As people are starting to use large language models like ChatGPT to find businesses, marketers are realizing that tracking results is much harder than it was with traditional SEO.
Us SEOs have been spoiled. We know exactly what people type into Google and which webpage they click on. With large language models, we have no idea what they typed. And even when someone does choose to work with us, they typically aren’t clicking through to our website.
So can you track conversions from ChatGPT? Sort of. You won’t get the granular data you’re used to from Google, but there are ways to gauge whether your AEO efforts are working. And here’s the thing: since your competitors also don’t have that data, most of them are going to devalue the importance of showing up in large language models entirely.
This could actually work to your advantage.
What Data Can You Get from ChatGPT and AI Platforms?
Let’s be direct about what you can and can’t track.
What you can’t track:
- What prompts people are typing into ChatGPT
- How many people saw your brand mentioned in an AI response
- Traditional keyword data like search volume or impressions
- Direct attribution from AI mention to conversion
LLM providers don’t share what people ask. There’s no analog to Google Search Console’s keyword reports. AI firms keep prompts and user queries private for privacy and business reasons.
What you can track:
- Referral traffic from ChatGPT, Perplexity, and other AI platforms in Google Analytics
- Whether your brand is being mentioned in AI responses (via specialized tools)
- Which sources AI models are citing when recommending businesses like yours
- Trends in your AI visibility over time
The catch is that ChatGPT click-through rates are tiny. One analysis found that ChatGPT answers “rarely require visiting external sites,” meaning very few users actually click through to the source. We’re talking about 1-5% click-through rates compared to roughly 40% on traditional Google results.
This means counting only link clicks makes AI’s impact seem small. But that’s misleading.
Why Zero-Click Answers Change Everything
Here’s what most marketers miss: AI search is mostly a brand discovery channel, not a direct traffic driver.
When someone asks ChatGPT “what’s the best window tinting shop in Phoenix,” they might get a direct recommendation and then go search for that business by name. Or they might call them directly. That conversion never shows up in your referral data.
This is why measuring AEO is often compared to measuring offline ads like billboards or radio. You can’t draw a direct line from seeing a billboard to buying something. You only infer brand lift through proxies like unprompted branded searches and uplift in direct traffic.
AEO has a few advantages over traditional media though. We can count mentions and citations. We can estimate “share of voice” (how often an AI model cites your brand versus competitors). And any click or referral from an AI source, however rare, can be tracked.
Tools for Gauging AI Visibility
There are tools that help us gauge visibility across likely prompts. We can get a fairly accurate view of whether things are trending upwards or downwards. And these tools can tell us the most common sources and types of content that large language models are citing.
Here’s what’s available:
SEO Suites with AI Tracking: Major SEO tools like Ahrefs and SEMrush are adding features to monitor AI answers. Coverage is still patchy, but they scrape AI chat interfaces or APIs to see if your site is mentioned.
Dedicated LLM Tracking Platforms: Startups like Profound, Brandlight, and Karrot.ai focus on generative search. They simulate thousands of queries to capture AI citations and measure your answer share of voice.
Analytics Integration: You can use Google Analytics 4 with custom filters to catch referral traffic from known AI domains. This at least quantifies the portion of sessions coming through ChatGPT, Gemini, and others.
Manual Testing: As a stopgap, you can manually ask ChatGPT questions relevant to your industry and inspect source citations. Many LLM answers now list sources, so you can identify which pages the AI is learning from.
Why Your Competitors Are Sitting This Out
Many businesses are reluctant to invest in AEO because they see unclear data and no guaranteed ROI. Marketers trained on SEO and paid search are used to rich analytics: keyword rankings, CTRs, direct conversion paths.
AEO offers none of that.
As one SEO expert put it, working on LLM mentions feels like a step backward and akin to “entering the online billboard business.” Without direct clicks or sales to point at, all results are “vanity metrics” that are nice to track but hard to tie to revenue.
Conservative companies tend to avoid any channel where concrete conversion data is lacking. They fear throwing money at “dark funnels” that don’t yield clear reports. Others doubt that AI users will actually click through. After all, if ChatGPT gives a 1% click chance on answers, why invest heavily?
This skepticism leads many to pause. They’d rather keep optimizing known SEO channels than chase what they see as early AI hype.
Why Limited Data Might Be Your Competitive Advantage
Here’s my prediction: companies that are willing to make the investment on limited data are going to see an outsized return on that investment.
Why? Because your competitors are leaning on marketing channels with reliable conversion data. They’re going to underspend on what I believe is becoming the most common channel people use when deciding which brand to work with.
Look at the trends. ChatGPT alone now handles hundreds of millions of queries per day. Gartner predicts that by 2026, a quarter of all search traffic will come via AI chatbots.
And here’s something most people overlook: large language models convert users to customers at about 8 times the rate of traditional search engines. When ChatGPT recommends your business specifically, that carries far more weight than appearing as one of ten blue links.
Some early adopters are already seeing results. One attribution framework found that users first exposed via ChatGPT converted 3-5x more than unexposed users over 90 days, even though the initial AI interaction didn’t produce an immediate click.
How to Measure AEO Success Without Perfect Data
If you’re going to invest in AEO, here’s how to evaluate whether it’s working:
Track branded search volume. If more people are searching for your business by name, that’s often a sign they discovered you somewhere. AI recommendations frequently lead to branded searches.
Monitor referral traffic trends. Even if the numbers are small, watch whether referral traffic from AI platforms is growing month over month.
Use polling-based tools. Run a set of high-intent prompts through ChatGPT and other models regularly. Track whether your brand is mentioned more or less often over time.
Look at overall lead quality. If leads coming from organic sources have higher close rates, AI visibility might be contributing to that.
Watch your share of voice. Track how often AI recommends you versus your competitors for key queries in your industry.
This is similar to how companies used to measure offline advertising before digital attribution existed. It’s not perfect, but it’s far better than billboards or radio ever were.
The Bottom Line
Tracking AEO is harder than traditional SEO. You won’t get precise keyword data or clear conversion paths. But “harder to track” doesn’t mean “not worth doing.”
The tools are improving. The tracking methods are getting more sophisticated. And most importantly, the opportunity is real.
Your competitors are going to wait for better data. They’re going to sit on the sidelines until AI analytics catches up to what we have for Google.
By the time that happens, businesses that invested early will have already established themselves as the go-to recommendations in their industries.
If you want help getting your business in front of AI algorithms, reach out to our team. We stay ahead of what’s working in AI optimization, so you don’t have to.