Measure receivables turnover by counterparty
You changed the payment terms, but nobody checked whether customers actually pay faster. The agent shows average payment days by month and by client.
Medium · 20 min · once a month
What you get
a table in the reply · once a month
Average days to payment Jan 48 Feb 44 Mar 39 Apr 41 By customer: Romashka LLC 62 days, was 71 Supplier A 28 days, unchanged Counted on revenue excluding VAT, prepayments ignored. Four customers have fewer than three shipments — their figures are shaky, don't build conclusions on them.
A sample on made-up data — your numbers will be your own.
Who it fits
- You need to show the bank or the board whether customer settlements sped up or slowed down.
- You changed the deferral terms and want to see it reflected in actual payment days.
When it won't work
You want a list of debtors to call — this is a metric and its trend, not a collections plan.
How the agent does it
Agree on the formula
Say whether you count payment days on revenue with or without VAT and whether prepayments are included. Different formulas give different numbers.
Run the calculation
The agent takes shipments, payments and outstanding balances from 1C, measures the days on monthly snapshots and writes the trend into a spreadsheet.
Check the outliers
The number is easy to improve by accident, with one large shipment at period end. Ask for the figures with and without it and see if the story holds.
What you set
You'll need 1C and Google Sheets. From you: the period, the granularity and the formula — revenue with or without VAT, prepayments in or out.
What you'll need
Starter prompt
Copy the prompt or open it straight in a chat with the agent.
Calculate receivables turnover for [period] broken down by [months / quarters] using 1C data. Give company-wide figures: turnover in times, average days sales outstanding, average receivables for the period. Then the same metrics per customer and by groups [wholesale / retail / chains]. Calculate the average balance from monthly snapshots, not from the start and end of the period. If a customer has fewer than [three] shipments in the period, don't average their payment days — mark it "not enough data". Don't explain a change in the metric by seasonality or sales growth until you show the figures that confirm it. Output a Google Sheets table: company-wide dynamics, the customer breakdown, and a "not enough data" column.
Open in chatReview the turnover calculation. List: — customers whose metric was calculated on fewer than [three] shipments; — months where the average balance was taken from two points instead of snapshots; — the effect of large one-off shipments and prepayments on the final figure — show the numbers with and without them; — bad and disputed debts that push the average days up and turnover down; — which conclusions about the trend are backed by data and which are your interpretation. State the formula you used explicitly.
A second prompt — the agent uses it to review its own work and show what's left for you.