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Roofing Marketing Guide

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The U.S. roofing market hit $23.35 billion in 2024, and competition is fiercer than ever. With over 96,000 roofing contractors registered nationwide, you’re not just competing with the shop down the street anymore.

While 79% of homeowners still find roofers through word-of-mouth, 62% also go online. And here’s the game-changer: many of those searches now happen through AI tools like ChatGPT and Google’s AI Overviews before homeowners ever see a traditional search result.

Search interest in “roofing companies” grew 107% year-over-year. The roofing business has always been built on trust and reputation. What’s changed is how potential customers find you and decide whether to call.

This guide breaks down the marketing strategies that work for roofing companies in 2025. No theory, just the tactics that help you get found and hired.

Key Takeaways

  • Roofing customers make decisions based on urgency and trust. Storm damage creates immediate need, while planned replacements involve months of research and multiple contractor comparisons.
  • Local visibility matters more for roofers than almost any other industry. Homeowners rarely hire contractors outside their service area, making hyper-local SEO and Google Business Profile optimization essential.
  • Your online reputation competes directly with word-of-mouth referrals. Homeowners check reviews before calling, and a strong rating can override even a neighbor’s recommendation.
  • AI search tools now answer roofing questions like “how much does a roof replacement cost” before showing traditional results, changing how you need to structure content to get cited.
  • Roofing marketing must address both emergency repairs and planned replacements. Your strategy needs to capture homeowners searching “roof leak repair now” and those researching “best roofing materials” six months before they’re ready to buy.

Why Do Roofing Businesses Need Marketing?

72% of roofing contractors expect sales growth in 2025, but hoping for growth and planning for it are two different things. Marketing is about making sure you’re visible when a homeowner’s roof starts leaking or when they’re ready to replace those 20-year-old shingles.

67% of homeowners say online reviews are extremely or very important in their purchasing decision. That means your reputation online matters just as much as the quality of your work. Maybe more, because prospects check your reviews before they ever meet you. When you look for a roofer in your area, reputation signals like ratings and reviews are front and center in the SERP.

Results for "Roofer near Minneapolis."

Marketing also keeps your pipeline full during slow seasons. Storm damage creates spikes in demand, but you need a steady flow of leads year-round to keep crews working and revenue stable. Without marketing, you’re reactive. With it, you’re in control.

The roofing companies that invest in marketing don’t just survive. They grow, scale, and dominate their local markets. The ones that don’t? They’re competing on price alone, and that’s a race to the bottom nobody wins.

What Makes Roofing Marketing Unique?

Roofing sits at an unusual intersection in home services. Half your leads need you right now because of storm damage or leaks. The other half are planning six months out, researching materials and comparing quotes.

Most roofing demand comes from re-roofing, with the median U.S. home age nearing 40 years. That creates a predictable replacement cycle, but it also means homeowners treat roofing as a major investment. They’re not impulse buying. They’re checking multiple contractors, reading dozens of reviews, and asking neighbors who they used.

Trust matters more in roofing than almost any trade. You’re asking homeowners to spend $15,000 to $30,000 or even more on something they can’t see once it’s installed. 

The buying cycle also varies wildly. Emergency repairs convert in hours. Full replacements take weeks or months of consideration. Your marketing needs to serve both audiences without confusing either one.

Digital Marketing Strategies For Roofing

The tactics below aren’t theory. They’re what actually works for roofing companies competing in local markets right now.

Each strategy addresses a specific part of the customer journey. LLM marketing and SEO capture homeowners in research mode. Paid ads grab emergency leads when speed matters. Social media and content build trust over time. Email nurtures prospects who aren’t ready to buy today. Reputation management turns past customers into your best salespeople.

You don’t need to master all of these on day one. Start with the channels where your best customers are already looking, then expand as you see results.

Roofing SEO

SEO puts your roofing company in front of homeowners during their research phase, weeks or months before they’re ready to get quotes. 76% of people who search on their smartphones for something nearby visit a business within a day, making local SEO critical for roofing contractors competing in specific service areas. Businesses that appear in the Google 3-pack see a 34% higher click-through rate compared to other organic results.

Here’s what drives SEO results for roofing companies:

  • Optimize your Google Business Profile completely. Fill out every section of your Google Business Profile, choose “Roofing Contractor” as your primary category, add secondary categories like “Roof Repair Service” or “Metal Roofing Company,” and upload photos weekly. 
A Google Business Profile for a roofing company.
  • Target service-specific local keywords. Create separate pages for “roof replacement [city],” “storm damage repair [city],” and “roof leak repair [city].” Don’t lump all services onto one generic page. Homeowners search for specific solutions in specific locations.
  • Build consistent local citations. List your business on Angi, HomeAdvisor, BBB, and roofing-specific directories with identical NAP (Name, Address, Phone) information everywhere. Inconsistent listings confuse Google and hurt rankings.
  • Create location-specific content for each service area. If you serve multiple cities, build individual pages for each location with unique content about local roofing challenges, weather patterns, and building codes. Don’t just swap city names in template pages.

Roofing Social Media

Social media isn’t optional for roofing companies anymore. Social media content now ranks prominently in Google search results, meaning your Facebook posts and YouTube videos can appear when homeowners search for roofing services. 89% of consumers will buy from a brand after following it on social media.

Some roofing companies might avoid social media because they don’t want to be on camera or don’t know what to post. But social media isn’t about you. It’s about showing homeowners what to expect and staying top of mind when their roof needs work.

Here’s how roofing companies should use social media:

  • Post project transformations consistently. Before-and-after photos of completed jobs prove you can solve problems. Show storm damage repairs, full replacements, and material upgrades. Too much promotional content is a major turn-off, so focus on showing your work, not selling your services.
An Instagram page for a roofing company.
  • Feature your crew, not just roofs. Show your team working safely, explain the process, and humanize your brand. Homeowners hire people, not companies. Let them see who shows up to their house.
  • Create educational content about local roofing issues. Post about how local weather affects roofs, when to replace vs. repair, and what homeowners should look for during inspections. Educational content positions you as the expert.
  • Respond to comments and messages immediately. Social media is a customer service channel. Homeowners asking about pricing or availability in your comments expect fast responses. Slow replies lose jobs to competitors.

Roofing Content Marketing

Homeowners research roofing projects for months before hiring a contractor. Content marketing puts your company in front of them during that research phase, building trust before they’re ready to get quotes.

Content works differently for roofing than other industries. It’s not about entertainment. You’re educating homeowners who need to make a major financial decision about something they don’t understand. Most people replace a roof once or twice in their lifetime. They don’t know what questions to ask.

Here’s what roofing content should cover:

  • Create buying guides specific to your region. Write about which roofing materials work best in your local climate, how local weather patterns affect roof lifespan, and what building codes homeowners need to know. A guide for Florida roofs looks completely different than one for Colorado.
A guide on a roofing website.
  • Break down the replacement process. Explain timeline expectations, how crews protect landscaping, what noise levels to expect, and how homeowners should prepare. Demystifying the process reduces anxiety and objections during sales calls.
A graphic explaining the roofing process.
  • Address insurance and financing. Homeowners want to know if insurance covers storm damage, how to file claims, and what financing options exist. Content that answers these questions captures leads who are ready to move forward but need help with payment logistics.
  • Show your work through project galleries. Before-and-after photos with detailed captions explaining the problem, solution, and materials used build credibility better than any sales copy.
A project gallery on a roofing website.

Roofing Paid Media

Paid ads put your roofing company in front of homeowners at the exact moment they need help. When someone searches “roof repair near me” at 8 AM after a night of heavy rain, that’s not casual browsing. That’s intent. PPC advertising captures those high-intent leads before they call your competitors.

For roofing and gutters, the average cost per click can be expensive compared to other home services, but the payoff justifies the cost. Well-optimized campaigns can bring in up to $8 for every $1 spent, especially during storm season when demand spikes.

Here’s how to make paid ads work for roofing:

  • Separate emergency from planned replacement campaigns. Someone searching “roof leak repair now” needs different messaging than someone researching “best roofing materials.” Create distinct campaigns for each stage of the buying cycle with appropriate landing pages when someone clicks through from a paid ad. The examples below show that path down the sales funnel.
A local search for roof leak repair now.
A landing page from a sponsored ad on a roofing website.
  • Use location targeting aggressively. Bid higher on zip codes you actually service. Storm-damaged areas command premium ad costs, but they also convert faster. Adjust bids based on weather patterns and recent storm activity.
  • Track phone calls, not just form fills. Most roofing leads call directly from mobile search results. Set up call tracking so you know which keywords and ads generate actual conversations, not just website visits.
  • Add negative keywords religiously. Exclude searches for “DIY roof repair,” “roofing jobs,” and “roofing materials wholesale” unless you serve those markets. Wasted clicks drain budgets fast in high-CPC industries like roofing.

Roofing LLM Marketing

AI SEO for roofers helps roofing companies appear in answers from large language models like those that power  ChatGPT, Perplexity, and Google’s AI Overviews. When a homeowner asks “What should I do about a roof leak?” or “How much does a roof replacement cost?” they’re not always clicking through to websites anymore. They’re getting answers directly from AI.

Market projections suggest that LLMs will capture 15% of the search market by 2028. That’s not replacing Google, but it’s changing how homeowners research roofing services before they ever pick up the phone.

When homeowners search for roofing services, AI-generated overviews now often appear before traditional search results, answering questions with cited sources. Getting your roofing company included in those citations means more visibility even when prospects don’t click through to your site.

AI overviews for roofing services.

Here’s what works for roofing companies optimizing for AI search:

  • Answer specific questions directly. Create content that addresses exact homeowner concerns like “How long does a roof replacement take?” or “What causes shingles to curl?” AI tools favor sources that give clear, complete answers.
  • Use structured data. Add FAQ schema and How-To schema to your pages. This helps AI understand what your content covers and makes it easier to cite you as a source.
  • Build topical authority. Cover one roofing topic completely rather than surface-level content on 20 topics. Write comprehensive guides on roof types, materials, and local weather considerations specific to your service area.
  • Keep information current. AI tools generally pull from fresh, accurate content. Update your pricing guides, material comparisons, and storm preparation advice regularly with current information and timestamps.

Email Marketing For Roofing

Most roofing jobs don’t happen immediately. Homeowners research for months before getting quotes, then take more time comparing contractors. Email keeps your company in front of prospects during that entire decision-making process without requiring constant manual follow-up.

Email marketing is one of the highest ROI channels for roofing companies. Unlike social media where algorithms control visibility, email lands directly in the inbox of people who actually want to hear from you.

Here’s how to use email marketing for roofing:

  • Segment your list by customer type. Emergency repair leads need different messaging than planned replacement prospects. Past customers get maintenance reminders. Property managers receive commercial service updates. 
  • Send seasonal maintenance reminders. Email past customers before storm season with inspection offers. Send fall gutter cleaning reminders. Winter ice dam prevention tips. Timely, helpful emails keep you top of mind when they need work again.
  • Nurture leads who requested quotes but didn’t book. Set up automated follow-up sequences for prospects who got estimates but haven’t committed. Share financing options, customer testimonials, and limited-time offers to move them toward a decision.
  • Build your list with valuable content. Offer free roof inspection checklists, seasonal maintenance guides, or storm damage assessment tools in exchange for email addresses. Gated content attracts qualified leads who are actively researching roofing services.

Roofing Reputation Management

Your reputation online directly impacts whether prospects call you or your competitor, especially when considering high-stakes decisions like roofing. Reputation management for roofing companies means actively controlling what homeowners see when they research your business. One bad review on the first page of Google can cost you thousands in lost jobs.

