Beyond ROAS: How to add AI search visibility to paid media reporting (+ examples)

Ah, ROAS. Our beloved return on ad spend data point. 

For years, marketers such as we have clung to this (relatively) clean way to calculate how much sweet, sweet revenue do our ad budgets actually yield. Personally, I love a clean paper trail: a person sees an ad, gets excited and clicks, converts, and there you go! A clear, reportable pathway between ad spend and revenue.

Of course, AI search has somewhat complicated what was once a seemingly easy trail to follow. We can’t have nice things.

For example, a buyer can now experience your brand behind their walled garden AI search experiences, without ever hitting your website. They can gain exposure to your brand, your messaging and positioning, how you stack up against competitors, and so on inside a ChatGPT conversation, a Gemini answer, or a Google AI overview days (or even weeks) before they decide:

“You know what? Maybe I should check out their website.”

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Only then do they show up in some trackable way on your digital doorstep either through direct traffic or a branded search term. 

I literally did this earlier today, as an off-the-clock marketer with a spending problem. Last week, I researched tons of different LEGO sets inside of my ChatGPT window, while binging reruns of The West Wing. But it was only today that I went to the LEGO website directly (with my decision already made!) to buy the Vincent Van Gogh Sunflowers set. (I mean, just look at her! She’s gorgeous.) 

So, LEGO’s analytics platform saw my final visit this morning, which some might argue is the only visit that matters. But it never saw any of the interactions I had with their brand that helped create that moment.

Don’t get me wrong, ROAS is still important. (I literally wrote about ROAS a few weeks ago for a reason.) 

But if you’re overseeing paid campaigns at a high-growth brand, and you continue to only rely on ROAS, without accounting for what AI search is now doing to consumer buying and decision-making behavior, you’ve got a problem. 

Your brand, right now, is already speaking on your behalf in ways you cannot see in this new AI search reality: through citations, summarized sentiments, and more. Your buyers are being influenced in seismic ways before you even have a chance to track a single click. 

So, what does your expanded reporting model need to include now, if ROAS isn’t enough? Can Pixis Visibility help solve for those gaps?

To answer those questions, we need to talk about what’s changed and how these breakdowns are occurring and why. 

Why ROAS alone is no longer enough for paid media

I know there are likely a few of you who may need more clarity around where ROAS now falls short, even if it’s still valuable for telling certain parts of your performance story. 

Here’s where the ROAS breakdown occurs:

• ROAS depends on a measurable connection between ad spend and conversions. Someone clicks an ad, buys the product, and the system records the revenue against the spend.
• AI Overviews interrupt that path by answering more questions directly on the search results page, without requiring any interaction with you. A person may get what they need from the summary without clicking an ad or organic result, even when the answer includes your brand.

Yes, your company still influenced the decision, because AI search can’t return any results about you if you’re not putting yourself online. You just may not see any of it, because a potential customer doesn’t need to leave a search result to get answers to their initial questions.

Go deeper: Is there such a thing as too many keywords with Google Ads? (benchmarks + examples)

Data from Seer Interactive illustrates the shift pretty clearly. In September 2025, paid click-through rates for queries that produced AI Overviews fell from 19.70% to 6.34%, a 68% decline. Organic CTR on informational queries with AI Overviews also fell, from 1.76% to 0.61%.

At the same time:

• 26% of marketing leaders can’t track AI discovery through to conversion.
• 24% say their analytics technology can’t handle AI attribution.
• AI Overviews have driven a 10% or greater increase in usage for the query types they cover.

This sucks, right?

You’re now influencing buyers in ways you can no longer see, track, or report on, which is a dangerous place to be when you’re trying to build strategies that aren’t a crap shoot and showcase the value of the work that you’re doing. 

This is why you’re creating a serious problem when ROAS is treated as the sole judge of campaign performance. Brand and awareness campaigns may look unprofitable because their influence appears later through AI citations, direct traffic, organic branded searches, or another channel that receives the final attribution.

