Interpret analytics metrics with correct context. Use when the user asks "is this good", "what's a normal X", or quotes a rate without denominator. Covers realistic ranges for bounce rate, engagement, session duration, pages per session, conversion rate by model type, SaaS unit economics (LTV:CAC, CAC payback, MRR churn, activation, retention), plus when each metric lies and minimum sample sizes.
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Metric context and benchmarks
The reference skill for answering "is this number good, bad, or noise?" correctly. Almost every wrong answer to that question comes from quoting a cross-industry average when the user's industry-specific number is 3× different, or quoting a benchmark without checking if the sample size even supports the comparison.
Read analytics-diagnostic-method first. Sample-size discipline applies here more than anywhere: benchmarks are meaningless if your data is noise.
[Description truncada. Veja o README completo no GitHub.]