Here’s how to manage your roofing reputation:

  • Ask for reviews immediately after job completion. Send a text or email with a direct link to your Google Business Profile while the customer is still happy. Timing matters. Ask three days later and response rates drop significantly. Be sure to have a section for relevant testimonials on your site as well.
Testimonials on a roofing website.
  • Respond to every review, good and bad. Thank customers for positive reviews and mention the specific project. For negative reviews, acknowledge the issue publicly, explain what happened, and offer to make it right. Future prospects read your responses.
  • Monitor review sites beyond Google. Track Angi, HomeAdvisor, BBB, Facebook, and Yelp. Homeowners check multiple platforms before calling, so you need consistent positive reviews everywhere.
  • Address negative reviews offline first. Call unhappy customers before they leave public reviews. Solve the problem directly. Many will update or remove negative reviews if you fix the issue quickly.

Measuring Your Roofing Marketing Success

You can’t improve what you don’t measure. Marketing without tracking is just hoping things work. What you are looking to focus on may vary based on short-term and long-term goals.

Track these metrics to understand what’s actually driving results:

  • Cost Per Lead (CPL): Divide total marketing spend by number of qualified leads in your service area who are ready to book. If you’re spending $500 per lead when competitors spend $150, something’s broken.
  • Lead-to-Customer Conversion Rate: How many leads become paying customers? Even a slight improvement from 2% to 4% can double your leads without increasing traffic. Track this by marketing channel to see which sources close.
  • Return on Ad Spend (ROAS): For every dollar spent on paid ads, how much revenue comes back? If you’re spending $5,000 monthly on Google Ads but only booking $3,000 in jobs, you’re burning money.
  • Website Conversion Rate: Track phone calls and form submissions separately. Most roofing leads call directly from mobile search, so call tracking matters more than form fills.

Use Google Analytics, call tracking software, and your CRM to monitor these metrics monthly. Set up dashboards showing performance by channel so you can cut what doesn’t work and double down on what does.

FAQs

How do I market a roofing company?

Start with local SEO and Google Business Profile optimization since most homeowners search for roofers nearby. Get reviews systematically after every job. Run Google Ads targeting emergency repair keywords and service-specific terms in your area. Post project photos and educational content on social media. Build an email list to nurture leads who aren’t ready to book immediately. Track which channels produce the best leads and focus your budget there.

What is roofing marketing?

Roofing marketing is the process of attracting homeowners who need roof repairs, replacements, or inspections and converting them into paying customers. It combines local SEO, paid advertising, content creation, social media, email marketing, and reputation management to capture leads at different stages of the buying cycle. Effective roofing marketing addresses both emergency repair needs and planned replacement projects with different strategies for each.

Conclusion

Roofing marketing isn’t about choosing one tactic and hoping it works. It’s about building a system that captures homeowners at every stage, from the first Google search to the follow-up email six months later.

Start with what matters most for roofing: local visibility. Optimize your Google Business Profile, get reviews, and make sure you show up when homeowners search for help. Layer in paid ads for emergency leads and content for long-term trust building.

The roofing companies winning in 2025 aren’t the ones with the biggest trucks. They’re the ones who show up first online, prove they’re trustworthy before the phone rings, and stay in touch until homeowners are ready to buy.

Need help building a complete marketing strategy? My marketing consulting services can help you dominate your local market. 

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The Merits of Developing KPI Frameworks For Achieving App Success

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If you want to understand how your app is performing, tracking the right app Key Performance Indicators (KPIs) is essential. From downloads to in-app conversions, like newsletter sign-ups or subscriptions, KPIs provide crucial insights into how your app aligns with your goals.

In this post, we’ll guide you on how to define the most appropriate KPIs for your app, and how to structure them within a framework. This approach will empower you to understand your app’s performance at a glance and uncover actionable insights to fuel growth and long-term success.

Key Takeaways

  • Building a KPI framework gives you a structured way to organize app performance metrics, helping you see the bigger picture rather than isolated data points.
  • Five primary (level 1) KPIs – reach, activation, engagement, retention, and business-specific – form the foundation of an effective framework.
  • Supporting (level 2) KPIs provide diagnostic detail, explaining why higher-level metrics perform as they do and guiding optimization decisions.
  • A clear four-step process- defining purpose, mapping the user lifecycle, identifying the right KPIs, and ensuring measurability – keeps your framework actionable and aligned with business goals.
  • Regularly analyzing and segmenting KPI data enables smarter decisions, from refining acquisition strategies to improving retention and revenue outcomes.

What Is a KPI Framework?

The KPI framework is an essential tool in app marketing, offering a structured way to organize and analyze your app’s KPIs. In app marketing, these indicators help evaluate different aspects of an app’s success, such as user acquisition, retention, engagement, revenue generation, and overall app performance. The KPI framework helps you understand how different KPIs work together to drive growth, optimize user experience, and achieve long-term success.

Examples of common metrics and KPIs to track.

Why You Need a KPI Framework

To get any real value from your app KPIs, you need to view them holistically, rather than in isolation. They need to be mapped into a framework that highlights the relationships between them and how they impact one another. A well-structured KPI framework offers you this consolidated, 360-degree view of performance, ensuring that all lower-level KPIs are in place to support your overriding “North Star” metric (a key metric that aligns with user value and business growth and is used to track overall success). 

Let’s explore the key metrics that should be included in a well-structured KPI framework.

Breaking Down The KPI Framework

The KPI framework that we have developed at Yodel Mobile is built around five “level 1” (primary) metrics.

Level 1 metrics are the main indicators that show how well your app is doing overall. These metrics give you a big picture view of important areas such as user growth, engagement, retention, and their impact on your business goals. Think of these metrics as the foundation of your KPI framework. They directly connect to your app’s main objectives and your most important measure of success, the “North Star” metric.

Here’s how we break down the level 1 metrics:

  • Reach (e.g., total app installs)
  • Activation (e.g., the number of users who complete onboarding)
  • Engagement (e.g., Daily Active Users (DAU))
  • Retention (e.g., Churn Rate)
  • Business-specific (e.g., Customer Lifetime Value (LTV))

Each of these level 1 metrics is supported and driven by a corresponding set of  “level 2” metrics, which provide a more detailed breakdown. The level 2 metrics offer valuable insights into the specific factors driving the performance of level 1 metrics. Acting as diagnostic tools, they help to explain why level 1 metrics are performing as they are.

A breakdown of level 1 and level 2 metrics.

Measurement Framework

Let’s explain each metric in more detail.

Reach

These are KPIs that sit within the reach section of the framework and focus on acquisition and exposure. They help measure the effectiveness of efforts to attract and engage a broader audience. Examples at level 1 could include the number of installs and web visitors, while level 2 elements could include web-to-app conversion, splitting your installs by paid, owned, or earned channels to measure the effectiveness of efforts from various sources.

Activation

Activation metrics focus on a user’s initial engagement and the process of turning new users into engaged users by guiding them to experience the app’s core value early in their journey. This could be during the onboarding process, or later, as they use the app. Level 2 elements here might include specific actions such as a user registering their details or completing a required task. For example, in a language learning app, this could involve completing a quiz to set the user’s language proficiency level.

Engagement

Engagement metrics capture how actively and frequently users interact with your app and its features, shedding light on the depth of their involvement. Level 1 metrics can include Daily Active Users (DAU), Weekly Active Users (WAU), or session duration, which provide a broad understanding of user activity. At the level 2 stage, these metrics become more specific, for example, for a subscription app, this could be the number of users who start a free trial, indicating early-stage engagement and their interest in the premium offering.

Retention

Retention metrics measure how effectively an app keeps users returning over time, assessing its ability to maintain a loyal and engaged user base. The level 1 metric here could be day 1, day 7, day 30 retention (the number of users still active in the app 1/7/30 days after installing it). Level 2 metrics could be feature-specific, tracking how often users return to specific features within the app (e.g., viewing content, making purchases, using premium features). For example, in a music education app, the Monthly Lesson Return Frequency could measure how often users return to complete a lesson each month.

Business-specific

A business-specific KPI is a high-level metric that reflects the unique goals and performance indicators of a particular business. These metrics are directly tied to the organization’s strategic objectives, such as revenue growth, business health, or customer acquisition, and are designed to track progress in areas critical to the business’s success. Supporting level 2 metrics provides detailed insights into the factors influencing the performance of the level 1 KPI, offering a clearer understanding of what drives results.

Leveraging the KPI Framework to Drive App Growth

​​By breaking down the KPI framework in this way, you not only gain a clearer picture of how each element impacts overall performance but also create a roadmap for improving user acquisition, engagement, and retention.

Let’s say that you have established that you need 100,000 installs per month to reach your LTV KPI, based on the conversion rate of new users to paid subscription. If you’re falling short of this target, you can adjust your strategy by increasing your advertising budget or analyzing which channels are proving the most effective.

Regularly monitoring and adjusting your level 1 and level 2 metrics ensures that the app stays aligned with both user needs and business objectives. Ultimately, this approach helps refine strategies, drive growth, and work towards achieving the North Star metric, delivering long-term success for the app.

KPI frameworks and the sales funnel.

A Step-by-Step Guide to Creating a Successful KPI Framework

To create a successful KPI framework that will help you align your app’s goals with measurable actions, follow this four-step process.

Step 1: Define your App’s Core Purpose

Define what the core purpose of your app is, the real value it brings to its users. This will help in specifying the KPIs that best measure how effectively the app fulfills its purpose and delivers on its promise. 

Step 2: Map the User Lifecycle

Look at key points in the user lifecycle and at how they link to your business goals and objectives, in order to define the right KPIs for your app.

Step 3: Identify the Best KPIs to Focus on

To do this, focus on KPIs that are truly going to have an impact on the business. Don’t overwhelm yourself with too many metrics, as they can obscure actionable insights.  And while every KPI is important, the maturity of your app will dictate where you place most emphasis. So, for a new app, the focus is often on reach, aiming to achieve those initial install KPIs. For a more mature app, concentrate on optimizing for retention. 

Step 4: Make sure that Your Goals are Measurable

In order to gauge the progress of each KPI, whether that’s downloads, signups, or conversion rates, every KPI needs to be measurable to ensure that you can assess your progress against it. 

And remember that the KPI itself is really no more than a goal and one that can be achieved in a number of ways. What really counts is understanding the mechanisms and the levers you can pull to achieve it. You have to drill down into the KPI and ask yourself: “What actions can I take to influence this KPI? What factors in my control will impact it the most?” If the KPI is about generating revenues, for example, the key driver might be making sure that people are subscribing, or at least committing to a free trial that leads to a subscription.

With that in mind, you can optimize the flow of the app, the onboarding process, and your comms strategy, to support this goal effectively.

A step-by-step guide for creating a successful KPI framework.

How to Successfully Analyze Your Data and Make Informed Decisions

You’ve successfully created your KPI framework – great! But the next crucial step is learning how to read and interpret the data effectively. Without actionable insights, even the best framework won’t help you achieve success.

Digging deeper into the data relating to your KPIs will help you to make more informed and strategic decisions. For example, you might segment your users by OS (Android or iOS) or subscription plan, such as monthly or annual. Breaking things down in this way will help you establish useful facts such as:

  1. iOS users are 3x more likely than Android users to convert from a free trial to a paid subscription. 
  2. People on monthly subscriptions are twice as likely to churn as those on annual subscriptions. 
  3. The users you acquire through paid channels show much worse retention levels than those you acquire organically. 

Once you understand these issues, you can try to address them. For example, if you discover that iOS users are more valuable than Android users (as mentioned in point 1), you can adjust your paid advertising strategy to prioritize iOS users.

