The World Cup final took place on Sunday, closing out the most expensive advertising period in years. New data from creator marketing platform Billo shows advertisers’ price of a single video ad rose 17%, compared with the average from July through September 2025. There was an increase in 13 of the 15 e-commerce categories tracked.

Billo, a marketplace connecting brands with video creators, analyzed more than 13,000 ads across 15 categories on Meta, TikTok, and YouTube Shorts. The data points to what small businesses should do now that the tournament premium is lifting: spend on relevance, not volume.

The analysis showed that, unsurprisingly, the category that benefited from the World Cup the most was Sporting Goods. Their relevance helped them to achieve a 28.9% hook rate, making it the highest of 15 tracked categories. Purchases tied to those ads rose 26% over the 2025 monthly average, while click-through rates climbed about 31%.

Donatas Smailys, CEO of Billo, says rising costs and global campaigns leave small businesses with few good options.

“The World Cup creates a battle for attention that goes far beyond the matches themselves,” said Smailys. “Big brands can run campaigns across TV, social media, sponsorships, and creators all at once. Small businesses are chasing the same customers, but they can’t respond by matching that budget.”

Billo isn’t the only one tracking rising ad costs. According to Common Thread Collective, Meta’s cost per thousand impressions, what it costs to show an ad to 1,000 people, hit a four-year high this summer, above $17, up from roughly $12 in summer 2024. WARC expects the World Cup to add $10.5 billion to global ad spending this quarter.

“When advertising gets this competitive, a business really has three choices,” Donatas Smailys added. “Spend more, reach fewer people, or find a more relevant way to get noticed. The third option is what we saw play out in Sporting Goods.”

Sporting Goods Beat Reach with Relevance

Relevance is exactly what saved sporting goods, the category most connected to the tournament. Billo’s data shows sporting goods ads had a hook rate of 28.9%, the highest of all 15 categories tracked, meaning more viewers kept watching past the first few seconds instead of scrolling past. Purchase numbers tied to those ads rose 26% compared with the category’s 2025 monthly average, and click-through rates climbed about 31%.

Sporting goods advertisers also got roughly 15% more revenue per dollar than the overall average, while spending about 16% less per ad than average in other categories.

However the ads for this category were still more expensive than last year. Spend per ad in the category still rose, about 37% above if we compare it to the sporting goods 2025 benchmark.

“Sporting goods matched what people were already watching and talking about. However, the lesson for smaller brands isn’t to bolt a football reference onto every ad,” said Smailys. “It’s finding a real connection between the product and the moment – getting ready for a match, hosting friends, whatever people are already doing.”

The Post-Tournament Playbook

Billo’s advice for the weeks ahead: don’t put everything behind one big ad. Build several shorter versions with different hooks and different faces, test them, then move budget to whichever performs. Target communities that already care about a sport or a team rather than the whole tournament audience.

“Prices drop once the final’s over, and that’s your chance to make back some of what this month cost,” Smailys said. “Post a few ideas organically first and let the audience tell you what’s landing. That signal is free. Give creators a clear brief and let them run with it, then put money behind the one that’s already working.”

Methodology

Billo’s analysis compares advertising performance in June 2026 with the average monthly performance from July–September 2025, the most recent consistent dataset available. The 2026 dataset covers more than 13,000 creator-made video ads across 15 e-commerce categories, compared with 79,347 ads analyzed across the three-month 2025 comparison period. Spend-per-ad figures reflect media costs on advertising platforms, not Billo’s fees. Sporting goods changes were measured against the category’s 2025 monthly average; cross-category comparisons were made within June 2026.

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Artificial intelligence is becoming a competitive tool for lenders seeking to grow small-business portfolios, improve risk selection, and reduce the cost of fraud and manual underwriting. The opportunity is especially significant in segments where traditional credit models may overlook viable businesses because they rely too heavily on limited financial histories, collateral, or conventional borrowing patterns.

Saugat Nayak is a data science and risk analytics specialist with more than 15 years of experience across financial technology, telecommunications, and consulting. His work focuses on machine learning-driven credit risk, real-time fraud detection, behavioral analytics, and AI decision systems deployed in production environments. He has helped examine how alternative data and dynamic behavioral signals can give lenders a more current view of business performance while supporting faster, more consistent decisions.

In this interview, Nayak discusses how financial institutions can use AI to identify creditworthy small businesses that legacy models may miss, reduce false positives in fraud detection, and move risk models successfully from research into day-to-day operations. He also explains why data quality, explainability, model monitoring, and cross-functional adoption are essential for institutions that want to expand lending responsibly while improving efficiency and capturing underserved market opportunities.

Traditional credit scoring has been the foundation of lending for decades. Why do you believe these models often fall short when evaluating small and minority-owned businesses?

Traditional credit scoring was designed in a different era, for a different borrower profile. It relies heavily on credit history, debt-to-income ratios, and collateral, basically metrics that favor established businesses with long financial track records. The problem is that many small and minority-owned businesses simply don’t fit that mold, not because they’re poor credit risks, but because they’ve historically operated outside the systems that generate those signals.

A business owner who bootstrapped their operation, reinvested cash flow instead of taking on debt, or built their customer base through community networks won’t show up well in a FICO-based model. That doesn’t mean they’re not creditworthy but It means the model isn’t asking the right questions.

You’ve spent much of your career developing AI-powered risk models. How are machine learning and behavioral analytics changing the way lenders assess creditworthiness?

The shift I’ve seen is from static snapshots to dynamic patterns. Traditional models look at where a borrower has been. Machine learning lets us look at how they behave and that behavioral signal is often far more predictive than a credit score.

In my work building risk models for SME lending, I’ve seen how variables like cash flow consistency, transaction velocity, seasonal patterns, and even supplier payment behavior can tell a much richer story about a business’s health than a balance sheet alone. Behavioral analytics adds another layer and it captures how borrowers interact with financial products over time, flagging anomalies that indicate risk or, equally important, patterns that indicate reliability that traditional scoring would miss entirely.

What excites me most is that these models get better with data. The more diverse the borrower population I train on, the more nuanced and fairer the model becomes.

Many small businesses struggle to access financing despite having healthy operations. How can alternative data help create a more complete picture of a borrower’s financial health?

Alternative data fills in the gaps that traditional underwriting leaves blank. When I work on credit risk models for small business lending, I look at signals like point-of-sale transaction data, payroll consistency, inventory turnover, and even online review sentiment as proxies for business health. These aren’t exotic data sources but they’re traces that every operating business leaves behind naturally.

