Skip to content

SAAS GUIDE

Analytics for SaaS teams that need decisions, not surveillance.

A practical SaaS analytics model for activation, engagement, conversion and retention using aggregate product signals.

SaaS teams rarely need more events. They need a small chain of evidence from acquisition to activation, continued use and conversion. Define that chain with aggregate signals before adding instrumentation.

A privacy-aware SaaS metric map
StageUseful aggregate signalsDecision
AcquisitionSource, landing page, campaign, country and device share.Which channels and pages deserve better content or distribution?
ActivationGoal completion, event sequence, funnel step completion and time to first meaningful event.Where does onboarding need clearer guidance?
EngagementReturning activity estimates, feature events, measured engagement and active days.Which workflows are used enough to protect and improve?
RetentionCoarse weekly or monthly cohorts, with minimum-size safeguards.Does continued value appear after the first use?

Keep the denominator honest

Call a value a conversion rate only when the numerator and denominator come from the same supported population and period. Do not combine a source list and a goal list to claim source-level conversion unless the data explicitly links them.

Questions for the weekly review

  • What changed versus the previous period?
  • Which funnel step lost the most aggregate activity?
  • Which page, source or campaign deserves a product or content experiment?
  • What is missing because of sampling, opt-out or low coverage?

Use local AI reports to draft hypotheses, then validate them against the dashboard and deployment calendar. The model should explain uncertainty rather than invent individual stories.

See the product before you sign up.

Explore a real public dashboard, then bring your own product data.