the fact.

Why diagnosing performance changes is harder than it should be

Most sites aren’t static, and they’re rarely managed by a single person or team. In larger organizations especially, too many people often end up touching the same pages over time. Content teams update copy, SEO teams adjust metadata, developers change templates, paid teams launch new landing pages, and sometimes those updates happen without a centralized record of what changed or why.

That’s usually where confusion starts, because when performance shifts later, nobody has a clean timeline to reference. Teams are left piecing together changes from memory, Slack threads, tickets, or scattered documentation.

Content gets updated, metadata is adjusted, templates evolve, and sometimes changes are pushed live without full visibility across stakeholders.

Individually, those updates don’t seem like much. But over time, they stack up, and when performance shifts, it becomes difficult to isolate what actually triggered the change. You end up relying on memory, Slack messages, or scattered documentation to reconstruct a timeline, which slows everything down and leaves room for error.

That’s usually where frustration comes in, because the data shows that something changed, but it doesn’t explain why.

Where most teams lose visibility

The biggest gap isn’t in analytics, it’s in context. You can see that a page dropped in rankings or that traffic spiked, but without knowing what changed on the page, it’s hard to explain the movement with confidence.

This is especially true when multiple updates happen close together. A content refresh, a title change, and a structural update might all go live within a short window, and without a clear record, it’s difficult to separate their impact.

That’s when teams either overreact or do nothing at all, because they don’t have enough clarity to make a decision.

What page monitoring actually is (and how it works)

Page monitoring tracks changes to your site over time and connects those changes to performance data. Instead of trying to reconstruct what happened, you can see it directly, including what changed, when it changed, and how that aligns with shifts in rankings or traffic.

This includes updates to content, metadata, layout, and other on-page elements that influence how a page is evaluated. By capturing those changes consistently, page monitoring creates a timeline that makes it easier to understand cause and effect.

In practice, it becomes a searchable change log for your site. Instead of guessing when a page changed or trying to reconstruct updates manually, teams can quickly see what shifted and how those updates align with rankings, traffic, or conversion changes over time.

It’s less about tracking activity and more about adding context to performance.

Why this matters now, and what it looks like in practice

Performance doesn’t move randomly, even if it feels that way sometimes. There’s almost always a trigger, but without visibility into changes, that trigger is hard to identify.

Sometimes the impact shows up outside of SEO entirely. A dip in paid media performance, for example, can often be tied back to recent landing page updates, messaging changes, or structural adjustments that weren’t properly tracked. Without visibility into those changes, teams end up troubleshooting channels separately even though the root issue lives on the site itself.

That’s why page monitoring matters more as sites grow and teams become more distributed. The more moving parts you have, the harder it becomes to keep track of what’s happening without a system in place.

You can see how this plays out in environments where multiple updates are happening regularly. In our Clean Beauty Collective case study, being able to connect changes to performance made it easier to understand what was working and where to focus next. Instead of guessing, the team could make decisions based on a clear sequence of events.

That’s the shift.

When you can see what changed, you can respond faster, diagnose issues more accurately, and avoid repeating mistakes. It turns performance analysis from something reactive into something more controlled.

How this fits into a broader system

Page monitoring works best when it’s connected to the rest of your workflow. It doesn’t replace optimization or analysis, but it makes both more effective by adding the missing context.

It also creates visibility outside your own site. Monitoring competitor pages over time can reveal which messaging shifts, structural changes, or content updates are gaining traction, which gives teams a clearer sense of what’s actually working in the market instead of relying purely on assumptions.

Page Optimization helps you decide what to change, and page monitoring helps you see the changes over time . Content Similarity ensures those updates actually improve alignment with search intent, while Log Analysis shows how search engines respond to those changes at a crawl level.

You can explore how these pieces connect across the Barracuda Modules, and that’s where the system starts to come together. Each piece answers a different question, but together they create a clearer picture of performance.

Where to start

You don’t need to monitor every page at once. Start with a small set of high-impact pages and track changes over time, paying attention to how those updates align with performance shifts.

Even that limited view can surface patterns quickly, and once you start seeing those patterns, it becomes much easier to scale the process across the rest of the site.

Key takeaways

Frequently asked questions about page monitoring

What is page monitoring in SEO?
It’s the process of tracking changes to a page and connecting those updates to performance outcomes.

Why is tracking changes important?
Because even small updates can impact rankings, traffic, and conversions.

How does this help diagnose SEO issues?
It provides context, so you can see what changed before performance shifted.

Can page monitoring improve results?
Yes, because it helps teams identify what works and avoid repeating ineffective changes.

Where should I start?
Start by tracking a few key pages and comparing changes to performance over time.

Reach Out to Better Understand What’s Changing on Your Site

Performance shifts rarely happen without a reason. The challenge is knowing what changed, when it changed, and whether it actually impacted visibility, traffic, or conversions.

Barracuda Page Monitoring helps teams track website updates over time so they can diagnose issues faster, identify what’s working, and connect site changes directly to performance.

