Ecommerce analytics in CloudCart: sales reports, devices, customers

In short: ecommerce analytics in CloudCart lives in the Analytics menu, a dashboard of 36 reports on sales, orders, customers, sessions and traffic sources. Data refreshes within an hour, the default range is 30 days, and comparison with a previous period and with your industry depends on the plan. The details behind each report download as a CSV file of up to 150,000 rows.

This guide shows the dashboard the way a merchant sees it in the CloudCart admin, for stores selling anywhere in Europe: which card answers which question, where revenue by day is, how sessions by device work and why two numbers sometimes disagree. Which metrics to track and what good looks like is in ecommerce KPIs: 10 metrics an AI agent calculates for you. Card names follow the Analytics and Pricing pages.

What the CloudCart Analytics dashboard is

Analytics is the store's reporting dashboard: cards with charts and tables calculated from your orders, visits and catalog for a date range you choose. It reads pre-calculated data that refreshes once an hour, so heavy reports never slow down the storefront. The cards fall into groups, and each group answers one question:

Group	Cards in Analytics	The question
Sales	Total Sales, Total Orders, Total Customers, Average Order Value, Customer Value, Sales distribution	How much did we sell, from how many orders
Cart and funnel	Conversion Rate, Conversion Funnel, Abandoned carts, Abandoned checkouts	Where do we lose the shopper
Returns	Returns over time, Net revenue, Return rate	How much revenue comes back
Visits	Total Visits, Sessions by device type, Visits by location, Traffic by Source / Medium	Where people come from, on which device
Products and categories	Products by sales, Products by units sold, Products by traffic, bundles, manufacturers and categories	What sells and what only gets viewed
Sources and pages	Sales by location, Sales by traffic source, Sales by Source / Medium, Landing pages by sales	Which channel and page bring money
Discounts	Order discounts, Product discounts	Which codes and markdowns get used

Types of ecommerce analysis and the card for each

Ecommerce sales analysis comes in seven main types, and CloudCart has a ready card for each, so you never start from an empty spreadsheet:

Type of analysis	Card in Analytics	The decision it points to
Trend over time	Total Sales, Total Orders	Which days to cover with ads and newsletters
Order structure	Average Order Value, Sales distribution	Free shipping threshold, bundles, cross-sell
ABC analysis	Products by sales plus CSV export	Stock and ads for group A, markdowns for C
Comparison	Period and industry comparison	Whether growth is yours or seasonal
Channel and country	Sales by Source / Medium, Sales by location	Where to move ad budget, which market is next
Funnel and device	Conversion Funnel, Sessions by device type	Which checkout step to shorten
Customers	Total Customers (new and returning)	Post-purchase emails and loyalty

Who it helps and when to open Analytics

Analytics helps every store from the first order: cards fill within an hour of the first visit and order. Open it in four situations:

• Every Monday. Last 7 days against the previous period: Total Sales, Total Orders, Average Order Value and Conversion Rate. Four numbers, five minutes.
• After a campaign. Set the range to the campaign days. Sales by Source / Medium shows whether the money came from the newsletter or the ads, by UTM tags.
• After a price or shipping change. Average Order Value and Sales distribution show whether carts got bigger.
• Before peak season. Compare with the same month last year to see which categories led.

An example: a cosmetics store sells €9,600 from 240 orders, an average order of €40. If next month brings the same orders at a €44 average, revenue is €10,560, or €960 more from the same traffic. Analytics shows that difference without a spreadsheet.

How to set up the dashboard, step by step

1. Open Analytics in the admin sidebar. Staff see it only if their role has the reports permission (Settings → Staff).
2. Pick a date range. Quick picks or your own dates. Days count in the store's time zone, which matters when you sell across time zones.
3. Turn on comparison: previous period or previous year. Every chart gets a second line and every number a percentage change.
4. Open settings (the cog). Choose which order statuses count, your main industry for the benchmark, and whether tables show device columns.
5. Arrange the cards. Drag the important ones to the top, hide the rest, and save.

Tip: the page address keeps the range and comparison. Bookmark it, or send it to a colleague with admin access, and the same view opens.

Where to see revenue by day

Revenue by day is in Total Sales, the first card. The big number is the period total; the chart groups it by hour (ranges up to 2 days), day (3 to 60 days), week (61 to 90 days), month (up to 730 days) or year. Hover a point to see amount, order count and date.

