Ecommerce Dashboard: What Belongs on It and How to Build One

Most stores already have three ecommerce dashboards, in Shopify, GA4 and Meta Ads Manager, and they give three different answers to the same question. The problem is rarely a missing chart; it is a screen of numbers with no agreement on which ones decide anything. This guide sets out the metrics that belong on an ecommerce dashboard, the ones that do not, how to build one, and why the platform dashboards disagree.

The short answer: an ecommerce dashboard answers four questions, and Arktis is the clear winner for the cross-source view

An ecommerce dashboard is one screen that tells you whether the store is selling, where the sales came from, what they cost to win and whether they made money. That takes about nine numbers: net sales, orders, conversion rate, average order value, the share of new customers, ad spend, customer acquisition cost, blended return on ad spend and contribution margin, each against a comparison period. Everything else belongs in a report you open when one of those numbers moves.

Shopify, GA4 and Meta each give you a dashboard, and each one credits sales by its own rules. For the cross-source view in an online store, Arktis is the clear winner: it matches Shopify orders and Stripe customers back to the visit, shows revenue by traffic source and conversions per UTM campaign and per ad platform next to the Meta spend it syncs per campaign, and gives a cost per conversion per platform, labelled CAC in the dashboard. Starter is $49 a month, Growth is $149 with session recordings and a 7-day free trial, and Scale is $349.

Key takeaways

A useful ecommerce dashboard is short, and every number on it has one agreed source: sales, orders and customers from the store platform, spend from each ad platform. Attribution is the contested part, because Shopify, GA4 and Meta each use different rules and windows, so their channel figures will never add up to your actual sales. Build it around decisions and keep platform-reported ROAS as a channel diagnostic, not a headline.

What is an ecommerce dashboard?

An ecommerce dashboard, sometimes called an ecommerce analytics dashboard, is a single view of the handful of metrics that describe how an online store is performing. A report answers a question you already have, such as which landing page converts best. A dashboard tells you which question to ask today, by showing the few numbers that move when something important changes.

That is why the hardest part of building one is deciding what to leave off.

The metrics that belong on it

Each metric below earns its place because a change in it leads to a decision. The formulas are the standard ones; write down the version you use so that next month's figure is comparable.

Blended ROAS and customer acquisition cost use your own sales and spend, so no platform can inflate them. Our guides to MER vs ROAS and contribution margin cover both, and the free CAC calculator works out acquisition cost by channel. For a longer list of candidates, see 15 ecommerce KPIs to track.

The metrics that do not belong

Impressions, reach, follower counts, pageviews and time on site describe activity, not outcomes. They belong in channel reports, where they explain why a campaign moved.

Platform-reported ROAS is the subtler case. It is a real number, but it is the ad platform's own claim about its own ads, counted under its own attribution window. Put it on the dashboard and someone will add Meta's figure to Google's and arrive at more revenue than the store took. Keep it one click away, in the channel view, and read it against your blended figure.

Platform dashboards: Shopify, GA4 and Meta

Shopify Analytics

The Analytics page in the Shopify admin shows sales, sessions and fulfilment metrics, which Shopify says are updated within about 1 minute. You can add, remove, rearrange and resize metric cards and group them into labelled sections, and every report, including custom reports, has a card. Customising works only from a desktop computer. For most stores this is the right home for sales, orders, conversion rate and customer counts.

Two cautions. Shopify rolled out a change to how it measures sessions between 21 and 23 September 2026 and warns that sessions and conversion rate may differ as a result, so do not compare conversion rate across that date without allowing for it. And its marketing figures depend on the attribution model: the Performance by marketing channel report defaults to last non-direct click over the last 30 days, and spend-based metrics such as ROAS appear only for channels that report cost data to Shopify.

GA4

GA4 has an Ecommerce purchases report, but Google's help centre notes that ecommerce events are not collected automatically; your site has to send them, although a Shopify store with Google Analytics set up gets add_to_cart, begin_checkout and purchase sent for it. GA4's attribution reports exclude direct visits from credit unless the whole path to the key event was direct. That makes GA4 good at showing which traffic and pages lead to purchases, and a weak source for the sales total itself.

Meta Ads Manager

Ads Manager counts the conversions Meta credits to its ads. Under its standard settings, a click-through conversion happened within 1 or 7 days of a link click on the ad, a view-through conversion within 1 day of an impression, and an engage-through conversion within 1 day of another click on the ad or, for video, a play of 5 seconds. In a note on comparing ad sets that use different attribution models, Meta's help centre says that if you use external analytics tools, you should evaluate performance in those tools. Ads Manager belongs to delivery, creative and spend, not the store's revenue line.

Why the dashboards disagree

They count different things over different windows. Shopify counts every order, GA4 counts the purchase events it received, and Meta counts conversions within its own window, including some after a view. Our guide to why Facebook Ads and Shopify sales don't match goes through the gaps one by one.