Use the KPI framework to give you the big picture, then segment your data to really understand how your various KPIs are impacted to different degrees by different types of users. 

Additionally, leverage this data to conduct A/B tests. For example, you might test two different paywall designs to see which drives higher conversion to a free trial. 

Once you have your KPIs mapped out, platforms like Mixpanel will allow you to build a dashboard that calls out each of them. So, you create charts, add them to your dashboard, and quickly identify changes. If retention, frequency of usage, or the number of purchases drops, these changes will be immediately visible, allowing you to diagnose and address the issues promptly.

Mixbook Analytics Framework 

Turning Insights into Strategy

It’s really important to have a well-structured KPI framework that aligns with your business goals, that those goals are measurable, and that for each KPI, you understand the factors in your control, the levers you can pull, that will impact them. 

Putting all of this in a framework is much more useful and instructive than just listing it all out in a spreadsheet. The framework allows you to see the link between different KPIs. It’s scalable, so it’s easy to add additional metrics into the mix. And it helps you to stay agile in terms of understanding how the business and the app are working and then making adjustments based on the data that you get from your KPI analysis. Think of it as a framework for success. In short, every app should have one to be ready for the future of ASO.

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How to Use Marketing Attribution to Take Your Business to the Next Level

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Marketing today is more complex than ever. With so many channels, touchpoints, and customer behaviors to track, figuring out what actually drives conversions can feel impossible.

That’s where digital marketing attribution comes in. It shows you which marketing efforts are working and which ones are wasting your budget.

Without attribution, you’re guessing. With it, you can make data-backed decisions that improve return on investment (ROI) and help you grow faster.

This guide breaks down what attribution is, how different models work, and how to choose the right approach for your business.

Key Takeaways

  • Digital marketing attribution tracks which channels and touchpoints drive conversions, so you know where to invest your time and budget.
  • There’s no universal “best” model. Each attribution approach has strengths and tradeoffs based on your goals and customer journey.
  • Single-touch models (like first-touch or last-touch) are simple but miss most of the buyer journey.
  • Multi-touch models give you a fuller picture but require more setup and analysis.
  • The right model depends on your business goals, sales cycle length, and how customers interact with your brand.

What is Marketing Attribution?

Marketing attribution is how you figure out which marketing efforts actually drive results.

It assigns credit to the touchpoints (ads, blog posts, emails, social posts, webinars) that influence someone to convert.

Think of it as connecting the dots between your marketing spend and your revenue.

When someone makes a purchase or fills out a form, attribution helps you trace the path they took to get there. That insight helps you optimize campaigns, improve ROI, and stop pouring budget into channels that don’t work.

But here’s the problem: most marketers either don’t track attribution at all, or they oversimplify it. Only 28% of marketing professionals say their attribution strategies are very successful at achieving strategic objectives. The stakes of misattribution are high as well, potentially costing companies money and time:

A graphic showing ad spend wasted due to poor attribution.

Attribution models set the rules for how credit gets assigned across different touchpoints.

Some give all the credit to the first interaction. Others focus on the last. More advanced models weigh every step of the journey.

Understanding how these models work is the first step to using them effectively.

Why Marketing Attribution is Important

Marketing attribution matters because without it, you’re not measuring performance. You’re guessing.

It connects campaigns to conversions, showing you which efforts drive real impact and which ones drain your budget. The thing about it is it’s also getting harder. Less cookies to rely on and the presence of AI are notable factors.

On top of that, today’s buyer journey isn’t linear. People bounce between search, email, ads, and social, often across multiple devices. Without attribution, you miss the big picture.

That’s especially true if you’re running multi-channel marketing strategies. You might be getting results, but you can’t tie them back to the right touchpoints.

Take a look at what channels marketers are the most confident in when it comes to attribution:

A graphic showing confidence in attribution accuracy by channel.

Email and paid top the list. But here’s the thing: without proper attribution, you can’t tell if any channel is actually driving growth for your business, or if you’re just following what everyone else is doing.

Attribution also improves ROI. When you know what works (and what doesn’t), you can reallocate spend with confidence.

It gives marketing teams clarity, sales teams better leads, and leadership the data they need to make informed decisions.

Bottom line: attribution turns marketing from a cost center into a strategic growth engine.

Types of Marketing Attribution Models

There’s no one-size-fits-all approach to marketing attribution. Only what fits your business best.

Attribution models fall into two categories: single-touch and multi-touch.

Single-touch models give full credit to one touchpoint, like the first click or final conversion. They’re simple to track but miss most of the customer journey.

Multi-touch models spread credit across multiple interactions. They take more effort to set up but give you a clearer picture of what drives revenue. 

Let’s break down each model so you can find the right fit for your goals.

Option #1. First-touch attribution

The first-touch attribution model applies all the ‘credit’ to touch points that lead a visitor to your website for the very first time.

A graphic that says how first-click attribution definition works.

Source

That holds true even if they don’t make a purchase, subscribe to your email list, or complete any other converting action.

This model is all about the very first part of the customer journey. It’s the first few steps someone takes to visit your site for the very first time.

That’s why it works best for marketers who are focused on demand generation and lead forms. You want to see which actions are driving that very first connection with your brand.

A good thing about this model is that it’s pretty simple to put into effect with Google Analytics.

But, since this model only really focuses on one single touch point, it tends to over-prioritize a channel that might not be the most important.

In other words, the initial social ad used to drive traffic is important to an advertiser or brand marketer. However, it’s not all that helpful to people who are analyzing bottom-of-the-funnel conversions, that generally lead right to a sale or conversion.

The first-touch attribution model also doesn’t actually uncover what made a customer buy, so it doesn’t really allow for a whole lot of optimization.

Option #2. Last-touch attribution

The last-touch attribution model is the exact opposite of the first-touch attribution model, hence the name.

It’s often the “default,” go-to model for most marketers. It gives all the credit to the final touch point before someone buys.

For example, if a customer clicks a retargeting ad and buys, last-touch attribution credits that final ad, even if they interacted with your brand five times before that.

A graphic showing how last-touch attribution works.

Source

This model puts all the attention on the very end of the customer journey. The items are “in their carts,” so to speak.

This model is great for short sales cycles or conversion-focused teams.

But it ignores all of the factors that influence a customer’s journey to purchase by putting all of the attention on the final interaction.

If you’re using Google Analytics, try looking at Last Non-Direct Click instead. It skips direct visits (like people typing your URL) and highlights the last true channel that drove them in.

A graphic showing how non-direct click attribution works.

Source

Option #3. Lead-conversion touch attribution

The lead-conversion touch attribution model assigns 100% of the credit to the interaction that generated a lead.

A graphic that shows how the lead-conversion touch attribution model works.

Source

It’s a popular option in B2B and lead-gen-focused businesses because it gives a clear signal: which campaign, offer, or page got someone to convert.

This is helpful when you’re trying to understand what sparks initial interest, especially if you’re optimizing for marketing qualified leads (MQLs)  or sales-qualified leads.

But like other single-touch models, it only highlights one moment in a longer journey.

That means it misses the role of earlier awareness-building and any post-lead nurturing that helps close the deal.

If you’re using this model, be careful not to over-prioritize top-performing lead channels at the expense of brand-building or retention tactics.

It works best when used alongside other models that measure pipeline movement or final conversions, not as a standalone view.

Option #4. Linear attribution

The linear-attribution model splits credit up evenly across every touch point of the customer journey.

A graphic that shows how the linear attribution model works.

So, if there are five touch points, every touch point gets 20% of the credit. For ten touch points, each touch points gets 10%, and so on.

This model lets marketers make the best of the customer journey as a whole and optimize the entire picture, rather than just focusing on one touch point.

But, since it gives credit to all touch points evenly, some high-performing points will get less credit than they deserve, and some low-performing ones will get more.

Still, it’s a good starting point for teams who want a more balanced look at what’s working across their funnel, without needing complex analytics setups.

It can also serve as a baseline model for comparison when testing more advanced multi-touch approaches.

Option #5. Time-decay attribution

The time-decay attribution model gives more credit to touchpoints that occur closer to the final conversion.

In this setup, the last few interactions (like an email click or retargeting ad) carry more weight than earlier touchpoints.

A graphc showing how the Time Decay Attribution Model works.

This model makes sense for longer journeys, where timing and momentum are critical to pushing someone across the finish line.

It also reflects how user behavior changes closer to conversion. Someone may browse casually at first, but act with more intent later.

However, time-decay can undervalue the early-stage marketing that sparked interest in the first place. That means awareness efforts like content or top-of-funnel ads may look less effective than they really are.

If you’re running nurturing campaigns or have a long sales cycle, time-decay can give you insight into what’s accelerating purchase decisions, even if it doesn’t tell the full story.

Option #6. U-shaped (position-based) attribution

The U-shaped attribution model, also known as the position-based attribution model, gives 40% of the credit to the first and last touch points.

Then it splits up the remaining 20% among each of the touch points in between.

A graphic that show show U-shaped attribution works.

This setup recognizes the importance of both the entry point and the final push, while still accounting for the journey in between.

For example, if someone finds you through a blog post, returns via email, then converts after clicking a retargeting ad, both the blog and the ad would receive the highest share of credit.

This model is a popular middle ground. It highlights the two most critical steps without ignoring everything else.

This model might give inaccurate credit to the first and last touch points in the customer journey, though.

They receive a large, fixed percentage. So you might still see some over-reporting on both ends of the journey.

Still, for many teams, U-shaped attribution offers a practical balance of simplicity and nuance.

Option #7. Custom or algorithmic attribution

Custom, or algorithmic, attribution starts to get technical.

A data scientist creates and builds a model for attribution that matches the customer journey of a certain business in a precise way.

These models analyze your actual conversion paths and weigh each touchpoint’s impact accordingly.

That means your attribution is specific to your business, your audience, and how they buy.

It’s by far the most accurate model, but also the most complex to build.

You’ll usually need a data science team or an advanced analytics platform to get started. That makes it tough for lean teams or smaller organizations to implement.

Still, some platforms now offer algorithmic models out-of-the-box, giving you smarter attribution without having to build it from scratch.

If your marketing is already scaled and data-driven, this model can reveal deep insights you’ll never get from basic reporting.

Option #8. Rules-based attribution

Rules-based attribution lets you define how credit is assigned across the customer journey based on your own logic, not a fixed formula.

For example, you might assign 20% of the credit to first-touch, 20% to last-touch, and distribute the remaining 60% based on engagement or funnel stage.

A graphic showing how fractional attribution works.

Source

This approach gives you more control and customization without requiring advanced AI or machine learning.

It’s especially useful when you have a clear understanding of your sales cycle and buyer behavior, or when you need to align attribution with internal KPIs.

The downside? It’s still built on human assumptions. If your weighting is off, your data might mislead you.

Rules-based attribution works best for marketing teams that want more flexibility than single-touch or rigid multi-touch models but don’t have the resources for full algorithmic setups.

Option #9. W-shaped attribution

W-shaped attribution is a multi-touch model that assigns credit to three key moments: the first interaction, the lead conversion, and the opportunity creation.

Each of these gets 30% of the credit, with the remaining 10% spread across other touchpoints.

A graphic showing how w-shaped atrribution works.

Source

This model is particularly useful for B2B marketers who track leads through a defined sales funnel. It focuses on the moments that signal serious interest, not just casual engagement.

For example, a user might find your blog via search (first-touch), download a gated guide (lead conversion), and attend a webinar (opportunity creation).

W-shaped attribution highlights these hand-raising moments while still acknowledging the rest of the journey.

Downside? It assumes every journey fits that mold. Not every customer goes through clear-cut milestones, especially in shorter or less structured funnels.