View details opens a chart with its own grouping menu and a table of order lines with dates: products, shipping, fees, VAT and discounts. The screen shows up to 1,000 rows; the full list is in the export.

Total Sales counts only orders in your selected statuses, across all sales channels, and according to the platform documentation it excludes shipping. Allow for that when you reconcile with payouts from your payment provider or courier.

How to see sessions by device

The Sessions by device type card shows sessions and the share of desktop, phone and tablet. With device display on in settings, tables such as Sales by location also split every row into phone and desktop.

A session is one visitor within one hour from one source, so Total Visits counts visits, not people. It is the denominator of the Conversion Rate.

1. Start the range after 17 January 2023. Device data is recorded from that day; earlier ranges show N/A.
2. Compare the share of sessions with the share of sales. If 75% of sessions come from phones but phone sales are far below that, the problem is the mobile version: a slow page, small buttons or a long checkout form.
3. Switch the Conversion Funnel to Mobile. It shows at which step phones lose more shoppers. Reading the funnel is covered in the abandoned cart recovery guide.

The device card shows tablets separately, while most other cards count tablets with desktop, so shares will not match to the percent. What to fix when phones lag is in the mobile version of your online store.

What average order value is and where to find it

Average Order Value is revenue for the period divided by the number of orders, for your selected statuses: €12,000 from 300 orders is €40. Two neighbouring cards are often confused with it:

Card	Formula	Example at €12,000
Average Order Value	Revenue ÷ orders	300 orders: €40
Customer Value	Revenue ÷ unique customers	250 customers: €48
Sales distribution	Share of orders per price band	23% of orders between €40 and €60

Sales distribution has about 10 price bands that adjust to your average order, and it counts orders with shipping, so its center differs slightly from Average Order Value. It is the best card for setting a free shipping threshold: if 40% of orders fall between €30 and €45, a €50 threshold nudges exactly those shoppers to add one more product. Ways to raise the average are in upsell and cross-sell for an online store.

New and returning customers

Total Customers counts unique buyers in the period, split into new (first order) and returning (ordered before the period). A customer with three orders counts once, and guest orders are not included, so with many guest checkouts this number sits well below Total Orders.

Returning customers are the cheapest growth, because you do not pay for them in ads twice. If 50 of 250 customers return, the share is 20%; post-purchase emails and a loyalty program exist to raise it. Segments by who buys most often and most recently (RFM) are in Campaigns, on CC Pro and CC Master.

ABC analysis of products

ABC analysis splits products by share of revenue: A brings around 80% of sales, B the next 15% or so, C the rest. The starting point is Products by sales, whose details list up to 1,000 products by revenue, with variants combined in one row.

1. Pick a range of 90 days or more so one strong weekend does not decide group A, then download the CSV.
2. Sort by amount in Excel or Google Sheets, add a running percentage of total revenue and draw lines at 80% and 95%.
3. Add Products by traffic. A group C product with many visits is viewed but not bought: check photos, price and copy.
4. Act per group. A: stock, ads and SEO copy first. B: bundles and cross-sell with A. C: a markdown, a better description or out of ads.

Products by sales counts a fixed set of statuses (Paid, Completed, Pending, Payment authorized, Shipped), so its total can differ from Total Sales. Bulk price and text changes are in bulk catalog changes with an AI assistant.

Where sales come from: source, country and landing page

• Sales by Source / Medium groups orders by the UTM tags of the first visit (google / organic, facebook / cpc, newsletter / email) down to the single campaign. Orders without UTM tags appear in Sales by traffic source instead.
• Sales by location shows the top 5 countries by amount; the details drill into cities and then orders.
• Landing pages by sales shows the page where a buying visit started. A category that drives 30% of sales deserves ads and SEO copy first.

Sales by country and EU VAT. If you sell to consumers in other EU countries, Sales by location is your early warning for the distance selling threshold. Since 1 July 2021, once cross-border B2C sales of goods to other EU countries pass €10,000 a year in total, excluding VAT, VAT is due in each customer's country, and you can declare it through one registration in the One Stop Shop (OSS), as Your Europe explains. Add up the countries other than your own each month. Treat it as a trend, not a VAT record: the figure excludes shipping and follows your status settings, so your accountant files from invoices. More in OSS and EU VAT on cross-border sales and, for a separate store per country with its own language and currency, multilanguage, multicurrency and multistore.

