Retention and payments infrastructure

Catch customers before they leave

Retain spots the ones drifting from their own usual pattern, brings them back, and measures the result against a group deliberately left alone.

So the number on your dashboard is the difference we caused, not a coincidence. No other retention tool can show you that.

$19.99 a month, every feature, every user. The holdout is included and permanent.

77%
of customers stop using a product within 3 days
30%
faster churn for AI-built products, despite 41% more revenue per payer
$23.50
your real cost per retained customer, once four of five walk out
66
median days until coming back is a habit. Then they stay on their own.

Stop guessing.
Guesswork is expensive.

Every other retention tool sends a message, watches a number move, and takes the credit. None of them can tell you what would have happened anyway, because none of them hold a control group. We do, on every play, permanently. That one decision is what turns everything below from an opinion into a measurement.

Fewer messages, not more

Most of your customers should be left alone. Some stay regardless, some leave regardless, and some leave precisely because you contacted them. Only one group is actually worth reaching, and we can tell them apart.

Less wasted ad spend

We describe your paying customers precisely enough that you can stop buying the segment that never converts. For most businesses that saves more than anything we do on the retention side.

Nothing to pay for unproven work

You are not billed for retention we cannot show we caused. No difference, no invoice.

This is the whole thing, running

Not a mockup. The shipped dashboard on a sample account: who is active, whether each new cohort holds better than the last, every customer, every payment tagged reached or left alone, and the invoice that follows from it.

The Retain dashboard Every number here is example data. Tap to open it and click anything.
04080120160week 1week 14week 27 plays start 139 26 customers active, indexed to 100
customers we reached customers we deliberately left alone

This is the chart nobody else can draw.

Two matched groups. One we work on, one we deliberately leave alone. The line falls before we start, turns once the plays land, and keeps climbing through the ordinary dips. The gap between the two is not a correlation or a chart that happened to move: it is the difference we made, and it is on your dashboard from the first week.

This is the shape a recovery takes when the plays land, modelled on published industry rates. Your dashboard draws your own two lines from the first week.

Most of your customers cannot be saved.
We find the ones who can.

Every retention tool treats a leaving customer as a leaving customer. But run the same play against a control group for long enough and your customers separate into four groups, and only one of them is worth spending anything on.

Saveable

Going, not gone. They stay if you reach them, and leave if you do not. The only group worth spending on, and far smaller than the list a churn tool hands you.

Loyal

They had already decided to stay. Every message you send them is cost without return.

Gone

No message recovers them. The list looks urgent and responds to nothing, which is how most retention budgets disappear.

Let sleeping dogs lie

They leave because you contacted them. The message did not fail. It did the damage. Almost nobody knows this group is in their customer base.

A churn score cannot tell these apart, because it only predicts who leaves, not who responds. Separating them needs treated and untreated customers measured side by side, which is what our architecture produces by default. Fewer messages, sent to the people they actually work on.

Early on this resolves at segment level, and sharpens toward the individual as your data accumulates. The dashboard tells you which it is rather than implying more precision than it has.

Who this is for

Any business where customers come back, or do not. Subscription products, e-commerce stores with repeat buyers, membership sites, gyms and studios, clinics, courses and training programs, SaaS tools, and consumer apps.

If your customers reach you through a website or a store, Retain installs as a script. If they reach you through a booking system, a point of sale, a mobile app or anything else, that system sends events over the HTTP API. The behavioural engine does not care what the front door looks like.

Retention
Catch customers drifting from their own rhythm, bring them back, and prove what it caused against a control group.
Payment
Checkout on Stripe rails, in early access, so the layer that keeps a customer also takes the payment and attributes the revenue.
Security
Events, never content. No identity shared across apps. No funds held. Frequency caps enforced in the engine, not left to you.

Others have done retention.
None of them can prove it worked.

Braze, OneSignal, Iterable, real tools, real companies. Every one of them shows you what customers did after a message went out. That's a coincidence with a chart on it. We deliberately leave a slice of your customers alone, so what you see is the difference we actually made. It's the one thing the category has never offered, and it's free on every dashboard.

The money signal · lagging

"Your subscription is about to lapse."

True, useful, and three weeks late. By the time someone cancels, the habit died a month ago. The decision was made long before the billing system noticed.

Winning them back now means re-recruiting a stranger.

Already gone.
The behavioural signal · leading

"Their rhythm broke on Tuesday."

Habits die quietly, weeks before the money stops. A missed session against their own pattern is the first symptom, and the last moment intervention is cheap.

Pulling back a drifting customer beats resurrecting a dead one 60-70% to 5-20%.

Still saveable.

Get Retain running on your business

Web apps and PWAs are the cleanest fit. Anything else can send events over the HTTP API. Setup takes minutes and we handle the integration details.

Get started free