Optimize Startup Metrics Framework

Provides formulas, benchmarks, and reporting practices for the metrics that matter across startup business models - SaaS, marketplace, consumer/mobile, and B2B - from pre-seed through Series A. Covers universal metrics (MRR, ARR, MoM/YoY growth rate, CAC, LTV, LTV:CAC ratio, CAC payback period, burn rate, runway, burn multiple) alongside model-specific ones: SaaS revenue composition (new, expansion, contraction, and churned MRR), retention (logo retention, net dollar retention, gross retention), Magic Number, Rule of 40, and Quick Ratio; marketplace GMV, take rate, fill rate, repeat rate, and supply/demand balance; consumer engagement (DAU/MAU ratio, session frequency and duration), Day 1/7/30 retention curves, and viral K-factor; and B2B sales efficiency (win rate, sales cycle length, average contract value, pipeline coverage, and stage conversion rates). Each metric ships with its formula and stage-specific benchmark ranges - for example LTV:CAC above 3.0 is healthy, net dollar retention above 120% is best-in-class, and a burn multiple under 1.0 is exceptional - plus a per-stage focus list (pre-seed prioritizes retention and engagement over revenue; seed prioritizes MRR growth and baseline unit economics; Series A tracks ARR growth, unit economics, NDR, burn multiple, and Magic Number together) and a data-infrastructure and reporting-cadence checklist covering daily, weekly, monthly, and quarterly reporting rhythms.

Use it when setting up metric tracking for a startup, calculating unit economics, preparing an investor update or board deck, or diagnosing whether growth is efficient at the current stage. Skip it for tasks unrelated to startup metrics or outside this scope.

Input is the company's business model (SaaS, marketplace, consumer, or B2B) and stage (pre-seed through Series A); output is the matching set of formulas, target benchmarks, and a recommended 5-7 core metrics to track, plus common-mistake warnings - chasing vanity metrics like raw downloads, tracking too many metrics loosely, ignoring unit economics, not segmenting by cohort or channel, and gaming the dashboard instead of the business - and a sample investor-facing dashboard format showing current value, growth trend, and benchmark context together.

Not tied to a specific analytics platform - it names categories of tools by function (product analytics such as Mixpanel and Amplitude; SaaS-metrics platforms such as ChartMogul and Baremetrics; BI dashboards such as Looker and Tableau) as implementation options rather than prescribing one. Companion reference and example files - metric definitions, stage benchmarks, calculation walk-throughs, and sample SaaS, marketplace, and investor-deck dashboards - extend the core playbook.

Startup founders and operators building their first metrics dashboard, and anyone preparing fundraising materials who needs to know which numbers investors actually check at each stage - from pre-seed retention curves to Series A Rule-of-40 and burn-multiple targets.