For a restaurant, consistent weekend revenue spikes and steady supplier payments tell me far more about viability than a two-year-old tax return. The challenge is building models that can synthesize these signals responsibly, making sure the data is relevant, not just correlated.

AI has the potential to improve lending decisions, but it also raises concerns about fairness and bias. What steps should financial institutions take to ensure these systems remain transparent and equitable?

This is something I think about deeply in my work, especially given the populations these models most directly affect. The first step is acknowledging that bias in AI doesn’t appear out of nowhere but it’s inherited from biased historical data. If my training data reflects decades of discriminatory lending, my model will learn those patterns unless I actively intervene.

Practically, that means building fairness constraints directly into the model development process, not treating them as an afterthought. It means testing model outputs across demographic segments before deployment, not just overall accuracy metrics. And it means investing in explainability, lenders need to be able to tell a borrower why they were declined in plain language, which is both a regulatory expectation and a basic matter of fairness.

Explainable AI isn’t just a compliance checkbox; it’s what makes these systems trustworthy enough to actually expand access rather than entrench exclusion.

Fraud prevention has become increasingly important as financial services continue to digitize. How can AI help organizations detect fraud while maintaining a positive customer experience?

The tension between fraud detection and customer experience is real, and it’s one I’ve worked on directly. The traditional approach, flagging anything that looks unusual and putting it through a manual review queue creates friction that legitimate customers feel acutely, while sophisticated fraudsters find workarounds.

What AI enables is much more precise targeting. By building behavioral baseline profiles for individual users, models can distinguish between a customer who is traveling and making unusual purchases versus a fraudster who has compromised an account. That precision means fewer false positives, which means fewer good customers getting blocked at the worst possible moment. The key is layering real-time scoring with contextual signals like device fingerprinting, geolocation consistency, session behavior, so the system is making decisions based on a full picture, not a single anomaly.

As financial institutions adopt more sophisticated AI systems, what are some of the biggest implementation challenges you’ve seen when moving these models from research into real-world production environments?

The gap between a model that works in a notebook and a model that works in production is where most AI initiatives quietly fail. I’ve seen this pattern repeatedly. In research, data is clean, latency doesn’t matter, and edge cases can be manually reviewed. In production, none of those luxuries exist.

The challenges I see most often are data pipeline fragility, model drift, and organizational readiness. A model trained on last year’s data starts degrading the moment the market shifts and in SME lending, economic conditions can shift fast. Building monitoring systems that catch drift early, and retraining pipelines that can respond quickly, is as important as the model itself.

The other challenge is people getting underwriters, compliance teams, and product managers to actually trust and act on model outputs requires investment in communication and education that most ML teams underestimate.

Looking ahead, How do you see AI reshaping access to capital for entrepreneurs and underserved communities over the next five to ten years?

I’m genuinely optimistic about this, with some important caveats. The next decade will see alternative data and real-time underwriting become standard practice rather than competitive differentiators. That structural shift will meaningfully expand the pool of bankable small businesses, particularly in communities that traditional lending has chronically underserved.

What gives me confidence is that the economic incentive aligns with the social one. There are hundreds of billions of dollars in untapped lending opportunity in the SME segment. Lenders who build models sophisticated enough to identify creditworthy borrowers that legacy scoring misses aren’t just doing good. They’re accessing a market their competitors are leaving behind. That alignment of profit and purpose tends to drive real, sustained change.

What advice would you give financial institutions that want to leverage AI not only to improve operational efficiency but also to expand responsible lending and better serve small business owners?

Start with the problem you’re actually trying to solve, not the technology. I’ve seen institutions invest heavily in AI infrastructure before they’ve clearly defined what success looks like for their specific borrower population and risk appetite. That leads to models that are technically impressive but operationally irrelevant.

The institutions doing this well are the ones treating AI as a continuous capability, not a one-time project. They invest in data quality upstream, they monitor model performance downstream, and they build cross-functional teams where data scientists work alongside credit officers and compliance leads from day one. Responsible lending isn’t a constraint on AI, rather it’s a design principle. The best models I’ve built have been the ones where fairness, explainability, and accuracy were treated as equally important from the very first line of code.

The post Saugat Nayak on How AI Is Helping Lenders Find Creditworthy Businesses Traditional Models Miss appeared first on SiteProNews.

European Digital Sovereignty

European regulators and privacy advocates have grappled with the overwhelming dominance of American tech giants for years. W seeks to change that by ensuring that its entire infrastructure is hosted in Europe, governed by European law, and funded by European shareholders. Zeiter emphasized this during the platform’s launch in Brussels. She also highlighted that Europeans have been providing non-Europeans companies revenue and their personal data.

W aims to keep these resources within the borders of the European Union. This commitment aligns with broader EU initiatives that are designed to reduce dependence on American and Chinese tech giants. There is a strong political movement towards autonomy with European leaders such as Ursula von der Leyen, Antonio Costa, and Christine Lagarde joining the homegrown platform.

Combating AI and Bots

To aggressively combat the flood of bots, AI-generated spam, and disinformation online, W requires users to verify their identity. This is done through a separate app called W Identity, where users must submit a photo of an official passport or national ID card, along with a real-time selfie, before they can post or interact. Users who do not verify themselves can only read content but cannot post anything.

Many believe this is a necessary step to clean up social media and creating a significantly safer online environment. However critics warn that without anonymity people will not be able to freely express themselves, especially for vulnerable individuals who rely on pen names to avoid harassment or political reprisal.

Built on Open Source Technology

W operates on the AT-Protocol, the exact same decentralized, open-source technology that powers Bluesky. This allows W to leverage tried and true social networking technology while customizing it’s ecosystem to fit strict European regulatory standards.

The Future

Taking on behemoths like X, Meta, and TikTok will be a huge challenge. The verification process on W and it’s focus on data privacy will help it but the platform must prove it can scale it’s business beyond tech enthusiasts. Whether or not W becomes the default social media platform for Europe, its launch marks a shift in how Europe and it’s people view the future of the internet.

The post Is W Europe’s Answer to American Social Media? appeared first on SiteProNews.

Bluesky’s Growth

Bluesky’s fast pace growth isn’t an accident, it has positioned itself as different than other established social media companies. Many social media users are looking for platforms that do not harvest their data or try to manipulate them with algorithms. Bluesky has provided a healthier alternative for its users by providing moderation tools and strict policies against using public posts to train AI. Bluesky operates a lot more like email; you own your data and your digital identity. This new approach to social media really appeals to tech-focus, privacy-conscious individuals.

