SEO 101: Basics for 2026

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Key Takeaways

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

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

That hasn’t changed. 

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

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

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

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

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

Google search results page showing an AI Overview answer

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

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

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

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

Why Is SEO Important?

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

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

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

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

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

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

How AI SEO Works

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

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

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

Traditional SEO AI SEO
Primary goal Rank in organic search results Get cited in AI-generated answers
Key signals Keywords, backlinks, on-page optimization E-E-A-T, brand mentions, structured data, topical authority
Content format Keyword-optimized, intent-matched Clear structure and direct answers, ideally in FAQ format
Success metrics Rankings, organic traffic, click-through rate (CTR) AI citations, brand mentions, share of voice
Technical foundation Crawlability, site speed, HTTPS, mobile Same, plus schema markup and structured data

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

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

Setting Yourself Up for SEO Success

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

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

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

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

Kim's Restaurant website site structure diagram example

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

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

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

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

Common SEO Myths

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

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

SEO Subtypes

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

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

SEO, GEO, and LLMO

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

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

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

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

SEO Basics #1: Keyword Research

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

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

Good keyword research can reveal:

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

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

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

Ubersuggest keyword ideas for vegan burger search terms

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

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

Quick Tips for Keyword Research

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

SEO Basics #2: Create Effective, Optimized Content

Good content is fundamental to SEO.

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

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

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

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

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

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

Here’s what each looks like in practice:

Key takeaways box example from NP Digital SEO blog
FAQ accordion section from NP Digital SEO blog post

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

Quick Tips for Content Creation

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

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

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

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

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

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

Urtopia meta description example in Google search results

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

Quick Tips for Crafting Title Tags and Meta Descriptions

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

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

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

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

Google knows this. 

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

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

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

Quick Tips for Improving UX

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

SEO Basics #5: Prioritize Mobile Experience

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

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

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

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

Google Lighthouse report showing 97 performance score

Quick Tips for Improving Mobile Experience

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

SEO Basics #6: Build Links

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

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

Ubersuggest backlinks report for neilpatel.com domain

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

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

Quick Tips for Building Links

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

SEO Basics #7: Don’t Neglect Technical SEO

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

Technical SEO is the foundation that makes everything else work.

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

Tips for Improving Technical SEO

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

SEO Basics #8: Measure Your Results

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

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

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

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

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

Semrush domain overview showing AI visibility metrics

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

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

Quick Tips for Measuring Results

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

FAQs

What is SEO?

SEO is the process of optimizing your website to increase the chances of it ranking high in search engine results. 

It includes a wide range of elements, including keyword research, content creation, backlinks, and mobile responsiveness.

How do I do SEO?

Start by auditing your existing content. Make your pages more readable, add keyword-optimized headings, and create unique title tags and meta descriptions. From there, work through the fundamentals covered in this guide.

What is on-page SEO?

On-page SEO is the process of optimizing the content and HTML elements on individual pages, including keywords, title tags, meta descriptions, and headings, to rank for the right queries.

What is technical SEO?

Technical SEO covers the infrastructure of your site, including speed, mobile-friendliness, crawlability, and structured data, ensuring search engines can find and index your content correctly.

What is local SEO?

Local SEO is the process of optimizing your online presence to appear in location-based searches, which is critical for brick-and-mortar businesses and service providers targeting customers in a specific area.

Conclusion

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

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

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

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

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Why your product is your most important SEO asset

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For a long time, we defined SEO success by rankings and traffic. If you reached the top of the search results and brought people to your site, you did your job. That approach worked when discovery was linear, and search engines were the primary gatekeepers. But modern search behavior does not stop at discovery. Users want clarity, reassurance, and confidence before they make decisions. With so many options to choose from, users want to understand what a product does, how it compares to alternatives, and whether it fits their needs.

There is a shift in SEO, one that pushes closer to product thinking and long-term value creation. Search engines reward content and experiences that help users make informed decisions, not just pages that match keywords. That means SEO can no longer exist solely in the acquisition channel. SEO must support the entire journey, from first touch to post-purchase experience.

Table of contents

Key takeaways

  • SEO now focuses on user clarity and informed decision-making rather than just rankings and traffic.
  • Businesses should adopt an approach that integrates product understanding and user intent into keyword research.
  • Technical SEO remains crucial; a well-structured site improves visibility for both users and AI systems.
  • Product content, including descriptions and FAQs, serves as a powerful SEO asset that should be optimized.
  • Schema markup is essential for AI systems to accurately interpret product information, enhancing visibility and recommendations.

Technical SEO has always been product thinking

Technical SEO has always mattered, and it’s been tied to product quality, or at least product page quality. Site speed, internal linking, structured content, and clear navigation all shape how users experience a product online.

