Move over, Google; large language models (LLMs) are taking over the search landscape, synthesizing vast amounts of data to generate direct, conversational answers. For marketers, this means the goal is no longer to solely rank highly on a results page, but to be a trusted source that an LLM will draw from.
However, if you think you have to rehaul your entire SEO strategy to get here, you don’t. SEO shouldn’t be treated as a completely different entity than answer engine optimization (AEO). Instead, look at SEO as the foundation for a strong AEO strategy.
What’s Changing in SEO Measurement?
AI has altered how people consume information, challenging marketers to redefine “success.” The traditional SEO playbook, once centered on keyword rankings and organic clicks, is being rewritten. Unless marketers understand and stay on top of these shifts, they’ll be left behind, missing opportunities for organic growth.
Understanding Generative AI Search
The overarching goal of search is to provide users with the most relevant information. However, AI is changing how that information is delivered, producing two new concepts that redefine success for SEO: zero-click search and Position Zero.
Unlike traditional search, which presents a list of “blue links” for the user to pore through and even decide on one to click on, generative AI search (such as AI Overviews or LLMs like ChatGPT) synthesizes information to provide a direct answer. This capability creates the zero-click search phenomenon, where a user’s query is satisfied directly on the results page without them ever needing to visit your website.
At the same time, this new model elevates the importance of Position Zero. Historically, Position Zero was the coveted “featured snippet” that appeared at the top of the search results, above the first organic link. Now, AI Overviews dominate the top of the SERP. This means your content’s success is no longer defined by simply ranking #1 on Google, but rather by its ability to be selected as a source for these answers.
Because of this, the primary goal of SEO is shifting from “rankability” to “retrievability,” which is how easily your content can be identified, understood, and used as a source by AI. This change requires a new approach to content and optimization to ensure your site can still capture visibility and traffic in an era of direct, synthesized answers.
The Erosion of Traditional Metrics
As search is shifting, some long-standing SEO metrics no longer accurately capture your digital presence.
Organic CTR
The most noticeable impact for many marketers is a decrease in organic click-through rates (CTR). When AI provides direct answers, users have less incentive to click on blue links. For the people who use LLMs to have their questions answered, they don’t see blue links at all.
Even if your content ranks high on the SERP, its visibility might be overshadowed by the AI Overview, leading to fewer visits to your website. Don’t panic, though; this doesn’t necessarily mean your content isn’t valuable. It does, however, mean that the pathway to that value has changed.
Keyword Ranking
Aiming to achieve the #1 keyword ranking is passé. While a top ranking can still drive organic traffic, the more impactful objective now is to secure inclusion and citation within AI-generated answers. So if your rankings aren’t at the very top of the SERP anymore, try not to worry; this doesn’t necessarily mean you won’t be visible where it’s most valuable.
Traffic Quantity
Now, the focus moves from traffic volume to traffic quality. While organic traffic might decrease due to zero-click searches, the traffic that does reach your site from AI-influenced searches is often highly qualified. These users are typically seeking more information or are further along their decision-making journey, having already received a summary from the AI.
Therefore, a smaller volume of conversion-ready leads is more valuable than a high volume of casual browsers. Instead of losing sleep over visitor counts, marketers need to prioritize conversion metrics and user engagement signals.
SEO Metrics That Still Matter in AI Search (& How To Track Them)
If you’re feeling overwhelmed by the rapid change in search, remember, this opportunity is a call for action, not a reason for despair. The foundational SEO metrics remain, but their application must evolve. To truly measure success, marketers need to start focusing on metrics that reflect their brand’s presence and influence within AI.
Engagement & Conversion Metrics
Since traffic coming from AI search is higher quality, marketers need to start focusing on metrics that measure the value of this high-intent traffic.
Traffic Quality & Conversion Rates
Marketers should remain focused on the number of visitors and what those visitors actually do on the site. Key metrics to track include conversions like sales, sign-ups, and downloads.
User Engagement Signals
Additionally, user engagement signals such as time on page, pages per session, and engaged sessions provide a deeper understanding of how well your content resonates with this valuable audience.
Assisted Conversions
AI often serves as an early touchpoint in the customer journey. For example, a user might see your brand cited in an AI Overview, search for your brand directly later, and then convert.
Tracking assisted conversions in tools like Google Analytics 4 (GA4) allows you to see how your content contributes to a conversion even when it’s not the final step. This metric helps prove the indirect value of your AI visibility, showing that your content is helping to build brand awareness and drive conversions further down the funnel.