If you want more visibility into how website updates are impacting performance, reach out to learn more about Barracuda Page Monitoring.

Most teams don’t actually have a strategy problem, even if it feels that way when performance stalls. They know they need more variation, more testing, and more ways to show up across platforms, but they can’t produce fast enough to support that. So instead of expanding, they narrow their focus and work with what they already have, and over time that limits what they can learn and how campaigns evolve.

That’s usually where things slow down. Not because the thinking is wrong, but because execution can’t keep up with what the strategy requires.

What’s actually limiting creative performance

Creative performance doesn’t come from a single strong asset, even though that’s still how a lot of teams approach it. It comes from testing different formats, angles, and executions, and then learning from what performs best. The goal isn’t to guess the right idea upfront, it’s to create enough variation that the data can point you in the right direction.

But that only works if you have enough in market. When variation is limited, learning is limited, and when learning is limited, performance tends to plateau. That’s why teams often feel stuck even when they’re doing everything “right.”

Where creative workflows break down

The issue usually isn’t a lack of ideas. Most teams have more concepts than they can realistically produce. The constraint is production, because creating high-quality images and videos takes time, coordination, and often external resources.

So teams prioritize a small set of assets, launch them, and wait to see what happens. That slows everything down, because performance doesn’t come from a single launch, it comes from iteration. And if iteration is slow, the feedback loop is slow, which means improvement is slow too.

What AI creative production actually is (and how it works)

AI creative production is a way to remove that bottleneck by making it easier to generate, adapt, and scale visual assets across formats. Instead of building one asset at a time, teams can take a single concept and turn it into multiple variations, then adapt those variations across channels without starting from scratch every time.

This doesn’t replace creative thinking, it gives it more room to work. When production is faster, teams can explore more directions, test more ideas, and make decisions based on actual performance instead of assumptions.

Why this matters now, and what it looks like in practice

Creative has moved much closer to the center of performance than it used to be, because platforms are increasingly driven by engagement signals. That means what you put in front of people has a direct impact on click-through rate, cost efficiency, and conversion performance.

If you’re only testing a handful of assets, you’re limiting what those platforms can learn, and that shows up quickly in performance. But when production scales, the learning cycle speeds up, and that’s where results start to change.

You can see that clearly in our Na Hoku case study, where the shift wasn’t about finding one winning concept. It was about building a system that could generate and test variations quickly, which made it easier to identify what actually resonated. That approach led to a 30% increase in CTR and more than 3,500% ROAS, not because the idea was different, but because the volume of testing was.

That’s the shift most teams are working toward. Instead of relying on a few assets to carry performance, they’re creating enough variation to let performance emerge.

How this fits into a broader system

Creative doesn’t sit on its own, even though it often gets treated that way. It connects directly to how messaging is developed, how landing pages perform, and how content aligns with what people are actually searching for.

Outlines help define the message before anything is built, so the creative has a clear direction. Page Optimization ensures that what people click into actually matches what they saw, which is where a lot of drop-off happens. Content Similarity keeps everything aligned with how queries are being answered, so the message holds up across channels.

You can see how these pieces connect across Barrauda Modules, and that’s where creative starts to feel less like output and more like part of a system.

Where to start

You don’t need to change everything at once. Start with one idea and push it further than you normally would, creating multiple variations across formats and angles. Then run them and see what actually performs.

That’s usually enough to show you where the gaps are and what direction to take next, and from there the process becomes easier to repeat.

Key takeaways

Frequently asked questions about AI creative production

Why does creative performance depend on variation?
Because performance comes from testing, not guessing. More variations give platforms more data to learn from and improve results.

What is AI creative production?
It’s the use of automation to generate and scale image and video assets quickly across formats and channels.

Does producing more creative actually improve results?
Yes, because it increases the chances of finding high-performing combinations and speeds up optimization.

How does this impact paid media performance?
Stronger creative improves engagement, which typically leads to higher CTR and more efficient spend.

Where should I start?
Start with one idea and build multiple variations, then use performance data to guide what comes next.

Reach Out to Scale Creative Production More Efficiently

Most teams don’t struggle with ideas. They struggle with producing enough variation to learn what actually performs.

Performance Creative helps teams generate, test, and adapt creative faster so they can improve CTR, ROAS, and overall campaign performance without slowing down production workflows.

If you want to create and test more performance-driven creative without increasing production bottlenecks, reach out to learn more about Performance Creative.

Most people form an opinion about your brand before they ever visit your site.

That opinion usually starts the moment they look you up, whether that happens through Google, AI-generated answers, social platforms, Reddit threads, reviews, or anywhere else people go to validate what they’re seeing.

By the time someone reaches your website, they’ve often already started deciding whether your brand feels credible, trustworthy, relevant, or worth exploring further.

Someone looks up your company, product, or leadership team, and within a few seconds they’ve already started deciding whether they trust you. Not because they’ve read your positioning or seen a campaign, but because of what appears around your brand in search results.

