Most businesses don’t invest in Answer Engine Optimization (AEO) because they can’t track conversions from ChatGPT and other large language models the same way they track traditional SEO. When someone finds your business through ChatGPT, you typically won’t know what they typed into the AI or even that they came from ChatGPT at all. This lack of clear attribution data makes executives nervous about investing in AEO. However, this tracking gap actually creates a competitive advantage for businesses willing to invest in limited data.
The truth is, we can track AEO performance, just not in the way SEOs are used to. There are specialized tools that monitor brand visibility across AI platforms, and we can extrapolate results from the limited traffic that does come directly from large language models. While the data isn’t as clean as traditional SEO metrics, companies that start investing in AEO now are positioning themselves to dominate their industries as AI-powered search continues to grow.
Can You Track Website Traffic from ChatGPT?
Not perfectly, but you can capture some of it. ChatGPT doesn’t reliably pass referrer information or tracking data to your website. When ChatGPT includes a link to your site, it may or may not append tracking parameters. In Google Analytics 4, visits from ChatGPT can appear with chatgpt.com as the source if a URL has the right UTM parameter. But if ChatGPT provides your link without any tracking tags or referrer header, Google Analytics simply classifies the visit as Direct traffic.
The bigger issue is that most people don’t click through at all. They read the answer directly in ChatGPT. That interaction isn’t captured by your analytics.
Here are the main tracking methods:
Use custom UTM parameters: Add unique UTM tags to your content links (e.g.,?utm_source=chatgpt&utm_medium=ai-answer) so that if ChatGPT does pass them along, GA4 will log the session correctly. Build a custom report filtered on your AI UTM tags to isolate AI-driven traffic.
Filter AI referrals vs. Direct traffic: In GA4, create a segment for known AI referral domains (like chat.openai.com, perplexity.ai, etc.). ChatGPT visits might show up as those domains if a referrer is sent. However, any ChatGPT link without referrer data will simply inflate your “Direct” sessions.
Monitor server logs: Some SEO teams monitor server logs for AI crawler agents. Certain bots use distinctive user-agent strings (e.g., containing “ChatGPT-User”). Seeing these can confirm when an AI tool is indexing your content, even if it didn’t generate a click.
Use specialized AI tracking tools: There are emerging tools (Profound, LLMref, Otterly.AI) that actively query AI platforms and log when your content is referenced. They can tell you if and where your content appears in AI answers, even without clicks.
The reality is, we’ve been spoiled as SEOs. We know exactly what people type into Google and which webpage they click on. With large language models, we don’t have that luxury. But we can still piece together a fairly accurate view of whether things are trending upward or downward.
Why Is AEO Tracking More Difficult Than Traditional SEO?
AI-driven search offers no public analytics. Google and Bing provide keyword reports, click and impression metrics via Search Console. You know exactly which queries brought users and how often your content was served. With ChatGPT and similar large language models, you have none of that visibility.
Here’s what makes AEO tracking harder:
No query or impression data: You can’t see what questions users are asking ChatGPT, or how often your content is being served. There’s no “Search Console for LLMs” to tell you your rankings or click-through rates.
Opaque user behavior: In traditional SEO, users browse a results page and click on links. AEO users typically ask a question and read an AI-generated answer, only sometimes clicking the provided sources. Most of the “ranking” and answer-delivery happens off-site, invisible to your analytics. You often only know your content was helpful if someone later searches for your brand name.
Different success metrics: SEO success is measured by traffic volume and rankings. AEO success is about mentions and placements in AI answers, which aren’t tracked by GA4 or Search Console. You lose SEO’s fine-grained keyword and click data and must rely on proxies like “how often do we show up in AI answers?” or “did branded search grow after being featured in ChatGPT?”
Attribution is murky: Even if an AI answer influenced a conversion, it may not be attributed properly. Someone could see your answer in ChatGPT, bookmark it mentally, and buy later by searching your brand directly. You won’t see the original AI touchpoint in your analytics.
What Tools Help Measure Brand Visibility in Large Language Models?