A fast, well-structured site helps users and AI platforms better understand your products. That means better visibility in search engines and AI recommendations alike. Good SEO looks at the system as a whole, prioritizes changes based on impact, and focuses on removing friction, which are the same principles that guide good product decisions.

Think like a product marketer, not just an SEO

Ranking for keywords does not automatically mean you are reaching the right audience or communicating the right value. Product marketers spend time understanding who the product is for, what problem it solves, and why someone should choose it over alternatives. SEO benefits enormously from that same approach.  

Keyword research is not just a targeting exercise. It reveals how people describe their problems, what they care about, and what information they need before making a decision. Applying those insights to product descriptions, category pages, and supporting content pulls SEO closer to real user intent. 

This is how SEO moves beyond traffic and starts contributing to the full customer journey: awareness, consideration, conversion, and, just as importantly, retention.  

Your product is your most underrated SEO asset

Many SEO strategies still treat content as something separate from the product. Blogs live in one place while product pages are left to focus purely on conversion.  

But products are content. Product names, descriptions, specifications, FAQs, reviews, and even post-purchase information all reflect the real information users are looking for. This content often holds far more SEO value than a generic blog post. Still, most brands do not optimize it with the same level of care.

When product pages are clear, well-structured, and written in the language customers actually use, they become powerful discovery assets.

AI is changing how products are discovered and bought

Users are turning to AI platforms to ask for recommendations, evaluate options, and understand differences between products.  

ChatGPT now supports direct purchases through integrations with platforms like Shopify, using OpenAI’s Agentic Commerce Protocol. That means users can discover and buy products directly within an AI conversation without ever visiting a product page on a website.  

For businesses, this changes what visibility looks like. SEO is no longer just about ranking in search results. SEO is about making sure your products are understandable, trustworthy, and accessible to AI systems that act as intermediaries.  

And the scope of that is broader than it first appears. Google’s Universal Commerce Protocol (UCP) extends AI-mediated commerce well beyond the checkout, covering the full lifecycle from product discovery through to order management, post-purchase support, and loyalty. That means the journey SEO needs to support has grown significantly. It is not just about being found and bought; it is about being the kind of brand an AI agent would confidently recommend, follow up with, and return to. Read more about ACP and UCP and what they mean for SEOs.

Why schema matters more than ever

If AI systems are going to recommend and sell products, they need structured information to rely on. Schema provides that structure. It tells search engines and AI platforms what a product is, how much it costs, whether it is available, how it is reviewed, and how it fits into a broader catalog.  

Without structured data, products become harder for machines to interpret and surface. With it, they become eligible for richer visibility across search engines, LLMs, and emerging shopping experiences.  

This goes beyond the basics. Pricing, availability, reviews, FAQs, shipping details, and even compatibility information all contribute to how well an AI agent can evaluate and surface your products. Third-party reviews on platforms like Trustpilot also play a role. Agents use external signals to validate brand credibility before making a recommendation. If that structured data is incomplete or inconsistent, your products risk being entirely invisible to agent-mediated discovery. 

Conclusion

The rules of SEO have not been torn up but extended. Product thinking, structured data, clear content, and technical rigor have always mattered. What has changed is the audience you are optimizing for. Alongside the human visitor, you now have AI agents evaluating, recommending, and, in some cases, completing purchases on a user’s behalf. The businesses that will thrive are those that make their products easy to understand, easy to trust, and easy to surface, whether a person or a machine is doing the searching. 

The post Why your product is your most important SEO asset appeared first on Yoast.

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What are Backlinks and Why are they Crucial for SEO?

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 Key Takeaways

  • Backlinks are links from other websites to yours, and they still matter because they help search engines evaluate how authoritative and trustworthy your site is. 
  • Not all backlinks are equal. A few relevant, high-quality links from authoritative sites are usually more valuable than many weak or spammy ones. 
  • Backlinks support AI visibility because generative engines and language models favor content from authoritative, trustworthy sources, and backlinks are one of the clearest signals of that authority. 
  • Tracking backlinks means monitoring quality and growth. Pay attention to referring domains, anchor text distribution, and link stability over time. 
  • The best way to build backlinks is to earn them through useful content and targeted outreach. You will need to keep refining your approach based on what works. 

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

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

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

So, What Exactly Are Backlinks?

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

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

Example backlink of Wikipedia linking to Plausible.io

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

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

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

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

Backlink Examples/Types

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

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

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

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

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

Why Are Backlinks Important For SEO?

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

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

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

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

Ubersuggest’s backlink profile displaying Ubersuggest’s domain authority and credibility.

