Measuring success in search has never been more complicated — or more exciting. With answer engines, your content can shape what people see and trust, even if they never click through to your site. That’s both the challenge and the opportunity of Answer Engine Optimization (AEO). Traditional ROI models tied to rankings and traffic don’t fully capture this new reality. Instead, marketers need fresh ways to track visibility, authority, and influence inside AI-driven results.
To get there, it starts with understanding how ROI itself must be redefined in the context of AEO.
Defining ROI in Answer Engine Optimization (AEO)
For years, ROI in SEO was fairly straightforward: measure rankings, estimate traffic from click-through rates, apply your site’s conversion rate, and connect it to revenue. If your brand ranked at the top of Google, you could confidently model its financial impact.
With Answer Engine Optimization (AEO), the equation is more complex. AI-driven search engines like Perplexity, Bing Copilot, and Google’s AI Overviews no longer rely on the traditional “ten blue links.” Instead, they deliver direct answers synthesized from multiple sources. Sometimes your content earns a clickable citation; other times, it powers the answer without generating a visit at all.
This shift makes ROI in AEO fundamentally different:
- Visibility without traffic
In SEO, value was tied to clicks. In AEO, success may come from being named as a source, even if the user never leaves the engine. That exposure still influences brand perception and purchase decisions.
- Dual-layer value
ROI comes from two distinct but connected outcomes:
- Direct impact — measurable traffic and conversions from answer engines that link back to your content (e.g., Perplexity, Bing).
- Indirect impact — brand lift and authority from citations where no click occurs (including Google’s AI Overviews summaries).
- Authority redefined
In traditional SEO, backlinks and keyword relevance signalled authority. In AEO, structured data, factual clarity, and trustworthiness determine whether an engine will surface and cite your content.
Put simply, measuring ROI in AEO isn’t just about traffic anymore. It’s about how often your brand shows up in answers, whether people remember it later, and how much trust those appearances create.
The chart below highlights this transition. Historically, the #1 organic result alone captured nearly 40% of all clicks, making top rankings the cornerstone of ROI modelling. By contrast, in 2025, the entire organic channel accounts for only about 40% of clicks across all searches, while zero-click searches surged to nearly 60%. This shift underscores how much the search experience has changed: clicks are scarcer, and ROI must now include the visibility and authority earned inside AI-driven answers, not just traffic from rankings.
As the data in our chart shows, organic clicks are no longer a reliable proxy for success. If nearly 60% of searches in 2025 end without a click, and the remaining organic traffic is spread thinner than ever, then the question becomes: how do we measure the value of simply being cited? This is where ROI in AEO gets tricky.
Challenges in Tracking ROI from AEO Campaigns
Measuring ROI in Answer Engine Optimization sounds simple in theory — track mentions, clicks, and conversions — but in practice, it’s far more complicated. Unlike traditional SEO, where ranking and traffic data were relatively transparent, AEO lives in a murkier ecosystem where visibility and influence often go unmeasured.
1. Lack of Referral Visibility
Most answer engines don’t consistently pass referral data. Google’s AI Overviews may cite a page without driving a single trackable click. Platforms like ChatGPT often don’t provide links at all, meaning your content can power an answer without ever appearing in analytics. Even when links are present, UTMs are rarely preserved, leaving marketers unable to attribute visits back to AEO exposure.
2. Multi-Touch Attribution Gaps
AEO often influences users at the top of the funnel. Someone might see your brand cited in Perplexity or Bing Copilot, then later return via a direct search or branded query. In Google Analytics 4 (GA4) — Google’s current analytics platform — that visit typically shows up as “direct traffic,” severing the connection between the initial AI exposure and the eventual conversion. Traditional attribution models struggle to recognize these upstream AEO touchpoints.
3. Fragmented Data Sources
There’s no single dashboard for AEO. Marketers are forced to piece together:
- GA4 for assisted conversions.
- Ahrefs or SEMrush for branded search growth and unlinked mentions.
- Custom scrapers or APIs for citation monitoring in Perplexity, Bing, or AI Overviews.
This patchwork makes it difficult to form a holistic ROI model, especially when data from one tool contradicts another.
4. Evolving Benchmarks
In SEO, CTR studies provided dependable expectations for each position on the SERP. In AEO, there are no industry-standard benchmarks for citation frequency, visibility share, or brand recall. While SEMrush and Ahrefs have begun to experiment with AI visibility tracking, the metrics are still new, inconsistent across platforms, and not yet widely adopted. Until benchmarks mature, ROI calculations in AEO remain partly experimental.
In other words, while AEO visibility is real, the yardsticks we use to measure it are still emerging. That’s why ROI in this field often feels more like a hypothesis than a hard number.
Traffic sources tracked in Ahrefs for one of our projects, showing the share driven by AI.
Tools and Methods to Measure AEO ROI
The good news is that measurement isn’t impossible — it just requires stitching together multiple data sources. Some tools provide early signals of visibility in AI Overviews and answer engines, while others help translate that visibility into brand lift or conversion value. Together, they form the beginnings of a workable AEO ROI framework.
