AI dashboard · e-commerce
CMO dashboard, built by AI on your Data Model
Net sales, profit, ad spend, new customers and CAC for an online store, on one board view. Claude built it through OWOX MCP, and every number comes from a governed Data Mart, not from the AI's guess.
Four questions, one Data Model
Every view answers one question a marketing or sales lead asks. Between them they read seven of the twelve Data Marts in the e-commerce Data Model below, and each view names the ones it uses, so you can open the definition behind any number.
Summary
Is marketing paying for itself?
Opens with what the numbers mean: whether marketing makes money, how last month compared, which platforms lose money and where the opportunity is. Then net sales and profit against ad spend from all seven platforms, month by month, with net sales per $1 of ads and ad spend per new customer.
PurchasesOrdersUnified Ad SpendCustomersCustomer acquisition cost
Channels
Which platforms make money, and which lose it?
Net sales by channel group, then every ad platform's spend against the net sales and profit the store recorded from its visits, what is left after ad spend, and what each platform claims per $1 beside it. Then ad spend and its return against the budget plan, and a Scale, Hold or Cut call on each platform from a rule printed on the page.
Customers
Are we winning new customers?
New customer accounts each month and revenue by segment. The view says plainly why CAC by channel is left out: in this demo, most accounts carry no acquisition source.
The metrics on this dashboard
Each one is defined once in the Data Model and read the same way in every view. Follow a chip for what the metric means and how to calculate it.
Net salesNet profitAd spendCustomer acquisition costReturn on ad spendNew customers
An AI dashboard is only as true as what it reads
Most AI dashboards start from an exported file. That works until the second export.
On a CSV
The AI guesses what revenue means, every time
Each export is its own version of the truth, so two dashboards give two numbers. The file goes to whoever has it, and it is out of date the moment it is saved.
Which one goes to the board?
On your Data Model
Spend and revenue meet on one channel name
Ad spend, sessions and orders share the source, medium and campaign defined once in Traffic Sources, so cost sits next to the revenue it bought instead of in a separate report.
One definition, every view.
Connecting the AI straight to the warehouse is not enough either. A warehouse rarely holds the business context, so the AI still guesses what the numbers mean. The Data Model is where that context lives.
From your warehouse to a dashboard in five steps
Your analyst does step two once. After that, anyone with access asks their AI for the dashboard they need.
- 01Your warehouseBigQuerySnowflakeDatabricksRedshiftAthenaYour data stays where it is. OWOX runs on it and keeps no copy.
- 02Data ModelData MartsjoinsmetricsYour analyst defines once what net sales, an order and a channel mean.
- 03OWOX MCP and APIgovernedpermissionsThe only door the AI gets: the Data Marts it may read, nothing raw.
- 04Claude or ChatGPTyour own AIAsk for the dashboard in plain words. It builds it on the Data Model.
- 05AI dashboardReportevery runKept as a Report, refreshed every time it runs, like Sheets or Excel.
Build this on your own data
Connect your warehouse, describe your business once, and let your AI build the dashboards your team asks for.