Definition
A product usage signal is a pattern in how users interact with your product that tells you something meaningful about their intent or health.
Examples include hitting usage limits, repeatedly using a key feature, or suddenly dropping activity.
Signals can be events (something happened) or trends (a pattern over time).
Types of product usage signals
Intent signals: Visiting pricing pages, exploring premium features, hitting usage limits.
Engagement signals: Login frequency, feature breadth, depth of usage.
Risk signals: Declining activity, abandoned onboarding, decreasing use of core features.
Expansion signals: Adding teammates, using more of a usage-based resource, adopting new features.
Examples of product usage signals in PLG
Positive signals: completing onboarding journeys, inviting teammates, or consistently returning to core workflows.
Risk signals: declining logins, abandoned onboarding, or decreasing use of value-driving features.
A user who completes onboarding, invites two teammates, and logs in three days in a row is signaling engagement.
How to use product usage signals
PQL scoring: Combine signals to identify accounts ready for sales outreach.
Health scoring: Aggregate signals into a customer health score for success teams.
Automated workflows: Trigger emails, in-app messages, or alerts based on signal patterns.
Churn prediction: Use declining signals as leading indicators of churn risk.
Product usage signals and Skene
Skene ties journeys and milestones directly to analytics so you can define and monitor product usage signals with less custom wiring.
Those signals can then power PQL models, health scores, and proactive success playbooks.
Implementation notes
- Start with a few high-value signals rather than tracking everything—signal noise is a real problem.
- Define clear thresholds for signals (e.g., "logged in 3+ times this week" rather than "active").
- Validate signals by checking if they actually correlate with the outcomes you care about (conversion, retention, churn).