Stop Paying to Lose Customers
Supercharge Your Existing CRM System with Presage
In development. The waitlist opens the first slots.
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Built for subscription businesses with 1,000 or more recurring customers. Presage reads the history you already hold and turns it into one instruction per customer.
Which customers a message actually helps, which ones it does nothing for, and which ones it pushes out the door.
The point in a customer's own history where contact still changes the outcome, rather than the day the campaign calendar says so.
One instruction your CRM already knows how to execute: contact, suppress, or leave alone — with the offer size that fits.
English walkthrough · Watch on YouTube
The walkthrough runs on a synthetic book. Want it on your own numbers? Presage is in development — the waitlist opens the first design-partner slots, and those come with the waste audit on your own history.
No migration, no second sending tool. Presage reads the behavioural history out of the system you already send from — Salesforce, Braze, Klaviyo, Optimove, Emarsys — and writes one instruction back per customer. Your journeys keep executing. They stop firing at the people contact cannot help.
The CRM stays the system of record. Presage is the decision layer between the history it already holds and the sends it already makes.
Every book splits four ways on one question: what does contact actually change? Pick a class to find it in a sample of 600 customers.
600 customers, none selected.
Stays whether you contact them or not. Every retention offer sent here is margin handed over for a decision already made.
Would have stayed, until you reminded them they could leave. The contact itself is what moves them out.
The only class where contact changes the outcome in your favour. Usually the smallest of the four.
Leaves regardless. Offers here buy a short delay at full discount cost, then the same outcome.
No language model, no black box, no learned behaviour you cannot inspect. Nothing on this page is generated, guessed or extrapolated by a neural network.
The same customer history returns the same instruction on every run. No sampling, no temperature, no drift between two Tuesdays.
Each instruction traces back to the estimated uplift and the threshold it was measured against. You can check any single customer by hand.
Causal inference and uplift modelling, established statistics with a literature behind them. Not a proprietary claim you have to take on trust.
Per year: retention budget handed to customers who were staying anyway, plus the revenue you lose to churn your own outreach causes.
Per year: the spend you stop, the churn you stop causing, and the customers the same budget keeps once it is pointed at the persuadable ones.
A call list that is shorter and worth working, because the accounts a call cannot move are off it.
The same journeys you run today, firing at the segment where a send still changes the outcome.
A flag on the ticket telling you whether a save offer helps this customer or hands away margin.
In shortEveryone who works in a CRM system.
If that is you, the audit reads your own history and returns a recoverable figure you can check against your own reporting.
If the audit comes back small, we will tell you and end the conversation.
Join the waitlist and you are in line for the first design-partner slots.