The Future

Even through Bluesky has grown at an incredible speed they need to bridge a massive engagement gap. Bluesky’s daily active user ratio only hovers around 10% and it faces competition from Meta’s Threads, which has a much larger audience. Bluesky may never reach Facebook massive size but it doesn’t need to. It has changed social media by putting it users first with it’s leading privacy and data policies. It might not be the largest social media platform but it is undoubtedly a path for the future of the open internet.

The post Will Bluesky Become the Next Social Media Star? appeared first on SiteProNews.

This is the operating reality of businesses that have moved decisively on AI adoption — and it is backed by numbers that leave very little room for inaction. The question is not whether AI is reshaping how customers discover, evaluate, and buy.

Recently, the International Telecommunication Union (ITU) confirmed that six billion people — three-quarters of the world’s population — are now connected to the internet, up from 5.8 billion just one year prior. That is six billion potential customers living online. The question every business owner must answer is: how visible are you to them, and how well-equipped are you to serve them?

This article provides a section-by-section picture of how AI is changing the specific disciplines that drive online business growth — from search to content, from customer acquisition to personalisation.

Rising Evolution of News and Modern Digital Marketing Landscape

Before exploring specific tactics, it is worth understanding the structural forces creating this moment — because they explain why the changes happening in digital marketing today are not a temporary trend but a durable reset.

The U.S. Census Bureau’s Quarterly Retail E-Commerce Reported that one of the most authoritative sources of consumer digital behaviour — recorded that e-commerce accounted for 16.8% of all U.S. retail sales in Q1 2026, up from 16.1% in 2024 and 15.3% in 2023. Every year, without exception, another slice of consumer spending migrates online. For the full year 2024, U.S. e-commerce sales reached USD 1.19 trillion — an 8.1% increase over 2023.

Consumers now spend, discover, and decide online. The businesses that are winning the largest share of that consumer attention are the ones deploying AI to be more relevant, more responsive, and more present across every digital touchpoint than their competitors.

Integration of AI in Customer Discovery

The channel that drives the most website traffic for the majority of online businesses is search. If the outdated search engine strategy is still built around ranking for keywords and collecting backlinks, then your business is definitely optimising for a version of search that is actively being retired.

For instance, now the Microsoft Copilot answers directly from indexed content. Perplexity and similar AI-native search tools are gaining users who never visit a traditional search results page at all. The practical consequence is that a business that ranks third or fourth for a commercially relevant query may receive near-zero organic traffic if an AI overview satisfies the user’s intent before they scroll down.

This is the reason why SEO services are going though their most significant transformation since the Penguin and Panda algorithm updates of the early 2010s. The discipline is evolving from keyword-density management to what practitioners are calling Answer Engine Optimisation (AEO) — the practice of structuring content so that AI systems will cite, summarise, and surface it in response to user queries.

The businesses winning in this new search environment share several characteristics. Their content answers specific, well-formed questions rather than simply clustering around broad keywords. They use structured data markup (schema.org) so that AI systems can parse their content accurately. They build topical depth — comprehensive coverage of a subject area — rather than isolated pages targeting individual terms. And they invest in brand authority signals that AI systems use as proxies for trustworthiness.

Reason Behind Why Perspective-Driven Content Wins

One of the most consequential misreadings of the AI era is the belief that content production is now a volume game. The AI can write endlessly, so publish more and rank higher. This logic is not only wrong — it is actively destructive to brand authority.

The internet is now flooded with AI-generated text at a scale that was impossible three years ago. Every content category is being filled faster than search engines can evaluate. The content marketing landscape has therefore polarised sharply between two tiers: generic content that gets buried, and authoritative content that gets surfaced, cited, and shared.

The Federal Trade Commission has been explicit about what businesses cannot do with AI-generated content. In August 2024, the FTC finalised its Consumer Reviews and Testimonials Rule, making it illegal to publish fake or AI-fabricated consumer reviews, simulate testimonials, or misrepresent the authenticity of social proof. Enforcement actions have already been filed. The businesses caught on the wrong side of this rule are not fringe bad actors — some are mainstream e-commerce brands that cut corners on content authenticity.

The strategic framework for content in this environment is straightforward. AI can research faster, draft outlines, repurpose existing content across formats, and suggest structural improvements. The human contribution — judgement, experience, proprietary insight — is what makes content worth reading. That combination, applied consistently, is projected to build the significant domain authority that both human readers and AI search systems required.

Customer Acquisition in the New AI Era

Six billion people are now online which is simultaneously the largest and the most demanding customer pool in commercial history. These are people accustomed to Netflix knowing what they want to watch before they search for it, to Spotify building them a personalised playlist, to Amazon anticipating repurchase timing. The bar for what a personalised customer experience looks like has been set by the world’s best-resourced technology companies — and now every business is judged against it.

Around 71% of consumers now expect personalised interactions from the brands they engage with, and 76% report frustration when those expectations go unmet. For online businesses, that frustration does not produce a complaint — it produces a browser tab closure and a visit to a competitor.

The CRM software landscape has been rebuilt around this reality. Modern AI-enhanced CRM platforms do not simply store contact records. They analyse behavioural signals — purchase history, email engagement, on-site behaviour, support interactions — and use predictive models to identify which customers are about to churn, which are ready to buy, and which need a specific message at a specific moment. Businesses using these systems are not guessing at customer needs; they are responding to them in real time.

The same transformation is reshaping the growth and adoption of email marketing. Static, time-based drip sequences — send everyone the same email on day one, day seven, day fourteen — are being replaced by behavioural shift sequences that respond to what a specific contact actually does. A user who go through a pricing page twice in one week or thrice in a month gets a different email than one who has not visited the site in thirty days. AI makes this level of individual responsiveness operationally viable for businesses without dedicated marketing operations teams.

The Rising Evolution of Influencer Marketing

The influencer marketing sector has spent the last five years dealing with a fundamental credibility problem, such as the follower counts that could be purchased, engagement rates that could be fabricated, and attribution that remained frustratingly opaque. AI is solving all three of those problems simultaneously — and similarly making influencer partnerships significantly more accountable and more strategic.

