Churn prediction
for B2B companies
Churn doesn't announce itself in B2B. See the customers you're losing, before you lose them.
Turn invisible churn signals into a monday email to customer service.
Your B2B customers don’t cancel. They slowly drift.
Our churn prediction model – built upon your own customer data – spots the quiet shift in buying behaviour weeks before it shows up in revenue, and tells your sales team exactly who to call and why.
Results from our latest churn prediction project:
annual revenue at risk - identified in a 10-week test
analysed every week
covered by the model
A prioritised call list for each sales rep (could be any week day of course)
HOW THE IMPACT CHURN PREDICTION MODEL WORKS
1. We learn each customer’s rhythm from +25 signals
Some customers order daily, others weekly. Special categories. Specific roles making the orders. The model knows what “normal” looks like for each customer, so it reacts to deviations, not averages.
2. We spot the pattern
Each signal is small on its own. Almost invisible. Together they form a pattern the model recognises, much like AI recognises a face in a picture.
3. Your sales or CS team acts
Every week, at-risk customers are flagged in your CRM and sent to the responsible sales rep. The cost of a false alarm: one phone call. The cost of silence: a lost account.
Built on your own customers’ actual behaviour
- A churn definition built on your own customers’ actual buying cycles
- A model trained on your historical data
- A weekly at-risk list
- CRM integration so sales can log calls, outcomes and competitor wins
- Ongoing monitoring and model tuning
> Hear more about the churn prediction model
WHAT THE CHURN MODEL PICKS UP
- Shrinking volume: same products, smaller quantities.
- Broken rhythm: a customer who orders every third day starts ordering irregularly.
- Categories dropping out: one category quietly disappears while everything else looks normal.
- Relapse from new products: they tested your premium range, then went back to basics.
- Context: the same drop means something different for one type of customer than another.
Could also include: platform logins, service data (backorders, complaints, credit notes), payment behaviour and channel shifts + other relevant signals.
Blurry & invisible churn signals is A PROBLEM IN B2B
Revenue looks stable. Until it doesn’t.
In B2B, customers rarely say goodbye. They move their spend to a competitor one category at a time. By the time it shows in your revenue report, the decision was made weeks ago.
Your sales team can’t see it.
Account managers see relationships and revenue, not micro-patterns across hundreds of customers and thousands of order lines.
Classic churn models can’t either.
They’re built for subscriptions and cancellations, not for complex B2B customers who buy across many categories and many touchpoints.
DOES IT FIT YOUR COMPANY?
The churn prediction model works best if you:
- Sell B2B with frequent or recurring orders, monthly, weekly or more often
- Have transaction data at customer and order-line level
- Have a sales or customer service team that can act on the list
Not a fit for annual contracts or one-off project sales.
Want to know more about churn prediction in B2B?
Troels can tell you more and show you cases.