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

Why Quality Backlinks Matter

Quality beats quantity when it comes to backlinks. 

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

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

High-quality backlinks share a few common traits:

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

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

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

Infographic: good vs. bad backlink quality traits

Are Backlinks Important For AI?

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

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

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

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

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

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

Semrush’s bar chart showing the correlation between backlink metrics and AI visibility across 1,000 unique domains.

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

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

How to Track Your Backlinks

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

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

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

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

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

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

Backlink Building Best Practices

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

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

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

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

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

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

FAQs

What are backlinks?

Backlinks, also known as inbound links or incoming links, are links from one website to a page on another website. Search engines treat them as endorsements, using them to evaluate your content’s credibility and relevance, which can improve your visibility and rankings. They also play a role in AI search visibility. AI platforms tend to surface content from authoritative sources, and backlinks are one of the clearest signals of that authority.

How do I build backlinks?

Building backlinks ethically means creating content that earns links organically and reaching out to reputable sites in your industry. The strongest approaches include original research that journalists want to cite, digital PR campaigns that earn coverage on authoritative publications, and broken-link outreach that positions your content as a replacement for outdated resources. Quality and relevance matter more than volume.

How do I check my backlinks?

Ubersuggest’s free Backlink Checker is a strong starting point. It shows you which sites link to yours, flags links that look spammy or weak, and tracks referring domains, anchor text, and new or lost links over time. Those metrics together tell you whether your backlink profile is genuinely strong or just large.

Conclusion

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

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

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SEO for B2B: The AI Search Optimization Framework

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B2B SEO is the practice of making a business-to-business organization discoverable, accurately understood, and recommended by both traditional search engines […]

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Top 14 Best GEO Agencies in 2026: An Enterprise Buyer’s Evaluation

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The forgotten funnel: how brands can nurture post-conversion

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Most SEO strategies are built with one goal: getting people through the door. That usually means driving traffic to the website, ranking for high-volume keywords, and bringing in new users. But what happens after someone signs up or makes a purchase? That part of the funnel often gets ignored. SEO doesn’t stop at acquisition. It can and should be used to support retention, improve onboarding or post-purchase experience, and make your product or offering easier to understand. So let’s break down the opportunity in post-conversion content, why it matters for SEO, and how to identify and optimize it effectively.

Table of contents

Key takeaways

  • A lot of SEO strategies overlook post-conversion content, even though this type of content is great for an improved user experience.
  • Post-conversion content can include help docs, knowledge bases or product guides serving as long-tail SEO assets.
  • Engaged users generate positive signals, aiding in SEO through branded searches and reduced churn.
  • Identify post-conversion content by analyzing support tickets, customer interactions, and internal search queries.
  • Creating valuable guides and linking related content boosts retention and makes SEO efforts more effective.

Most brands stop too early

SEO strategies (understandably) love to focus on the top of the funnel: traffic, rankings, and new users. However, conversion isn’t the finish line. After someone signs up or makes a purchase, they’re still searching. They’re still learning, and they’re still deciding if they want to stick with you.  

This is where SEO can step in to support:  

  • Onboarding flows or post-purchase journeys  
  • Help docs
  • Community content
  • Knowledge bases

All of these are searchable, indexable, and incredibly useful. Not just for users, but for long-term organic growth.

The opportunity in post-purchase content 

Once someone starts using your product or receives their purchase, they often turn to Google (or your internal search) for answers about setup, usage, sizing, care, troubleshooting, or returns, depending on your business and industry. This is where content such as help centers, knowledge bases, product explainers, FAQs, or how-to guides comes into play. If they’re structured well, optimized for real user queries, and regularly updated, they become long-tail SEO machines.  

Another overlooked asset is community forums or customer reviews/Q&A sections. Real user questions and real answers lead to long-tail keywords and user-generated content that basically maintains itself.  

SEO benefits of retaining users and reducing churn

Retention isn’t just a product or support goal, but an SEO goal too. Engaged users generate more branded searches, click through internal content more often, share links, leave reviews, and make repeat purchases, creating positive engagement signals.

Reducing churn means people stay in your ecosystem longer, giving your website content more opportunities to show up, get linked, and build authority.

How to identify high-value post-conversion content 

This part isn’t guesswork; you already have the answers. The key is to tap into the real questions and friction points your users experience after they convert. Here’s how to do it: 

1. Support tickets

Look at the most common questions that indicate that something is not working or that users don’t understand something. If the same issue keeps popping up, that’s a signal you need better documentation or that your current documentation is not easy to find.  

How to use it: 
Turn top support issues into searchable help documents, step-by-step tutorials, or even short videos embedded in your knowledge base or product pages.  