The FTC’s endorsement disclosure guidelines have been updated and actively enforced. Any material relationship between a brand and a content creator — payment, gifted product, affiliate commission, employment — must be disclosed clearly, visibly, and before the audience engages with the content. This is not optional and it is not negotiable. Brands that use AI to manufacture simulated influencer endorsements or fake user-generated content are operating in direct violation of FTC rules that carry substantial financial penalties.

The business opportunity in this space is for brands willing to invest in genuine creator relationships, use AI for the analytical work of finding the right partners and measuring real outcomes, and treat influencer marketing as a long-term audience development strategy rather than a short-term traffic hack.

Why Compliance and Trust Are Becoming Competitive Differentiators

Businesses that treat AI marketing compliance as an exercise are missing a significant strategic opportunity. The brands that establish themselves as trustworthy, transparent operators in an environment full of AI-generated noise will earn a disproportionate share of customer loyalty.

Additionally, the FTC has finalised rules on fake reviews, issued active enforcement guidance on AI marketing claims, and is monitoring how AI-powered advertising systems handle consumer data. The White House’s Executive Order 14365 is establishing a unified national framework that will bring clearer, consistent standards across all states — replacing the patchwork of state-level rules that has created compliance complexity for businesses operating across multiple markets.

For practical purposes, four principles cover the vast majority of what compliance requires:

• Disclose AI involvement in content creation wherever that involvement is material to how a consumer evaluates the content.
• Never fabricate social proof. AI-generated reviews, testimonials, or simulated user feedback violate FTC rules and, increasingly, platform terms of service.
• Substantiate every AI performance claim you make in your own marketing — the FTC has explicitly warned businesses against inflated claims about AI tool capabilities.
• Own your data responsibly. First-party data collection that exceeds legal minimum requirements is both a compliance safeguard and a business asset.

Businesses that lead on these standards, that are transparent before they are required to be — build the kind of customer trust that is genuinely difficult to acquire through any other means.

The post What the AI Boom Really Means for Digital Marketers and Online Business Owners Trying to Stay Ahead appeared first on SiteProNews.

How It Works

The software begins with a built-in Hearing Test designed specifically for users with mild to moderate hearing loss:

1. Launch the test through the iPhone or iPad.
2. The software will use pure-tone audiometry to assess the hearing in each ear.
3. Test results are stored in the Apple Health app and the AirPods will automatically adjust their audio output. This will allow the user to hear specific frequencies they struggle to hear.

After the test is complete, the Apple AirPods make real-time adjustments to improve the users hearing. Users can also improve the software using tools like Conversation Boost, which focuses the AirPod mics on the person directly in front of you. Additionally, users can tweaking the tone, balance, and reduce ambient noise in the settings.

Real Accessibility

Traditional hearing aids can cost thousands of dollars and require professional fittings for proper use. Apple’s Airpods 3 Pro costs less than $400 and provide a cost effective entry point for millions of people. Additionally the AirPods Pro 3, can provide up to 10 hours of battery life in Hearing Aid mode so you can use them all day long.

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Managers are being asked to not only maintain productivity, but also help teams navigate stress and uncertainty and steer the ship during these trying times. Here are a few ways managers may be able to reduce tension and support a more productive workplace:

1. Make positive workplace culture a daily priority

Double down on a positive workplace culture and make it functional piece of each worker’s day. That sense of belonging and camaraderie can have a positive psychological impact on both their own self-esteem and their relationship with work and productivity.

2. Be transparent and communicate often

When people don’t receive all the information they are requesting, they tend to fill in the blanks themselves. When that happens, they often don’t make the kindest assumptions when they feel like information is being held from them. In stressful times, people want to know leadership has a plan. Just as importantly, they want to understand that plan and feel they have some voice in how it moves forward. Having some degree of agency can make tension productive, turning it into a spur to action rather than a purely negative emotion.

3. Address toxic dynamics early and consider outside help

If your workplace culture is less than positive, take that very seriously. At the risk of being self-serving, my advice is to bring in professionals with conflict resolution experience to help identify obstacles and opportunities that lay between the current state of affairs and the one you hope to create, and to lay out a plan to get from here to there. Why not use an inside resource? It’s rare that an insider, no matter how astute or experienced, can view a situation as objectively as an outside professional. Except in rare circumstances, insiders often lack the neutrality and credibility needed to be trusted by all parties involved. 

The topic of workplace tension is deeply complex, shaped by countless personalities, perspectives, backgrounds and interpersonal dynamics. At the workplace, we see a cross-section of people, and each person has a different tolerance for stress and triggers. We see them interact and have to be prepared to adapt our skills and abilities to all types of situations. That’s a big task, requiring supervisors to exercise flexibility, patience and sound judgement. While workplace tensions may be unavoidable during uncertain times, thoughtful leadership, clear communication and early intervention can help stress from becoming lasting conflict.

The post Rising Workplace Tensions: What Managers Can Do to Support Their Teams appeared first on SiteProNews.

The Pocket app allows anyone to create a game. It completely bypasses traditional game development engines. Users just provide a descriptive game idea and Meta’s generative AI does the rest, providing a playable game in seconds.

Gizmos

Meta refers to these AI created games as “Gizmos.” Gizmos are optimized for the smartphone and can use the following:

• Touch controls including tapping, swiping, and dragging.
• Game effects when shaking or tilting the device.
• Sound effects, custom audio tracks, and camera access.

A New Avenue For Meta

Pocket features a discovery feed that allows users to find and play new games built by creators around the world. It also provides a Remix function that allows users adjust other user’s creations by tweaking the original game idea or adding new assets. While the app is not yet widely available in major markets like the US and UK it marks a new avenue for Meta’s AI suite.

The post Create And Play Games with Meta’s New Pocket App appeared first on SiteProNews.

No matter if you’re a restaurant owner, repair shop owner or a law firm, this guide will lead you to a set of clear steps to get more visibility in your local area.

The Google Maps Marketing Context

Google Maps marketing is the technique of making your company more visible, when people look for local services on Google. It begins with your Google Business Profile—the listing that appears in the map results. Google displays a map containing a few businesses listed when a user types in the “plumber near me” query or “best pizza in town” query. The locations of those spots are not arbitrary. Google selects them according to the extent of the business description and trustworthiness.

This is different from regular SEO. You’re not simply optimizing a website. You have a real business listing for your address, hours, photos, reviews and more. All these things can affect whether or not Google displays your business or another’s.

