How AI Powered Search Is Changing Marketing, and What You Can Do About It.

Imagine you need a new washer/dryer. In the past you’d read through several review sites, but now an AI-powered search gives you a single, convenient answer in seconds. AI-powered search is fundamentally altering how customers find information, and this shift is already impacting marketing efforts.

The era of competing for page-one rankings and organic clicks is giving way to something more complex. Discovery is shifting from static search results with 10 blue links to dynamic, ongoing conversations with Large Language Models (LLMs) like ChatGPT & Gemini. In fact, 80% of U.S. consumers already use AI-generated content as part of their search process.

What makes this new path to discovery so powerful is that these LLMs retain memory of prior interactions and use that history to refine how they respond. They already know more about users than anything Google or Facebook could infer from browsing habits.

This shift introduces hyperpersonalization at a level previously unseen. For businesses of all sizes, this presents both a marketing challenge and an opportunity.
Visibility through traditional SEO methods is decreasing. Clear, meaningful communication to ideal customer profiles and related audiences will help organizations be better positioned for success in this new world.

Hyper-personalization introduces the potential for deeper relevance and stronger engagement with customers. Let’s break down what’s changing, and more importantly, what marketers can do to stay ahead.

The Shrinking SERP – From 10 Blue Links to AI Overviews

Historically, Google’s search engine results page (SERP) displayed a straightforward list of ten blue links, offering clear visibility for businesses that ranked organically. Recently, Google has significantly reduced this visibility, sometimes showing as few as five organic results.

Additionally, the introduction of Google’s AI Overviews and AI mode places summarized answers at the top, significantly reducing user clicks to traditional websites.

This shift challenges businesses to remain visible even without the traditional click-through metrics and traffic levels we use to measure results against. The result:

• Fewer organic listings on page 1.
• AI overviews consume the premium screen space above the fold.
• Click through rate are declining, even with strong organic rankings.

In fact, research shows that AI Overviews can reduce the click-through rate of the top organic result by as much as 34.5%.

How to Use SEO to Show Up in ChatGPT and AI Overviews

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AI Overviews Will Soon Impact Ad Performance in SERPs

This reduction in visibility affects paid advertising as well. Google currently tends to show AI Overview summaries in search categories with lower ad density. In fact, Ahrefs reported seeing AI overviews for SERPs with no ads 71.67% of the time.

However, we expect this result of not including AI overviews for queries that have ads to change. As user behavior shifts and competition from platforms like ChatGPT increases, Google will likely face pressure to prioritize long-term user retention over short-term ad revenue.

This creates a classic innovator’s dilemma for Google. On one hand, continuing to suppress AI Overviews on high-value queries protects short-term ad revenue. On the other hand, users are increasingly drawn to AI-first platforms like ChatGPT that deliver faster, more contextual answers.

If Google resists this shift, it risks losing users to competitors who better meet their evolving expectations.

For example, a user searching “best CRM for startups” today may see multiple ads and no AI Overview. But in a future where that user prefers summarized, AI-curated results, Google will be forced to include an AI Overviews response, potentially displacing ads or reducing their effectiveness. If it delays too long, it may lose the user entirely to other platforms like ChatGPT.

AI Answers Are at the Top of the Marketing Funnel

ChatGPT and Google’s AI Overviews increasingly address informational and top-of-funnel queries directly. Users no longer need to visit individual websites to gain basic knowledge about a product or service they’re researching.

As a result, businesses are experiencing reduced organic traffic for educational and glossary-style content. This reduction diminishes opportunities for nurturing leads and guiding visitors deeper into the sales funnel.

Less traffic to content that once fueled top-of-funnel awareness. Fewer opportunities to educate or differentiate early in the buyer journey.

In fact, the businesses currently hurting the most from this adjustment were those that were successfully engaging with customers and building brand relevance at the top of the funnel. They’re seeing the impact at the bottom of the funnel as well, less revenue

Clicks Are Dropping, Impressions Are Not

Marketers are noticing a concerning pattern: search impressions remain high, meaning your content is still being shown, but fewer users are clicking through to the website.

Data from Google Search Console demonstrates a clear divergence: businesses see higher impressions from more sites being included in AI overviews as source, but fewer clicks are driving users to third party websites. This divergence means marketers must recalibrate how they interpret these metrics.

According to recent studies, nearly 60% of searches now end in zero clicks, as AI-generated answers satisfy user intent directly on the results page.

An increase in impressions indicates broader brand visibility, though direct engagement via clicks decreases. Businesses can capitalize on this heightened brand awareness to create lasting impressions and recall value.

While conversions are still the ultimate marketing metric, tracking impressions across these AI systems helps validate whether your brand is still actively participating in the buyer’s journey. Impression tracking helps verify if you’re part of the conversions LLMs are having with potential customers.

Measure the Right Metrics in the Age of AI

But, tracking impressions is only the beginning. Inclusion in AI Overviews and large language model platforms like ChatGPT should now be considered a core marketing KPI. These appearances often serve as the new top-of-funnel entry point, similar to how clicks initiated the customer journey in the past.

Today, user-facing AI responses and LLM-generated summaries are shaping decisions long before a user reaches your website. Being present in those outputs is essential for brand visibility and long-term conversion potential.

Here’s how marketers can begin aligning strategies and measurement with this new landscape

Track AI Overview Visibility with Ahrefs

Ahrefs has introduced features that help marketers determine whether their URLs are appearing in Google’s AI Overviews. By mapping your existing keyword rankings to AI-generated results, you can start to gauge your domain’s inclusion rate. Focus especially on queries that drive awareness-stage interest, and identify whether your competitors are appearing more often in these summaries.