If you’re managing long, complex buyer journeys, this model gives you more granularity than U-shaped without requiring full customization.

Option #10. Data-driven attribution

Data-driven attribution uses machine learning to assign credit based on how different touchpoints actually contribute to conversions, not predefined rules.

Unlike linear or position-based models, it adapts over time based on real behavior.

Platforms like Google Analytics and certain CRMs offer this as a built-in model, making it more accessible than full-blown custom attribution.

Data-driven attribution in action.

The system looks at all conversion paths and analyzes what works best, distributing credit accordingly.

This gives you a more objective view of what’s really influencing performance, without the bias of manual weighting.

Of course, the quality of your attribution is only as good as your data. Inaccurate tracking, broken events, or missing conversions will lead to flawed insights.

How To Choose the Right Attribution Model for Your Business

There’s no single “best” attribution model. The right choice depends on your funnel, goals, and how much data you have access to. Here’s how to approach it:

Map the Customer Journey

Start by understanding how people discover, engage with, and convert on your site.

Look at your customer journey mapping or analytics tools to spot patterns in behavior. If most users follow a simple path, single-touch might work. If they interact across multiple channels, you’ll want a multi-touch model.

Define Actionable Goals

Your attribution model should help you make better decisions, not just report on past performance.

Are you trying to lower acquisition costs? Improve lead quality? Shift budget to better-performing channels?

Pick a model that aligns with your strategic focus.

Prioritize Lead Quality

Don’t just track what drives volume. Focus on what drives high-quality leads or customers.

Website traffic and leads are common examples, but those are vanity metrics if they don’t convert into revenue.

Attribution tied to lifetime value (LTV), conversions, or revenue will give you far more insight than clicks or impressions.

The best attribution models connect marketing activity to actual business outcomes, not just top-of-funnel metrics.

Test and Adjust Over Time

No model should be static. As your campaigns evolve, revisit your attribution model regularly.

Consider running model comparisons inside tools like Google Analytics or your CRM to see how attribution shifts under different assumptions.

Common Digital Marketing Attribution Challenges

Even with the right model, marketing attribution isn’t always easy to get right. Here are some of the most common roadblocks teams run into:

  • Incomplete or inaccurate tracking: If events aren’t firing properly or conversions aren’t tagged, your data will be flawed, no matter what model you use.
  • Cross-device behavior: A user might research on mobile but convert on desktop. Without unified tracking, you’re missing part of the journey.
  • Platform silos: CRMs, ad platforms, and analytics tools don’t always talk to each other. That can lead to duplicate or fragmented data.
  • Lack of internal resources: Attribution often requires analysts or at least someone who can set up and maintain tracking, and not every team has that bandwidth.
  • Misaligned KPIs: When sales, marketing, and leadership define “success” differently, attribution insights can get lost or misused.

Solving attribution challenges often means improving operations, not just picking a better model.

Attribution Model Reports in Google Analytics

Google Analytics 4 (GA4) includes built-in attribution model reports that help you compare how different models assign credit to your conversions.

This is a powerful way to explore which marketing channels contribute most to your results and how your view of performance changes depending on the model you choose.

You can find attribution reports in GA4 by navigating to:

Reports → Advertising → Model Comparison

How to look at attribution in GA4.

There, you can select multiple models (like last-click, first-click, linear, or data-driven) and view side-by-side results.

This helps you spot where credit might be over- or under-assigned based on your current model.

For example, your email channel might perform better in a linear model than a last-click one, revealing a need to rebalance budget or expectations.

Even if you’re not ready to commit to a new attribution approach, GA4’s model comparison is a low-risk way to experiment and build attribution literacy.

Additional Attribution Software Options

Not every team needs a custom attribution setup, but the right software can make a huge difference.

Platforms like SEMrush, HubSpot, Google Analytics 4, and Wicked Reports offer built-in attribution tools to help you get started without hiring a data science team.

SEMrush and HubSpot are especially helpful for combining attribution with broader campaign management and reporting.

Atrribution in HubSpot

Source

For more advanced needs, tools like Dreamdata or Funnel.io can integrate data across multiple platforms to give you a unified view of the buyer journey.

Attribution in DreamData

Source

The key is making sure your tools match your actual marketing complexity. If you’re not tracking conversions accurately or aligning on KPIs, no tool will magically solve that.

Use software to simplify attribution workflows, not replace strategy.

FAQs

Attribution in marketing refers to how credit is assigned to different touchpoints that lead to a conversion.

Whether it’s a first-click blog visit or a final retargeting ad, attribution shows you which parts of your funnel are influencing behavior and how to optimize for more impact.

What attribution model approach is mainly used in marketing?

Last-touch attribution is still the most commonly used model, mostly because it’s simple and built into most ad platforms and CRMs.

But that doesn’t mean it’s the best option. Many teams are now moving toward multi-touch or data-driven models as campaigns get more complex.

Why is attribution important in digital marketing?

Attribution gives you the visibility to connect marketing efforts to actual business outcomes.

Without it, you’re just guessing what works. With it, you can prioritize the right channels, improve ROI, and cut spend where it’s not performing.

What is an example of attribution in marketing?

Let’s say a customer first finds your site through organic search, then clicks a retargeting ad, and finally converts from an email offer.

Depending on your attribution model, credit could go to the search, the email, or all three.

That model determines how you report success and where you double down in future campaigns.

Conclusion

Now that you understand how marketing attribution works, you can focus on the right touchpoints without all the guesswork.

This means no more wasted spend on channels that aren’t moving the needle.

Choose between first-touch, last-touch, lead-conversion, linear, time-decay, position-based, or custom attribution models to determine how your efforts contribute to conversions.

Just remember: no single model works for every business. The right choice depends on your campaign goals, customer journey, and how you define success.

Start with a basic model, then build from there. Use tools like Google Analytics or customer journey mapping to improve visibility across your funnel.

Test often, stay flexible, and evolve your strategy as your data improves.

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Stop Wasting Ad Spend: 8 Step SEO Checklist for Maximizing Google PMax and AI Max ROI

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For years, the talk of ‘synergy’ between paid media and organic search teams was merely talk. But with the rise of Performance Max (PMax) and the new AI Max for Search Campaigns (Google’s latest suite of AI-driven optimizations for standard Search campaigns), that separation is no longer viable.

What are Google PMAX and AI Max? Performance Max is a single, AI-driven campaign that finds customers across all Google surfaces like Search, YouTube, Display, Discover, Gmail, and Maps. AI Max is an opt-in boost inside standard Search that broadens query matching and adapts your ad assets while retaining your classic keyword structure.

How do Google Performance Max and AI Max campaigns work? PMax and AI Max rely entirely on the quality and structure of your website’s content to create ads, determine relevance, and choose landing pages. If your website is a mess, the AI creates messy, low-performing ads. One of the biggest levers for improving PMax and AI Max performance and ROAS is not a budget tweak; it’s strategic website optimization guided by your SEO team.

This guide provides an actionable, 8-step blueprint for turning traditional SEO tasks into direct, high-impact improvements for your paid AI campaigns by ensuring your website is optimized as the AI’s core asset source. Crucially, I also outline the common, costly mistakes to avoid in each step so you can stop wasting budget and start converting.

Key Takeaways

  • Your Website is the Asset Source: For PMax and AI Max, your website is not just a destination; it’s the source material for Google’s AI to create ads. Poorly written, thin, or technically inaccessible pages will lead to lower quality, generic ads.
  • Focus on Content Intent and Depth: Move beyond traditional keyword optimization. AI excels at matching user intent. SEO content must be comprehensive, answer every facet of a topic, and map clearly to a point in the user journey.
  • Prioritize UX and Technical Health: Since both platforms use automated URL Expansion (sending users to the best fit page), an SEO audit that focuses on Core Web Vitals, mobile-friendliness, and simple conversion pathways directly translates into better ad ROI.
  • Embrace Structured Data and Rich Content: Make it easy for AI to understand what your page is about and what the call to action is by implementing relevant schema and providing high-quality, diverse visual assets.

The 8 Step SEO Blueprint for Conversion Value

Core Web Vitals for NeilPatel.com

1. Technical Health and UX: A poor landing page experience directly impairs the Smart Bidding algorithm’s most critical signal: Conversion Rate (CVR). Speed issues cause users to abandon the funnel, wasting every ad dollar spent on that click.

  • Mistake: Only fixing high-priority technical errors like crawl blocks (e.g., accidental Disallow rules in robots.txt or misapplied noindex tags) and broken links.
  • Recommendation: Max out Core Web Vitals: Aggressively optimize for page speed, mobile usability, and aim for a 1–2 second load time. While Server-Side Rendering (SSR) is the ideal for speed, if full SSR is not feasible, implement robust site-wide caching and leverage optimization services to ensure near-instantaneous content display.
  • PMAX Benefit: A high-speed, flawless landing page improves the conversion rate, which is the Smart Bidding algorithm’s key performance signal.
  • AI Max Benefit: Ensures the AI’s Final URL Expansion feature doesn’t route traffic to a page with a poor user experience, preventing wasted ad spend on bounce-inducing pages.
An embedded video on a Neil Patel blog.

2. Multimodal Assets and Rich Media: Asset quantity and quality are fundamental to PMax’s ability to run across all Google channels (YouTube, Display, Search). Missing video assets severely limits PMax reach and forces the AI to create low-quality, automated videos.

  • Mistake: Using generic stock images or not having any video assets on key landing pages.
  • Recommendation: Provide Diverse, High-Res Visuals: Upload high-quality, correctly-sized images (1:1, 1.91:1, 4:5) and embed high-quality vertical videos (15–30 seconds).
  • PMAX Benefit: Prevents the AI from auto-generating low-quality videos and ensures the PMax ad can run across the entire Google ecosystem (YouTube, Display, Discover) effectively.
  • AI Max Benefit: Future-proofs the site for new multimodal searches and gives the AI quality visuals to use in image extensions and richer search formats.

3. E-Commerce/Feed Data (Retail): For any retail client, the product feed is the single most important data source for PMax. Without a rich, accurate feed, Shopping Ads—a key component of PMax—will not function or perform efficiently.

  • Mistake: Writing product descriptions primarily for the organic search page copy.
  • Recommendation: Enrich Merchant Center Feed: Collaborate with the retail team to enhance product titles with attributes (brand, color, size) and fill out all descriptive fields (GTIN, MPN, custom labels).
  • PMAX Benefit: The retail feed is the foundation of Shopping Ads within PMax. Rich data drastically improves ad relevance and Quality Score.
  • AI Max Benefit: Allows the AI to match hyper-specific, long-tail product queries to the correct landing page and generate highly accurate ad details.
An NP Digital landing page.

4. Ad Asset Readiness (Text & Copy): This practice provides the direct, conversion-focused text the AI uses to build dynamic ads. High-quality copy is essential for improving Ad Strength and improving click-through rates.

  • Mistake: Writing vague, keyword-stuffed title tags and H1s that may not be conversion-focused.
  • Recommendation: Isolate USPs & Benefits: Ensure key value propositions, clear pricing, and strong, concise benefit statements are instantly visible and scannable.
  • PMAX Benefit: Feeds the PMax Asset Group with high-quality, on-brand text that the AI uses to automatically generate headlines and descriptions.
  • AI Max Benefit: Gives the AI’s Text Customization feature direct source material to dynamically write ad copy tailored perfectly to the user’s real-time search intent.
Structured data implementation in Google Search Console.

5. Structured Data Implementation: Structured data provides machine-readable signals that directly improve the appearance and information quality of the final ad unit, boosting Click-Through Rate (CTR) and providing richer ad formats.

