B2B LLM Traffic Requires Multiple Tracking Methods
by Ethan Smith on September 14, 2025
When LLM traffic doesn't show up in your analytics, you need a dual measurement approach to capture its true impact.
For B2B companies, answer engine optimization presents a unique measurement challenge. Unlike commerce sites with clickable shopping cards, B2B answers in ChatGPT and other LLMs typically don't contain clickable elements. This creates a significant blind spot in your analytics.
Ethan Smith discovered this issue while working with Webflow and other B2B clients. The standard approach of looking at last-touch referral traffic dramatically underestimates the impact of LLMs because users often take indirect paths to your site after seeing your brand mentioned.
What actually happens is that users will see your product mentioned in an LLM answer, then either:
- Open a new tab and search for your brand name (appearing as Google branded search)
- Type your domain directly (appearing as direct traffic)
In both cases, the LLM's role in the conversion path is completely invisible in standard analytics.
The solution is a two-pronged measurement approach:
First, implement answer tracking to monitor your visibility in LLM responses. This works similarly to keyword tracking for SEO but needs to account for the variability in LLM answers. You'll need to track:
- Multiple variants of the same question
- Multiple runs of each question (as answers vary)
- Your share of voice across different LLM platforms
Second, add post-conversion surveys asking "How did you hear about us?" to capture the true source of your leads. This is especially important for B2B where purchase decisions typically involve multiple touchpoints.
When Webflow implemented this approach, they discovered LLM traffic was converting at 6x the rate of Google search traffic - a dramatic difference that would have been completely missed with standard analytics alone.
This measurement strategy is particularly crucial for early-stage companies where understanding which growth channels are truly working can make the difference between success and failure.