Why Local Search Has Changed How Customers Find Businesses

People used to use phone books or ask friends for recommendations a few years ago. They now remove their phone and they search. Research has indicated that the majority of local searches take place on mobile devices, and that a significant number of mobile local searches result in a visit to a store within 24 hours. That change has revolutionized the way businesses operate locally.

Google maps is a critical determinant at times. There are 3 possibilities on the map that a customer may see. They will consider the star rating, read a few reviews, see the hours and perhaps view photos. This all takes place within one minute. Without a good “image” and ratings, they move on. If it looks good, they select you.

That’s why Google Maps marketing is not something to be considered optional. It’s a place where purchases are made.

The Local Pack and Why You Need to Be in It

This “local pack” is the pack of three businesses that Google displays at the top of local search results. This contains a little map and three listings. This section is prominent over the regular website search results and thus receives a great amount of attention.

One of the best things that a local business could do is get into the local pack. The clicks, calls and visits of the top three businesses are significantly more than those listed lower on the list. Fortunately, you don’t have to spend a ton of money to be there. You must have a good Google Business Profile and a solid local presence.

Below are some of the factors Google considers when identifying which business it will feature in the local pack:

•      Relevance: Do you have a business that fits with what the person is looking for?

•      Distance: How near is your business to the person searching?

•      Familiarity and trust are what’s considered as prominence.

You can impact all three of these factors. Relevance is based on your business description and the categories you select. Distance will not change but the service area can be expanded. Prominence is achieved through reviews, links and business information on the web.

Setting Up and Optimizing Your Google Business Profile

Your Google Business Profile is the support of your Google Maps presence. The first thing one should do, if he hasn’t already done it, is to claim it. Log in to Google Business Profile and claim your business. When confirmed, begin filling in all the sections.

Here are some things to keep in mind:

•      Business name: Use of a real business name. Avoid stuffing in keywords.

•      Category: Select the primary category that most closely matches the content of the text. Include secondary categories, if applicable.

•      Address and phone: Ensure they are identical to what’s listed on your site and any other registries.

•      Hours: Continue to update these including holidays.

•      Website link: Link to your home site or specific site.

•      Description: Your offer must be written succinctly and honestly. Use natural language.

•      Photos: Insert a picture of your location, team and products. Photos attract clicks.

A half-filled profile is a lost opportunity. Each blank area is one way that Google could have someone else ahead of you.

How reviews can contribute to the growth of local businesses

One of the most crucial components of local search ranking is reviews. They also have a direct influence on whether a customer will opt for you or not. A business that has 50 four-star reviews will nearly always be better than a business that has 5 reviews, even if the business is better defined as such.

There are no difficult steps to getting more of them. The best way to do this is to make it a friendly request to customers to leave one. This can be done by a follow-up email, text message or in person. Make it easy by providing them a direct link to your Google review page.

It’s also important to respond to reviews. By responding to a positive review, it demonstrates that you care. If you answer a poor review professionally and in a helpful manner, it demonstrates to prospective customers that you can deal with issues effectively. Google also takes review activity into account when ranking businesses.

Avoid purchasing fake reviews. Google is able to find patterns and it will penalize your listing. Even worse, it undermines trust if customers see it.

Google Posts you can use to stay active and visible

However, many business owners are not aware that they can create posts using Google Business Profile. These are short updates that will be displayed right on your listing in search results. They can be utilized for promoting offers, events, new products, or news.

Posts indicate that your listing is active to Google. An active listing will have a better performance than a stale listing. It is not necessary to post every day but a few times a month is good practice.

Keep it simple with your posts. Include:

•      Clear message on what you offer or share.

•      A picture if one is available.

•      Call to action, such as “Call now” or “Learn more”.

This will take 5 minutes and help keep your listing up to date.

Local Citations and the importance of information consistency

Any reference of your business name, address, and telephone number online is a citation. This includes sites such as Yelp, Yellow Pages, TripAdvisor, and other industry specific sites. Citations include verification that your business is legitimate and reliable from Google.

THE key is consistency. Google gets confused if your address is different on different websites. Small things such as “St.” instead of “Street” or an outdated phone number can have a negative effect on ranking. Make sure that your citations are correct and that they do not have any inconsistencies.

It is also beneficial to create additional citations. Become a member of local and industry directories. The more that your business is referenced online, the more authentic Google feels.

Google Maps Ads for Local Businesses

While organic is great, you can also afford to be in Google Maps via Local Search Ads. These ads are located at the top of map results and marked with a small “Sponsored”. They’re helpful when you’re in an area that is competitive or when you need to be seen more quickly when establishing your organic presence.

Local Search Ads are paid-for per click. You choose a budget, and Google displays your ad to those who are looking for your kind of business around your area. The ads can include your phone number, hours, and directions, which will help customers reach you immediately.

It is best to consider if your business is new, hasn’t earned a ranking organically, or if your business is in a market where there is intense competition for the local pack.

Learning to monitor performance and to identify what works

Google Business Profile comes with built-in insights providing information about your customers’ interactions with your profile and ways they find you. You can see:

•      How many customers visited your business as a result of a direct search on your business name, as opposed to a category search.

•      How many of the people that clicked for directions, called you or visited your website.

•      Any keywords that were used to link to your listing.

•      How often your photos were viewed.

These numbers give you a good indication of what works. When the call volume is not high enough, but the direction volume is, perhaps the phone number should be more conspicuous. If the photo views are not high, perhaps it’s time for better photos! The insights provide a point to focus on for improvement.

Monitor progress on a monthly basis. It takes time to get good results in local rankings, but this data keeps you on track.

When to Get Professional Help with Local SEO

It is possible to manage your Google Business Profile on your own, but it can be a time-consuming process. It’s easy to neglect things when you’re busy working on your business. Posts don’t reply to reviews, posts die and the profile goes stale.

Having a local SEO expert or agency will help make a difference. They take care of the technical things, monitor performance and keep things updated. In competitive markets, this type of assistance can frequently pay off rapidly, due to the fact that it brings in more leads and customers.

For instance, companies that have implemented Fort Lauderdale SEO Services will frequently discover that smart incorporation of professional local SEO along with a robust Google Maps plan can result in measurable increases in telephone calls, traffic, and income. Right support gives you the ability to do this without having to do it all on your own.

There are common mistakes that harm Google Maps rankings

There are a lot of businesses that make the same mistakes that are preventing their listings from being seen. Here are the most frequently found ones:

•      When the business name is overstuffed with keywords, Google will penalize it and it doesn’t look professional.

•      Address with a PO box: Google needs a business address for most businesses.

