SERVICE

Customers rarely leave without a signal. You just need to measure them.

Most B2B companies only discover churn when the cancellation notice lands in their inbox. We build an early-warning set on login activity, sentiment, payments and executive contact, with playbooks per risk level and a save-flow for when it really matters. Works in HubSpot, connects to your CS engine.

Book a churn conversation Take the Maturity Scan first

What you get

01
Early-warning signals Configured in HubSpot at account level
02
Intervention playbooks Per signal category, with escalation path
03
Save-flow and win-back For customers actively cancelling, plus recently lost accounts

The observation

Churn is usually discovered too late, not in time.

B2B churn of 15 to 25 per cent per year is not unusual in the mid-market. Customers rarely leave out of nowhere: login frequency drops, NPS shifts, executive contact disappears. But none of those signals show up in a central report. We bring them together at account level, with a playbook attached, and wire them into your broader customer success programme so that green, amber and red each get their own route.

Signals sit in four silos

Product knows the login data, support knows the ticket tone, finance knows the payment behaviour, sales knows the executive contact. Nobody knows everything, so nobody sees it coming.

Cancellation as a surprise

The email arrives and only then does the rescue begin. The decision was made weeks ago, often already communicated internally. Save rates rarely reach 10 per cent.

No save-flow in place

Every account manager improvises their own rescue attempt. No escalation to a manager, no alternative offer on the table, no learning loop for next time.

Win-back untapped

Lost customers are never approached again. Some would have come back, others had a useful reason to share. Neither happens.

Approach

Four phases to a retention discipline, then a monthly cycle.

We set up signal detection, playbooks and the save-flow in eight weeks. After that the monthly cadence runs, learning from every churn that occurred or was prevented, embedded in your broader service engine.

01 Phase 01

Churn analysis

Which customers left in the past 12 months, why, and when in hindsight was the first signal traceable. Root-cause patterns per segment on the table.

Wat je krijgt Churn analysis report, segment patterns and cost per lost customer

02 Phase 02

Signal architecture

Which signals to measure and how to weight them: login data, ticket sentiment, NPS trend, payment behaviour, executive contact. Combined in HubSpot into a risk score at account level.

Wat je krijgt Signal set, weighting and risk score property in HubSpot

03 Phase 03

Playbooks and save-flow

A playbook per risk level. Amber gets a CS check-in, red goes to manager escalation, a cancellation triggers the save-flow with an alternative offer and a learning loop afterwards.

Wat je krijgt Playbook set, save-flow workflow and escalation route

04 Phase 04

Win-back and reporting

Win-back campaign for customers lost in the past six months. Churn dashboard live with root-cause themes, save rate and win-back rate. Monthly cadence defined, owner assigned.

Wat je krijgt Win-back campaign, churn dashboard and monthly owner

Who builds it

Two people on the engagement.

You work with Kim and Carsten from phase 1. Kim designs the discipline and the playbooks, Carsten builds detection and workflows in HubSpot. No junior executing on behalf of someone you have never met.

Kim Loonen

Consultant & online marketeer

Runs the churn analysis, designs playbooks and the save-flow together with your CS team. Stays involved in the monthly cycle to keep things sharp.
Carsten Huiskamp

Consultant & online marketeer

Builds signal tracking, the risk score property and the save-flow and win-back workflows in HubSpot. Sets up the churn dashboard for leadership meetings.

Case · B2B mid-market

From cancellation as a surprise to a save rate of 8 to 22% with manager escalation

A professional services organisation only discovered cancellations when the email arrived. No save-flow, every account manager improvised their own rescue attempt, save rates stayed below 10 per cent. Lost customers were never approached again.

In eight weeks we set up the signal set (login, sentiment, payments, executive contact) and routed every cancellation to the manager with three alternative offers on the table: a smaller subscription, a pause or a project arrangement. Save rate went from 8 to 22 per cent within two quarters. Win-back cohort set up for customers from six to twelve months ago, with a layer of customer support automation to keep low-risk queries out of the CS team.

What clients usually ask.

Honest answers to questions we hear before every churn prevention engagement.

How early should you start with churn prevention?

From day 1 of the customer relationship. Onboarding determines 80% of retention. Waiting until a customer appears to want to leave is usually too late: by that point the decision has already been made, you just have not noticed it yet.

Which signals predict churn best?

It varies by business model. In SaaS: declining login frequency and feature adoption. In services: loss of wallet share and delayed invoice acceptance. In both: an NPS shift, an irritated tone in tickets, executive contact that disappears. We always build a custom signal set.

How long does the engagement take?

Eight weeks for setting up the signal set, playbooks and save-flow. The win-back campaign runs in parallel or afterwards. Then a monthly cadence. First real save rate data after one quarter.

What does it cost?

Custom per situation. Scope depends on signal complexity, existing data and whether we build a save-flow and win-back flow straight away. Many clients fit this into a RevOps-as-a-Service retainer where strategy and execution come together. Book a conversation and we will put together a quote for your situation.

Can we do this in-house?

The churn analysis and signal set can be built together with us. The monthly discipline after go-live is often taken over internally by a CS lead. Our value is in the initial setup and in making sure the loop keeps running when day-to-day pressures take over.

Does this work for non-SaaS businesses too?

Yes, you just measure churn differently. For product companies you look at the repeat-purchase window. For service contracts you look at wallet-share loss per customer. The discipline and the signal architecture are the same, the measurement points differ. The risk score also becomes input for your forecasting and pipeline management towards renewal cycles.

What if our data is not in order?

Go ahead, but start with the two or three signals that are reliable. A simple risk score that works is better than a complete one that takes three months to get running. We often build in parallel with CRM architecture when the data layer is too far away.

How does this connect to customer success?

Directly. Churn prevention sits in the red-zone half of your CS engine. Many clients do both at the same time: the health score for green and amber, the churn flow for red. Combining is logical, separate is fine too.

Ready to start?

Ready to see churn coming, not after the fact?

Book a conversation. We look at your current churn rate, the signals you already have and what you are missing. After that you get an honest scope and direction.