Field notes · iDIG how-tos

The accounts missing from your depletion report

By the Sightglass team9 min read21 August 2026

A depletion report can only list accounts that bought something. When an account stops ordering altogether it doesn't appear as a zero — it stops appearing at all. No row to sort, no blank cell to notice, no flag to filter for. It was in last year's file and is nowhere in this one, and nothing in the report says so. The customers you are losing are, mathematically, the ones you cannot see in the standard report.

That is not a flaw in your reporting. It is what a transaction file is: a record of transactions. An account that transacts appears; an account that doesn't, doesn't. The gap becomes visible only when you hold this period's file up against a stack of earlier ones — the one piece of work that never reaches the top of a Monday.

Why the gap is invisible

Three things stack.

Volume. A single export runs to tens of thousands of rows — one line per account, per product, per period. One importer's monthly file that we worked through came to roughly 30,000 rows naming 13,109 accounts. That is not a document; it is a database wearing a spreadsheet's clothes. The honest ceiling of what anyone does with it on a Monday is: open it, wait for the filter dropdowns to populate, sort by cases descending, read the top forty, close it. Everything read that way bought recently and bought a lot. The accounts that took none are not in the file to scroll to.

Absence. Every other problem in your book is a value: a number that fell, a rank that moved, a margin that thinned. You can sort it, filter it, put a conditional format on it and let it find itself. A lapsed account is not a value. It is a missing key, and there is no column called 'stopped'. To see it you need a second list — the accounts you had before — and something that compares the two. No single export knows what last year's file said, so the information exists only across files: a different kind of work from reading one.

It is also why the largest losses are the quietest. An account that halves its order still files rows, and rows land in a variance column. An account that leaves files nothing at all.

Timing. Quarterly is too slow, and not for analytical reasons. Draft lines, cold-box doors and shelf facings are finite and get reallocated continuously; a handle that went to somebody else in March is not free again in June because you noticed in June. Winning space back means displacing whatever replaced you, and asking a buyer to reverse a decision they have already explained. On a quarterly cadence you hear about the last order one to three months after it landed — by which point the call has stopped being a save and become a fresh sell.

The comparison, in one line
Accounts in last period's file, minus accounts in this period's file, equals the list nobody has. Rank it by what those accounts used to take, and the top twenty rows are the next two weeks of somebody's work.

Do it by hand, once

You can build this in a spreadsheet, and the first build is an afternoon. Pull twelve months of depletions, one export per period, and keep every file. The archive is the whole trick: no single export reaches back far enough to show an absence, so whether this report exists in a year is decided by whether the folder starts today.

01Pull the export on the same day every period and save the raw file untouched, named by the period it covers — not a cleaned copy, not one with your pivot in it.
02Normalize the account key first. The same bar arrives as three different strings across three distributors: case, punctuation, entity suffixes, a trade name under one wholesaler and the license holder's legal name under another. Key on distributor plus account number — never the number alone, which is unique inside one distributor's system and nowhere else.
03Stack every period into one long table, stamping each block with the period you pulled it for — a date column inside the file may carry an order date, an invoice date or a ship date.
04Collapse to one row per account per period, cases summed across SKUs. Cases, not dollars: price changes, allowances and mix move the dollar figure for reasons unrelated to whether the account is still buying.
05Pivot it — accounts down, periods across, cases in the cells. Note which periods the archive actually covers, so a blank in a month you never exported is never read as a blank in a month you did.
06Flag on two tests: does the account have a history worth caring about — volume in most of the last twelve periods, above whatever floor makes a call worth a rep's morning — and are the two most recently completed periods both empty.
07Rank the flagged list by cases taken in the twelve months before the gap opened, not by lifetime volume, which flatters accounts that were big three years ago. That ranking is the call order.

Two traps sit in the middle of that; both manufacture ghosts.

Trap one: reporting lag. Depletion data runs a day or two behind, so the newest period is always still filling. Evaluate on completed periods only, and never call an account lost on one empty period. A six-week ordering cadence, a distributor cutoff on the wrong side of a month end, an order placed on the 2nd instead of the 30th — each looks like churn in one period and like nothing in two. Wait for two consecutive empty periods.
Trap two: seasonal SKUs. An account that only ever took an Oktoberfest or a summer cider goes quiet on schedule, every year, and nothing is wrong. The instinct is to drop them from the test, which hides the seasonal listing that genuinely failed to come back. Compare each to the same window a year earlier instead: a season that simply ended looks normal against last year, and one that never returned still shows up.

Refresh it monthly, a few days after the new export lands, right behind the archive pull. The file is monthly, so a weekly rebuild mostly re-reads the same numbers; the flagged list is what gets worked through the weeks that follow. The refresh takes about twenty minutes, nearly all of it on account keys you haven't seen.