•      Not verifying the listing: Unverified listings are not visible as much.

•      Not responding to negative reviews: It doesn’t look good on Google, nor with visitors.

•      Name, address and phone numbers should be consistent in NAP information.

•      This directly impacts on which search your business will pop up.

•      No photos: Listings without photos don’t receive quite as many clicks.

The solutions are simple and won’t take very long to complete but the potential for improved rankings is great.

The benefits of Google Maps Marketing can be felt for a long time

Google Maps marketing is not a one-time effort. It’s a continuous process. Those that are successful in local search over time are the businesses that are active in their profiles, respond to reviews, post regularly and actively develop citations over time.

The payoff is real. The more visible you are the more calls, more foot traffic, and more money you will have. You don’t need to pay to have your local presence on the website; it will not stop appearing once you stop paying. A robust Google Maps presence continues to serve you from month to month.

Get it down and dirty: claim your profile, complete all of the fields, solicit reviews, and post regularly. Then, build on that. Google Maps is at the heart of local search, one of the most profitable marketing channels for SMBs.

Final Thoughts

If local businesses don’t pay attention to Google Maps, they’re in trouble. It helps customers choose their destinations and phone numbers daily. The strong presence there means more people locate you before they locate your competitors. The path to reach the site is not difficult. Claim your profile, maintain it, earn more reviews, post regularly, and resolve any conflicts in your business data on the web.

These actions build trust with Google and with customers. Over time, that trust turns into higher rankings, more visibility, and more business. Start with what you can do today, and keep improving from there.

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Design and Customization

The new Meta Glasses come in 26 distinct styles with various colors, lenses, and frames. Meta Glasses are also fully compatible with prescription lenses. The initial launch will offer three distinct frame styles, a classic rectangular shape called Meta Adventurer, a bolder frame design called Meta Fury, and a frame designed with Kylie Jenner called Meta Glasses by Kylie.

Muse Spark AI Features

Meta Glasses are powered by Muse Spark and developed by Meta Superintelligence Labs. The Muse Spark AI assistant is available via a dedicated button on the glasses. The AI assistant is available to help users with local recommendations, schedule management, or location questions.

Additional Hardware Features

Audio and Mic: Open-ear speakers that allow users to listen to media or take calls and the advanced mic provides built-in noise reduction that ensures quality voice calls and commands.

Hands-Free Capture: Enables users to take video or photos on the go.

Battery Life: Over 8 hours of standalone battery life, supplemented by a portable charging case that provides up to 40 hours of additional charge.

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A recent study from the British Medical Journal revealed that 85% of Australian children aged 12 to 15 were still actively using social media three months after the ban started. 66% of these children bypassed the restrictions by lying about their birth year or uploading a selfie that was mistaken accepted as being over 16 by an automated verification system.

The government in Australia has stated it will take legal action against the five largest social media platforms for not enforcing the ban. Some social media companies are pushing back against the ban including Reddit, who is launching a free speech challenge in Australia’s High Court.

The social media ban in Australia has shined an light on the dangers of social media for children. Parents are now more willing to monitor their children’s online activity, and social norms around an acceptable age for using social media and smartphones is changing. The world will continue to watch as Australia leads the way.

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The Shortage of Memory and Storage Chips

The reason for the price increases is a severe shortage of memory and storage chips. This shortage is related to the rapid growth of AI data centers, which has caused an unprecedented demand for memory. Memory manufacturers such as Samsung and Micron have been hard pressed to keep up with this demand, leaving far less supply for consumer electronics companies like Apple. Apple’s CEO Tim Cook described the rising in costs as “unsustainable” and stated that product price increases had become “unavoidable”.

Future Outlook

While Apple’s iPhone and the Apple Watch have been spared from the most recent price hikes, this is unlikely to last. It is widely expected that Apple will raise prices for its new iPhone and Apple Watch lines when the devices are announced in the fall.

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In many cases, the factors that impact replacement costs are rarely driven by a singular problem. Beyond the market conditions causing rises in labor and material prices, installation quality can also have a significant effect on a roof’s replacement cost and lifespan. If a roof is poorly installed, it can lead to serious damages to inventory, machinery, and assets sooner than expected while posing a safety hazard for workers and raising reparation costs. Another issue caused by a leaky roof is moisture penetrating the roofing system. Water that enters important sections of a roofing system and damages its structure can create a bigger repair job that leads to more expensive costs. 

Sometimes the size of the building can have a great effect on roofing expenses. Replacing a roof on a warehouse that is about 17,500 square feet will cost less than doing the same thing on a warehouse that is more than 4 million square feet. Increases in square footage means more material, labor, and time will be needed to complete the roofing work and end up hiking the price to possibly millions of dollars. 

While larger buildings are more likely to require a greater investment, replacement costs are also affected by the choice of roofing system. Even two commercial buildings that are close in size can vary quite differently when it comes to replacement costs depending on whether the roofing system is built-up roofing, single ply, or standing seam metal roofing. The specific roofing choice subsequently influences how that roof is installed. Systems can rely on different attachment methods, ranging from mechanical fastening to ballast to secure the roofing materials, with each requiring varying amounts of labor and time commitment that can affect both upfront costs and long-term maintenance costs. 

When it comes to commercial roofing for businesses, they also need to satisfy industry roofing requirements based on the operations. For example, a hospital would prefer a different roof compared to a restaurant. Industry roofing requirements influence what roofing systems and installation methods specific businesses need to use and therefore affect the final roofing price. In some cases, there may even need to be additional change orders made during the installation process if unforeseen construction challenges present, which in turn will affect the original plans and expenses. 

One way to reduce unnecessary expenses is to choose the right roofing system from the very beginning. Additionally, it is important to determine the right management plan after installation is complete. Conducting routine inspections and maintenance plays a big role in how long a system lasts and its overall costs. Keeping drains clean and removing buildup from snow or ice can further alleviate the need for expensive repairs later. But even with proactive maintenance, roofing issues cannot be completely avoided. Damage can still occur when other trades like plumbing and solar access the roof and make uncertified installs or conduct improper maintenance procedures. 

A well-maintained roof can provide even more benefits beyond an extended lifespan. When maintenance records are properly documented, they make it easier to understand a roof’s condition and reassure insurers that the property is being managed responsibly. 