A team looking only at direct conversions may cut the campaigns creating the awareness and authority that eventually cause AI systems to mention the brand.

The answer isn’t to abandon ROAS. It’s to measure the influence ROAS misses.

What AI search visibility and Generative Engine Optimization (GEO) mean

OK, time for a vocabulary lesson, because AI search, GEO, and all of those other terms are thrown around like confetti (and sometimes interchangeably), without much clarity. 

AI search visibility measures whether, where, and how your brand appears inside AI-generated answers.

When someone asks a complex question, an AI search platform may synthesize information from multiple sources and deliver a direct response. Your brand has AI search visibility when it appears in that response, whether the platform links to your website or simply mentions your company.

Generative Engine Optimization, or GEO, is the practice of making your brand and content easier for those systems to find, understand, trust, and cite.

Traditional SEO focuses heavily on helping a page rank within a list of search results. GEO focuses on increasing the likelihood that your information becomes part of the answer itself.

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This means we need to change up how we optimize our content for search. For example, in the pre-AI days, a good meta description shouldn’t give away the whole answer. Yes, it should be clear about the value someone is getting, but the goal is to entice a click. Today, a great meta description should actually include the answer to a question (as much as is realistically possible), rather than being more of a tease.

AI systems need to be able to parse the information, retrieve a specific passage, understand the claim, and find enough supporting evidence to consider it credible.

Important GEO signals include:

• Technical accessibility
• Clear, passage-level answers
• Structured data and schema
• Original research
• Proprietary data
• Authoritative backlinks
• Earned media
• Third-party citations
• Consistent mentions from trusted industry sources

AI models frequently look for patterns of consensus and authority. One optimized article on your website may help, but it carries more weight when respected publishers, reviews, research reports, and other third-party sources support the same claims.

Information gain is one of the strongest opportunities here. Original research and proprietary data give AI systems something they can’t easily find elsewhere, making those assets particularly valuable for GEO.

Key metrics for measuring AI search visibility

So, if ROAS is failing us, and we can see how AI search and GEO have flipped over the table on every status quo we’ve cherished throughout our careers, what are we supposed to do? If clicks and conversions can’t capture the full influence of an AI citation, because it’s happening in ways we can’t track, what are our options?

Don’t worry, there are ways. I didn’t write all of this to simply tell you:

“Suck it up, cupcake, there’s nothing you can do.”

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Imagine a buyer asks an AI platform for a software recommendation, sees your company included in the answer, closes the tab, and visits your site directly three days later. Last-click attribution credits direct traffic. The AI interaction that introduced or validated your brand disappears.

To account for that influence, paid media reporting should add several AI visibility metrics.

Citation frequency

How often does your brand appear in AI-generated answers across the prompts and platforms you’re monitoring?

Citation frequency helps you see whether your presence is increasing, declining, or remaining flat over time.

Share of voice

What percentage of relevant AI citations belong to your brand compared with your competitors?

Share of voice shows whether you’re leading the category conversation or watching other companies occupy more of the answer.

Sentiment analysis

How does the AI system describe your brand?

A mention alone isn’t automatically positive. Sentiment analysis helps you identify whether the platform recommends your company, describes it accurately, presents it as one alternative among many, or associates it with outdated or unfavorable information.

Brand mentions

How often does an AI response discuss your company without linking directly to your site?

These unlinked references still influence buyers, even though they won’t appear as referral traffic.

AI referral sessions

How much website traffic arrives directly from AI platforms?

GA4 dashboards and tracking parameters can identify at least some visits from ChatGPT, Perplexity, Gemini, Copilot, and other platforms. This won’t capture every interaction, but it adds another piece to the reporting picture.

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Pixis Visibility brings these data points together across channels. For Solutions 8, that creates a way to compare AI citations and brand visibility with changes in direct traffic, branded search demand, qualified leads, and other downstream activity.