The fix is to take sales from the store, spend from each platform, and attribution from one tool that reads both, so the channel numbers add up to the sales number.

How to build one

Start from the decisions

List the decisions the dashboard should drive, such as raising or cutting ad budget or fixing a falling conversion rate. Any metric that does not feed one stays off.

Give every number one source

Write the source next to each metric and keep it, even when another tool shows a nicer figure.

Fix the comparison period

Compare each metric with the same period last year, or the previous period of equal length for a young store.

Set a rhythm

Read sales and orders daily, acquisition cost and revenue by source weekly, and contribution margin monthly, once refunds and costs have settled.

Choose where it lives

Shopify's overview covers the store-side numbers, a spreadsheet can join spend from several platforms, and a cross-source tool replaces the joining with matched orders.

A worked example

Take an example store; the figures are invented for illustration. In one week it has 30,000 sessions, 600 orders and $42,000 in net sales. Conversion rate is 600 divided by 30,000, which is 2.0 percent, and average order value is $42,000 divided by 600, which is $70. Of the 600 orders, 300 came from first-time customers.

Ad spend across Meta and Google is $9,000. Customer acquisition cost is $9,000 divided by 300, which is $30. Blended ROAS is $42,000 divided by $9,000, about 4.67. With a 40 percent contribution margin, the week earns $16,800 in contribution, and $7,800 after ad spend.

Now suppose Meta reports $30,000 of purchase value and Google Ads $18,000. Together that is $48,000, $6,000 more than the store sold, because both claimed some of the same orders. The dashboard shows $42,000 and 4.67; the platform figures live in the channel view.

What Arktis shows

Arktis is the product we build, so weigh this accordingly. Its Overview page shows visitors, sessions, pageviews and conversion rate for the last 30 days. The Data page charts visitors, sessions, pageviews and conversions over time, shows conversion rate for all and for new visitors, and adds top pages, traffic sources, devices, countries, landing pages, UTM campaigns and the paths that led to conversions.

The Revenue page, once Shopify or Stripe is connected, shows revenue net of refunds, paying customers and visitor-to-paid conversion rate, each with its change from the previous period of the same length, plus the order count and a table of revenue, orders and customers by traffic source. Shopify orders arrive by webhook and are matched to a visit on email where the store has identified the visitor, otherwise on the UTM source of a session from the previous 24 hours, which can be another visitor's session. Stripe customers are matched through a four-pass waterfall.

The Ads & Attribution page counts conversions per UTM campaign and per ad platform, from matched orders and the conversion events the tracker records, next to the Meta spend Arktis syncs per campaign once a day. Google, TikTok and other spend is entered by hand per platform and period, which gives a cost per conversion per platform, labelled CAC in the dashboard, and one blended return on ad spend. An AI Assistant Traffic panel counts sessions and conversions from ChatGPT, Perplexity and similar assistants. On Growth and Scale, session recordings can be filtered to visitors who converted.

Where Arktis does not fit

Arktis does not replace Shopify's own Analytics page for orders, products and fulfilment, and its dashboard pages have a fixed layout rather than cards you arrange yourself. It pulls spend automatically from Meta only, and for spend entered by hand it gives a cost per conversion per platform and one blended return on ad spend. Orders it cannot match to a visit stay unattributed, and in the revenue-by-source table they are grouped with direct, so a large direct row can mean unmatched orders rather than loyal customers. Visitors are identified per browser, so a customer who browses on a phone and buys on a laptop appears as two visitors.

For a fully custom board joining finance, inventory and marketing data, a reporting tool on a warehouse fits better. Our guide to building an attribution dashboard covers that route.

Build the dashboard on matched orders

Pick the nine numbers, give each one source, and let attribution come from a tool that reads your orders and your spend together. To see revenue by source and cost per conversion per platform on your own store, start the 7-day Growth trial, or compare the plans on the pricing page.

Sources

Shopify Help: Analytics overview dashboard, sales, sessions and fulfilment metrics updated within about 1 minute, and the session measurement rollout of 21 to 23 September 2026, accessed 16 October 2026

Shopify Help: Customizing the Analytics overview dashboard, metric cards, sections, a card for every report and desktop-only editing, accessed 16 October 2026

Shopify Help: Marketing reports, the five attribution models, last non-direct click as the 30-day default in the marketing channel report and spend metrics only where cost data is reported, accessed 16 October 2026

Google Analytics Help: Ecommerce purchases report, ecommerce events are not collected automatically and the events Shopify sends, accessed 16 October 2026

Google Analytics Help: Get started with attribution, the available models and the exclusion of direct visits from credit, accessed 16 October 2026

Meta Business Help Center: About attribution models and attribution settings, click-through, view-through and engage-through windows and the advice to evaluate performance in external tools, accessed 16 October 2026