Even with regular maintenance a roof can still encounter issues that lead to damage. So businesses often need additional protection in the form of warranties, which can increase upfront costs. However, a good roof warranty can last a long time while providing protection against really extensive damage and increasing the value of commercial facilities. Businesses can choose between a manufacturing warranty that typically covers defects in the roofing materials, or a workmanship warranty that addresses issues associated with the installation work. 

When deciding on the best warranty, the best option for businesses is to get both a manufacturing and workmanship warranty from a reliable warranty provider. It is crucial for businesses to follow warranty requirements as well since failing to do so can jeopardize coverage. Unauthorized roof modifications, poor maintenance practices, and undocumented services can all affect warranty eligibility and reduce the value of the warranty leading to even greater costs. 

Commercial roof replacements do not immediately become expensive the day they need a replacement. The expenses build up over time through multiple decisions like the roofing system, installation technique, maintenance practices and warranty choice which all influence how long a commercial roof can last. While rising labor and material costs are out of our control, businesses that focus more of their attention on a long-term approach to roof management are more likely to avoid premature replacements and reduce unexpected repair expenses.

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Credit scores are absolutely not fixed numbers, and may differ more than people realize. Several people who compared their scores from the various reporting agencies noticed that at least one of the scores differed by about 10 points. Others had a score that differed by at least 20 points while certain cases found a score that differed by 40 points or more. This means many consumers’ credit scores could look different depending on which reporting agency’s report is used, either making their credit scores look weaker or stronger than they actually are. With the tri-merge standard, this discrepancy is reduced by using more than one data source to determine a reliable credit score that accurately portrays a borrower’s financial profile. 

It may seem like a 20-point difference in credit scores is not too important. But when considering a mortgage loan, the smallest difference in credit scores can mean putting someone within a different credit range or even tier. These changes can then affect one’s interest rates, loan pricing, mortgage insurance costs, and overall borrowing costs. And these changes are not small. A move to a different credit range can increase costs by thousands of dollars over the life of the loan. So depending on just a single data source may result in a borrower being priced incorrectly. 

Furthermore, each of the reporting agencies not holding the exact same information means some tradelines are absent from several reports, payment histories will have inconsistencies, and risk indicators might go unnoticed. Using just one reporting agency makes it highly likely that some important financial information might be missing from the final credit score. But with a complete data set, blind spots can be reduced and a more accurate evaluation of borrower risk is produced. 

A non-tri-merge standard approach creates a situation where people may gravitate towards “score shopping”, which refers to the phenomena where borrowers or originators pick the credit score that produces the best lending outcome. It is estimated that about 9% of consumers could potentially inflate their apparent credit score by 20 or more points if they use the highest available score instead of the tr-merge standard method. Unfortunately, if more people are inclined to “score shop,” this could dilute the overall risk performance and make risk assessment more inaccurate and difficult to do. 

If credit scores are no longer reliable, this could lead investors to respond unfavorably as these investors rely on accurate credit data to estimate risk, expected returns, and financial performance of borrowers. If credit scores introduce increased unpredictability, investors may view mortgages as riskier and demand higher returns to compensate for the risk. As a result, borrowers will suffer from higher interest rates. 

Some think that using fewer data sets to create a credit score could reduce costs. Although obtaining fewer reports can lower initial expenses at first, this will be short-lived. A large financial burden will be put on lenders in the form of “unrecouped fallout,” which refers to applications that enter the mortgage credit lending process but never end up closing. In these cases, lenders will have wasted time and resources evaluating loans that will lead to lost costs when the transactions do not finalize. Instead of reducing data sources, lenders can gain better savings if they use techniques such as using soft credit pulls early in the process, providing reliable cost estimates, and improving the overall borrower qualification screening. 

It is interesting to note that lower-scoring borrowers experience more of a score discrepancy between the top reporting agencies than higher-scoring borrowers. So reducing available data could significantly affect those whose credit profiles are already harder to evaluate accurately. A fuller data set can make risk evaluations more accurate for these borrowers and provide lenders with more confidence in making the right lending decision. 

When it comes to mortgage credit lending, accuracy and consistency are crucial for comprehending a borrower’s actual financial behavior. With the tri-merge standard, risk assessment can be properly perceived, loan pricing can be accurately calculated, investor confidence is boosted, and consistent lending choices are made while limiting the risk of score manipulation. Although using one data set sounds easier and lower costs in the short term, the long-term uncertainty could ultimately result in greater costs and risks later down the mortgage lifecycle.

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As with a great many other things in life, what makes a campaign successful varies from an incomplete to complete data set. Businesses who use data appending services experience higher rates of engagement, better email deliverability, and faster sales cycle times. This article explains how data appending companies work to solve this dilemma.

The Silent Cost of Incomplete Contact Data

Marketing Managers in B2B companies know the frustration. One campaign launch that everyone had hoped would be successful bounces back. Phone numbers are no good. Potential clients can’t be reached because their information is incorrect. The costs of a failed campaign are staggering.

Incomplete data creates various problems:

• A campaign falls short of its goal simply because your contact information is not up-to-date.
• Marketing automation tools flag invalid addresses, damaging sender reputation.
• Salespeople waste time validating information rather than selling.
• Without business information, lead scoring is ineffective.
• Budget allocating fails because targeting criteria are based on imperfect information.

The cost of poor B2B database management gradually builds. Let’s say a marketing administrator manages 50,000 contacts but discovers 30 percent of the contacts are missing crucial data, resulting in 15,000 lost leads. If the average deal is $50,000, that represents a lost opportunity of $750 million.

In general, company records in B2B databases degrade catastrophically due to work profile changes, relocations, mergers and acquisitions, and role transitions. This deterioration happens regardless of maintenance efforts. A recent survey cited that around 23% of email lists in B2B databases degrade and become invalid every year. Phone numbers change. Job titles evolve. Without intervention, databases become progressively less valuable.

Understanding Data Appending: Beyond the Basics

Data appending services address this issue by adding missing information to existing customer records through verifiable data sources. Unlike data cleansing that removes duplicates and errors, data appending adds new or additional data to existing customer records in databases.

Data appending companies operate differently than data acquisition providers. Instead of selling new contact lists, they enhance existing databases. An organization provides a list of 10,000 prospects. The data append company matches these records against proprietary databases containing billions of verified contacts. Missing details like direct phone numbers, mobile contact information, email addresses, and company intelligence get added to matching records.

The decision to outsource data appending services makes sense for several reasons:

• Accuracy: Data appending companies verify their information constantly.
• Scale: Appending solutions employed by outsourcing partners append millions of records within minutes, making large-scale enrichment extremely efficient.
• Compliance: Professional suppliers adhere to stringent compliance procedures during the appending process.
• Time: It would take months of internal time to append what vendors do in days.