For example, a top-of-funnel programmatic campaign may be followed by an increase in AI citations and then a rise in qualified branded searches. Traditional reporting may treat those events as unrelated. A broader visibility model helps teams examine the relationship between them before deciding an awareness campaign isn’t working.

Navigating attribution challenges with Pixis Visibility

Now, this is where the Solutions 8 team can help you, thanks to our proprietary solution Pixis Visibility. 

AI answers create an attribution problem because they can influence a buyer without producing a click, cookie, or tracking parameter:

• A person asks a question.
• The platform provides an answer featuring your product.
• The person leaves satisfied and returns later another way.

When finance asks what an awareness campaign produced, the marketing team may struggle to demonstrate its value because the traditional tracking chain broke at the AI interaction.

Cross-channel attribution and influence measurement help reconnect those events.

Pixis Visibility is intended to track the journey from AI mention to branded search, direct traffic, lead, or conversion. It monitors the queries and prompts where a brand appears, then compares those changes with downstream behavior.

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That reporting can help teams examine questions such as:

• Did an increase in AI citations precede an increase in branded search?
• Did stronger visibility around a specific topic coincide with more qualified leads?
• Did a paid awareness campaign increase mentions across AI platforms?
• Did visibility decline after a campaign or content initiative ended?
• Which prompts appear most closely associated with downstream demand?

This won’t turn every buyer journey into a perfectly traceable line, but it will give marketing teams more evidence than last-click attribution can provide on its own.

That evidence can help defend investments in campaigns that influence demand without generating an immediate conversion.

Integrating AI visibility into your paid media strategy

Your only next step here is to rethink your paid media reporting, because if AI visibility is not part of the picture, you’re going to have a big, big problem. 

For example, a direct-response campaign can capture existing intent (currently trackable), but it’s going to have a much harder time creating the wider set of brand signals that AI systems use to determine which companies deserve to appear in an answer.

That broader visibility can come from programmatic awareness campaigns, video, display, audio, earned media, publisher coverage, industry blogs, forums, original research, backlinks, and consistent brand discussion across the web.

Your strategy should connect those efforts.

Here’s how you do it… 

Align paid campaigns with GEO priorities

Use paid media to increase awareness around the topics and product categories where you want your brand to be recognized. Programmatic campaigns can help generate the broader digital footprint associated with brand interest, searches, mentions, links, and citations.

Structure owned content for retrieval

Organize website content so AI systems can extract concrete information. That means using clear schema, direct answers, specific facts, product details, structured FAQs, and passages that can stand on their own when retrieved through a system using Retrieval-Augmented Generation.

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Find the prompts where your brand is missing

Use Pixis Visibility to identify high-intent questions where competitors appear and your brand doesn’t. Those gaps can inform your paid campaigns, content priorities, research, PR outreach, and distribution strategy.

Support the topics you want to own

Paid media can surround important topics and increase exposure to the content, claims, and brand associations you want the market to recognize. The goal isn’t to “force” an AI system to cite you. It’s to create enough relevant, credible, distributed evidence that your brand becomes harder to overlook.

Use a full-funnel campaign model

Transactional targeting still has a job. It shouldn’t be responsible for the entire strategy. A buyer may encounter a video ad, see your research cited in a publication, search the category later, find your brand in an AI answer, and finally convert through a branded search.

The mention feeds the AI system. The AI response informs the buyer. The buyer eventually purchases. That path is longer than the old click-to-conversion model, but it increasingly reflects how discovery and evaluation work.

The role of earned media and content

You can buy an ad placement. That’s not breaking news. You know this. I know this. 

But you can’t buy your way directly into every AI answer. Yes, paid media is all about “pay-to-play,” that’s literally the whole ecosystem. But there are limits to that when it comes to AI. 

AI systems tend to favor information they can verify through trusted sources. They’re looking for evidence, consistency, and third-party support rather than a brand repeatedly announcing its own greatness into the void. This is why you need to think about earned media as playing a major role in your strategies, because of their influence. 