2. Customer interactions

Your customer-facing teams hear things you won’t get from tickets. They will understand why certain products, features, or steps in the buying journey cause confusion. 

How to use it:  
Create content that supports onboarding or post-purchase usage, expands on underused products, features, or clarifies key steps in getting value from what was purchased. Pull direct language from how customers describe problems and try to use it to your advantage. They’ll likely use the same language to search for a solution.  

3. Internal search queries

Pro-tip: If you have a WordPress website, you can read our guide on how to optimize your internal search.

Your internal site or knowledge base search is one of the best indicators of intent. What users search for after logging in or visiting your site tells you exactly what they are struggling with.  

How to use it:  
Identify top queries that return poor results or no results. Create or improve content that answers those questions. Optimize titles, headers, and metadata so the right article appears first. 

4. Feature usage or product engagement data

Low usage doesn’t always mean low interest; it might mean unclear setup, poor discoverability, or hidden value.  

How to use it:  
Look at features or products with low adoption but high impact. Interview users who use them and reverse-engineer what made it work for them. Then build content that guides others to the same outcome.  

Types of high-value content to create

  • Feature walkthroughs or product usage guides: clear, step-by-step guides and how-tos with screenshots or GIFs.
  • Setup checklists: especially for more complex products
  • Integration or compatibility guides
  • Advanced use case tutorials
  • Other explainers and tactful guides for common mistakes

These pieces not only improve user experience but also target long-tail search queries, reduce support load, and strengthen retention. 

Below are examples of great post-conversion content:

An image from the Microsoft website, highlighting their Educator center and product guides.
Microsoft combines training hubs, such as the Educator Center, with help content and community resources to support users throughout their post-purchase journey.
An image of 3 articles from Nike's product care content section
This example comes from Nike’s website, which mainly focuses on product care and styling tips to help customers use and maintain their products.

Internal linking strategies that keep users engaged 

Post-conversion content shouldn’t live in isolation. It should be linked, surfaced, and reused across your entire ecosystem.  

Ways to keep users moving:  

  • Link between related help documents 
  • Add “next steps” CTAs to knowledge base articles 
  • Include product education content in lifecycle emails
  • Use breadcrumbs, related content widgets and in-context links

Done right, this turns your post-conversion content into an internal SEO web that improves engagement and makes users more confident in using your products.  

Why supporting existing users is good SEO and good business 

If your SEO strategy only focuses on acquisition, you’re leaving money (and traffic) on the table. Post-conversion content helps users get more value from your products, reduces friction, and builds long-term loyalty, all while creating indexable, intent-driven pages that search engines can surface at key moments.  

Want to take action? Start by auditing your post-conversion content. Map out the key moments after signup or purchase, and ensure users receive support at each step. Surface help docs, feature guides, and tutorials where they are needed most and connect them with clear, intentional internal links.  

SEO isn’t just about discovery. It’s about usability. It’s about confidence. It’s about making sure your users stay, not just show up. If you want to build long-term, defensible growth, that’s where you should be focusing. 

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What is Connected TV Advertising?

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Key Takeaways

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

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

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

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

What is Connected TV?

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

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

What Is CTV Advertising?

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

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

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

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

Google Ads vs DV360 CTV targeting options comparison
Google Ads vs DV360 CTV targeting options comparison

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

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

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

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

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

How Does CTV Advertising Work?

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

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

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

There are three main ways to buy CTV ads:

  1. Open auction or RTB: Prices are determined during a real-time auction.
CTV programmatic buy supply chain diagram

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

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

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

The key players in this process are:

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

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

Benefits of CTV Advertising

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

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

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

How to Plan and Execute a Connected TV Campaign

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

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

1. Develop Your Strategy

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

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

2. Choose the Right Platform

CTV advertising platforms including Netflix Roku and Hulu

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

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

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

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

3. Create Compelling Content

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

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

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

Examples worth studying

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

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

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

4. Set Your Budget and Bidding Strategy

CTV advertising rewards intentional spending over volume.

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

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

5. Monitor and Optimize Your Campaign

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

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

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

FAQs

What is connected TV (CTV)?

Connected TV (CTV) refers to any device that connects a TV screen to the internet to stream video content, including smart TVs, streaming sticks, and game consoles.

How does connected TV (CTV) advertising work?

Connected TV (CTV) advertising works by placing video ads within streaming content on connected TV devices, either through direct publisher deals or programmatic buying. Advertisers can then target, measure, and optimize campaigns using platform and publisher data.

What is the difference between CTV and OTT?

