Definition
Time to Value (TTV) is the time from a user’s first interaction (signup) to reaching a defined value milestone (activation event).
Answer-first summary
Time to Value (TTV): Time to Value (TTV) is the time from a user’s first interaction (signup) to reaching a defined value milestone (activation event).
Formula
TTV
TTV = Timestamp(Activation Event) - Timestamp(Signup/Trial Start)
- Activation Event: First value milestone
- Signup: Start time of user journey
If signup is Monday 10:00 and activation is Monday 10:12 → TTV = 12 minutes.
How to improve
- Use templates and defaults.
- Provide sample data/importers.
- Guide users to the shortest path to value.
Common pitfalls
- Choosing activation events that don’t represent value.
- Measuring average only; track distribution (p50/p90).
Track Time to Value (TTV) automatically
Use dashboards, reports, and KPI definitions to keep your team aligned. Start a trial or book a demo.
FAQ
- Should TTV be measured in minutes or days?
- Depends on product. Use the unit that matches buying/usage cadence; track p50 and p90.
- How does TTV relate to churn?
- Long TTV typically correlates with lower activation and higher early churn.
Related metrics
- Activation Rate
Activation rate shows what percent of new users reach first value. Learn definitions, formulas, and practical levers to increase activation.
- Product Qualified Lead (PQL)
PQLs are leads qualified by product usage. Learn definition, criteria examples, and how to operationalize PQL routing.
- Trial-to-Paid Conversion
Trial-to-paid conversion measures how many trials become paying customers. Learn levers to improve.
- Retention Rate
Retention rate measures how many users/customers come back or stay active. Learn cohort retention and levers.
- DAU/MAU (Stickiness)
DAU/MAU indicates how frequently users return. Learn interpretation and levers.
Related templates
- PLG Activation Template
A template to define activation events, track time-to-value, and improve onboarding.
- Cohort Retention Template
Template to track cohort retention curves and identify retention drop-off points.