Lean Analytics
About this book
Croll and Yoskovitz work through which metric matters at which stage for six business models covering ecommerce, SaaS, free mobile apps, media, user generated content and two sided marketplaces. The One Metric That Matters, drawing a line in the sand before you measure, and the five stages from empathy to scale organise the material. Includes benchmark figures and a large number of company examples with real numbers.
Description via Product Digest.
Topics
Related concepts
- Churn and revenue retentionChurn counted in customers set beside churn counted in money, the formulas for gross and net revenue retention, two worked cases where the two counts point in opposite directions, and what net revenue retention above one hundred per cent does to the growth a company has to buy.
- Product metricsThe four kinds of number a product produces, what each one is good for and how each one misleads, a worked case where the mean and the median disagree by the width of the whole population, and the property that separates a measure a team can act on from one that only ever rises.
- Product profitabilityWatching how the product performs in the market, what it costs the company to run, and what it contributes to profit, after the launch has stopped being news.
- Product analyticsWhat product analytics is, how it differs from business intelligence and from user research, the event as the unit everything else is counted from, and the single test that separates a practice from a wall of dashboards.
- Product metric frameworksAARRR from Dave McClure in 2007 and HEART from Google's research team in 2010, what each one was built to solve, the Goals Signals Metrics process that sits underneath HEART, and the honest criticism of both alongside the north star.
- Product Economics: Cost of Delay, Opportunity Cost, LTV and CACUse product economics to compare investments, calculate customer contribution and avoid misleading lifetime value or prioritisation claims.
- Funnels and conversionA funnel as a sequence of steps with a count at each one, the three choices that decide what it measures, a worked conversion calculation from forty thousand visitors down to four hundred and eighty customers, and why the denominator has to be stated before any rate means anything.
- Retention curvesThe shape a cohort traces over time, what a curve that flattens says about a durable audience, what a curve that reaches zero says about the absence of one, and how far apart day N, unbounded and bracket retention put the same cohort on the same data.
- Cohort analysisGrouping people by when they arrived or by what they did and following each group forward, the difference between an acquisition cohort and a behavioural cohort, a worked case where a blended figure falls while no cohort gets worse, and the three directions a cohort table is read in.