Funnel Segmentation Deep Dive AI Prompt

Analyze how conversion rates differ across key user segments in this funnel.

Funnel data: {{funnel_data}}
Segmentation dimensions: {{dimensions}} (e.g. acquisition channel, device, plan type, geography, user tenure)

1. Per-segment funnel tables:
   For each dimension, produce a funnel table showing conversion at every step broken out by segment value.
   Highlight: which segment has the highest overall conversion? Which has the lowest?

2. Segment-step interaction:
   - Are drop-off patterns consistent across segments, or does one segment struggle at a specific step?
   - Example: mobile users may convert well at sign-up but drop at payment entry
   - Identify any step where segment A converts at more than 2x segment B

3. Volume-weighted impact:
   - A segment with 5% conversion but only 2% of volume has low total impact
   - Compute: (segment volume %) x (conversion gap vs best segment) = impact score
   - Rank segments by impact score to prioritize where improvement matters most

4. Cohort conversion analysis:
   - Do users acquired in recent months convert better or worse than older cohorts?
   - Is there a trend suggesting the product is getting easier or harder to convert?

5. Statistical significance:
   - For the largest conversion gap between segments: run a proportion z-test
   - Is the difference significant (p < 0.05) or within random variation?

6. Recommendations:
   - Which segment should be targeted for conversion improvement first and why?
   - What product or UX change would most help the lowest-converting high-volume segment?

Return: per-segment funnel tables, segment-step interaction analysis, impact scores, significance test, and top recommendations.