Whether delivering faster brings customers back

Your dashboard now answers the question the subscription argues for. Of the customers who had work delivered in the previous period, it shows the share who started something new in this one — cut by how fast their work was delivered, and by where they are.

Every bucket carries its count

A rate on its own hides its own sample. A bucket of three customers is an anecdote and reads identically to a bucket of thirty, so every bucket shows how many customers are in it and how many of them came back. Nothing is suppressed for being small, and there is no “other” bucket to be merged into.

Both cuts count off the same list of customers, so the speed buckets and the region buckets add up to the same population and the same number of returners. If they ever disagreed, one of them would be wrong — here they cannot.

How delivery speed is measured

Each customer is placed by their median delivery time across the work delivered to them in the previous period — not their average, so one unusually long job does not drag a customer into a slower bucket than the rest of their work deserves.

Delivery time runs from the day the lead was sourced to the day the work reached delivered, counted as whole calendar days in your own time zone. The four buckets are 14 days or fewer, 15 to 30, 31 to 60, and over 60. The median is used exactly as calculated: a customer at 14 and a half days sits in the 15-to-30 bucket, because nothing is rounded before the bucketing.

How regions are worked out

Customers are grouped by the country recorded on the engagement itself, not the one on their profile today. A customer who moves country stays counted where they were at the time, so a period you have already read never changes underneath you. Where a customer had several engagements delivered in the period, their most recent one places them.

Countries map to regions through your own region list. Where no country was recorded, or where a country belongs to no region you have set up, the customer appears in an unknown-region bucket that is always shown — never folded into a named region, never assigned to yours, and never dropped. It is both a retention figure and a data-quality one: a large unknown bucket is telling you something.

A rolling twelve months alongside

A trailing twelve-month figure sits beside the headline with its own customers and its own returners, so a quiet quarter has a longer view next to it. When the period you are looking at is already the last twelve months, it is not shown twice.

Opening any of it

Every bucket opens to the customers in it — the ones who came back and the ones who did not — adding up to exactly the counts on the row. Where the previous period had no customers at all, no rate and no change is shown: a change from nothing is not a percentage, and the surface says what it is waiting for rather than showing a zero that looks like a result.

Where the period you are looking at is still running, it says so, and says that it is being compared against a period that has finished.