Use case · ecommerce brands
Revenue was up 12% and nobody in the room could say why. Shopify knows what sold, Klaviyo knows what the email list did, Meta knows what was spent, and the answer only exists once someone puts all three next to each other, which is a job that gets skipped in a busy week.
Rather than rebuild the spreadsheet every Monday, the team handed over the join. The droid reads all three systems, splits growth into the part that was paid for and the part that came back on its own, and posts it before anyone sits down.
Started as a much longer report. Got cut down after two weeks because nobody read past the first screen.
Every Monday trips the same loop:
Four weeks of Mondays. Three of them were unremarkable, which is the point — the fourth is the one that mattered.
Revenue up 4%, split roughly as usual between new and returning. Nothing worth flagging, so it said so in two lines.
Repeat rate down for a second week. Noted it without flagging, since two weeks is still noise.
Third week down and blended CAC up 24%. Flagged both together: revenue grew, but all of the growth was bought.
Winback flow relaunched off the back of the flag. Repeat rate turned before spend had to rise again.
We'd have called that a good month. It was a good month we paid for, and the repeat rate had been sliding since April.
An illustrative workflow built from real product mechanics. The connected apps, the weekly schedule and the metric split are how a droid actually runs; the brand, the quote and the figures are composites rather than a customer's numbers.
Copy the brief below and paste it into Unify. It’ll walk you through the prerequisites, connect what it needs, and stand the workflow up with you.
We're a DTC brand and we run a trading meeting every Monday. Connect Shopify, Klaviyo and Meta Ads. Schedule a task for Monday at 07:00. On each run, pull the last twelve weeks of orders, revenue, new versus returning customer revenue and repeat purchase rate from Shopify, campaign and flow revenue from Klaviyo, and ad spend with blended CAC from Meta. Report last week against the four-week average and against the same week last year where we have it. Split new-customer revenue from returning-customer revenue every time and say which one moved. Flag it if repeat rate has fallen three weeks running, if blended CAC has risen more than 20% against the four-week average, or if flow revenue drops while list size grows. Post the write-up to #trading in Slack with a dashboard link, and keep the tone short — we read it on a phone.
Tell us the job that never gets done before close. We'll wire it up on a call and you can watch it work.
