Retention use case

Reach at-risk customers before they walk

Zoice tracks NPS, CSAT, and sentiment across every conversation, fires churn alerts when an account turns negative, and calls with a personalised save offer — with full memory of everything the customer has told you before.

Churn-risk save call

VoiceWhatsAppWeb Chat
AI agent

Hi Meera, I'm calling from your broadband provider. I can see you've raised three speed complaints this month, and your renewal is next week — I wanted to check in before that. Is the issue still happening?

Customer

Honestly, yes. I've already started looking at other providers.

AI agent

That's completely fair, and I'm sorry it got this far. Here's what I can do right now: book a priority engineer visit for tomorrow morning, and apply a loyalty credit to your renewal while we fix it. Would that work?

Customer

If the engineer actually shows up this time — okay.

AI agent

Booked: tomorrow, 10 am–12 pm, and the credit is applied. I'll message you on WhatsApp after the visit to make sure everything's resolved.

Objective: save_offer_acceptedChurn reason: network_qualityFollow-up: WhatsApp after visit

Churn reasons are extracted on every call, so you fix root causes — not just symptoms.

The problem

Churn is silent until the cancellation

The signals were in your conversations all along — nobody was listening at scale.

You hear about churn last

By the time a cancellation request lands, the customer decided weeks ago. The warning signs were in their support conversations.

Save calls only reach big accounts

A human renewal desk can't call everyone, so smaller at-risk customers churn untouched.

Generic offers save nobody

A discount that ignores why the customer is unhappy reads as desperation, not care.

One attempt, then a goodbye email

Retention rarely succeeds on the first touch — but manual teams almost never make the second.

How it works

A save motion that runs itself

From churn signal to confirmed save, without waiting on desk capacity.

1

Catch the churn signal early

NPS, CSAT, and per-conversation sentiment feed churn alerts the moment an account's trend turns negative — weeks before the cancellation email.

2

Call with full history

Contacts long-term memory brings every past complaint and promise into the call, so it starts at "I know what happened", not "how can I help?"

3

Present a tested save offer

A/B experiments run competing offers and scripts head-to-head, so what the agent presents is the variant that actually saves customers.

4

Close the loop with follow-ups

Voice → WhatsApp → voice touches confirm the fix landed, and extracted churn reasons flow into Ask Anything analytics for your product team.

Capabilities

From churn signals to saved revenue

Six capabilities that make retention proactive instead of reactive.

NPS/CSAT tracking + churn alerts

Satisfaction is scored on every conversation, and declining accounts trigger alerts automatically.

Long-term contact memory

Every prior conversation is on hand at call time — complaints, promises, preferences — across voice, WhatsApp, and chat.

Sentiment + churn-reason extraction

Each call is scored for sentiment, and the stated reason for leaving is captured as structured data.

A/B-tested save offers

Test offers, scripts, and voices against each other and keep the variant with the higher save rate.

Multi-touch follow-up sequences

Voice → WhatsApp → voice sequences make the second and third touches your team never gets to.

Ask Anything analytics

"Why did customers cancel in May?" — answered from your real conversations, in plain English.

60%

faster agent ramp-up

Save customers before they say goodbye

Churn alerts, personalised save calls, and follow-up sequences that close the loop.

Retention — Frequently Asked Questions

ZOICE