Event Analytics was Built for Buttons
How Analytics will change with the new AI modalities
The analytics tools that dominate product teams right now were designed around a specific assumption: users click things.
They click buttons, fill out forms, move through flows that someone on the product team designed in advance. “Step 1 leads to Step 2 leads to Step 3.” The analytics layer sits on top of those flows and measures who made it through, who dropped off, and where.
That model worked well for over a decade because the products matched the assumption. SaaS apps are deterministic. You design the path, users walk it, and you measure the walk.
AI products break that assumption.
When a customer opens a conversation with an AI agent, there is no designed path. There’s no Step 1. The customer types what they want in their own words, and the conversation goes wherever it goes. Ten customers with the exact same goal will have ten completely different interactions.
Try mapping that to a funnel.
You can’t, because there aren’t stages to map. There’s no “top of funnel” in a conversation. There’s no conversion event between Step 2 and Step 3 when steps don’t exist.
Event analytics tools will still give you numbers. They’ll show session counts, message volume, time spent. They’ll tell you things are happening. What they won’t tell you is whether any of it is working.
That’s the part that matters, and it’s the part that’s missing.
The tools aren’t broken. They’re measuring what they were designed to measure. The problem is that the products changed and the measurement approach didn’t change with them.
Product teams are stuck interpreting AI products through a lens built for button clicks. It’s like measuring a phone call by counting how many times someone pressed a key on the dial pad. Technically accurate, completely useless.
The products moved on. The analytics didn’t.
This leaves product times blind and customers confused.