Power BI Dashboard for Ecommerce

An ecommerce business generates data in a dozen places at once: orders in the storefront, settlements in the payment processor, spend in each ad platform, and costs in a spreadsheet someone updates monthly. A Power BI dashboard for ecommerce pulls these together into a single governed view so you can see real revenue, real margin and real customer acquisition cost without exporting four CSVs and reconciling them by hand. Done well, it replaces gut feel with numbers your whole team trusts.

This guide covers the KPIs that earn their place on the page, how to connect Shopify, Stripe and the ad platforms, and a template approach that keeps the build maintainable as you grow.

The KPIs that matter for ecommerce

Resist the temptation to put everything on one canvas. A focused ecommerce dashboard answers a handful of questions clearly.

• Revenue and orders: gross revenue, net revenue after refunds, order count and average order value (AOV), trended daily and month-on-month.
• Margin: contribution margin after cost of goods sold, shipping and payment fees. This is the number most storefront analytics hide.
• Customer acquisition cost (CAC): blended and by channel, calculated as ad spend divided by new customers acquired.
• Return on ad spend (ROAS): revenue attributable to spend, by platform and campaign.
• Retention and repeat rate: percentage of customers placing a second order, and customer lifetime value (LTV) cohorts.
• Conversion and funnel: sessions to add-to-cart to checkout to purchase, where the platform exposes it.

The discipline is pairing revenue with cost. AOV rising while CAC rises faster is a problem a revenue-only dashboard will never surface.

Connecting Shopify, Stripe and the ad platforms

Power BI can reach ecommerce sources through native connectors, certified third-party connectors and APIs, but the right architecture depends on how blended your metrics need to be.

Direct connectors are tempting for a quick start, but the moment you need CAC (ad spend from one system divided by new customers from another) or contribution margin (revenue minus costs from a third source), you need the data in one place. For anything beyond a single-store proof of concept, stage your sources in a warehouse or Microsoft Fabric lakehouse first, then model in Power BI. That removes timezone and currency mismatches, keeps refreshes reliable, and gives you a single definition of "a customer" across systems. Our data integration and warehousing work exists precisely for this step.

For email and retention reporting alongside store orders, connect Klaviyo to Power BI. Keep attributed campaign revenue separate from total store revenue so the dashboard can compare the two without counting an order twice.

A template approach that scales

Building one dashboard for one store is easy. Building something you can extend to new stores, channels and brands without starting over takes a little structure.

1. Build a star schema. A central orders fact table linked to dimension tables for date, product, customer and channel. This keeps DAX measures simple and performance fast.
2. Centralise measures. Define revenue, margin, CAC and ROAS once as DAX measures, not repeated in each visual. Change a definition in one place and every page updates.
3. Use a marked date table. Almost every ecommerce metric is time-based, so a proper date dimension powers period-over-period comparisons and rolling averages.
4. Parameterise the source. Use Power Query parameters for store URLs and date ranges so the same template serves multiple stores.
5. Govern the model. Row-level security if multiple brands or regions share a workspace, and clear naming so the next person can maintain it.

This template thinking is the difference between a dashboard that lasts a quarter and one that becomes your reporting backbone. If your team lives in spreadsheets today, our Excel to Power BI migration path is a natural first step toward a maintainable model.

If you run a single Shopify store, first compare Shopify reports with Power BI. That guide helps you decide whether the cross-system reporting here warrants a separate build.

Licensing and what it costs

To share an ecommerce dashboard with colleagues you will need Power BI Pro licences (low per-user monthly cost) or, for larger audiences and advanced features, Premium Per User or Fabric capacity. Copilot in Power BI requires paid Fabric F2 or higher, or Power BI Premium P1 or higher capacity, with the relevant admin settings enabled. Pro or Premium Per User alone is insufficient. Microsoft licensing changes regularly, so check current Microsoft pricing before you commit.

For the build itself, UK Power BI day rates run roughly £400 to £850 per day. A scope-locked build typically lands between £8,000 and £14,000 depending on the number of sources and the depth of metrics. We recommend starting with a short paid review (£2,000 to £4,000, fee credited toward a subsequent build) to confirm scope, data quality and the right architecture before any code is written. Confirm current pricing as of 2026.

Getting started

The fastest route to a dependable ecommerce dashboard is to fix the data foundation first, then build to a clear, scope-locked specification. If you want to see how this would work for your store stack, book a Trusted Numbers Review and we will map your sources, define your KPIs and recommend the right architecture. You can also explore our wider Power BI consultancy and a related read on building a Power BI dashboard for SaaS if you run a subscription model alongside your store.