---
title: "Case study: how AI-forward CS teams tackle churn signals"
description: "Birdie's Chief Customer Officer on running an AI-forward CS team: churn escalation and commercial attainment now run on a layer of certified metrics over Birdie's internal data, so the answer is consistent no matter who asks or how."
canonical: "https://rig.so/case-studies/birdie-cs"
format: markdown
---

[All case studies](https://rig.so/case-studies)

UK · Series B · HealthTechDomiciliary Care SaaS

# How AI-forward CS teams tackle churn signals

When the same question returns different answers based on how it's asked, churn escalation and commercial attainment don't scale. Birdie now has a layer of certified metrics over its internal data, so the answer is consistent no matter who asks or how.

> “The result is going to be consistent every single time, and now I can't imagine operating without it.”

JudyChief Customer Officer @ Birdie

Hear from Judy, Chief Customer Officer @ Birdie

## A different answer to the same questions

Trust

Consistent-sounding answers that weren't consistent

Querying Notion, Snowflake, Intercom and HubSpot straight through general agent tools got answers that varied depending on how a question was phrased, exactly the kind of imprecision that churn and commercial-attainment numbers can't afford.

Admin

Prep time eating into customer time

Reps were leafing through contracts, product usage and Slack history before every call, time that wasn't going toward the one part of the job that's actually irreplaceable: the human conversation.

The unlock

## Fix the answer once, underneath every tool

Instead of hoping each agent tool arrived at the right number on its own, Birdie put a certified metric layer underneath the tools the team already used. Churn, escalation and commercial-attainment definitions now live in one place, so the same question returns the same answer no matter who asks or how they phrase it. That closed the gap between an AI-generated answer and one the team could act on without double-checking it first.

## What they built on it

A certified layer under every agent

- The same context and metric layer sits under Claude and other agent tools, so churn, escalation and commercial-attainment numbers come back consistent no matter who asks or how
- Closed the gap between an AI-generated answer and one the team could act on without double-checking it first

CS dashboards on Rig

- Churn reporting, escalations and commercial attainment now run through Rig dashboards directly, more flexible than HubSpot allowed
- The team drives execution gaps and commercial excellence off numbers everyone trusts by default, without re-litigating whether the number is right

On the roadmap

- A prioritised inbox reading signals across contracts, product usage and Slack messages to flag who most needs a call or a message next, dynamic as those signals change
- The goal: five minutes reading synthesised context before each call, then straight into the conversation, so admin stops eating into the only part of the job that's actually irreplaceable

## The impact

Trust in the numbers took time to build, but churn, escalations and commercial attainment now run on certified metrics everyone trusts by default, freeing up prep time for the calls that actually need a human on them.

> “The result is going to be consistent every single time, and now I can't imagine operating without it.”

JudyChief Customer Officer @ Birdie

## Want results like this?

[Book a demo](https://rig.so/book-demo)[See how Rig works](https://rig.so/walkthrough)

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