Use case · Retention & churn
Retention & churn
See who renews, who lapses and when, and what changes it, for subscriptions and contracts alike.
Questions Avir answers
- 01Which customers are most likely to leave in the next three months?
- 02If we drop the annual discount, how many switch to monthly, and how many leave?
- 03Which contracts are at risk at renewal, and what are they worth?
The situation
A subscription business planned to remove its annual-plan discount.
Assumed
Annual customers will just renew at the full price.
Simulated
Most renewed, but the newest annual customers lapsed at twice the usual rate at their first renewal.
Keep the discount for first renewals only.
An illustrative example. Your simulations run on your own customers.
What the simulation shows
The result, by customer group.
Every scenario comes back as a month-by-month forecast with its range, and the difference for each group of customers.
Scenario
Remove the annual-plan discount
Revenue +1.8% over the year
Renewals at the next renewal date, against no change
What goes into it
What you need to get started.
Your data
- Subscriptions or contracts with their start, renewal and end dates
- Plan and price of each
The world outside
- Seasons
Time and cost
- A forecast in seconds, once your data is connected
- A scenario with the AI panel in about a minute
- The cost in AI credits is shown before anything runs