Leading Indicators
These are early signs that suggest whether you’re on track to achieve a goal. They tend to be predictive and actionable.
Think of them as “canaries in the coal mine.”
🔹 Examples:
- Number of daily signups (may predict future revenue)
- % of users completing onboarding (may predict retention)
- Weekly active users (early sign of growing engagement)
- Referral invites sent (may forecast user growth)
- Add-to-cart rate (can precede purchase rate)
✅ Pros:
- Help you pivot quickly
- Provide fast feedback
- Useful in short-term experiments
❌ Cons:
- Not always accurate predictors
- May fluctuate a lot (less stable)
Lagging Indicators
These are outcomes — they tell you what happened, not what’s about to happen. They’re more stable but slower to reflect change.
Think of them as “scoreboards” — they tell you the final result.
🔹 Examples:
- Revenue
- Customer Lifetime Value (LTV)
- Retention after 30 days
- Conversion to paying user
- Churn rate
✅ Pros:
- Clearly tied to business goals
- Easy to quantify impact
❌ Cons:
- Time-delayed
- Hard to improve reactively
🎯 In Practice:
In an A/B test, you might track leading indicators to get early feedback and lagging indicators to confirm long-term value.
Example:
You launch a new onboarding flow for an app.
-
Leading Indicator: % of users completing onboarding in the first 10 minutes
-
Lagging Indicator: Day-30 retention rate