Natural-language analysis can feel effortless before its assumptions become visible.
Fast answers support exploration, while silent semantic errors weaken confidence in the result.
Who you’d be doing this for
“The chart looked right until finance asked why the numbers didn’t reconcile.”
Torsten Holmberg · Growth Analytics Lead
Uses behavioral funnels to diagnose trial-to-paid conversion for a subscription product.
What is at stake
Human review found first-pass funnel correctness at 72% for ambiguous customer properties. You have to balance fast natural-language analysis with safeguards that catch semantic mistakes.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- query speed vs. semantic validation
- self-service flow vs. clarification burden
- generic language models vs. customer-specific schemas
- correctness gains vs. compute limits
Why Amplitude
AI-assisted funnel creation in Amplitude must preserve the event-level meaning customers use to make product decisions.
Written with these in mind
Not your kind of problem? 6 more at Amplitude, or browse every organization.
This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.