A new category of AI visibility tools has emerged to monitor brand presence in chatbots. These platforms actively query large language models and report when your brand or URLs appear.
AI monitoring platforms: Tools like Profound, LLMref, Otterly.AI, and SEO suites with AEO modules (Semrush AI Toolkit, SE Ranking AI Tracker) scan ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude for mentions of your brand and content. These tools often provide share-of-voice metrics (how often you’re cited vs competitors), lists of queries that trigger your brand, and sentiment of mentions.
Brand mention trackers: Some marketing analytics solutions (e.g., Brand24) now include “AI mention” monitoring. They track when your brand appears in AI-generated content, similar to tracking search impressions.
Custom dashboards: Some marketers build dashboards that combine GA4 AI segments, Google Trends for branded search spikes, and inputs from AI-monitoring tools to create an AEO performance score.
The tools tell us which sources and types of content large language models are citing most often. So while it’s not as clean as traditional SEO data, it’s actually much better than billboard or radio advertising. We can see trends, track visibility, and understand what’s working.
Why Do Most Businesses Hesitate to Invest in AEO?
Most companies are skeptical because AEO lacks clear, immediate ROI data. Marketers are accustomed to channels where every dollar can be tied to a click or sale. AEO offers “visibility without clicks,” which makes decision-makers nervous. Without concrete conversion stats, they worry it’s hard to prove value.
Additionally, resource constraints play a role. Budgets are limited, so marketing leaders often only fund proven tactics. Since AEO is new and data is still emerging, it’s seen as a gamble. Companies prioritize traditional SEO or paid channels that deliver obvious attribution.
Here’s the thing, though: 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. They’re going to lean on marketing channels with reliable conversion data. And as a result, they’re going to underspend on what I believe is becoming the most common channel people use when deciding which brand to work with.
The Early Mover Advantage in AEO
Companies that start investing in AEO now are setting themselves up for success. Early adopters get known in AI search before others do. By developing content that AI systems favor now, you become the “go-to source” that large language models repeatedly surface. This builds a positive feedback loop of visibility and trust.
The logic is similar to the early days of Google SEO. Those who optimized first gained lasting authority. Such pioneers “establish authority before competitors adapt to this search paradigm shift.” You lock in a higher share-of-voice in AI answers.
My prediction is that companies that are willing to make the investment in limited data are going to see an outsized return on that investment. All else equal, a company that invests in AEO today will likely dominate the conversation in its industry as AI-driven discovery grows.
How Should You Approach AEO Measurement?
Think of AEO like brand-building rather than direct response marketing. Frame AEO as brand awareness and category leadership, not traffic generation. Getting your content cited in ChatGPT answers is top-of-funnel influence at scale.
Track these metrics instead:
Brand mentions: How often does your brand appear in AI answers for industry-related queries?
Share of voice: How often are you cited compared to competitors?
Branded search lift: Monitor trends in branded search volume. Are more people searching for your company name after your content appears in AI platforms?
Survey new customers: Ask, “How did you hear about us?” Increasingly, people may reply, “I saw you mentioned in ChatGPT.”
Assisted conversions: Look for patterns where AI visibility correlates with increases in direct traffic, branded searches, or conversions.
The key is accepting that you won’t have perfect attribution. Just as you wouldn’t measure a billboard by direct clicks, you shouldn’t judge AEO solely by immediate conversions. Focus on visibility trends, brand lift, and downstream effects.
Start Investing in AEO Now
The businesses that invest in AI optimization and SEO today will own mindshare tomorrow. While your competitors wait for perfect tracking data, you can be building the content and authority that positions your brand as the go-to source in AI-powered search.
At TJ Digital, we help businesses optimize for both traditional search engines and large language models like ChatGPT. We track visibility across AI platforms, monitor brand mentions, and build content strategies that get you cited where your customers are searching. If you’re ready to get ahead of the curve, let’s talk about how we can help.
The tracking might not be perfect, but the opportunity is clear. The question is whether you’ll act on it before your competitors do.