  • Mistake: Ignoring Schema Markup or using basic site-wide types.
  • Recommendation: Implement Granular Schema: Add specific and accurate schema for Product, Service, FAQ, HowTo, and Review on key conversion pages.
  • PMAX Benefit: The AI extracts this machine-readable data to generate richer, more compelling Ad Extensions (sitelinks, star ratings, prices) which boost CTR.
  • AI Max Benefit: Provides explicit signals about the intent and structure of the page, ensuring the AI confidently selects the right URL and generates accurate, fact-based ad copy.
A Topical Authority model in a graphic.

6. Content Structure and Topical Authority: This shift is crucial for improving long-term content relevance and the accuracy of the Final URL Expansion. It ensures Google’s AI can quickly find the single most authoritative page for a broad search intent.

  • Mistake: Focusing on creating many separate pages for hyper-specific, long-tail keyword variations.
  • Recommendation: Build Content Pillars/Hubs: Create a single, comprehensive “pillar” page for a core service/product with clearly defined sub-sections and use a Table of Contents.
  • PMAX Benefit: Ensures Final URL Expansion can confidently map broad ad intent to the best, most authoritative landing page across all Google channels.
  • AI Max Benefit: Provides the AI with a deep topical map, allowing Search Term Matching to expand reach to complex, “keywordless” queries with high relevance.
An author page on NeilPatel.com

7. Credibility & Authority: E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness) signals are an essential factor for overall quality, trust, and long-term organic success, which implicitly benefits ad quality by building Brand Trust Signals that influence user decision-making.

  • Mistake: Focusing only on acquiring basic backlinks from any domain.
  • Recommendation: Reinforce E-E-A-T Signals: Prominently display author bios, expertise statements, customer reviews, testimonials, and clear contact/policy pages. Ensure all key personnel have detailed, well-linked “About Us” or “Author” pages that establish their qualifications and credibility.
  • PMAX Benefit: Builds implicit Brand Trust Signals that the AI incorporates into its decision-making, leading to higher ad quality and better conversions.
  • AI Max Benefit: Ensures the AI is more likely to cite and leverage your content for dynamic ad copy, as AI models prioritize information from authoritative and trustworthy sources.

8. Cross-Team Collaboration: This is the operational foundation that enables the seven other factors to be consistently implemented and optimized. It turns one-off fixes into a scalable, self-improving marketing machine.

  • Mistake: SEO only looking at Google Search Console and organic rankings.
  • Recommendation: Adopt a Shared Insights Loop: Work with the paid team to review the PMax/AI Max search term reports and asset performance ratings at least monthly.
  • PMAX Benefit: Informs Content Gaps: PMax insights reveal high-converting search queries that the SEO team should create new pages for, feeding the PMax campaign with better landing pages.
  • AI Max Benefit: Allows the SEO team to identify negative/irrelevant AI Max search terms for the paid team to exclude, reducing wasted spend on traffic that won’t convert.

Conclusion

The future of high-performance digital advertising is not about manually writing better ads. It’s about building a better website to fuel the AI. When an SEO team shifts its focus from passively chasing organic rankings to actively structuring content, optimizing technical health, and providing rich assets, they become the most valuable partner to the paid media team.

This strategic collaboration ensures that PMax and AI Max campaigns stop operating on generic guesswork and start running on quality, conversion ready data, ultimately maximizing ROI for the client. The AI is only as smart as the website it crawls, so the key to success is making that website as intelligent as possible. Want to have a quick reference for all these practices? Feel free to use the table below.

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LLM optimization in 2026: Tracking, visibility, and what’s next for AI discovery

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LLM optimization in 2026: Tracking, visibility, and what’s next for AI discovery

Marketing, technology, and business leaders today are asking an important question: how do you optimize for large language models (LLMs) like ChatGPT, Gemini, and Claude? 

LLM optimization is taking shape as a new discipline focused on how brands surface in AI-generated results and what can be measured today. 

For decision makers, the challenge is separating signal from noise – identifying the technologies worth tracking and the efforts that lead to tangible outcomes.

The discussion comes down to two core areas – and the timeline and work required to act on them:

  • Tracking and monitoring your brand’s presence in LLMs.
  • Improving visibility and performance within them.

Tracking: The foundation of LLM optimization

Just as SEO evolved through better tracking and measurement, LLM optimization will only mature once visibility becomes measurable. 

We’re still in a pre-Semrush/Moz/Ahrefs era for LLMs. 

Tracking is the foundation of identifying what truly works and building strategies that drive brand growth. 

Without it, everyone is shooting in the dark, hoping great content alone will deliver results.

The core challenges are threefold:

  • LLMs don’t publish query frequency or “search volume” equivalents.
  • Their responses vary subtly (or not so subtly) even for identical queries, due to probabilistic decoding and prompt context.
  • They depend on hidden contextual features (user history, session state, embeddings) that are opaque to external observers.

Why LLM queries are different

Traditional search behavior is repetitive – millions of identical phrases drive stable volume metrics. LLM interactions are conversational and variable. 

People rephrase questions in different ways, often within a single session. That makes pattern recognition harder with small datasets but feasible at scale. 

These structural differences explain why LLM visibility demands a different measurement model.

This variability requires a different tracking approach than traditional SEO or marketing analytics.

The leading method uses a polling-based model inspired by election forecasting.

The polling-based model for measuring visibility

A representative sample of 250–500 high-intent queries is defined for your brand or category, functioning as your population proxy. 

These queries are run daily or weekly to capture repeated samples from the underlying distribution of LLM responses.

Competitive mentions and citations metrics

Tracking tools record when your brand and competitors appear as citations (linked sources) or mentions (text references), enabling share of voice calculations across all competitors. 

Over time, aggregate sampling produces statistically stable estimates of your brand visibility within LLM-generated content.

Early tools providing this capability include:

  • Profound.
  • Conductor.
  • OpenForge.
Early tools for LLM visibility tracking

Consistent sampling at scale transforms apparent randomness into interpretable signals. 

Over time, aggregate sampling provides a stable estimate of your brand’s visibility in LLM-generated responses – much like how political polls deliver reliable forecasts despite individual variations.

Building a multi-faceted tracking framework

While share of voice paints a picture of your presence in the LLM landscape, it doesn’t tell the complete story. 

Just as keyword rankings show visibility but not clicks, LLM presence doesn’t automatically translate to user engagement. 

Brands need to understand how people interact with their content to build a compelling business case.

Because no single tool captures the entire picture, the best current approach layers multiple tracking signals:

  • Share of voice (SOV) tracking: Measure how often your brand appears as mentions and citations across a consistent set of high-value queries. This provides a benchmark to track over time and compare against competitors.
  • Referral tracking in GA4: Set up custom dimensions to identify traffic originating from LLMs. While attribution remains limited today, this data helps detect when direct referrals are increasing and signals growing LLM influence.
  • Branded homepage traffic in Google Search Console: Many users discover brands through LLM responses, then search directly in Google to validate or learn more. This two-step discovery pattern is critical to monitor. When branded homepage traffic increases alongside rising LLM presence, it signals a strong causal connection between LLM visibility and user behavior. This metric captures the downstream impact of your LLM optimization efforts.

Nobody has complete visibility into LLM impact on their business today, but these methods cover all the bases you can currently measure.

Be wary of any vendor or consultant promising complete visibility. That simply isn’t possible yet.

Understanding these limitations is just as important as implementing the tracking itself.

Because no perfect models exist yet, treat current tracking data as directional – useful for decisions, but not definitive.

Why mentions matter more than citations

Dig deeper: In GEO, brand mentions do what links alone can’t

Estimating LLM ‘search volume’

Measuring LLM impact is one thing. Identifying which queries and topics matter most is another.

Compared to SEO or PPC, marketers have far less visibility. While no direct search volume exists, new tools and methods are beginning to close the gap.

The key shift is moving from tracking individual queries – which vary widely – to analyzing broader themes and topics. 

The real question becomes: which areas is your site missing, and where should your content strategy focus?

To approximate relative volume, consider three approaches:

Correlate with SEO search volume

Start with your top-performing SEO keywords. 

If a keyword drives organic traffic and has commercial intent, similar questions are likely being asked within LLMs. Use this as your baseline.

Layer in industry adoption of AI

Estimate what percentage of your target audience uses LLMs for research or purchasing decisions:

  • High AI-adoption industries: Assume 20-25% of users leverage LLMs for decision-making.
  • Slower-moving industries: Start with 5-10%.

Apply these percentages to your existing SEO keyword volume. For example, a keyword with 25,000 monthly searches could translate to 1,250-6,250 LLM-based queries in your category.

Using emerging inferential tools

New platforms are beginning to track query data through API-level monitoring and machine learning models. 

Accuracy isn’t perfect yet, but these tools are improving quickly. Expect major advancements in inferential LLM query modeling within the next year or two.

Get the newsletter search marketers rely on.

See terms.

Optimizing for LLM visibility

The technologies that help companies identify what to improve are evolving quickly. 

While still imperfect, they’re beginning to form a framework that parallels early SEO development, where better tracking and data gradually turned intuition into science.

Optimization breaks down into two main questions:

  • What content should you create or update, and should you focus on quality content, entities, schema, FAQs, or something else?
  • How should you align these insights with broader brand and SEO strategies?

Identify what content to create or update

One of the most effective ways to assess your current position is to take a representative sample of high-intent queries that people might ask an LLM and see how your brand shows up relative to competitors. This is where the Share of Voice tracking tools we discussed earlier become invaluable.

These same tools can help answer your optimization questions:

  • Track who is being cited or mentioned for each query, revealing competitive positioning.
  • Identify which queries your competitors appear for that you don’t, highlighting content gaps.
  • Show which of your own queries you appear for and which specific assets are being cited, pinpointing what’s working.

From this data, several key insights emerge:

  • Thematic visibility gaps: By analyzing trends across many queries, you can identify where your brand underperforms in LLM responses. This paints a clear picture of areas needing attention. For example, you’re strong in SEO but not in PPC content. 
  • Third-party resource mapping: These tools also reveal which external resources LLMs reference most frequently. This helps you build a list of high-value third-party sites that contribute to visibility, guiding outreach or brand mention strategies. 
  • Blind spot identification: When cross-referenced with SEO performance, these insights highlight blind spots; topics or sources where your brand’s credibility and representation could improve.

Understand the overlap between SEO and LLM optimization

LLMs may be reshaping discovery, but SEO remains the foundation of digital visibility.

Across five competitive categories, brands ranking on Google’s first page appeared in ChatGPT answers 62% of the time – a clear but incomplete overlap between search and AI results.

That correlation isn’t accidental. 

Many retrieval-augmented generation (RAG) systems pull data from search results and expand it with additional context. 

The more often your content appears in those results, the more likely it is to be cited by LLMs.

Brands with the strongest share of voice in LLM responses are typically those that invested in SEO first. 

Strong technical health, structured data, and authority signals remain the bedrock for AI visibility.

What this means for marketers:

  • Don’t over-focus on LLMs at the expense of SEO. AI systems still rely on clean, crawlable content and strong E-E-A-T signals.
  • Keep growing organic visibility through high-authority backlinks and consistent, high-quality content.
  • Use LLM tracking as a complementary lens to understand new research behaviors, not a replacement for SEO fundamentals.

Redefine on-page and off-page strategies for LLMs

Just as SEO has both on-page and off-page elements, LLM optimization follows the same logic – but with different tactics and priorities.

Off-page: The new link building

Most industries show a consistent pattern in the types of resources LLMs cite:

  • Wikipedia is a frequent reference point, making a verified presence there valuable.
  • Reddit often appears as a trusted source of user discussion.
  • Review websites and “best-of” guides are commonly used to inform LLM outputs.