Connected TV (CTV) refers to devices that connect a TV screen to the internet, such as smart TVs, streaming sticks, and game consoles. Over-the-top (OTT) is the broader method of delivering video over the internet and can include phones, tablets, and desktops. A CTV buy targets that living room device specifically, while a broader OTT buy reaches audiences across all screens.

How much does CTV advertising cost?

Most connected TV (CTV) inventory is priced on a cost per mille (CPM) basis, with rates for most U.S. campaigns ranging from $20 to $40 per thousand impressions and many settling around $25 CPM, depending on targeting depth and inventory quality. Self-serve platforms have made it possible to test CTV without a traditional TV budget, though you still need enough spend to generate data worth acting on.

Conclusion

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

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

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Google adds AI-qualified call leads to improve measurement

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Google Ads

Google is upgrading Google Ads call campaign measurement with a new AI-qualified call leads feature, designed to optimize for lead quality — not just call length.

What’s new. AI-qualified call leads use machine learning to analyze calls and determine whether they represent meaningful business opportunities. The system then feeds that higher-quality data into bidding and reporting.

Zoom in. Advertisers will get AI-generated call summaries and tags, giving more transparency into what happened during each interaction. At the same time, smart bidding can prioritize higher-value leads based on these signals rather than simple time thresholds.

Why we care. Call campaigns have long relied on blunt metrics like duration to signal value. This update shifts optimization toward actual lead quality, filtering out low-value interactions like spam or robocalls. This should result in better ROI, less wasted spend, and clearer insight into which calls actually matter.

How it works. Call recording is turned on by default for most advertisers so AI can assess call quality, though industries like healthcare and financial services are excluded. Advertisers can still adjust call length thresholds or disable recording in account settings.

The fine print. The feature is currently limited to calls in the U.S. and Canada.

Bottom line. Google is turning call tracking into call qualification, helping advertisers focus on leads that are more likely to convert.

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The funnel flip: Why AI forces a bottom-up acquisition strategy

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The funnel flip- Why AI forces a bottom-up acquisition strategy

The industry has been building top-down for 30 years. Start with awareness, get in front of as many people as possible, and work them down through the acquisition funnel.

The logic made sense in the broadcast era, and it wasn’t entirely wrong in the search era.

In AI-driven environments, it’s simply wrong.

Search engines, assistive engines, and agents build their ability to recommend your brand from the bottom up. They need to understand who you are before they can evaluate whether you’re credible. They need to evaluate your credibility before they recommend you to anyone.

If you build from the top down, you’re wasting budget on awareness while the engines and agents have no foundation to attach it to.

Agential systems make the stakes absolute. An agent acting on behalf of a user evaluates your brand, your offers, and your credibility, then commits.

If the machine doesn’t understand who you are, what you offer, and whom you serve, the agent can’t act in your favor. If it understands you but doesn’t find you the most credible option, it selects your competitor.

This is the ultimate zero-sum moment in AI: the recommendation you never saw happening, to the prospect you never knew was considering.

The acquisition funnel runs simultaneously in opposite directions

The user experience of the acquisition funnel hasn’t changed. Someone hears about you, considers you, and decides whether to commit. That journey runs wide to narrow, top to bottom: awareness first, evaluation second, and decision at the bottom.

This is the familiar funnel. Elias St. Elmo Lewis formalized it in 1898. Every marketing model since has been built around it, and for 128 years, nothing fundamental has changed. The channels evolved, but the direction was always the same: reach first, relationship second, commitment third. 

In 2002, my friend Philippe Lanceleur described the web perfectly for search: building a website and hoping people find it is like opening a shop in the middle of a field. Nobody passes by accident. You go where your audience hangs out, engage with them, and invite them to cross the field and visit your shop. Awareness was still the prerequisite, and your marketing had no chance of working without it.

The shift to entities changed the prerequisite. When Google introduced the Knowledge Graph in 2012, the machine began forming opinions about brands independently of what users were searching. The machine was drawing its own map and building roads for you. 

Those machine-built roads are built from the shop outwards by the machines, which means brand understanding and reputation, not awareness, become the prerequisite. All my work since 2012 has been focused on brand understanding and reputation for exactly this reason.

AI makes the acquisition funnel flip more powerful still. Assistive engines and agents now actively direct users toward destinations they’ve assessed as credible. Lanceleur’s shop in the field is no longer a handicap if the machines know it’s there and believe it’s the best destination for their users: they provide the roads.

This is the first genuine structural break in how brands must think about marketing since 1898. The display funnel is unchanged: the user still travels from awareness to decision. What makes you a candidate at the top of that funnel in AI engines and agents is built by training the machine to bring users to you.

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How top-down and bottom-up coexist

The big takeaway is that the build funnel runs in the opposite direction. 