Free Tools for Initial Tracking
- Google Search Console (GSC): While GSC doesn’t yet report AI Overview impressions separately, it remains essential for spotting trends in branded searches and tracking SERP features that overlap with AEO.
- Google Analytics 4 (GA4): Can help capture assisted conversions, revealing when ‘direct’ traffic is actually influenced by earlier AEO exposure, as well as which AI assistant contributes the most traffic.
- Bing Webmaster Tools: With Bing Copilot citations on the rise, its search data provides additional signals of answer engine visibility.
Paid Tools Filling the Gap
- SEMrush: Has introduced AI Overview tracking in its Organic Research and Sensor reports, helping marketers monitor which queries trigger AI answers and whether their domain is cited.
- Ahrefs Brand Radar: Tracks AI citations, brand mentions, and “AI Share of Voice,” giving a first glimpse into how often your site powers generative answers.
- Similarweb & SparkToro: Provide macro-level visibility on the rise of zero-click searches and declining clickshare.
Emerging Solutions & Approaches
- Custom Scrapers: Some teams are experimenting with APIs or crawlers that detect brand citations in Perplexity and ChatGPT.
- Brand Lift Surveys: Asking audiences directly about brand recall after AI exposure offers a qualitative measure of ROI.
- Equivalent Ad Value Modelling: Translating AI citations into an estimated CPC-based media value (e.g., if your page appears in 1,000 AI answers, what would those impressions cost in paid ads?).
Combining Data for ROI Modelling
A practical AEO ROI model requires blending these streams:
- Direct Conversions: Captured in GA4 when answer engines drive clicks.
- Value of AI Citations: Quantified through SEMrush/Ahrefs visibility data and benchmark CPCs.
- Brand Lift: Measured through branded query growth, recall surveys, or rising direct traffic.
Practical ROI Measurement in AEO
To determine ROI, it is necessary to set up monitoring of how incoming traffic is distributed across different AI assistants, as well as the share of AI search compared to all traffic on your site. In addition to configuring traffic channel tracking and understanding the percentage of AI traffic, it is important to set up Google Tag Manager and event tracking to identify where leads originate.
For instance, in SaaS, there is often no direct communication to confirm whether a lead came from advertising, SEO, or AI — which makes accurate tracking essential. In B2B, by contrast, there may be more opportunities for direct communication that helps clarify the channel.
At LenGreo, we approach this holistically. AI SEO is not charged separately but included as part of our SEO package. We measure what percentage of leads and customers come from AI SEO and AI engines, follow their conversions, and then, by connecting this to total revenue, calculate the ROI for AEO.
Key Metrics That Actually Matter in AEO ROI
With so many moving parts in answer engine optimization, it’s easy to get lost in the data. The truth is, most traditional SEO metrics don’t tell the full story anymore. Rankings, impressions, and CTR still have value, but they don’t capture the visibility and influence that happen inside AI Overviews or answer engines. Instead, measuring ROI in AEO comes down to a handful of core metrics that reflect both direct and indirect value.
1. AI Citations
How often your brand is named in an AI-generated answer. This is the closest equivalent to “ranking” in the AEO era — if you’re cited, you’re visible. Tools like SEMrush and Ahrefs are already rolling out features to track citation frequency across AI Overviews, Bing Copilot, and Perplexity.
2. AI Share of Voice (Visibility Share)
The percentage of AI answers in your category that reference your brand vs. competitors. Much like the share of voice in paid search, this gives a sense of your relative visibility in generative results. Even without clicks, a high share signals authority and influence.
3. Branded Search Growth
One of the clearest downstream signals of AEO success. When users consistently see your brand in AI answers, they’re more likely to search for it later. Tracking branded keyword growth in Google Search Console, SEMrush, or Ahrefs can reveal whether AEO exposure is driving recall.
4. Assisted Conversions
Not all conversions will trace directly back to a click from an AI answer. Many happen later, after a direct visit or branded search. By monitoring assisted conversions in GA4, you can capture the hidden value of AEO exposure that nudges prospects further down the funnel.
5. Equivalent Ad Value
The most effective way to translate AEO visibility into dollar terms for stakeholders. If a citation in an AI Overview earns exposure equivalent to 1,000 impressions, and the average CPC in your category is $6, that visibility represents roughly $6,000 in media value — even if no clicks occurred.
Conclusion: Redefining ROI for the AEO Era
ROI in answer engine optimization isn’t measured the same way as SEO. Rankings and clicks tell only part of the story — true value also comes from visibility, citations, and the trust that builds when your brand appears in AI-driven answers. The key is to focus on the metrics that capture this broader impact and frame them in a way that stakeholders can understand.
At LenGreo, we help brands move beyond outdated SEO reporting and build AEO strategies that connect visibility to growth. By combining technical tracking with a focus on business outcomes, we make ROI in the age of answer engines both measurable and meaningful.
