A converter’s worst revenue news rarely arrives as news. There’s no cancelled contract, no angry email, no lost bid to do a post-mortem on. There’s just an account that ordered folding cartons every nine weeks for three years — and at some point, quietly, didn’t anymore.
For most converters, the bulk of revenue is repeat business. That’s the strength of the model: plates are made, dielines approved, specs settled, trust built. But it produces a blind spot that bites hard: when revenue mostly arrives on its own, nobody builds the muscle of noticing when it stops arriving.
Why lapse is invisible week to week
Imagine an account that orders roughly every 8 weeks. One cycle it’s 10 weeks — a normal wobble; inventory runs long, a promotion slipped. The next gap is 12. Then 15. At no single moment did anything happen. Every individual week, the account looked fine. That’s what makes reorder leakage different from every other kind of loss: it has no event. A lost quote has a date. A complaint has an email. A lapsing account is pure absence, and absence doesn’t show up in anyone’s inbox.
The usual detection mechanism is the annual revenue review, which finds the problem 6 to 12 months after it started — when the account has a new supplier, new plates somewhere else, and a switching cost working against you instead of for you.
What actually pulls accounts away
It’s tempting to assume lapsed accounts left for price. Talk to enough of them and a different list emerges:
- A person changed. The buyer who knew your CSR by name retired or moved on. The replacement inherited a vendor list, not a relationship — and a competitor called them during their first month.
- A stumble you never heard about. A late delivery, a color complaint handled at the plant level, a quality wobble. Small enough that nobody escalated; big enough that the buyer started splitting orders.
- Convenience drift. A competitor offering slightly faster turnaround or an easier ordering process started getting the rush jobs. Then the regular jobs followed the habit.
- The customer’s own business shifted. A product line discontinued, volumes moved between plants, a new co-packer entered. Your account didn’t reject you; their map changed.
Notice what these have in common: every one of them is discussable — if you find out in time. A check-in call at week 11 of a stretched gap surfaces the new buyer, the unspoken complaint, the competitor sampling. The same call at month 9 is a eulogy.
The order-gap audit: one afternoon, real numbers
You don’t need software to find out how exposed you are. You need your order history and a spreadsheet. Here’s the procedure:
- Export 24 months of orders — account, order date, order value. From most ERPs or invoicing systems this is one report.
- For each account, compute the gaps between consecutive orders, in weeks. A pivot table or a sorted sheet gets you there.
- Write down each account’s typical gap — the median, not the average, so one weird summer doesn’t skew it.
- Flag every account whose current gap (weeks since last order, as of today) exceeds 1.5× its typical gap. That multiplier is a starting point: tight enough to catch drift, loose enough to skip normal wobble.
- Sum the trailing-12-month revenue of the flagged accounts. That figure is your revenue currently in the lapse zone.
Run honestly, this audit produces two things. First, the number — for many converters, the flagged list is uncomfortably long, precisely because nobody has ever looked at order gaps account by account. Second, a worked call list: every flagged account is a specific conversation a CSR could have this week.
To be clear about what the flag means: an account at 1.5× its cycle isn’t lost. Many have boring explanations — inventory, seasonality, a delayed product launch. The point of the flag isn’t prediction; it’s that someone should find out which kind of quiet this is. The cost of checking is a phone call. The cost of not checking is occasionally an account.
Why CSR memory can’t be the system
The standard objection: “Our CSRs know our customers — they’d notice.” For the top accounts, true. But run the math on attention. A converter with 300 active accounts and four CSRs is asking each person to hold 75 order rhythms in mind, while their actual job — order entry, art approvals, press scheduling, freight problems — interrupts them every few minutes. The top 20 accounts get noticed. The middle 200, where a large share of lapse-risk revenue usually sits, do not. This isn’t a CSR quality problem; it’s a job description problem. Humans are excellent at the conversation and terrible at the watching. Software is the reverse. The division of labor writes itself: a system watches every account’s cycle and produces a short, ranked list; the CSR who knows the customer makes the call.
What to do about it
If the audit above flagged real revenue, three moves, in order of effort:
This week: have CSRs call the top ten flagged accounts by revenue. No script needed beyond honesty: “You usually run these about now — wanted to check whether we should hold press time.” Tally what comes back: ordering soon, fixable problem, or gone. That tally is your first real attrition data.
This month: make the audit repeatable. Same spreadsheet, refreshed monthly, twenty minutes once the formulas exist. Put the flagged list on the agenda of one standing meeting.
When the manual version creaks: the monthly refresh depends on someone doing it during busy season — the exact time accounts drift. That’s the point of installing it as a permanent early-warning layer on the CRM your team already works in: per-account thresholds, a board sorted by revenue at risk, and drafted check-ins a CSR approves instead of composes. The mechanics stop depending on the calendar and the leak stays closed.
Either way, start with the export. Converters are sitting on the one dataset that predicts their quietest losses — two years of order dates — and most have never sorted it by gap.