On-Site User Journey Analysis
By analyzing user flows and click paths, you can identify which pages are most effective at guiding users toward a conversion as they navigated to your page after they saw your brand in an AI search result. This insight helps you optimize your site’s structure and content to capitalize on the high-quality traffic you receive.
Audience Behavior Metrics
Beyond the typical engagement metrics, look for shifts in audience behavior. Are users arriving from AI searches spending more time on your in-depth guides or product comparison pages? Are they more likely to subscribe to your newsletter? These behavioral patterns can inform your content strategy, helping you create more of the content that resonates most with this audience.
Business Impact Metrics
Ultimately, the goal of any SEO strategy is to drive results, and these metrics directly connect your AI optimization efforts to your bottom line.
Organic Conversions > Indirect ROI From AI Traffic
This is the most direct way to measure success. By tracking the revenue generated from users who arrive at your site via AI search, you can prove the financial value of your optimization efforts.
Keyword Rankings > Share of Voice in AI Results
This metric measures your brand’s presence and authority within AI answers. It tracks how often your brand is cited as a source compared to your competitors. A higher share of voice indicates that your content is more frequently trusted and used by AI, translating to increased brand recognition and authority among users.
High Cost Support > Cost Efficiency & Support Reduction
When your content is highly effective at answering user questions, it can proactively address customer needs before they require human intervention. A well-optimized FAQ page or a comprehensive knowledge base that is easily retrieved by AI can lead to a measurable reduction in support tickets and customer service inquiries, thereby saving your business time and resources.
Visibility Metrics
These metrics focus on how your content is being seen and used by algorithms, moving beyond SERP rankings to gauge your influence within AI.
First Page Rankings > Answer Inclusion & Citation
Answer inclusion tracks how often your content or brand is referenced, linked to, or synthesized into an answer by generative AI. While it may seem that the traditional importance of ranking highly doesn’t matter anymore, it does. A website that ranks highly is a signal of trust and credibility, meaning that it will still have a higher chance of being cited in an AI answer.
Organic Search Volume > Branded Search Volume
While organic search volume is still important as AI is more likely to cite content that ranks, and organic search volume is a direct reflection of that, you may notice an increase in branded search volume as well. When your brand is consistently cited by AI, users are more likely to search for your company directly. A rise in branded search volume is an indicator that AI-driven discovery is boosting brand awareness and recall, even if the initial AI interaction was “zero-click”.
Search Engine Crawlability > AI Crawlability & Indexing
If your content isn’t able to be crawled and indexed by search engine bots, then how would you expect LLM bots to be able to do it either? Crawlability is about ensuring that both search engine and AI bots, like Googlebot and GPTBot respectively, can successfully crawl and index your content without errors. If AI can’t read your content, it can’t use it as a source, regardless of its quality.
Individual Keyword Success > Topical Authority
AI models prioritize sources that demonstrate comprehensive knowledge on a given topic. This is measured by the visibility of your “topic clusters,” or interconnected groups of content that cover all facets of a subject. However, keyword research can be conducted to help you come up with topics that your target audience is actually searching for.
Tools to Measure AI-Era SEO Metrics
To effectively track and analyze the KPIs of AI-era SEO, marketers must leverage existing platforms in new ways, while also integrating emerging AI-specific tools to fill data gaps.
Google Analytics 4 (GA4)
While a familiar tool, GA4 can measure user behavior by tracking assisted conversions and on-site engagement signals like time on page and engaged sessions to understand the value of AI-driven traffic.
Google Search Console (GSC)
GSC remains a foundational tool, helping you monitor AI crawlability and indexing, what queries your site shows up for, and full site and page-specific impression and view counts. It can also identify which of your pages are being featured in rich results that can lead to AI Overview inclusion.
AI-Specific Tools
Platforms like Goodie, Semrush AI Toolkit, or Conductor’s AI features are designed to monitor answer inclusion and citations across various LLMs and AI Overviews. These tools provide a direct view of your brand’s share of voice in the new search landscape.
Custom Dashboards
The most effective approach is to combine data from all these sources into a single dashboard. Using tools like Looker Studio or Power BI, you can correlate your AI citation rates with your website’s traffic quality and conversion metrics. This allows you to create a holistic view of your performance and prove the ROI of your AI-centric SEO strategy.
Conclusion
AI isn’t killing SEO; it’s redefining it, with good SEO being the foundation of any AI search optimization strategy. To achieve growth, marketers have to blend pre-existing and new KPIs to create a new winning formula that targets both traditional and AI search. The winners will be those who embrace a strategy of creating valuable, well-structured content that is built for both humans and machines.