Now, when I say “earned media,” I’m talking about:

• PR coverage
• Publisher partnerships
• Product reviews
• Industry citations
• Original research
• Proprietary studies
• White papers
• Authoritative backlinks
• Local pages
• Structured FAQs

When a respected industry publication reviews your product or cites your research, the AI system can associate your brand with the topic and evaluate the context around the mention. Original research is also especially valuable. Other websites may cite, discuss, and link to the findings, creating multiple sources that reinforce your authority.

Alternatively, local pages and structured FAQs can give AI platforms clean information they can retrieve when answering specific or location-based questions.

Case study: How The Foot Doc achieved lead gen goals through strategic campaign optimization

Paid media can then amplify those earned assets. When you secure a strong piece of coverage, put distribution behind it. More reach can lead to more readers, shares, discussion, links, and future citations.

That creates a feedback loop:

1. Paid media increases visibility.
2. Visibility helps generate earned attention and engagement.
3. Earned attention strengthens the brand’s authority.
4. Stronger authority can increase the likelihood of AI citations.

Your ad budget is doing more than buying an immediate visit. It’s also supporting the wider information environment through which buyers and AI platforms come to understand your brand.

Choosing and reporting on AI search platforms

AI search visibility isn’t consistent across every platform… of course it’s not. Nothing is consistent. Google AI Overviews, ChatGPT, Gemini, Microsoft Copilot, Claude, and Perplexity use different data, retrieval systems, interfaces, and citation practices. 

That means a brand may appear constantly on one platform, but barely register a blip on another. That means your reporting needs to cover the platforms most relevant to your audience and examine both the mention and the source behind it.

Google AI Overviews

Track citation frequency and source links to understand how your brand appears within the dominant search engine’s AI answer layer.

ChatGPT

Monitor brand mentions in conversational responses to see how your company or product is described and recommended in natural-language exchanges.

Gemini

Review sentiment, context, and supporting sources to understand how Google’s standalone AI model frames your brand.

Microsoft Copilot

Measure visibility in enterprise and workplace-oriented search contexts, particularly when B2B buyers may be using Copilot to research possible solutions.

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Perplexity

Review citation sources in research-heavy queries to identify which publishers, reviews, or third-party pages are driving your visibility.

Claude

Track how your brand appears in longer, research-oriented answers and how the platform interprets source material relevant to your category.

For each platform, reporting should answer:

• Was the brand mentioned?
• How frequently did it appear?
• What was the sentiment?
• Which products, claims, or attributes were included?
• Which competitor brands appeared?
• What source did the platform cite?
• Was the source your website, a review, a publisher, a forum, or a news article?

Pixis Visibility consolidates data from multiple AI platforms into one dashboard, reducing the need to run the same prompts manually across several tools and assemble the results in a spreadsheet.

That makes it easier to spot changes. If visibility in Microsoft Copilot falls, you can investigate which enterprise search contexts or cited sources changed. If Perplexity repeatedly cites the same third-party publication, you can examine what that source provides and adjust your content and distribution strategy accordingly.

A framework for getting started

Start with a baseline. Document where your brand appears today across the major generative platforms for your most important products, services, and categories. Then compare that performance with your leading competitors.

1. Establish your AI visibility baseline

Track citation frequency, sentiment, share of voice, source URLs, brand mentions, and referral traffic across your priority platforms.

2. Conduct competitive benchmarking

Choose your three most relevant competitors and identify the prompts where they appear and you don’t.

Look at the sources AI platforms cite for those competitors. Those sources may reveal gaps in your content, earned media, research, reviews, or authority.

3. Track prompts, not only keywords

Buyers don’t always interact with AI through short keyword phrases. They ask long, detailed, conversational questions.

Track the questions they’re likely to ask during discovery, comparison, evaluation, and purchase. Record which brands appear and how they’re presented.