  • The machine starts at the bottom. Does it know who you are? 
  • It works up through credibility. Does it trust what you do? 
  • Only then does it reach advocacy. Will it recommend you proactively? 

The moment of commitment by the user stays the same: know-like-trust the brand, but the only way for the user to arrive at that moment in AI assistive engines is that the machine knows, likes, and trusts your brand.

The coexistence of the bi-directional funnel is real. You can build top-down in channels you control: paid media, broadcast, and direct outreach. You can still buy awareness and pull people to decision. In the engines themselves, the user still has the top-down experience. 

The difference is that within the engines for organic, you have to build from the bottom of the funnel (BOFU) up because that’s how the machines build the roads to your brand.

Every algorithm, assistive engine, and agent operates on entity and brand signals, not on how loudly you push. Reach on social media has always been influenced by brand recognition, engagement, and topic, and here too, brand understanding and trust are gaining increasing weight.

With AI, roads to your shop in the field are increasingly machine-built, and machine-built roads are built from brand understanding outwards to awareness.

The original 1898 funnel still describes what users experience. In AI assistive engines and agents, it no longer describes the strategy that gets you in front of them: for that, you need to flip the funnel.

In short, you can’t build your funnel in AI engines and agents top-down in a world where those machines are the mediators between you and your audience. The machine won’t recommend brands it doesn’t understand, and it will only advocate for brands it trusts. This is a mechanical fact.

AI infrastructure works like this, so you also must. 

  • Understandability creates the entity node.
  • Credibility gives it preferential consideration.
  • Deliverability gives it visibility.

Foundation. Proof. Reach. Put like that, it really does seem obvious, unavoidable, and comfortable.

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How the funnel becomes a guided sequence in AI

The user journey on Google used to be a series of single-composed SERPs that users navigated themselves. Search engines composed those pages cleverly (Google and Bing have run a whole page algorithm since universal search launched in 2007, Darwinistically pulling elements from across verticals and scoring the composition as the “product”), but the navigation across the funnel was the user’s job.

As an SEO, you optimized for a position in the composition, and the user carried themselves from awareness to consideration to decision by browsing, comparing, and choosing.

Over the last few years, the algorithmic trinity has fundamentally changed that dynamic. The LLM reasons about what the user is asking, decides whether to answer directly, ground, search, or fact-check via the knowledge graph, and runs fan-out queries to retrieve across multiple angles of the question.

Those fan-out queries (which I’ve also called cascading queries) help the assistive engine answer the question more completely and more accurately than a single query would. But the breadth of what it gathers also lets it do one more thing — and this is the mechanic that actually matters in the funnel that leads to the perfect click: it can anticipate what the user is likely to do next, and set the current answer up to flow toward it.

The explicit representation of the LLM’s prediction of “next step” is the follow-up questions you see in the results. But there’s an additional implicit side to this architecture you might have missed: the way it composes the current answer shapes what the user is likely to do next. The AI is, to a very large extent, defining the acquisition journey. It seems to me the user is less in control than they feel.

That means your job appears to be to fight for a slot in a sequence the machine has already built.

That’s fair. But I’d argue that the brand’s job is also to train the machine’s expectations about what a logical next step looks like, so that when the LLM composes, your content is the natural thing it reaches for. 

You supply the ideas, you structure the follow-ups, you publish the logical bridges (“if you’re thinking about X, the next thing to consider is Y, and here’s the evidence”) in enough places, and with enough corroboration, that the machine treats those bridges as settled, not speculative. The machine then guides users toward you because your content is what its prediction landed on, because your framing is what made that prediction logical in the first place.

Now, is the AI thinking one step ahead? Or playing chess and planning several moves in advance? It depends. How far ahead the machine can usefully look depends on the territory. 

On well-traveled ground, the paths are well-worn, and the branches are narrow, so the LLM can stage two, three, or more moves ahead. Think of this as established neurological synapses: your influence on the paths is limited here. 

In unusual territory, the branches collapse the prediction horizon back to one, perhaps two steps. That’s an opportunity for a brand to create the synapses with your brand firmly anchored. Here’s yet another good reason to niche down, solve very specific problems, and have a very clear funnel pathway.

When defining the content I work on and terms I track, I use the concept of funnel pathway for exactly that reason — a top-of-funnel (TOFU) query that naturally leads to my brand at BOFU with a series of steps that are logical and relatively predictable.

So, track a set of terms that have a natural pathway to your brand at the zero-sum moment at the bottom of the funnel. Some start at TOFU and move through MOFU to BOFU. Others begin at MOFU with a clear path to BOFU, and some start (and end) at BOFU.