Analytics counts orders in your store; Search Console shows the searches behind the visits, and GA4 shows on-page behaviour and ad conversions. GA4 runs in the browser, and under EU rules analytics cookies need consent before they are set, according to Your Europe on online privacy. So GA4 often reports fewer purchases than happened, while Analytics takes orders from the store's own records. Setup is in GA4 and Google Tag Manager, Google Search Console and GDPR and cookies for an online store.

Comparing with last period, last year and your industry

Period comparison sets your store against the previous period or the same period last year, using your statuses and refreshing with the data. Industry comparison draws a dashed line for the average of CloudCart stores in your main industry; it uses a fixed status set for all stores and recalculates once a week. Both are on the plans that include them; when locked, the menu is greyed out and its tooltip lists those plans.

How far back you can look depends on the plan, per the Pricing table:

Plan	Price excl. VAT (annual / monthly billing)	Analytics range	Reports
Baby Pack	€168 a year / €19 a month	100 months	Sales report
Starter Pack	€390 a year / €39 a month	100 months	Sales report
CC Pro	€990 a year / €99 a month	300 months	Sales, product, payment method, customer; RFM
CC Master	€2,990 a year / €299 a month	500 months	Sales, product, payment method, customer; RFM

Every plan has a 0% transaction fee, so Total Sales is never reduced by a platform percentage. See zero commission ecommerce.

Details and CSV export

1. Open View details on a card, or View more on a table card.
2. Set range and grouping. The export takes exactly what is on screen. With comparison on, you can add a second CSV for the previous period.
3. Click export and confirm with your two-factor code. The file is built in the background and a notification tells you when it is ready.

Limits: up to 150,000 rows per file, one export per card at a time, and staff need both the reports permission and a separate export permission.

Keep in mind: exports by city or by order line can include customers' personal data, and the GDPR requires it to be processed with appropriate security and confidentiality. Store files where only the right people can open them. If you use OSS, VAT records must be kept for 10 years from the end of the year of the transaction; the CSV is a working file, your invoices are the record.

Why numbers in Analytics sometimes do not match

What you see	Reason	What to do
An order from 20 minutes ago is missing	Data is calculated hourly	Check again in an hour
Fewer orders than in Orders	Only selected statuses count	Cog → order statuses
AOV differs from the center of Sales distribution	Distribution includes shipping	Nothing, by design
N/A in device columns	Range starts before 17 January 2023	Move the start date
A card asks you to shorten the period	Range too heavy for that card	Shorten it; other cards load
Products by sales total differs from Total Sales	Fixed status set and product line values	Compare products with each other

Status meanings are in order management in CloudCart.

Ecommerce analytics with an AI assistant

An AI assistant connected with a read-only PAT token reads the same reports through the CloudCart Admin GraphQL API (analyticsMetadata and analyticsReport) and answers in one table. Setup is on the store run by an AI assistant page: one sentence in Claude Code, ChatGPT Codex, Gemini CLI or Cursor. Example prompts:

• "Give me revenue by day for October and the 3 strongest days."
• "Compare phone and desktop sessions and sales for the last 30 days. Where is the biggest gap?"
• "Show sales by country this year, excluding my home country, with a running total."

Check the first answer against the card: both read the same data, so numbers should match. A report can also arrive every morning, see a sales report at 8:00 with an AI agent. More in run your online store with Claude.

7 good practices for Analytics

1. Pick statuses once and keep them, or month-to-month comparison loses meaning.
2. Put Total Sales, Total Orders, Average Order Value and Conversion Rate on top.
3. Always look with comparison on. €9,600 says little; +13% on last month says a lot.
4. Set the right industry so the benchmark fits your store.
5. Tag every campaign with UTM, or newsletter and ads blend together.
6. Read products by traffic next to products by sales.
7. Export a CSV every month for your accountant, the EU distance selling check and next month's plan.

Mistakes to avoid

• Watching only revenue. It can grow from higher prices while orders fall.
• Comparing November with October. Black Friday makes November stronger; compare with last November.
• Expecting new orders instantly. For real time, use the Orders list.
• Treating sessions as people. Unique buyers are in Total Customers.
• Giving export rights to everyone. Set them by role in Settings → Staff.

Frequently asked questions