As before, the organization submits the contact information. The data append company then performs fuzzy matching against the matched sources. Information is validated to fill the gaps. The enriched database is returned to the organization with a confidence score.

The Three Critical Gaps Most B2B Databases Share

Marketing administrators see three types of data gaps, and knowing what gaps to close helps them determine if data appending services would help them.

1. Missing Contact Details

Most visible is the absence of basic contact information such as company name and general email address, but not:

• Direct phone numbers for decision-makers.
• Mobile phone numbers for field contact.
• Personnel email addresses verified outside corporate systems.
• Correct job titles and department assignments.
• Job profiles for relationship building.

Hence, marketing teams have to work around this gap. They spend hours on LinkedIn searching; they call their companies’ main numbers to find departments; they try out different types of emails to make sure that what they send reaches the right person. Their manual labor lessens the impact of their campaigns.

2. Outdated Company Intelligence

In another case, the company’s records may contain outdated information: the name of the company, its age, the type of business etc.

• For more detail please read the information from our previous earnings report.
• Old classifications of industries that changed.
• The old leadership teams are replaced.
• False company size estimates.
• Change in status in connection with a merger or acquisition.

Such a disconnect can be especially harmful for account-based marketing programs. Targeting criteria may become unreliable. A prospect who appears to be a “startup” may have grown to mid-market size. A company that appears unsuitable for solutions may have recently purchased another.

3. Behavioral Signals That Reveal Buying Intent

The third is actionable intelligence about buying signals. Records are missing:

• Recent job changes in target accounts.
• Information about the stack of technology for compatibility.
• Various funding announcements for growth investments.
• Industry event attendance.
• Website behavior and content consumption signals.

Professional B2B data appending firms address all three gaps by drawing upon various data sources — workforce databases, company registrations, technology tracking, and business intelligence systems — to support the appending process. This results in a real-world database that is no longer just a collection of snapshots.

Real Impact: How Better Data Changes Campaign Results

Theoretically not so important. Organizations that use data appending services see significant improvements in several metrics.

I. Deliverability Improvements

Each bounce hurts the sender’s reputation. Email service providers pay attention to bounce rates. The highest bounce rates trigger filters that send legitimate messages to spam folders. Using data appending services reduces bounce rates greatly. Organizations saw a tremendous drop in bounce rates after implementing data appending services. Email marketers are now able to run successful email campaigns that had once failed.

II. Engagement Rate Increases

Reaching the right person matters. When marketers reach decision-makers directly and not via departmental inboxes, response rates increase. Organizations report higher email open rates with an addition. If emails go to the right people, they also report higher click-through rates.

III. Faster Sales Cycles

Databases with correct contact information help an organization to accelerate sales interactions. Sales team members with valid phone numbers can connect with prospects quickly and in a big way. Salespeople with accurate job titles and descriptions understand the decision-makers and can properly match their offers to those of the company. Industrial categories or service details, such as the name of the company, can help them pitch their offerings well and close deals as soon as possible. These factors reduce sales time.

IV. Improved Lead Scoring Accuracy

Lead scoring with marketing automation tools is only possible with accurate data. Firm size, industry type, and lead-based engagements all influence the lead scoring process. Imperfect or incomplete data means poor lead scoring, as sales teams pursue low-quality leads and ignore potential leads. B2B data appending services ensure a smooth operation of the scoring algorithms.

Choosing the Right Data Append Company for Your Needs

Marketing administrators should be aware that not all data appending outsourcing services providers will provide equal quality and support. They should conduct a thorough evaluation of all vendors before signing up with them.

The following selection criteria are asked during the initial stage of the selection process:

• What data sources are used by the vendors to append data? Proprietary databases are more precise than public data repositories.
• How frequently are records updated? The data are refreshed on a monthly basis more often than every year.
• What match rates does the vendor say they achieve? Vendors should provide examples of projects or portfolios that show consistent match rates of added records.
• How does the vendor ensure the quality of the data? Be sure the team that pushed the data has gone through multiple stages of verification.
• What compliance certifications does the vendor have? GDPR, CCPA, and SOC 2 are the top compliance certifications in the regulated industries.
• Can the vendor connect ad-hoc data to existing marketing applications? An API connection eliminates the need for implementation.

Administrators should ask for data samples as well. A reputable vendor should offer examples of appended records to show the quality of enriched information. Ask about confidence scores. Many vendors provide levels of confidence for matches. These ratings allow teams to identify which records to trust completely.

Integrating Appended Data Into Your Marketing Stack

But this is only the beginning. Smart integration converts this data into marketing advantage.

• Prioritize Segmentation: Segment newly appended business data based on industry type, company size, revenue range, and location. Develop separate campaigns targeting specific segments with tailored messages. A mid-market manufacturing company receives different messages than a financial enterprise.
• Next, Activate Direct Contact Channels: Phone numbers and mobile contacts are valuable for outbound calling campaigns. Initiate direct calls with valuable prospects and combine email outreach with phone follow-up for greater engagement and conversion outcomes.
• Implement Progressive Profiling Through Web Forms: Rather than requesting all information upfront, progressively enrich business profiles as visitors engage. The website recognizes returning visitors and selectively requests new details, improving form completion rates while accumulating additional data points.
• Establish Measurement Processes: Monitor campaign performance before and after data appending. Evaluate open rates, click rates, and conversion rates. Document the revenue impact of improved data quality. This documentation justifies continued investment in data appending outsourcing services.

Moving Forward: Making Better Decisions With Complete Data

Marketing teams that work with a data appending service provider have a competitive advantage over the competitors in more than managing campaigns. They have also established sustainable processes for database management.

Marketing executives can plan and execute a scheduled database refresh. Rather than adding another record to your database, add to your data cycle annually or semi-annually. This keeps the database current with prospects who change jobs, move companies, or enter new markets. A rolling database refresh maintains database quality rather than degrading.

Stakeholders consider the quality of data when conducting lead capture activities. Real-time appending during form submissions. When a prospect provides a minimum amount of information, the system adds it immediately to the records for completeness, eliminating the need for marketing staff to manually enter information.

Marketers should document their internal benchmarks. Know the baseline metrics before adding them. Measure open rates, click rates, bounce rates, and conversion rates over time. These metrics will tell you how quality improvement projects affect your business.

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