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AI Product Tools / MIF Explorer / Library / UX
Truth Layer
MeaningfulLeading Truth Layer
The Truth Layer is the badge system that tells you how trustworthy, directional, or risky a measure is.
Why it matters: It helps teams separate meaningful signals from vanity, misuse, or AI distortion before they optimize the wrong thing.
Example: A metric can be Meaningful, Leading, or Vanity Risk.
Return Visit Rate
The percentage of users who return to the product within a defined time window after their first visit.
Evaluation method
users_with_2plus_sessions / total_users × 100
Signal type
leading
What it is best for
Early indicator of product-market fit
What it tells you +
Whether the initial experience created enough value to bring users back.
What it does not tell you +
Explain why users returned or whether return visits were productive.
When to use it +
- Early indicator of product-market fit
- Evaluating whether onboarding changes affect long-term engagement
When not to use it +
- For products with naturally infrequent use cycles (tax software, moving tools)
How leaders misuse it +
- Counting email-driven returns as organic engagement
Anti-patterns +
- Using re-engagement emails and counting those visits as organic returns
Companion entries +
This entry is stronger when paired with:
Instrumentation or evaluation guidance +
Define the time window clearly (7 days, 14 days, 30 days). Track by cohort for meaningful trends.
Sample events
session_start Examples +
A fitness app has a 7-day return visit rate of 38%. After personalizing the first workout, the rate rises to 54%.
Suggested decisions +
- If 7-day return rate is below 20%, the first experience is not creating enough pull