Retention plateau as a product-market fit signal

Maya

An investor asked me straight out: “Do you have product-market fit?” I said yes, obviously. What in our data would actually back that up?

Alex Tutor

Product-market fit means a real market needs the product enough to keep using it without being pushed. One of its clearest signals is a retention plateau: the level where a cohort's curve stops falling.

Every curve drops at first: curious people leave. If it keeps sliding toward zero, nobody found lasting value. If it flattens, you've found people who need the product.

Here are last summer's sign-ups, July to September 2025, by the type of their first group, followed for a year. Monthly bracket retention: opened the app at least once in month k.

Alex Tutor

Summer 2025 sign-ups: share active by month since sign-up600 couples, 800 flats, 1,600 trips. “Flat, any event” also counts users whose only activity was a recurring bill created by the server.

Chart data

Months since sign-up	Couple, opened the app	Flat, opened the app	Flat, any event	Trip, opened the app
0	100	100	100	100
1	72.2	65.9	68.9	33.5
2	64.5	54.9	59.9	12.4
3	60.3	48.9	55.9	8.4
4	57.3	45	53	7.4

Show 8 more rows

5	55.8	43	52	5.6
6	55	41.6	51.6	6.1
7	55.3	40.6	50.6	7.2
8	53.8	40.9	50.9	7.6
9	53.8	40.4	51.4	10.3
10	53.7	40	51	13.9
11	52.5	39.6	50.6	19.4
12	52.7	39.4	50.4	21.8

You

Couples drop from 72.2% in month 1 to about 55% by month 6, and then barely move.

Alex Tutor

That's a plateau. Measure its level as the average of months 6 to 12, where the curve is flat.

Alex Tutor

Question 1

From the chart, compute the couples' plateau level: the average of months 6–12 (opened the app). In %, one decimal.

Your answer

Units: % (e.g. 45.5)

Maya

Great, 54% of couples stay for good. So that's product-market fit, done?

Alex Tutor

It's strong evidence that couples who try Halves find lasting value. It doesn't say how many couples there are to win, whether they'll pay for Plus, or whether newer cohorts will flatten too. One summer's cohort is one data point.

And size matters. A plateau at 50% of 20 hand-picked beta users says much less than one at 30% of thousands who came from the store.

Alex Tutor

Question 2

The couples' curve flattens at about 54%. Which of these does that plateau not show on its own? Select all that apply.

Choose all that applyThat some couples found lasting value in HalvesHow many couples there are left to winWhether retained couples will pay for Halves PlusThat this year's cohorts will flatten at the same levelThat the users who stay don't need to be pushed back by campaigns

You

Flats have two lines. By any event they level off around 51%, by app opens around 40%.

Alex Tutor

The gap is people who set up the rent as a recurring bill and never open the app again. The server keeps logging expenses for them, so an “any event” curve looks flatter and higher than real use.

Maya

Automation is value too, though. They don't need to open the app.

Alex Tutor

Maybe, and that's worth checking: do they still settle up, or will they cancel when they move out? Until you know, report the curve by app opens and name the other one.

Alex Tutor

Question 3

In month 12, how many percentage points higher is the flats' curve by any event than by app opens? One decimal.

Your answer

Units: points (e.g. 5.5)

Maya

And trips? 5.6% by month 5. That's no plateau at all. Should we stop marketing to travelers?

Alex Tutor

Look at the end of the line: from month 9 it climbs back to 21.8% by month 12, and most of those users are in a new group. A trip group ends when the trip ends. The group's lifetime isn't user churn; these people came back for next summer's trip.

You

So for trips the question isn't “are they active every month” but “do they come back for the next trip”.

Alex Tutor

Question 4

Trip users fall to 5.6% by month 5, then rise to 21.8% by month 12, mostly in new groups. What's the best reading?

Choose one answerTrip groups end by design; many users return for the next trip, so judge trips by their yearly return, not monthly activityTrips have no product-market fit; stop marketing to travelersA data error: users can't come back after leavingTrips now have the best retention, because their curve rises at the end

Theo

Can't we just show the investor one curve for everyone? Simpler.

Alex Tutor

Blended, the three types go from 29.6% in month 3 to 32.7% in month 12. It looks like retention improving, when it's trips returning for summer on top of two flat curves.

You

So one curve would tell the investor retention grows, while couples and flats are slowly slipping.

Alex Tutor

Question 5

True or false: the blended curve for all three types rising from 29.6% in month 3 to 32.7% in month 12 shows that Halves retention improved over the year.

TrueFalse

Maya

Then help me answer properly: do we have product-market fit, and for whom?

Alex Tutor

Answer by segment, with the plateau levels, the measure you used, and what you still don't know.

You

Couples and flats by app opens, trips by return for the next trip, and one line on the limits.

Alex Tutor

Question 6Short answer · AI-checked task

Write Maya's 3–5 sentence answer to the investor: does Halves have product-market fit, and for whom? Use the plateau levels, name the measure, and state one limit.

Write your answer and get a score with feedback from our AI reviewer.

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Alex Tutor

“Obviously yes” wasn't wrong for couples. It just needed a curve, a measure and a “for whom”.

Alex Tutor

That’s the lesson. You answered every task — nicely done.

Next lesson: Case: couples, flats and trips