I’ll probably get pushback here. The number of possible paths is effectively infinite because conversations with AI can go anywhere. True. But this is a better system than chasing search volume or tracking the terms the boss likes: it forces you to think, focus, and prioritize — and it works.

Get your foot in the door, and keep it there

Strategically, you have to get a foot in the door as early as possible in the conversation, and ensure that you keep your foot there as the conversation evolves and the AI guides the user down the funnel.

The stronger your foot in the door, the more you shape the conversation the machine builds, the more that conversation thins the field of competitors the machine considers for the next step, and, by virtue of elimination, the more likely you are to get the perfect click at the zero-sum moment at the bottom of the funnel.

I’m advocating for educating the algorithms (remember, Google is a child?). The better you guide, the more the machine’s best-brand prediction converges on you step after step, because the path it’s following is the path you built into its brain. 

Get in high, and the compounding works in your favor. Get in late, and your competitors’ bridges become the machine’s bridges, and every subsequent step is a fight to re-enter a sequence where your competitor is Top of Algorithmic Mind.

Display is where your acquisition funnel lives in the AI engine pipeline

The AI engine pipeline runs 10 gates from discovered to won. 

  • Everything up to annotation (Gate 5) is infrastructure: can the machine access, store, and classify your content? 
  • From recruitment (Gate 6) onward, the engine compares you to every alternative. 
  • The understandability, credibility, and deliverability (UCD) layer is where the user sees the machine evaluation at display (Gate 8). Understandability is the key to won (Gate 9).

The three dimensions of brand visibility at display

Display is the moment when the machine can make or break your brand by being the most visible in the market at every touchpoint when your ideal customer profile (ICP) is having a conversation with the engine or agent. 

It’s obvious that this is the key moment when you need the engine or agent to be absolutely convinced that you’re the best solution to the specific user’s problem at the exact moment they convert (see the 95/5 rule here).

Understandability (U) is the trusted partner/decision layer, without which nothing else will work long term. Does the machine know who you are, what you do, and who you do it for? 

U is BOFU, which is both the moment of decision and (logically) the deepest trust layer for both the AI user and the human user. When someone searches your brand name or asks an AI assistant directly about you, the machine draws on its understanding of your entity. 

If that understanding is weak, contradictory, or absent, the machine either hedges or stays silent. Typical failure modes show up in AI responses as “claims to be,” “appears to offer,” or “no idea who you are talking about.” The doubt tax — where prospects ready to buy get a hedge instead of a confirmation — is a U failure.

Credibility (C) is the recommender/consideration layer. Does the AI believe you’re genuinely better than your competitors at what you do? 

C is MOFU, the comparison and evaluation layer. When someone asks an AI who is the best in market, the machine draws on its confidence in your N-E-E-A-T-T credibility and will exclude you if you haven’t built a rock-solid argument to be cited. 

If AI confidence in you is weaker than its confidence in the credibility of your competitor, you lose the comparison. The ghost tax – absent from competitive evaluation and ignored in shortlists — is a C failure.

Deliverability (D) is the advocate/awareness layer. Does the AI surface your brand to people who aren’t searching for you, recommend you unprompted when they research the market, and treat you as the reference option in your category? 

D is TOFU, the reach layer. When someone asks an AI about a problem, you solve without knowing your brand exists, the machine draws on its confidence that you are the right answer to put in front of them. 

Advocacy only happens when the machine has first understood who you are (U), and judged you better than the alternatives (C). The invisibility tax — never mentioned to prospects researching the market — is a D failure.

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The business case for UCD: The three taxes

My untrained salesforce framing is super clear for a non-technical audience. Google, ChatGPT, Perplexity, Claude, Copilot, Siri, and Alexa are seven employees working 24/7, and they’re either selling for your brand or for your competitors. AAO can be defined as training AI assistive engines and agents to sell for you at the top, middle, and bottom of the funnel.

Here’s the part most of the industry still hasn’t internalized: machines aren’t an alternative audience. They’re a mirror of how people process information, with the noise filtered out. 

Optimizing for machines is optimizing for humans with less guesswork. A brand SERP is Google’s opinion of the world’s opinion of you, and Google’s opinion is built from the same signals that form human opinion, only weighted more consistently, and corroborated across millions of data points. 

When you optimize to improve what Google believes about your brand, you’re not gaming an algorithm. You’re correcting and reinforcing what the world already believes about you, expressed with the precision humans rarely articulate. The algorithm is the clearest feedback loop marketing has ever had. 

Each tax is a specific failure mode of that untrained salesforce. 

  • The doubt tax is what you pay when they can’t confirm who you are to a prospect ready to buy. 
  • The ghost tax is what you pay when they can’t argue your case against competitors in a shortlist. 
  • The invisibility tax is what you pay when they don’t mention you at all to the prospect researching the market. 