Citation patterns across ChatGPT, Gemini, Perplexity, and Google’s AI Overviews show consistent trends, though each engine favors different sources.

This means that traditional link acquisition strategies, guest posts, PR placements, or brand mentions in review content will likely evolve. 

Instead of chasing links anywhere, brands should increasingly target:

  • Pages already being cited by LLMs in their category.
  • Reviews or guides that evaluate their product category.
  • Articles where branded mentions reinforce entity associations.

The core principle holds: brands gain the most visibility by appearing in sources LLMs already trust – and identifying those sources requires consistent tracking.

On-page: What your own content reveals

The same technologies that analyze third-party mentions can also reveal which first-party assets, content on your own website, are being cited by LLMs. 

This provides valuable insight into what type of content performs well in your space.

For example, these tools can identify:

  • What types of competitor content are being cited (case studies, FAQs, research articles, etc.).
  • Where your competitors show up but you don’t.
  • Which of your own pages exist but are not being cited.

From there, three key opportunities emerge:

  • Missing content: Competitors are cited because they cover topics you haven’t addressed. This represents a content gap to fill.
  • Underperforming content: You have relevant content, but it isn’t being referenced. Optimization – improving structure, clarity, or authority – may be needed.
  • Content enhancement opportunities: Some pages only require inserting specific Q&A sections or adding better-formatted information rather than full rewrites.

Leverage emerging technologies to turn insights into action

The next major evolution in LLM optimization will likely come from tools that connect insight to action.

Early solutions already use vector embeddings of your website content to compare it against LLM queries and responses. This allows you to:

  • Detect where your coverage is weak.
  • See how well your content semantically aligns with real LLM answers.
  • Identify where small adjustments could yield large visibility gains.

Current tools mostly generate outlines or recommendations.

The next frontier is automation – systems that turn data into actionable content aligned with business goals.

Timeline and expected results

While comprehensive LLM visibility typically builds over 6-12 months, early results can emerge faster than traditional SEO. 

The advantage: LLMs can incorporate new content within days rather than waiting months for Google’s crawl and ranking cycles. 

However, the fundamentals remain unchanged.

Quality content creation, securing third-party mentions, and building authority still require sustained effort and resources. 

Think of LLM optimization as having a faster feedback loop than SEO, but requiring the same strategic commitment to content excellence and relationship building that has always driven digital visibility.

From SEO foundations to LLM visibility

LLM traffic remains small compared to traditional search, but it’s growing fast.

A major shift in resources would be premature, but ignoring LLMs would be shortsighted. 

The smartest path is balance: maintain focus on SEO while layering in LLM strategies that address new ranking mechanisms.

Like early SEO, LLM optimization is still imperfect and experimental – but full of opportunity. 

Brands that begin tracking citations, analyzing third-party mentions, and aligning SEO with LLM visibility now will gain a measurable advantage as these systems mature.

In short:

  • Identify the third-party sources most often cited in your niche and analyze patterns across AI engines.
  • Map competitor visibility for key LLM queries using tracking tools.
  • Audit which of your own pages are cited (or not) – high Google rankings don’t guarantee LLM inclusion.
  • Continue strong SEO practices while expanding into LLM tracking – the two work best as complementary layers.

Approach LLM optimization as both research and brand-building.

Don’t abandon proven SEO fundamentals. Rather, extend them to how AI systems discover, interpret, and cite information.

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Build Brand Awareness: Strategies to Boost Visibility

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If your target audience doesn’t know you exist, they won’t buy from you. Simple as that.

That’s why you need to build brand awareness the right way. Not just through paid ads or ranking for keywords. Real brand awareness is how people remember you, talk about you, and choose you when they’re ready to buy. 

Here’s something most marketers miss: AI tools like ChatGPT and Google’s AI Overviews are now major discovery channels. These platforms cite recognizable brands more than unknown ones. If your brand isn’t mentioned across the web, you’re invisible in AI search results too. 

This guide focuses on organic growth. We’ll cover consistent messaging, smart partnerships, and making the most of platforms you already use. If you want to show up, stand out, and stick in people’s minds, here’s how to do it.

Key Takeaways

  • Brand awareness drives visibility in both traditional search and AI-powered searches
  • Consistent branding across platforms builds familiarity faster than sporadic campaigns. 
  • Thought leadership and strategic partnerships amplify reach without ad spend. 
  • You can build strong brand awareness organically with a focused, persistent plan.

Why Brand Awareness Matters More Now Than Ever

Familiarity breeds trust. The more people recognize your brand through brand mentions, the more likely they are to choose you over competitors.

Studies back this up. According to Invesp, 59% of customers prefer to buy from brands familiar to them. The more people recognize your brand, the more likely they are to choose you over competitors. Familiar brands feel safer. That trust shows up in clicks, conversions, and customer loyalty.

But there’s a new wrinkle: AI visibility.

Platforms like ChatGPT, Perplexity, and Google’s AI Overviews pull from recognizable brands when generating responses. If your brand isn’t mentioned in high-quality content, forum discussions, or authoritative sources, AI tools skip over you. That means potential customers never see your name.

Take a look at a Google AI Overview result for “best project management tools.” You’ll see names like Asana, Monday.com, and Trello cited repeatedly. Those brands didn’t get there by accident. They earned consistent mentions through strong branding, thought leadership, and organic content.

AI overviews for "Best project management tools."

Brand awareness also builds equity. The more recognizable you are, the easier it becomes to launch new products and charge preferred prices. Recognition compounds over time.

Elements of a Brand Awareness Strategy

Before you jump into tactics, you need a foundation. Brand awareness doesn’t happen from random acts of marketing, but a formal strategy.

Start with a clearly defined brand identity. That means locking in your tone of voice, visual style, core values, and key messaging. These elements should carry through your website, social profiles, email campaigns, and any other channel you use. Ideally, put this together in a guide that your team can reference when needed.

Next, understand your audience. You can’t build awareness if you don’t know who you’re targeting. Create detailed buyer personas and perform customer journey mapping so you know what platforms they use, what content they consume, and what problems they’re trying to solve.

You also need a clear content distribution plan. Will you focus on LinkedIn and YouTube? Or prioritize SEO and email marketing? The best strategies start narrow and expand once you’ve mastered one or two channels.

Organic Strategies to Increase Brand Awareness

Here’s where we get tactical. These strategies don’t require ad budgets, but they do require consistency.

Refine and Define Your Brand Identity

Let’s get into a little more detail about brand identities. After all, if you can’t clearly describe your brand’s personality, your audience won’t be able to either.

A real identity goes beyond logos and color palettes. It’s about consistent voice, values, and visuals across every touchpoint. Look at Slack: their playful tone and clean design are instantly recognizable whether you see a billboard or a tweet.

A Slack billboard.

Buffer does this exceptionally well. Check out their homepage and Instagram side by side. The fonts, colors, photography style, and tone are completely aligned. That consistency makes the brand easier to recognize and harder to forget.

The Buffer website.
Buffer's Instagram.

This is what you’re aiming for. Unified branding builds memory and trust.

Here’s your action plan:

  • Document your brand guidelines (tone, colors, fonts, logo usage)
  • Train your team on how to apply those guidelines
  • Audit your current channels to spot inconsistencies
  • Fix the gaps before launching new campaigns

Optimize Profiles on Search Engines and Social

Your digital storefronts often make the first impression, not your website.

Google Business Profiles, LinkedIn, Facebook, Instagram, and even TikTok bios are discovery points. If those profiles are incomplete or outdated, you’re wasting opportunities to build awareness.

Take this optimized Google Business Profile for a local coffee shop. They’ve included high-quality photos, accurate hours, keywords in the business description, customer reviews, and direct links to their website and menu. This kind of completeness signals credibility to both users and search algorithms.

The Google Business profile for the Black Pearl Coffee shop.

The same logic applies to social platforms. A half-finished LinkedIn profile or an Instagram bio with no link hurts your brand more than it helps. Fill out every field. Use keywords naturally. Link to your site.

Pro tip: Claim your brand name on every major platform, even if you’re not active there yet. You don’t want someone else grabbing your handle or creating confusion.

Consider Influencer/Other Brand Partnerships

You don’t need to go viral to reach more people. You can start by tapping into someone else’s audience.

Influencer marketing and strategic brand collaborations amplify your visibility organically. But follower count isn’t everything. Look for:

  • Alignment in audience demographics and values
  • Authentic content that matches your brand tone
  • A track record of real engagement, not just vanity metrics

Gymshark is a perfect example. They partnered with micro-influencers who created TikTok workout videos while wearing their gear. The content looked native to the platform and felt genuine because it was. That authenticity drove massive brand awareness without traditional advertising.

Influencers that partner with Gymshark on TikTok.

Another route: collaborate with complementary brands. If you sell coffee, partner with a local bakery for a co-branded event. Cross-promote on social. Share each other’s audiences. Both brands win.

Find Engagement Opportunities With Your Audience

Conversations spark memory. The more your audience interacts with you, the more likely they are to remember you.

Engagement doesn’t have to be complicated. It can be as simple as replying to comments on Instagram or as involved as hosting live Q&A sessions on LinkedIn. Spotify Wrapped is a masterclass here. Users eagerly share their personalized results every year, generating millions of organic impressions.

Spotify Wrapped

Duolingo takes a different approach with humor. Their social team replies to comments with witty, on-brand responses that often get more engagement than the original post. That two-way interaction builds presence faster than broadcasting alone.

A social media interaction with Duolingo.

Here are practical ways to boost engagement:

  • Respond to every comment on your posts (yes, every one)
  • Ask questions in your captions to spark replies
  • Run polls and surveys to gather feedback
  • Host AMAs (Ask Me Anything) on Reddit or Instagram Live
  • Create shareable content that encourages tagging and reposting

 The more people interact with your brand, the more familiar you become.

Use A/B Testing

Guessing what resonates with your audience is a waste of time. Test it.

A/B testing helps you figure out what messaging, visuals, and formats drive the most engagement. More engagement means more brand recognition.

Start simple. Test two email subject lines to see which gets more opens. Try two different Instagram captions to see which gets more comments. Experiment with video thumbnails on YouTube.

Tools like Google Optimize, Optimizely, or even native platform analytics can help you run these tests. The insights you gain will help you refine your brand messaging over time.

Practice an Omnichannel Strategy

Your audience isn’t glued to one platform. They move between email, social media, search engines, podcasts, and even voice assistants.

Omnichannel marketing means showing up across all of them with consistency. Not copy-pasting the same content everywhere, but adapting your core message to fit each channel’s format and audience expectations.

Canva nails this. Their email campaigns, LinkedIn posts, and TikTok videos all maintain the same visual identity and helpful tone. The messaging shifts slightly to match each platform, but the brand feels cohesive.

An email from Canva.
Canva's Linkedin Page.
Canva's Instagram page.

That cohesion makes the brand easier to remember and trust. People see you everywhere, and repetition builds familiarity.

Here’s how to execute an omnichannel strategy:

  • Identify the three to five platforms your audience uses most
  • Develop content formats that work on each (blog posts, videos, infographics, podcasts)
  • Use scheduling tools to maintain a consistent presence
  • Track performance to see where you’re gaining traction

 You don’t need to be everywhere. Just be consistent where you want to show up.

Provide Value (Without Asking For Something Back)

Not every piece of content needs a CTA or a sales pitch.

Free value builds goodwill and gives people a reason to remember you. Think templates, tutorials, calculators, and guides. No gates. No hard pitch. Just useful content.