What to do with the list

A list is not an outcome. The report is finished when a named person has a named account and a first sentence. Two hundred rows in a shared folder is the same as no report, and costs more.

01Split by ownership first. Every flagged account goes to the rep who holds it, and only to them. Leaders get the same list as a rollup — territory, distributor, brand — not as work.
02Cut each rep's slice to the top ten. Ten get closed out in a normal week alongside everything already booked. Sixty get read once, and the report is dead by week three.
03Read the distributor column before anyone drives. If every account behind one wholesaler went quiet in the same period, that is one phone call, not forty visits — and suspect the file first: wholesalers renumber accounts after a system change, and a re-keyed book looks like a walkout.
04Confirm the venue is still open — before the drive, not from the parking lot.
05Then work down in rank order: distributor first, account second.

The order of those last two matters. The distributor rep knows what your export cannot: whether the account is still open, whether the order simply stopped being placed, whether the buyer left in April. Turning up at a bar to ask why they stopped buying, when the answer is that the truck stopped coming, spends credibility you will want later.

Telling a lapsed account from a closed venue is mostly signals you already have, plus a few that are public record.

Same address, different name. A venue that disappears under one name and reappears at the same address under another has not churned — it changed hands. That is a first call on a new operator, a different conversation entirely.
The operator's other locations. If a group's other sites are still ordering, this is a switch or a single-site decision, not a closure — and whoever made it is reachable.
The license register. Retail licenses are public record, and one that has lapsed, been surrendered or transferred is about as close to an authoritative answer as you get. What is published, and how current it is, varies state to state.
The obvious checks. A disconnected number, a listing marked permanently closed, a page that stopped posting a year ago — two minutes each, and together they take a real share of the list off the drive plan.
The first sentence
Open with the number, not the concern. Something like: you were taking about five cases a month for eleven months, and nothing in the last two reporting periods — did something change? It is checkable, it is not an accusation, and it gives the buyer an easy factual answer: the manager left, the tap went elsewhere, the delivery stopped turning up. What a supplier may and may not do about it varies state to state — a question for your compliance people, not for a report.

What one importer's data showed

We ran this comparison across more than a year of one importer's own depletion exports — their data, our analysis. None of it had surfaced in their monthly reporting, and nothing was wrong with that reporting: it was doing what a transaction file does.

13,109
accounts listed in a single export
5,085
accounts absent from it that had ordered the prior year
80,932
cases those absent accounts took the prior year

Read the middle number carefully: it is not 5,085 lost customers. A book that size accumulates venues that closed, venues that changed hands, one-time buys, and accounts a distributor re-keyed. The honest statement is narrower and still large — five thousand accounts that ordered in the prior year did not appear in this file, and 80,932 cases sat behind them. Nobody could say which share was dead weight, because nobody had the list.

The other half of the finding is about accounts still in the file — sliding rather than gone.

630
accounts quietly sliding — 4.8% of the book
113
of 242 distributors with no sale in 90+ days

The 630 are the reachable ones: still filing rows, still taking deliveries — and roughly one account in twenty was carrying essentially the whole annual decline. The distributor figure is a different warning. Not every quiet wholesaler is a problem — plenty are dormant by design. But a quiet distributor takes every account behind it dark at once, which is why that column is worth reading before anybody works the account list.

Nobody at the company knew any of this, and not because anyone had been careless. The data was correct and sitting in files they already owned. What was missing was an afternoon to line a year of them up next to each other, in a quarter that had no spare afternoon in it.

Or have it done every night

That is the weakness of the manual version. The build is genuinely an afternoon. What it doesn't survive is a quarter with a price increase, a distributor transition and a national account review in it. A month gets skipped, then another; the keys go stale, the history test starts failing quietly, and the sheet goes on producing a number nobody quite trusts.

Sightglass reads the VIP depletion feed you already pay for, every night, and keeps every snapshot, so history accumulates well past any single export's window. It watches for the gaps, allows for the reporting lag, and hands each rep a short ranked list of their own accounts — the reason in plain numbers, the outreach already drafted in your house voice, one to the account and one to the distributor. Nothing sends until a person approves it, and approved mail goes from the rep's own mailbox, so replies come back to them. It arrives in Slack, in an email digest, or in the dashboard.

Leaders get the same data as conclusions rather than a grid — lapsed accounts, distributors gone quiet, concentration, territory by territory — every figure traceable to the file it came from. When the data is too thin to support a conclusion, it stays quiet rather than inventing one. Your VIP subscription and your existing reporting stay where they are.

Want to see it on your book? Twenty minutes, screen shared. No file required. Book a 1-1 demo