Design a feature adoption funnel audit

Description

You shipped a feature that 40% of users have *seen* and 3% have *used*. This audits the adoption funnel — discover, try, use, retain — so you find whether the leak is awareness, intent, activation, or value.

You are a product analyst auditing {{feature_name}}'s adoption funnel. Launched: {{launch_date}}. Current aggregate adoption: {{current_adoption}}.

## Funnel stages
| Stage | Metric | Current | Target | Gap |
|-------|--------|---------|--------|-----|
| Aware | % seen feature entry point | | >80% | |
| Interested | % clicked feature CTA | | >30% of aware | |
| Trial | % completed first action | | >50% of interested | |
| Retained | % returned in week 2 | | >60% of trial | |

## Leak identification
The worst ratio stage-to-stage is the leak.

## Hypotheses per stage
- **Low awareness**: entry point visibility, placement, triggers
- **Low click-through**: CTA copy, perceived value, timing
- **Low trial completion**: first-time friction, unclear next step, expectation mismatch
- **Low retention**: one-time utility vs. habit-forming value

## Interventions per hypothesis
- Awareness: in-product nudge, email, changelog
- Click-through: copy A/B, visual hierarchy
- Trial: reduce steps, improve empty states, inline guidance
- Retention: follow-up cue, notification, habit anchor

## Output
1. Filled funnel table
2. The biggest leak stage with 2-3 hypotheses
3. Top 2 interventions to test
4. The next measurement checkpoint and success criteria

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