Monitor Inclusion in ChatGPT and Other LLMs

Profound tracks brand mentions and source citations across ChatGPT, Gemini, and other popular LLMs. It provides insight into where your company is mentioned, how frequently, and in what context. These signals can help you understand if your content is contributing to top-of-funnel conversations happening entirely within AI environments.

Use Google Search Console to Track Brand Impressions

While GSC won’t explicitly tell you if you’re part of an AI Overview, impression data is still a valuable directional signal. If impressions are rising while clicks are falling, it could mean your site is being surfaced in AI Overviews or cited without direct visitation. Pair this data with observations from Ahrefs to build a clearer picture of where you’re showing up.

The Great Equalizer: Hyper Personalization

AI prioritizes user intent and context that’s perfect for the user they’re assisting. As top-of-funnel research and conversations shift to platforms like ChatGPT, AI Overviews, and Gemini, new opportunities emerge for businesses of all sizes.

Personalization enables businesses to deliver precisely tailored experiences, matching content directly to individual users’ specific contexts and needs. Businesses that provide highly relevant, targeted content to their ideal customers can now compete more effectively than ever before, regardless of size or historical authority.

Examples of Hyper personalization & Marketing

Let’s review an example of a complex purchase decision made simple by AI-curated answers. Consider someone searching for a washer and dryer set. In the past, they would scroll through a wide range of options, manually comparing specs and pricing. With AI, that process is changing. If the system knows the user is a couple living in an apartment, it can suggest an all-in-one washer/dryer combo that saves space and fits their lifestyle.

If the user is part of a large family of six, AI understands that an all-in-one model would likely be insufficient, and instead recommends a high-capacity, durable solution designed for frequent loads. This new AI powered discovery reduces the time a user needs to find what’s best for them and points them directly to what meets their preferences.

Another example is one for local restaurants and how AI handles local queries with multiple requirements. Local restaurants once had to compete against the marketing budgets of large national chains to attract customers. Today, that dynamic is shifting. LLMs can now:

• Identify if a user prefers small, locally owned restaurants over big brands.
• Suggest whether a restaurant is kid-friendly, without the user needing to ask directly.
• Find places that have the type of deserts the user loves.

These capabilities stem from the LLM’s ability to learn from user interactions and apply that context to future searches. OpenAI has publicly stated that its models will use memory to personalize and adapt searches on a user’s behalf.

In this example, the AI search can bypass the usual list of links, meaning a restaurant’s ability to be recommended now depends on being featured in that AI-driven answer, which is generated by the detailed content present on a restaurants website, not just traditional SEO tactics to appear at the top of results.

Including this level of details and information on web pages and marketing material can help LLMs quickly identify which products are perfect for the user they’re assisting.

Create ICP-Centric Content That Actually Helps

Effective content creation revolves around your Ideal Customer Profile (ICP). Businesses must:

• Understand and target specific audience segments (region, industry, demographics).
• Explicitly state why their product or service fits that group.
• Provide relatable examples and differentiators that speak directly to ICP needs.

Content should do more than inform, it should signal alignment. Use specific, real-world scenarios that make your value proposition unmistakable to the exact people you’re trying to reach.

Prepare for LLM-Powered Personalization

Since LLMs reshape user queries based on personalization, intent, and historical context. Clearly structured content on your website allows LLMs to effectively interpret and represent your business’s value proposition.

Implementing structured data, clear markup, and concise messaging ensures that AI can accurately understand and summarize your content. These efforts and ensuring that your content semantically aligns with what’s being generated by LLMs can increase how often your brand is included as part of the new top of funnel user conversations.

Making this effort will reward you at the bottom of the funnel, potentially even increasing conversions and revenue as more customers that are perfect for what you offer find you, when before they may have gotten lost in 10 blue links.

How Go Fish Digital is helping our customers navigate this change.

At Go Fish Digital, we’re spending significant time and resources to help understand these new models, how users interact with them, and how they’re impacting businesses.
Some of the efforts include:

• Studying and researching the patents that OpenAI and Google are being awarded to understand how their select which sites and brands to include in their generated responses.
• Building new tools that help us see and score content semantically the same way LLMs do.
• Testing and data gathering to identify what we can influence and how long it takes with LLMs like ChatGPT and AI Overviews.
• Monitoring all aspects of this new user journey to identify where our clients’ sites may be creating friction during the buying process.
• Leverage internal SEO & GEO tools built upon Google’s own large language model technology to measure and analyze semantic clarity.
• Building scalable strategies to provide more contextual detail about who the ideal ICP is for each of your products & services.

These efforts & proprietary tools allow us to verify whether value propositions are discoverable and clearly presented. Large businesses can gain some of the top of funnel exposure they’ve lost. Small and medium businesses can benefit by increasing discovery of their unique offering to their customers.

All businesses can grow and thrive in this new marketing environment through SEO and Generative Engine Optimization services. We’d love to help, get in touch with our team today!

About Dan Hinckley

Dan specializes in innovative digital marketing solutions, brand strategy, and technical web development and support. He works in step with clients to manage SEO, ORM, Conversion Rate Optimization, and website design and development projects, from start to finish. He is Google Analytics Certified and leads the Google AdWords programs. Dan began his career in brand strategy management before transitioning into IT consulting for the US Government. These experiences uniquely position him to develop comprehensive strategies for SEO that span across branding and IT domains. Nearly twenty years of SEO experience have made Dan a seasoned industry veteran in tune with the latest capabilities. As a consultant, his clients have included GEICO, AAG, NY Times, Business Insider, Marriott, US Department of Defense, Airbnb, US State Department, George Mason University, and Penn State University among others.