The customer who used to order every fortnight
A trade customer has ordered from you every couple of weeks for years. At some point the orders thin out. Then they stop. Nobody notices, because nothing happened: there was no complaint, no cancelled contract, no angry email. Months later, someone reviewing sales asks what happened to them. By then they have been buying from a competitor long enough for it to be a habit.
Often a phone call at the first sign of change would have found a simple reason: a new buyer who did not know you, a delivery problem nobody mentioned, a competitor offering a better price on one item.
Why lapsing is invisible
Businesses are set up to notice events, and a customer stopping is the absence of an event. Sales reports show totals, which hide one customer's decline behind another's growth. Account managers have too many customers to track each one's rhythm in their heads. And the CRM, if you use one, is usually focused on new deals rather than repeat orders.
What makes it tricky is that every customer has a different normal. A customer who orders monthly and is a week late is not the same as a customer who orders weekly and has missed three.
What quiet lapses cost
- Revenue from existing customers, which is usually cheaper to keep than new revenue is to win.
- The chance to fix a problem the customer never raised.
- Insight into competitors, since a lost customer often knows exactly who is undercutting you and on what.
- Accurate forecasting, because you are counting on revenue that has already gone.
How we spot customers who are drifting
- Read order or invoice history from your ecommerce platform, ERP, order system or accounting software such as Xero or QuickBooks, through their APIs.
- Learn each customer's pattern: typical gap between orders, typical order value, and the product ranges they buy.
- Flag changes: overdue relative to their own rhythm, order value shrinking, or a product range they used to buy that has stopped, which often means that line has gone to a competitor.
- Rank and explain: a weekly list for each account owner, most important first, with the reason in plain words, such as 'normally orders every 14 days, last order 38 days ago'.
- Suggest the approach: the last few orders, any recent support tickets or complaints, and open invoices, so the call is informed.
- Record the outcome: the account owner notes what they found, which builds a picture of why customers drift and whether calling helped.
| Signal | Often means |
|---|---|
| Longer gaps between orders | Buying elsewhere some of the time |
| Smaller orders | Splitting business with a competitor |
| One product range stopped | A competitor won that line |
| Orders stopped entirely | A bigger change: new buyer, problem, or closure |
We start with clear rules based on each customer's own history. A machine learning model can be added later if you have the volume for it, but for many businesses the simple version does the job.
What your account managers get
A short, prioritised list each week, instead of either nothing or a spreadsheet of every customer. Calls happen while the relationship is still warm and the problem is still small. And over time, the recorded reasons tell you which issues cause customers to drift, so you can fix them for everyone.
Sales reviews change too. Instead of looking only at this month's total against last month's, you can look at how many established customers are ordering normally, how many are drifting and how many have come back after a call. That is a much more useful conversation about the health of the customer base than a single revenue figure.
The same data also works in the other direction. Customers whose orders are growing, or who have started buying a new product range, are worth a call too, for a different reason.
Could customers be slipping away unnoticed?
- You have found out months later that a regular customer stopped ordering.
- Sales reports show totals but not changes in individual accounts.
- Account managers rely on memory to know when customers usually order.
- Nobody asks lapsed customers why they left.