--- title: "Net Sales Review: an AI Dashboard on Your Data Model | OWOX" canonical: "https://www.owox.com/marketing-dashboards/net-sales-review" updated: "2026-10-22" --- AI dashboard · e-commerce # Net Sales Review, Built by AI on Your Data Model Net sales, profit, channels, customers, products and conversion for an online store. Claude built it through OWOX MCP, and every number comes from a governed Data Mart, not from the AI's guess. 9 Data Marts · Built by Claude via OWOX MCP · Refreshed every Report run · [E-commerce data model](/data-models/e-commerce) ## The dashboard ## What each view answers ## Eight questions, one [Data Model](/data-models/e-commerce) Every view answers one question a sales, marketing or operations lead actually asks. All of them read the same twelve Data Marts of the e-commerce Data Model below, and each view names the ones it uses, so you can open the definition behind any number. ![The E-commerce data model: 12 Data Marts and how they join](https://cdn.owox.com/www/portfolio-management-data-model/e-commerce/diagram/10.svg/w=1600,fit=scale-down,format=auto) [E-commerce data model · 12 Data Marts · 15 relationships · open it →](/data-models/e-commerce) Summary ### How is the year going? Net sales, profit, orders, sessions and conversion against the same dates last year, with each month's net sales next to its gross booked value, so cancelled and returned orders stay visible instead of quietly inflating the total. [Purchases](/data-models/e-commerce#mart-purchases) [Orders](/data-models/e-commerce#mart-orders) [Sessions](/data-models/e-commerce#mart-sessions) [Conversion rate](/marketing-metrics/ecommerce-conversion-rate) [Sessions](/marketing-metrics/website-sessions) Forecast ### Where will the year land? Cumulative net sales day by day against last year, and where the year closes at this pace. The demo store has no plan in its Data Model, so the page compares with last year and says so rather than inventing a target. [Purchases](/data-models/e-commerce#mart-purchases) [Orders](/data-models/e-commerce#mart-orders) Top 5 ### What moved net sales most? The five biggest moves across channel, customer segment, category and country. Each cut splits the same revenue, so the moves overlap; the page tells you that instead of letting them look additive. [Traffic Sources](/data-models/e-commerce#mart-traffic-sources) [Customers](/data-models/e-commerce#mart-customers) [Product Category](/data-models/e-commerce#mart-product-category) [Countries](/data-models/e-commerce#mart-countries) Acquisition ### Do the ad platforms tell the truth? Net sales by channel, then each platform's spend against the revenue the store itself recorded, next to what the platform claims. Facebook claims 1,091 conversions; the store recorded 720 orders from it. [Unified Ad Spend](/data-models/e-commerce#mart-unified-ad-spend) [Sessions](/data-models/e-commerce#mart-sessions) [Traffic Sources](/data-models/e-commerce#mart-traffic-sources) [ROAS](/marketing-metrics/return-on-ad-spend) [Facebook ROAS](/marketing-metrics/facebook-roas) [Conversion value](/marketing-metrics/conversion-value) Customers ### Who buys, and where? Net sales by customer segment and by market. Segment and geography are each defined once in the Data Model, so every view cuts revenue the same way. [Customers](/data-models/e-commerce#mart-customers) [Countries](/data-models/e-commerce#mart-countries) [Orders](/data-models/e-commerce#mart-orders) Products ### Which categories earn their keep? Margin by category against the target margin each one is managed to, and the products that carry the year. Cost of goods sits in the Data Model, so profit is a field, not an estimate. [Products](/data-models/e-commerce#mart-products) [Product Category](/data-models/e-commerce#mart-product-category) [Purchases](/data-models/e-commerce#mart-purchases) Conversion ### Why did net sales move? A bridge that splits the change into more sessions, a lower conversion rate and order value, then conversion by traffic type and device. [Sessions](/data-models/e-commerce#mart-sessions) [Orders](/data-models/e-commerce#mart-orders) [Conversion rate](/marketing-metrics/ecommerce-conversion-rate) [Average order value](/marketing-metrics/average-order-value) Data ### Can I trust these numbers? The Data Model behind the page, how its Data Marts join, when the source tables last changed, and the checks that reconcile: segment revenue adds up to the total, and orders agree across Data Marts. [Purchases](/data-models/e-commerce#mart-purchases) [Orders](/data-models/e-commerce#mart-orders) [Sessions](/data-models/e-commerce#mart-sessions) ## Metrics ## 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 sales · Net profit · [Conversion rate](/marketing-metrics/ecommerce-conversion-rate)[Average order value](/marketing-metrics/average-order-value)[Sessions](/marketing-metrics/website-sessions)[Return on ad spend](/marketing-metrics/return-on-ad-spend)[Facebook ROAS](/marketing-metrics/facebook-roas)[Conversion value](/marketing-metrics/conversion-value) ## Connected, not a snapshot ## 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. ![Two exported files showing 29 and 32 orders for the same days](https://cdn.owox.com/www/content-marketing-dashboard/net-sales-review/body-vector/1-7by02w.svg/public) Which one goes to the board? On your Data Model ### Net sales is one field, defined once by your analyst Every view reads the same Data Marts, so the numbers agree across tabs and tools. Data Marts and Contexts decide who sees what, and the dashboard is a Report, refreshed every time it runs. ![Purchases in the e-commerce Data Model, joined through Orders to Sessions and Customers](https://cdn.owox.com/www/portfolio-management-data-model/e-commerce/diagram/10.svg/w=1600,fit=scale-down,format=auto#mart-purchases) 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. ## How it is built ## 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. 1. 01 · Your warehouse · BigQuery · Snowflake · Databricks · Redshift · Athena · Your data stays where it is. OWOX runs on it and keeps no copy. 2. 02 · Data Model · Data Marts · joins · metrics · Your analyst defines once what net sales, an order and a channel mean. 3. 03 · OWOX MCP and API · governed · permissions · The only door the AI gets: the Data Marts it may read, nothing raw. 4. 04 · Claude or ChatGPT · your own AI · Ask for the dashboard in plain words. It builds it on the Data Model. 5. 05 · AI dashboard · Report · every run · Kept as a Report, refreshed every time it runs, like Sheets or Excel. ## Build yours ## Build this on your own data Connect your warehouse, describe your business once, and let your AI build the dashboards your team asks for. [Get Started Free](https://www.owox.com/app-signup) · or [book a demo](https://calendly.com/team-owox-bi/demo-call) ## Book a call You are booked. The invitation is on its way to , with the calendar invite and the meeting link. [Reschedule](#) [Cancel](#) ## Links Pages this page links to, on this site and on docs.owox.com. Where the page has a Markdown twin, its address follows the link. - [E-commerce data model](https://www.owox.com/data-models/e-commerce) — /data-models/e-commerce.md - [Conversion rate](https://www.owox.com/marketing-metrics/ecommerce-conversion-rate) — /marketing-metrics/ecommerce-conversion-rate.md - [Sessions](https://www.owox.com/marketing-metrics/website-sessions) — /marketing-metrics/website-sessions.md - [ROAS](https://www.owox.com/marketing-metrics/return-on-ad-spend) — /marketing-metrics/return-on-ad-spend.md - [Facebook ROAS](https://www.owox.com/marketing-metrics/facebook-roas) — /marketing-metrics/facebook-roas.md - [Conversion value](https://www.owox.com/marketing-metrics/conversion-value) — /marketing-metrics/conversion-value.md - [Average order value](https://www.owox.com/marketing-metrics/average-order-value) — /marketing-metrics/average-order-value.md - [Get Started Free](https://www.owox.com/app-signup)