Telecommunications

How do you predict churn early instead of reacting after they leave?

By the time a subscriber cancels, the decision was made weeks ago. The signals were there, scattered across systems that do not talk.

June 20264 min read

Why reacting is always too late

A subscriber who cancels decided weeks earlier, after usage drifted down, a bill caused a dispute, or a support issue went unresolved. Retention that starts at the cancellation is retention that already lost.

Score the risk while there is time to act

The signals, usage decline, payment friction, support history, plan fit, predict churn before renewal when they are read together. This sits across the customer and billing domains the TM Forum framework defines, which is exactly why a single view matters.

Accurate, predictable billing is itself a retention lever: dispute-driven churn is preventable.

Where the ERP closes the loop

On Hudace, usage, billing, support, and the catalogue share one platform, so a churn score reflects the whole relationship, not one feed. Xenon AI scores the base and proposes a next-best action, and because the catalogue and margin sit alongside, a retention offer reflects real margin, not just discount depth.

A retention manager decides the offer.

The numbers to watch

Watch churn and ARPU together; protecting one must not cost the other.

Churn rate

Subscribers lost in period / subscribers at start. The headline retention number.

ARPU

Recurring revenue / average subscribers. A retention offer should protect it, not erode it.

At-risk identified early

Share of churners flagged before renewal. The window to act.

Save rate

At-risk subscribers retained after outreach. What turns a score into value.

See churn prediction on Hudace

Talk to our team about joining usage, billing, and support to protect ARPU.

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