Analytics
Define MVP analytics for experiments: event scope, decision rules, dashboard ownership, and evidence quality needed to decide go, pivot, or stop.
Key takeaways
- Define MVP analytics for experiments: event scope, decision rules, dashboard ownership, and evidence quality needed to decide go, pivot, or stop.
- Use this chapter as a first-pass operating checklist before changing systems, data, permissions, or customer-facing workflows.
- Validate platform-specific details against current official docs or internal policy before rollout.
Analytics should answer the experiment question, not collect every possible event. MVP analytics must be simple, reliable, and connected to the decision rule.
Event Plan
| Event | Purpose |
|---|---|
page_view | Traffic and source baseline |
primary_cta_click | Offer interest |
signup_started | Intent beyond browsing |
activation_completed | Core value reached |
demo_requested | Sales-ready conversion |
payment_started / payment_completed | Willingness to pay |
Metric Set
| Metric | Use |
|---|---|
| Conversion rate | Whether the offer or flow works |
| Activation rate | Whether users reach value |
| Drop-off point | Where the test path breaks |
| Time to value | Whether the promise is quick enough |
| Qualitative objections | Why users hesitate |
Instrumentation Checklist
- Track the primary conversion event.
- Track enough diagnostic events to explain failure.
- Include source, segment, and experiment version where possible.
- Verify events in the analytics tool before launch.
- Keep raw qualitative notes tied to user/session where allowed.