Why online shops look at ai reporting.
Shop owners open four dashboards every morning and still don't know their margin, because ad spend lives in one place, orders in another and returns in a third.
Problems such as a best-seller about to sell out or a campaign that stopped converting are noticed days late.
What the agent does, step by step.
Runs after midnight on yesterday's data.
Orders, refunds, payouts, ad spend and stock levels.
Contribution margin after product cost, shipping, fees and ads, by your definitions.
Low stock on fast sellers, conversion drops, refund spikes.
What changed versus last week, in a few sentences.
Systems it works with.
Product costs come from your own data; if they don't exist yet, we set up a simple sheet for them.
Where a human decides.
Numbers you act on must be traceable.
How you know it works.
Measure: time spent on daily reporting, and how quickly stock-outs and campaign problems are noticed.
Example with assumed numbers: an owner spends 30 minutes every morning collecting numbers, about 15 hours a month. A daily report removes most of that, and a single avoided stock-out on a best-seller may be worth more than the time.
The example uses assumed numbers to show the method. It is not a client result or a promise.
What it costs.
All prices excl. VAT. The fixed quote comes from the AI Blueprint.
When this is not the right build.
If your shop runs on one platform with built-in reporting you already read daily, add only the alerts, not a full report.
Common questions.
Can it include marketplace sales (e.g. Bol or Amazon)?
If the marketplace offers API or report access for your account, yes.
Can I ask follow-up questions?
Yes, optionally, in Slack or WhatsApp, answered from the same data.
Want this in your business?
Tell us how you work today. We'll tell you honestly what AI can take off your team's plate, what it costs, and whether we are the right fit.