The save desk that starts with context: churn agents in telecom
Predictive models flag at-risk accounts; an agent assembles the full account story and drafts in-policy retention offers — reps approve, customers stay.
The problem
A telecom's retention team was fighting churn blind. By the time a cancellation call arrived, the rep had seconds to skim a sprawling account history — tenure, tickets, outages, billing disputes, plan changes — while the customer waited. Offers were generic because context was unreachable, and the churn model's monthly risk list arrived too aggregated to act on.
The hypothesis
Saves are won on context and speed. Our hypothesis: score churn risk continuously rather than monthly, and when an account flags — or a cancellation contact begins — have an agent assemble the complete account story and draft a retention offer within policy, so the rep opens the conversation already knowing it.
The build
- Continuous churn scoring — models over usage trends, ticket history, network experience, and billing friction, refreshed daily with reason codes per score.
- Context agent — on trigger, an agent pulls the account timeline across systems and compresses it into a one-screen story: what this customer has lived through, what they value, what went wrong.
- Offer drafting with policy rails — the agent proposes a retention offer from an approved matrix — right-sized, margin-aware — and the rep approves, adjusts, or overrides. No offer reaches a customer without a human decision.
Design choice that mattered: the offer matrix is business-owned configuration, not model output. Finance sets the rails; the agent works within them. That's what made the CFO a sponsor.
Rollout
We piloted on one region's save desk with an A/B split against standard workflow. Reps using agent-prepped context resolved calls faster and saved more priority accounts; their feedback — mostly "show me less" — tightened the context template before national rollout.
Results
Context assembly went from minutes of frantic tab-switching to seconds. Save rates improved where it matters most — high-value, genuinely at-risk accounts — and offer spend stayed inside policy because policy is enforced by construction.
What we'd tell you
- Daily scores beat monthly lists. Churn risk is a stream, not a report.
- The rep is the product's user, not its supervisor. Build for their thirty seconds.
- Put the offer rails in config that finance owns — autonomy inside constraints is what scales.
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