The fixes run in one order: U before C, C before D, because the taxes are mechanically ordered, and the remediation has to match.

Content was king in the keyword era, context took the throne around 2016, and confidence is king now. The AI engines don’t just store and retrieve. They stake their own credibility on the brands they recommend, and that staking runs on accumulated confidence at every layer. 

Build U to retire the doubt tax. Build C to retire the ghost tax. Build D to retire the invisibility tax. Every tax retired is a recommendation earned, and every recommendation earned is revenue the machine now generates on your behalf instead of your competitor’s. 

Strategy: Your brand SERP and AI résumé tell you where to begin

Brand SERP is what Google shows when someone searches your brand name. The AI résumé is the same object in conversational format. The agent dossier is the machine’s silent judgment during evaluation before any recommendation reaches a person. 

All three are dual-function objects. They’re the machine’s output to every audience that asks about you, and your diagnostic instrument for reading the machine’s current confidence. That dual function is why they’re both the product and the audit.

Read all three as the machine’s understanding of you, its assessment of your credibility, and its confidence in you as a solution provider. The diagnostic triage is short.

If the machine gets things wrong, hedges facts, or the results don’t reflect your brand narrative, that’s an understandability problem. The entity record is inconsistent, weak, or contradictory, and the work is on your entity home: clean structured data, consistent descriptions, clear schema, and entity resolution that points to a single authoritative source.

If the results are unconvincing, unflattering, or don’t do you full justice, that’s a credibility problem. Your N-E-E-A-T-T is weak, and the work is offsite: third-party mentions, review platforms, earned media, and co-citations from sources the machine trusts.

If the results don’t reflect your digital marketing strategy, that’s a deliverability issue. The work is in content, both on your channels and on third-party properties, the type of material the machine treats as proof rather than a claim.

In every case, the diagnosis comes before the tactics. U before C, C before D, and the sequence isn’t optional.

Acquisition is one act in a 15-stage play

The acquisition funnel feels dominant because it’s where conversion happens. The funnel sits on the display gate, where UCD determines whether the machine recommends you. 

Everything else, the work that lets display happen at all and the work that compounds afterward, runs across the nine gates before it and the five gates after it.

Those five gates after Won are where most of the money is made and most of the confidence is generated. Onboarded, performed, integrated, devoted, and codified — every client outcome feeds signals back into gate zero for the next prospect who has never heard of you. 

The flywheel is the mechanism. Get it right, and every satisfied client strengthens the machine’s confidence in your brand for the next one. Get it wrong, and every neutral outcome decays it.

That’s more than just an acquisition strategy; it’s a business strategy, with the machine as a constant participant at every stage.

The final articles in this series will show you what happens after won: how every satisfied client either trains the machine to recommend you more confidently next time, or quietly erodes the confidence you’ve already built. 

The funnel isn’t where the money is made, but it is the critical moment the flywheel feeds where the path to money is.

This is the 10th piece in my AI authority series. 

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Google rolls out new AI safety features in Ads Advisor

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What 23 tests reveal about AI Max performance in Google Ads

Google is adding three new “agentic” safety features to Ads Advisor, its AI assistant inside Google Ads, aimed at reducing manual work while tightening security and compliance.

As campaigns grow more complex, advertisers are spending more time fixing policy issues, managing access, and handling certifications. Google’s pitch: let AI handle the heavy lifting so marketers can focus on performance.

What’s new. The update introduces proactive troubleshooting, always-on security monitoring, and instant certifications — all powered by AI and Gemini capabilities.

Zoom in:

  • Ads Advisor can now flag and help resolve policy violations automatically, even before advertisers notice them.
  • It monitors accounts 24/7, surfacing risks like suspicious domains or inactive users through a new security dashboard.
  • Certifications that once took weeks can now be granted instantly or submitted with a single click.

How it works. Instead of waiting for user prompts, Ads Advisor scans accounts and websites proactively, suggests fixes, and confirms resolution before appeals are submitted. On the security side, it continuously evaluates account health and recommends improvements, while new passkey support reduces reliance on passwords.

Why we care. Tasks that used to take hours — fixing policy issues, monitoring account security, and handling certifications — can now be done proactively by Ads Advisor, reducing delays and aims to reduce risks. The result is faster campaign execution, fewer disruptions, and less manual overhead.

What to watch. These features are rolling out in the coming months to English-language accounts, with more languages expected later.

Bottom line. Google is turning Ads Advisor into a hands-on operator, not just a helper — aiming to make ad accounts safer, faster, and far less manual to manage.

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