Monetization: LTV, Payback and the Formula That Lies
By the end of this lesson, you should be able to: build a cumulative revenue curve instead of quoting an LTV number, explain why the standard formula fails in a predictable direction, use payback period as the decision metric it actually is, and connect all of it back to the acquisition channel that produced the user.
Stop quoting LTV, start drawing the curve
Lifetime value normally arrives as a single number on a slide. That number hides everything worth knowing, so build the curve instead: cumulative revenue per acquired user, by days since signup.
| Days since signup | Cumulative revenue per user |
|---|---|
| 7 | $26.76 |
| 14 | $44.82 |
| 28 | $74.23 |
| 42 | $98.06 |
| 56 | $119.00 |
One number in that table matters more than the rest. 38% of eight-week revenue arrives after day 28. A team reading LTV at four weeks, which is what most teams have when they need to decide, is looking at under two thirds of what shows up in eight, and the curve hasn't stopped.
The formula, tested
The textbook estimate is everywhere:
Fit it on Basket's first four weeks, which is what a real team would have:
| Weekly ARPU (first four weeks) | $18.56 |
| Implied weekly churn | 15.3% |
| LTV estimate | $121.08 |
Now look at what that claims. $121 is supposed to be the whole relationship, forever. Basket users reached $119 by day 56, leaving $2.08 for the entire rest of their lives, while the curve was still climbing at $20.94 per fortnight.
The formula isn't 2% off. It's going to be wrong by multiples, and it's wrong in a direction you can predict before running it.