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4. Test paid media’s influence

Run controlled tests where possible.

For example, launch a targeted awareness campaign in one region and compare changes in AI citation frequency with a control region. Look for movement in branded search, direct traffic, mentions, and downstream conversions.

5. Use Pixis Visibility for ongoing optimization

Solutions 8 uses Pixis Visibility to monitor AI search performance and make adjustments as new data arrives.

That can include:

• Adjusting bids
• Shifting budgets
• Refining content
• Changing campaign emphasis
• Targeting missing prompts
• Responding to changes in citation frequency or sentiment

Rather than waiting for a monthly report, the team can monitor visibility and compare it with paid media performance over time.

The goal is to treat AI visibility with the same discipline applied to paid search: establish a baseline, form a hypothesis, test it, measure the result, and adjust.

AI search will never be a perfectly transparent channel. It can become far less mysterious when you consistently track the prompts, sources, citations, and downstream behavior surrounding it.

Frequently asked questions

Why is ROAS no longer enough for paid media in the AI era?

ROAS captures revenue that can be connected to advertising spend. It can’t fully account for influence that happens inside AI Overviews and other zero-click experiences.

A buyer may encounter your brand in an AI answer and convert later through direct traffic or branded search. Last-click reporting usually assigns credit to the final visit and misses the earlier AI interaction.

ROAS remains an important performance metric. AI citation frequency, share of voice, sentiment, brand mentions, and AI referral sessions give you a broader view of paid media’s influence.

What is AI search visibility, and how do I measure it?

AI search visibility describes how often and in what context your brand appears in AI-generated answers from platforms such as Google AI Overviews, ChatGPT, Gemini, Microsoft Copilot, Claude, and Perplexity.

You can measure it through:

• Citation frequency
• AI share of voice
• Sentiment analysis
• Brand mentions
• Citation sources
• AI referral sessions
• Competitive prompt tracking

Together, these metrics show more of your brand’s presence across AI search than click-based reporting alone.

Go deeper: How to do a PPC audit the right way (process + examples)

How does Pixis Visibility help with AI search reporting?

Pixis Visibility tracks citations, mentions, sentiment, prompts, and related visibility signals across AI platforms.

Solutions 8 can use that information alongside cross-channel performance data to examine how AI visibility relates to branded search, direct traffic, qualified leads, and revenue.

That gives clients a broader view of brand influence than ROAS can provide by itself.

What is Generative Engine Optimization?

Generative Engine Optimization is the practice of improving the likelihood that your brand or content will be selected and cited within generative AI answers.

While traditional SEO focuses on improving a page’s position in search results, GEO also considers technical accessibility, passage-level clarity, structured data, original information, earned media, and third-party authority.

The goal is to help AI systems retrieve, understand, verify, and accurately represent your information.

Future-proofing your paid media investment

ROAS isn’t disappearing. It’s becoming one part of a larger measurement system.

The buyer journey now includes AI-generated answers that can shape awareness, evaluation, and purchase decisions without producing a trackable click. Marketing teams need reporting that accounts for that influence alongside direct conversions.

That means connecting:

• Paid media
• Earned media
• Content
• Technical structure
• AI citations
• Brand mentions
• Share of voice
• Sentiment
• Branded search
• Direct traffic
• Revenue

Companies that begin tracking these relationships now will have a better understanding of where demand comes from and how their brand is being represented across AI search.

Solutions 8 uses Pixis Visibility to help clients map AI citations and brand mentions alongside paid media performance. Our team can help you establish a baseline, identify visibility gaps, track the prompts your buyers use, and build these new signals into your reporting.

You can also learn more about setting campaign goals and KPIs so your paid media strategy reflects the metrics that actually connect to your business. The goal is profitable, sustainable growth and a clearer view of what your advertising is influencing, including the parts that happen before anyone clicks.

Need more help with AI search visibility and your paid media reporting? The Solutions 8 team can help. We’d love to talk with you.