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These are the signals that matter if OpenKol is doing its job: reducing noise and making verification shareable.

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Core product metrics

  • Analyses created per day / week (overall and per-user)
  • Activation rate: % of new users who run at least one analysis
  • Retention: users returning to analyze again (D1 / D7 / D30)
  • Time-to-value: time from landing → first completed analysis
  • Free → paid conversion (and churn, once paid tiers exist)

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Growth & distribution metrics

  • Share rate of OG cards and permalinks
  • Share → return rate: visits driven by shared links
  • KOL adoption: number of KOLs linking/sharing their OpenKol pages

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Coverage metrics

  • Number of tracked KOLs with enough calls for a meaningful profile
  • Depth of historical calls (how far back analyses go)
  • Chain/DEX coverage (once multi-chain expands)

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Integrity & reliability metrics

  • Reanalysis ratio: reanalyzes vs new analyses (signals trust + revisits)
  • Data freshness indicators (post retrieval and candle availability)
  • Provider error rate / missing-data rate by source
  • % of analyses completed without manual intervention
A strong candidate north-star metric is: Weekly Active Verifiers (WAV): unique users who complete at least one analysis per week. It captures the core behavior OpenKol is built for: verification, not browsing.