07

Keep customers

Who stays, who leaves, and can we change it?

3 tools 1 law, 1 frame, 1 folklore, of 3

7.1 Evidence tier: Frame

Cohort Retention Curves

The proportion of each joining group still active, plotted against time since joining.

Breaks when You cannot read flattening before enough time has passed. A curve drawn from three months of data is drawn from hope.

7.2 Evidence tier: Law

Buy-Till-You-Die Models

A family of probability models that predict, from purchase history alone, how many purchases a customer will make next and whether they have quietly stopped buying.

Breaks when The models assume a customer's underlying purchase rate is stationary — that it does not change. So they break precisely when you intervene: sustained promotion, a price change, a category shift, a competitor entering. They are a forecast of what happens if nothing is done, which makes them a strong baseline and a poor evaluator of your own campaign. They also explain nothing: a customer with a 4% survival probability comes with no reason and no lever.

7.3 Evidence tier: Folklore

The Hook Model

A four-step loop — trigger, action, variable reward, investment — proposed as the mechanism by which a product becomes a habit.

Breaks when The loop's own examples break it. Several of the most habit-forming products ever built work by removing variability rather than adding it, and others run investment before any reward at all, which reverses the stated order. It also cannot separate a habit the user wants from one they resent, offers no account of why a habit ends — the thing a retention team is actually trying to predict — and imports variable reinforcement from animal schedules without the boundary conditions that came with it.