That’s what makes reputation management different from traditional SEO.

It often uses many of the same tactics, things like content strategy, authority building, visibility optimization, and search positioning, but the goal is different. Traditional SEO is usually focused on expanding visibility and driving discovery, while reputation management focuses more on shaping perception and controlling the narrative around a brand.

Because of that, the work isn’t just about whether you appear. It’s about what people see, what context surrounds your brand, and what conclusions they draw before they ever engage directly with you.

Why rankings alone don’t tell the full story

A lot of teams still think about search in terms of position. If the site ranks well, visibility feels healthy, and on paper that seems reasonable.

But people don’t experience search one result at a time. They experience the entire page at once.

That includes:

All of those pieces combine into a perception layer that shapes trust, credibility, and intent.

So even if your site ranks first, negative or misaligned content surrounding it can completely change how someone interprets your brand.

That’s why rankings alone don’t tell the full story anymore.

Where brands lose visibility into perception

Most teams monitor reputation reactively. They check branded search occasionally, look at reviews when something escalates, or respond after a negative result gains traction.

The problem is that perception shifts gradually, and small changes often go unnoticed until they start affecting performance.

A comparison article moves up in rankings. A Reddit thread gains visibility. AI-generated results begin pulling in outdated or incomplete information.

Individually, those changes may not seem significant. But together they reshape the narrative around your brand, especially for people discovering you for the first time.

And because those shifts happen across multiple surfaces at once, it becomes difficult to understand what people are actually seeing when they search.

What reputation management actually is (and how it works)

Reputation management is the process of tracking, analyzing, and influencing how your brand appears across search results and discovery platforms.

That includes more than monitoring rankings.

It means understanding:

Instead of asking “do we rank?”, the question becomes:

“What story does the results page tell about us?”

That’s the shift.

Because perception is no longer shaped by your site alone. It’s shaped by the ecosystem around it.

Why this matters now, and what it looks like in practice

Search behavior has changed significantly over the last few years. People move faster, compare more sources, and increasingly rely on summaries instead of deep research.

That means trust forms earlier.

Someone may never click through to your site before deciding whether your brand feels credible, elevated, outdated, trustworthy, or worth considering at all.

AI-driven search accelerates this even further because systems now summarize information directly instead of simply presenting links. Something we’ve been using as a baseline for the SEO/GEO space is this study from Ahrefs showing a 58% decline in click-through rate for search results with an AI Overview. If those summaries rely on weak, outdated, or inconsistent signals, perception can shift quickly without most brands realizing it.

That’s why reputation management has become closely tied to visibility and performance, not just PR.

You can see this clearly in more competitive search environments like our Bandwidth case study, where visibility across high-intent search queries influenced both traffic quality and pipeline. It wasn’t just about whether the company appeared in results. It was about what surrounded those results and whether the overall picture reinforced the brand’s positioning.

That’s the real shift.

Once you start looking at the entire search experience instead of isolated rankings, different priorities emerge. You begin thinking less about individual keywords and more about how your brand is represented across all the places people encounter it.

How this fits into a broader system

Reputation management works best when it’s connected to the rest of your visibility strategy instead of treated like a separate initiative. When aligned with your content, search, and brand efforts, it reinforces consistent signals that shape how people perceive you at every touchpoint.

Content Similarity helps ensure your messaging aligns with how topics are being discussed and surfaced. Page Optimization improves the pages that influence first impressions most directly. Page Monitoring helps identify when shifts in rankings or content begin affecting perception over time.

You can explore how these pieces connect across Barracuda Modules, and together they create a much clearer picture of how visibility, trust, and performance interact.

That’s what makes reputation management more proactive and less reactive.

Where to start

Start by searching your brand the way a customer would.

Don’t just look at your ranking. Look at the entire page and pay attention to what surrounds you.

What themes appear repeatedly? What third-party sources dominate visibility? What impression would someone form in the first thirty seconds?

That gap between how you want to be perceived and what actually appears in search is usually where the work starts.

Key takeaways

Frequently asked questions about reputation management in search

What is reputation management in SEO?
It’s the process of monitoring and influencing how your brand appears across search results and discovery platforms.

Why do search results impact brand perception?
Because people form opinions based on what they see before they click, including reviews, articles, and third-party content.

Does reputation management affect SEO performance?
Yes. Perception influences click-through rates, engagement, and trust, which all impact performance over time.

How do AI search results impact reputation?
AI systems summarize information directly, which means inaccurate or outdated signals can shape perception quickly.

Where should I start?
Start by reviewing your branded search results and identifying what themes and sources dominate visibility.

Reach Out to Understand How Your Brand Appears Across Search

Your rankings only tell part of the story. What people see around your brand often shapes perception before they ever visit your site.

Barracuda Reputation Management helps teams monitor visibility across search, AI-generated answers, reviews, forums, and third-party content so they can better understand how their brand is actually being represented.

If you want a clearer view into how your brand appears across search and AI-driven discovery, reach out to learn more about Barracuda Reputation Management.