solutions/churn & retention

Keep the customers worth keeping.

Stop exporting a churn score and guessing what to do with it. Xplainable returns a ranked, costed save plan: who to keep, with which lever, inside the budget you set.

save_plan.runready
0%
of at-risk value recoverable
ranked save plancost
01retention_call$14,200
02fee_waiver$9,400
03win_back_offer$6,000
[✓] $29,600 plan ≤ $30,000 cap
Why a score isn't enoughA / the problem >>>

A churn model tells you who is leaving. It doesn't tell you who is worth saving, which intervention will work, or what it costs. So the list lands on a CSM's desk and the budget gets spent on whoever shouts loudest.

From data to decisionB / how it fits >>>
// you feed it

Your customers, their history, and the levers you can pull: calls, waivers, win-back offers, each with a cost.

// it decides

It scores save-probability per account and matches the highest-value lever to each, then packs the plan to fit your budget.

// you get

A ranked, costed save plan with the reason behind every account, ready to hand to the team or push to your CRM.

How it worksC / the engine >>>
01

score risk + value

Every account gets a churn probability and an expected value at risk, explained by its own drivers.

02

match the lever

The engine picks the highest-EV intervention per account from the levers and costs you defined.

03

fit the budget

It packs the plan to your spend cap, maximising retained value, and shows what it left out and why.

What it runs onD / inputs >>>
[✓]CRM / subscription data
[✓]Usage & support history
[✓]Your retention levers + costs
[✓]A budget cap
What you walk away withE / outcomes >>>
71%of at-risk value recoverable inside a typical budget
1 planranked and costed, not a score to interpret
every rowcarries the reason it was chosen
Common questionsF / faq >>>
Other leversG / more >>>

Stop guessing. Start deciding.

engine: online