HubSpot mastered this years ago. Their free CRM, blog templates, and educational resources turned them into a go-to source for marketers. People associate HubSpot with helpfulness, not just software.

Reports from HubSpot.

You can do the same on a smaller scale:

  • Publish how-to guides that solve real problems
  • Create free tools or templates your audience can download
  • Share behind-the-scenes insights into your processes
  • Offer free consultations or audits (if it fits your business model)

When you consistently give without asking, people remember. And when they’re ready to buy, you’re top of mind.

Build Out A Thought Leadership Plan

Thought leadership isn’t about ego. It’s strategic positioning.

People trust brands that demonstrate expertise. That trust leads to mentions, shares, backlinks, and citations in AI tools. All of these feed into organic brand awareness.

Effective thought leadership formats include:

  • Guest posts on authoritative industry blogs
  • Original research or data studies published on your site
  • Speaking opportunities at conferences or webinars
  • Contributions to expert roundups and interviews
  • Regular insights shared on LinkedIn or Twitter

The key is consistency. One viral post won’t make you a thought leader. Publishing valuable insights month after month will.

And here’s the bonus: thought leadership directly impacts E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness), which Google uses to evaluate content quality. The more you establish your expertise, the better your content performs in search and AI results.

Generate Social Proof

People trust people more than they trust brands.

That’s why social proof (testimonials, reviews, user-generated content) is one of the most effective ways to build credibility and awareness.

Feature happy customers in your marketing. Encourage product photos and reviews. Highlight tweets or Instagram posts tagging your brand. Showcase case studies that demonstrate real results.

This example from Glossier does it perfectly. They regularly feature customer photos and testimonials across their social channels and website. Real people using real products. That authenticity drives trust and recognition.

Social proof from Glossier.

Here’s how to generate social proof:

  • Ask satisfied customers for testimonials and reviews
  • Create a branded hashtag and encourage customers to use it
  • Run contests that incentivize user-generated content
  • Feature customer stories in your email campaigns and blog posts
  • Display review ratings prominently on your website

The more your customers talk about you, the more awareness you build.

How To Measure Brand Awareness Strategy Success

Not everything that matters can be measured, but a lot of it can.

Here are the key signals that your brand awareness strategy is working:

  • Search traffic for branded keywords: Track how many people search for your brand name or variations in Google Search Console. Rising branded searches indicate growing awareness.
  • Brand mentions: Use tools like Brand24, Mention, or Google Alerts to monitor how often your brand gets mentioned across the web and social media. More mentions mean more visibility.
  • Social engagement: Look beyond follower counts. Are people commenting, sharing, and tagging your brand? High engagement signals strong awareness.
  • Direct traffic: Check your analytics for direct traffic (people typing your URL directly into their browser). This suggests they already know who you are.
  • Survey responses: Run simple brand awareness surveys asking, “Have you heard of [Your Brand]?” Track the percentage over time.
  • AI visibility: Search for industry-related queries in ChatGPT or Google’s AI Overviews. Does your brand get mentioned? This is becoming increasingly important for brand mentions and overall visibility. Dedicated tools like Profound also specifically focus on AI visibility.

Here’s a snapshot of brand tracking in Mention:

How brand mentions are tracked in Mention.

Review these metrics monthly. Trends matter more than one-off spikes. A consistent upward trajectory means your strategy is working.

FAQs

How to build brand awareness?

Start with a clear brand identity and consistent messaging. Optimize your profiles across search and social platforms. Publish valuable content regularly. Engage with your audience. Partner with influencers or complementary brands. Focus on providing value without always asking for something in return.

Why build brand awareness?

Because people buy from brands they recognize and trust. Brand awareness drives customer loyalty, makes new product launches easier, and increases your visibility in both traditional search and AI-powered tools. Without awareness, you’re invisible to potential customers.

How long does it take to build brand awareness?

Typically, three to six months to see initial traction, but long-term brand awareness builds over years. Consistency matters more than speed. Stick with your strategy, measure your progress, and refine based on what’s working.

<h2>Conclusion</h2>

Conclusion

Brand awareness isn’t a vanity metric. It’s the foundation of every sale you’ll make tomorrow.

If people don’t remember you, they can’t choose you. That’s why consistent branding, smart engagement, and value-driven content matter so much. These strategies don’t require massive budgets. They require focus and persistence.

Start with one or two tactics from this guide. Master those before expanding. Track your metrics to see what’s working. Improve your visibility step by step.

Want help building a brand people actually remember? NP Digital can help you develop a full-funnel strategy that drives awareness and growth.

Read more at Read More

The future of SEO teams is human-led and agent-powered

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The conversation around artificial intelligence (AI) has been dominated by “replacement theory” headlines. From front-line service roles to white-collar knowledge work, there’s a growing narrative that human capital is under threat.

Economic anxiety has fueled research and debate, but many of the arguments remain narrow in scope.

  • Stanford’s Digital Economy Lab found that since generative AI became widespread, early-career workers in the most exposed jobs have seen a 13% decline in employment.
  • This fear has spread into higher-paid sectors as well, with hedge fund managers and CEOs predicting large-scale restructuring of white-collar roles over the next decade.

However, much of this narrative is steeped in speculation rather than the fundamental, evolving dynamics of skilled work.

Yes, we’ve seen layoffs, hiring slowdowns, and stories of AI automating tasks. But this is happening against the backdrop of high interest rates, shifts in global trade, and post-pandemic over-hiring.

As the global talent thought-leader Josh Bersin argues, claims of mass job destruction are “vastly over-hyped.” Many roles will transform, not vanish. 

What this means for SEO

For the SEO discipline, the familiar refrain “SEO is dead” is just as overstated.

Yes, the nature of the SEO specialist is changing. We’ve seen fewer leadership roles, a contraction in content and technical positions, and cautious hiring. But the function itself is far from disappearing.

In fact, SEO job listings remain resilient in 2025 and mid-level roles still comprise nearly 60% of open positions. Rather than declining, the field is being reshaped by new skill demands.

Don’t ask, “Will AI replace me?” Ask instead, “How can I use AI to multiply my impact?”

Think of AI not as the jackhammer replacing the hammer but as the jackhammer amplifying its effect. SEOs who can harness AI through agents, automation, and intelligent systems will deliver faster, more impactful results than ever before.

  • “AI is a tool. We can make it or teach it to do whatever we want…Life will go on, economies will continue to be driven by emotion, and our businesses will continue to be fueled by human ideas, emotion, grit, and hard work,” Bersin said.

Rewriting the SEO narrative

As an industry, it’s time to change the language we use to describe SEO’s evolution.

Too much of our conversation still revolves around loss. We focus on lost clicks, lost visibility, lost control, and loss of num=100.

That narrative doesn’t serve us anymore.

We should be speaking the language of amplification and revenue generation. SEO has evolved from “optimizing for rankings” to driving measurable business growth through organic discovery, whether that happens through traditional search, AI Overviews, or the emerging layer of Generative Engine Optimization (GEO).

AI isn’t the villain of SEO; it’s the force multiplier.

When harnessed effectively, AI scales insight, accelerates experimentation, and ties our work more directly to outcomes that matter:

  • Pipeline.
  • Conversions.
  • Revenue.

We don’t need to fight the dystopian idea that AI will replace us. We need to prove that AI-empowered SEOs can help businesses grow faster than ever before.

The new language of SEO isn’t about survival, it’s about impact.

The team landscape has already shifted

For years, marketing and SEO teams grew headcount to scale output.

Today, the opposite is true. Hiring freezes, leaner budgets, and uncertainty around the role of SEO in an AI-driven world have forced leaders to rethink team design.

A recent Search Engine Land report noted that remote SEO roles dropped to 34% of listings in early 2025, while content-focused SEO positions declined by 28%. A separate LinkedIn survey found a 37% drop in SEO job postings in Q1 compared to the previous year.

This signals two key shifts:

  • Specialized roles are disappearing. “SEO writers” and “link builders” are being replaced by versatile strategists who blend technical, analytical, and creative skill sets.
  • Leadership is demanding higher ROI per role. Headcount is no longer the metric of success – capability is.

What it means for SEO leadership

If your org chart still looks like a pyramid, you’re behind. 

The new landscape demands flexibility, speed, and cross-functional integration with analytics, UX, paid media, and content.

It’s time to design teams around capabilities, not titles.

Rethinking SEO Talent

The best SEO leaders aren’t hiring specialists, they’re hiring aptitude. Modern SEO organizations value people who can think across disciplines, not just operate within one.

The strongest hires we’re seeing aren’t traditional technical SEOs focused on crawl analysis or schema. They’re problem solvers – marketers who understand how search connects to the broader growth engine and who have experience scaling impact across content, data, and product.

Progressive leaders are also rethinking resourcing. The old model of a technical SEO paired with engineering support is giving way to tech SEOs working alongside AI product managers and, in many cases, vibe coding solutions. This model moves faster, tests bolder, and builds systems that drive real results.

For SEO leaders, rethinking team architecture is critical. The right question isn’t “Who should I hire next?” It’s “What critical capability must we master to stay competitive?”

Once that’s clear, structure your people and your agents around that need. The companies that get this right during the AI transition will be the ones writing the playbook for the next generation of search leadership.

The new human-led, agent-empowered team

The future of SEO teams will be defined by collaboration between humans and agents.

  • These agents are AI-enabled systems like automated content refreshers, site-health bots, or citation-validation agents that work alongside human experts.
  • The human role? To define, train, monitor, and QA their output.

Why this matters

  • Agents handle high-volume, repeatable tasks (e.g., content generation, basic auditing, link-score filtering) so humans can focus on strategy, insight, and business impact.
  • The cost of building AI agents can range from $20,000 to $150,000, depending on the complexity of the system, integrations, and the specialized work required across data science, engineering, and human QA teams, according to RTS Labs.
  • A single human manager might oversee 10-20 agents, shifting the traditional pyramid and echoing the “short pyramid” or “rocket ship” structure explored by Tomasz Tunguz.

The future: teams built around agents and empowered humans.

Real-world archetypes

  • SaaS companies: Develop a bespoke “onboarding agent” that reads product data, builds landing pages, and runs first-pass SEO audits, human strategist refines output.
  • Marketplace brands (e.g., upcoming seasonal trend): Use an “Audience Discovery Agent” that taps customer and marketplace data, but the human team writes the narrative and guides the vertical direction.
  • Enterprise content hubs: deploy “Content Refresh Agents” that identify high-value pages, suggest optimizations, and push drafts that editors review and finalise.

Integration is key

These new teams succeed when they don’t live in silos. The SEO/GEO squad must partner with paid search, analytics, revenue ops, and UX – not just serve them.

Agents create capacity; humans create alignment and amplification.

A call to SEO practitioners

Building the SEO community of the future will require change.

The pace of transformation has never been faster and it’s created a dangerous dependence on third-party “AI tools” as the answer to what is unknown.

But the true AI story doesn’t begin with a subscription. It begins inside your team.

If the only AI in your workflow is someone else’s product, you’re giving up your competitive edge. The future belongs to teams that build, not just buy.

Here’s how to start:

  • Build your own agent frameworks, designed with human-in-the-loop oversight to ensure accuracy, adaptability, and brand alignment.
  • Partner with experts who co-create, not just deliver. The most successful collaborations help your team learn how to manage and scale agents themselves.
  • Evolve your team structure, move beyond the pyramid mentality, and embrace a “rocket ship” model where humans and agents work in tandem to multiply output, insights, and results.

The future of SEO starts with building smarter teams. It’s humans working with agents. It’s capability uplift. And if you lead that charge, you’ll not only adapt to the next generation of search, you’ll be the ones designing it.

