- Feb 19
- 4 min read
The evolution of SEO, driven by the rise of AI chatbots like ChatGPT and Gemini, has created several challenges for marketers. One of the biggest ones is the attribution gap.
Traditional last-click metrics are no longer providing an accurate attribution picture, as the moment a customer is truly won often happens unseen, within a conversational AI environment.
Prime example: Someone finds, researches, and chooses a product through a conversational search in ChatGPT, then Google’s the product to make the purchase.
Here’s how marketers can address this attribution problem for more effective generative engine optimization—and marketing in general going forward.
How attribution worked in traditional SEO
For years, search marketing was a fairly predictable process. Marketers focused on optimizing for specific keywords to appear on Google Search Results Pages, otherwise known as the SERP.
The goal was to drive traffic via the "10 blue links" on Google results, and attribution was relatively straightforward. Your content ranked, people clicked on it, and some of them (hopefully) converted to customers. Crucially, you could attribute these AI conversions to the original piece of content that ranked, and you could optimize your pages with this knowledge.
That attribution model assumed the click. That assumption no longer holds.
The funnel hasn’t disappeared; it’s been preceded by a conversational layer you can’t track with clicks.
How LLMs complicate attribution for marketers
Now, 58.5% of U.S. Google searches end without a click, according to SparkToro.
And when a consumer uses an AI search platform like ChatGPT or Perplexity to research a product, as millions of people do, they form a shortlist and decide on a brand they like from the conversation.
From there, they may leave the AI environment and use a traditional search engine like Google to search for the brand name or a specific term to complete the transaction.
In this scenario, the last click is recorded on a traditional channel (e.g., paid or organic Google search), but the actual moment the customer was won—the research and recommendation phase—started in the AI conversation. There’s no clear attribution for the original conversation that happened in ChatGPT.
In my recent AI Search Summit, Dan Slagen, CMO at Zapier, highlighted this shift in buyer behavior. He believes the question you need to focus on is whether you’re being mentally selected by customers before they even get to your page.
“That's what's going to matter before someone actually comes to your site,” he said. “So even if you're seeing a decrease in organic traffic, you might actually be getting more conversions because the people that are coming to your site are the ones that found you after doing research. They're now coming to your site having already determined that you are the thing that they need.”
The business, reading the raw data, mistakenly attributes the win to the wrong channel and ends up optimizing for the wrong thing.
How to adjust your attribution model for more effective marketing
To succeed in this new landscape, marketers must adapt their strategy to accurately measure— and capitalize on—AI conversations. The changes you need to make as a marketer or business owner fall into two categories:
Shifting your mindset
Shifting your metrics
How to shift your mindset for more accurate AI search attribution
Marketers must now place a layer of human intelligence on top of the raw data to correct this attribution problem, because the data isn’t telling the full story.
Start by asking customers directly. Add "How did you find us?" to your onboarding, including options for ChatGPT, Perplexity, and traditional search. Then, compare those answers to what your analytics show. The gap between customer-reported discovery and attributed source is your AI blind spot.
Look at your Google Search Console data differently. AI-influenced searches tend to be more conversational and long-tail. If you're seeing high branded search volume but can't trace where the brand awareness started, AI tools are likely playing a role upstream.
This is where you, as the marketer or the founder, need to think to yourself, where is my customer? What is my customer using? Are they typically a Perplexity user? Or are they using ChatGPT?
If you spend a ton of money on ChatGPT, but your customer is on Perplexity, you wouldn't be seeing the outcome you want because you’ve misread where your consumer is. Read this piece by Rand Fishkin to better understand if your target market is using AI.
New metrics to track for AI search
To accurately measure the influence of AI and conversational search, marketers need to track new GEO KPIs and metrics.
Mentions: Track how often your brand is mentioned in the AI-generated answer and in what position over time.
Citations/sources: Track how often your website or content is cited as a source and how regularly.
Broad queries: Track a broad set of both brand and non-branded queries to understand overall visibility.
Sentiment: It's not enough to simply be mentioned in AI responses. Marketers must track how AI is describing their brand to ensure that the framing aligns with their goals.
The key concept is that AEO uniquely merges traditionally siloed marketing functions (market research → strategy → execution) into one channel. Unlike traditional marketing, where these operate separately, AI search lets us track brand sentiment in real-time and understand how people talk about brands and what questions they're asking. This convergence is what makes AEO high-leverage.
We built Searchable to help businesses understand AI search and to optimize toward driving customers and success. Our system shows you exactly where your sources are, plus your citations or mentions over time.
There are lots of tools to track brand visibility in AI search. Wix users can also take advantage of the AI Visibility Overview, now available in Wix Analytics, to see how their site is performing across major AI platforms like ChatGPT, Gemini, and Perplexity.
The most important thing is to recognize that the future of search requires marketers to shift both their mindsets and metrics. Only then will you truly understand how your customers are finding you, what information they’re receiving about your brand, and—everyone’s ultimate goal—how to win them over.
