Solutions · Digital-native & Scale-ups
For apps, marketplaces, fintech and SaaS past product-market fit, where a few points of activation, conversion or retention decide the year. Moveo One predicts each customer's next move at runtime and simulates onboarding, pricing and paywall changes on cohorts calibrated to your real users.
Predict which new accounts will reach first value, and intervene while they are still in the product.
Read the use case →Score every trial and free account for its probability to pay, and aim offers at the cohort that will.
Read the use case →Per-customer churn probability with the reason behind it: UX friction, price, missing feature or support.
Read the use case →Run a new paywall, plan structure or price on calibrated synthetic cohorts before real customers see it.
Read the use case →Models that predicted a customer's next move and changed the decision in the same session, and simulations that caught a problem before a real customer saw it. Every model runs with a holdout, so the lift is measured, not assumed.
+44%
Paid conversion
0.9% → 1.3% of new accounts converting to paid
Problem
Thousands of new accounts a month, and conversion to paid looked random.
Approach
Moveo One scored every account and identified 250 of 2,570 with at least 80% probability to subscribe. Only that cohort received conversion interventions: email, in-app and offer timing.
Creative software · SaaS
+27%
Revenue per signup
Revenue per signup, both intent cohorts combined
Problem
A strict purchase gate converted better but cut top-of-funnel growth. There was no rule for when to use which.
Approach
Moveo One predicted purchase intent at session start. High-intent customers went straight to the purchase path; exploratory customers got a lighter entry. Both cohorts performed.
Consumer education app
+61%
Onboarding completion
Onboarding completion among at-risk users
Problem
Customers abandoned onboarding between steps 3 and 7. Generic reminders moved the number by 2%.
Approach
Moveo One predicted likelihood to abandon mid-flow. At-risk customers were fast-forwarded before they left, not reminded after.
Gaming platform · 200K users
B2C ed-tech
89.2%
of onboarding abandoners flagged in advance
49,718 held-out sessions, 93.6% accuracy. Flagged users were routed into a shorter onboarding.
AI creative platform · 40K+ users
+10%
of revenue recovered
Late users separated from gone users, past the activation window. Offers routed into the client's own tooling.
Case study · Ed-tech · iOS
Yuno App: adaptive onboarding driven by predicted conversion.
01
Your warehouse (BigQuery, Snowflake, Redshift, Segment), your product analytics, or the SDK. Or let your AI assistant install it through the MCP server.
02
Moveo One trains on your behavioral history for the outcome you choose: activation, conversion, churn or any event.
03
Predictions over API and webhooks at runtime; simulations against staging before each release.