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Search Engine Land Awards 2025: And the winners are…

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Search Engine Land 2025 Awards

Every year, Search Engine Land is delighted to celebrate the best of search marketing by rewarding the agencies, in-house teams, and individuals worldwide for delivering exceptional results.

Today, I’m excited to announce all 18 winners of the 11th annual Search Engine Land Awards.

The 2025 Search Engine Land Awards winners

Best Use Of AI Technology In Search Marketing

  • 15x ROAS with AI: How CAMP Digital Redefined Paid Search for Home Services

Best Overall PPC Initiative – Small Business

  • Anchor Rides – Post-Hurricane PPC Comeback (AIMCLEAR)

Best Overall PPC Initiative – Enterprise

  • ATRA & Jason Stone Injury Lawyers – Leveraging CRM Data to Scale Case Volume

Best Commerce Search Marketing Initiative – PPC

  • Adwise & Azerty – 126% uplift in profit from paid advertising & 1 percent point net margin business uplift by advanced cross-channel bucketing

Best Local Search Marketing Initiative – PPC

  • How We Crushed Belron’s Lead Target by 238% With an AI-Powered Local Strategy (Adviso)

Best B2B Search Marketing Initiative – PPC

  • Blackbird PPC and Customer.io: Advanced Data Integration to Drive 239% Revenue Increase with 12% Greater Lead Efficiency, with MMM Future-Proofing 2025 Growth

Best Integration Of Search Into Omnichannel Marketing

  • How NBC used search to drive +2,573 accounts in a Full-Funnel Media Push (Adviso)

Best Overall SEO Initiative – Small Business

  • Digital Hitmen & Elite Tune: The Toyota Shift That Delivered 678% SEO ROI

Best Overall SEO Initiative – Enterprise

  • 825 Million Clicks, Zero Content Edits: How Amsive Engineered MSN’s Technical SEO Turnaround

Best Commerce Search Marketing Initiative – SEO

  • Scaling Non-Branded SEO for Assouline to Drive +26% Organic Revenue Uplift (Block & Tam)

Best Local Search Marketing Initiative – SEO

  • Building an Unbeatable Foundation for Success: Using Hyperlocal SEO to Build Exceptional ROI (Digital Hitmen)

Best B2B Search Marketing Initiative – SEO

  • Page One, Pipeline Won: The B2B SEO Playbook That Turned 320 Visitors into $10.75M in Pipeline (LeadCoverage)

Agency Of The Year – PPC

  • Driving Growth Where Search Happens: Stella Rising’s Paid Search Transformation

Agency Of The Year – SEO

  • How Amsive Rescued MSN’s Global Visibility Through Enterprise Technical SEO at Scale

In-House Team Of The Year – SEO

  • How the American Cancer Society’s Lean SEO Team Drove Enterprise-Wide Consolidation and AI Search Visibility Gains for Cancer.org

Search Marketer Of The Year

  • Mike King, founder and CEO of iPullRank

Small Agency Of The Year – PPC

  • ATRA & Jason Stone Injury Lawyers – Leveraging CRM Data to Scale Case Volume

Small Agency Of The Year – SEO

  • From Zero to Top of the Leaderboard: Bloom Digital Drives Big Growth With Small SEO Budgets

“I’m going to SMX Next!”

Select winners of the 2025 Search Engine Land Awards will be invited to speak live at SMX Next during our two ask-me-anything-style sessions. Bring your burning SEO and PPC questions to ask this award-winning panel of search marketers!

Register here for SMX Next (it’s free) if you haven’t yet.

Congrats again to all the winners. And huge thank yous to everyone who entered the 2025 Search Engine Land Awards, the finalists, and our fantastic panel of judges for this year’s awards.

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Why a lower CTR can be better for your PPC campaigns

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Why a lower CTR can be better for your Google Ads campaigns

Many PPC advertisers obsess over click-through rates, using them as a quick measure of ad performance.

But CTR alone doesn’t tell the whole story – what matters most is what happens after the click. That’s where many campaigns go wrong.

The problem with chasing high CTRs

Most advertisers think the ad with the highest CTR is often the best. It should have a high Quality Score and attract lots of clicks.

However, in most cases, lower CTR ads usually outperform higher CTR ads in terms of total conversions and revenue.

If all I cared about was CTR, then I could write an ad:

  • “Free money.”
  • “Claim your free money today.”
  • “No strings attached.”

That ad would get an impressive CTR for many keywords, and I’d go out of business pretty quickly, giving away free money. 

When creating ads, we must consider:

  • Type of searchers we want to attract.
  • Ensure the users are qualified.
  • Set expectations for the landing page.

I can take my free money ad and refine it:

  • “Claim your free money.”
  • “Explore college scholarships.”
  • “Download your free guide.”

I’ve now:

  • Told searchers they can get free money for college through scholarships if they download a guide.
  • Narrowed down my audience to people who are willing to apply for scholarships and willing to download a guide, presumably in exchange for some information.

If you focus solely on CTR and don’t consider attracting the right audience, your advertising will suffer. 

While this sentiment applies to both B2C and B2B companies, B2B companies must be exceptionally aware of how their ads appear to consumers versus business searchers. 

B2B companies must pre-qualify searchers

If you are advertising for a B2B company, you’ll often notice that CTR and conversion rates have an inverse relationship. As CTR increases, conversion rates decrease.

The most common reason for this phenomenon is that consumers and businesses can search for many B2B keywords. 

B2B companies must try to show that their products are for businesses, not consumers.

For instance, “safety gates” is a common search term. 

The majority of people looking to buy a safety gate are consumers who want to keep pets or babies out of rooms or away from stairs. 

However, safety gates and railings are important for businesses with factories, plants, or industrial sites. 

These two ads are both for companies that sell safety gates. The first ad’s headlines for Uline could be for a consumer or a business. 

It’s not until you look at the description that you realize this is for mezzanines and catwalks, which is something consumers don’t have in their homes. 

As many searchers do not read descriptions, this ad will attract both B2B and B2C searchers. 

OSHA compliance - Google Ads

The second ad mentions Industrial in the headline and follows that up with a mention of OSHA compliance in the description and the sitelinks. 

While both ads promote similar products, the second one will achieve a better conversion rate because it speaks to a single audience. 

We have a client who specializes in factory parts, and when we graph their conversion rates by Quality Score, we can see that as their Quality Score increases, their conversion rates decrease. 

They will review their keywords and ads whenever they have a 5+ Quality Score on any B2B or B2C terms. 

This same logic does not apply to B2B search terms. 

Those terms often contain more jargon or qualifying statements when looking for B2B services and products. 

B2B advertisers don’t have to use characters to weed out B2C consumers and can focus their ads only on B2B searchers.

How to balance CTR and conversion rates

As you are testing various ads to find your best pre-qualifying statements, it can be tricky to examine the metrics. Which one of these would be your best ad?

  • 15% CTR, 3% conversion rate.
  • 10% CT, 7% conversion rate.
  • 5% CTR, 11% conversion rate.

When examining mixed metrics, CTR and conversion rates, we can use additional metrics to define our best ads. My favorite two are:

  • Conversion per impression (CPI): This is a simple formula dividing your conversion by the number of impressions (conversions/impressions). 
  • Revenue per impression (RPI): If you have variable checkout amounts, you can instead use your revenue metrics to decide your best ads by dividing your revenue by your impressions (revenue/impressions).

You can also multiply the results by 1,000 to make the numbers easier to digest instead of working with many decimal points. So, we might write: 

  • CPI = (conversions/impressions) x 1,000 

By using impression metrics, you can find the opportunity for a given set of impressions. 

CTR Conversion rate Impressions Clicks Conversions CPI
15% 3% 5,000 750 22.5 4.5
10% 7% 4,000 400 28 7
5% 11% 4,500 225 24.75 5.5

By doing some simple math, we can see that option 2, with a 10% CTR and a 7% conversion rate, gives us the most total conversions.

Dig deeper: CRO for PPC: Key areas to optimize beyond landing pages

Focus on your ideal customers

A good CTR helps bring more people to your website, improves your audience size, and can influence your Quality Scores.

However, high CTR ads can easily attract the wrong audience, leading you to waste your budget.

As you are creating headlines, consider your audience. 

  • Who are they? 
  • Do non-audience people search for your keywords?
    • How do you dissuade users who don’t fit your audience from clicking on your ads? 
  • How do you attract your qualified audience?
  • Are your ads setting proper landing page expectations?

By considering each of these questions as you create ads, you can find ads that speak to the type of users you want to attract to your site. 

These ads are rarely your best CTRs. These ads balance the appeal of high CTRs with pre-qualifying statements that ensure the clicks you receive have the potential to turn into your next customer. 

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A recap of the October 2025 SEO Update by Yoast

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The message from this month’s SEO Update is clear: AI and data accuracy are reshaping how we plan, optimize, and measure SEO. This is not just a slate of updates, but a signal to rethink impressions, content creation, and tooling so you stay effective. Chris Scott, Yoast’s Senior Marketing Manager, hosted the session. Alex Moss and Carolyn Shelby shared deep dives on AI trends, Google updates, and Yoast product news.

Data and rankings in flux

A key shift centers on data. Google removed the num=100 parameter, which changed how much ranking data shows up per page in Google Search Console. The result isn’t a sudden performance drop; it’s a correction. Impressions can look lower because the data is being cleaned up, and that matters more than the raw numbers. Paid search data stays solid, since ads rely on precise counting for financial reasons.

AI content and media: use it, don’t rely on it

Sora 2 can generate short videos from text prompts, providing handy visuals to accompany blog posts. Use AI visuals to complement your core messaging, not to replace it. In e-commerce, Walmart, WooCommerce, and Shopify are testing AI-enabled shopping features. Don’t rush a full switch before major buying events.

Local SEO and engines beyond Google

Bing’s Business Manager now has a refreshed UI focused on local listings, signaling a push into local search. Diversifying beyond Google can reveal new AI-powered opportunities. It’s about testing where AI-driven search and shopping perform best, not moving budgets blindly.

AI mode and how people behave

Research into AI-dominant sessions shows a distinct pattern: users linger 50 to 80 seconds on AI-generated text, and clicks tend to be transactional. Intent patterns shift, too. Now, comparisons lead to review sites, decisive purchases land on product pages, and local tasks point to maps and assets.

Meta descriptions and AI generation

Google tested AI-generated descriptions for threads lacking meta content, but meta descriptions aren’t obsolete. Best practice is to lean on Yoast’s default meta templates (like %excerpt%) as a reliable fallback. Write with an inverted pyramid in mind, which puts key information first, so AI can extract it cleanly. Keep a fallback description in Yoast SEO so automation stays under your control.

AI in everyday workflows

ChatGPT updates push toward more human-to-human interactions, and tools like Slack can summarize threads and search discussions by meaning, not just keywords. Growth in AI usage feels steadier now; some younger users opt for other AI tools.

Insights from Microsoft and Google

The core rules haven’t changed: concise, unique, value-packed content wins. Shorter, focused writing works best for AI synthesis; trim fluff and sharpen clarity. The message is simple because clarity beats complexity, especially as AI becomes more central to how content is consumed.

Yoast product updates to watch

The Yoast SEO AI+ bundle adds AI Brand Insights to track mentions and citations in AI outputs, and pronoun support has been added to schema markup for inclusivity. If you’re tracking AI relevance beyond traditional signals, this bundle can be a smart addition.

Next actions and a quick invitation

For more news, you can join the next SEO Update by Yoast on November 24. The transcript, video, and news items are all available on the SEO Update by Yoast October Edition webinar page. For more information and options to watch future webinars, you can also visit the main Yoast webinars listings.

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