Store analytics: what the numbers mean

What it is

The Analytics tab in your store dashboard answers one question: where do the people who open my store come from, and what do they look at. It counts visits to your storefront, joins them to your orders, and lays the result out over 7, 30 or 90 days.

There is nothing to install. Counting starts the moment your store is published.

How visits are measured

Every page of your published storefront sends a small, silent message when it loads, and again whenever a shopper moves to another page without a full reload. That message carries the page path, whether it is the first page of this browsing session, and the site that linked them here. Nothing on the page waits for it, so it can never slow your store down or break it.

• Bots are filtered out by their browser signature. Search-engine crawlers, uptime checkers, link previews and the like are dropped before anything is recorded. This is why the number here is usually lower than a raw server log.
• No IP address is ever stored. A visitor is identified by a scrambled key made from their network address, their browser and today's date. It cannot be turned back into a person, and it changes every day.
• Country, region and city come from the network, not from the shopper. They are approximate, and a shopper on a mobile network can appear in a different city from the one they are standing in.
• Device is read from the browser signature and reported only as mobile, tablet or desktop. Only published stores are counted at all.

What each number means

The date switch at the top right of the tab moves everything between 7 days, 30 days and 90 days. The top row of numbers is traffic.

• Page views is every page opened, including the same shopper looking at four products. The line under it compares the period with the one immediately before it, so *+18% vs. prior* on a 30-day view means the last 30 days against the 30 before them.
• Visitors is unique people, counted per day. Someone who comes back on Tuesday and Thursday counts as two.
• Sessions is *store opens*: the first page of each browsing session. Close the tab, come back an hour later, that is a second session.
• Avg / day is page views divided by the days in the range.

The second row joins your orders to that traffic, counting every order in the period except cancelled and archived ones.

• Conversion is orders divided by unique visitors, as a percentage.
• Orders is how many orders were placed in the period.
• Revenue is the sum of those order totals, in your store's currency.
• Revenue / visit is that revenue divided by page views. A rough sense of what a visit is worth, useful when deciding whether an advert pays for itself.

The panels underneath

• Traffic over time plots views and visitors day by day.
• Conversion funnel shows three steps: *Visitors*, *Viewed a product*, *Purchased*. The middle step counts visitors who opened at least one product page. A wide gap between the first two usually means your home page is not sending people into the catalogue.
• Busiest times shows views by hour of the day and by day of the week, converted into your own timezone. Use it to pick when to post on Instagram or send a broadcast.
• Locations ranks cities and regions, with the countries beneath. Useful for deciding where to offer faster delivery.
• Devices splits mobile, desktop and tablet. If yours reads mostly mobile, check every change on a phone.
• Top products ranks product pages by views. A product with many views and no sales usually has a price, photo or description problem, not a traffic problem.
• Top pages is the same by page address, and Traffic sources lists the websites that sent people to you, by domain.

The honest limits

These numbers are good for direction, not for accounting. It is worth knowing where they bend.

• Visitors reset every day. A shopper who browses on Monday and buys on Friday is counted as two visitors. That makes the conversion rate read lower than a tool that follows people across days.
• Conversion counts orders that never involved a visit. An order taken over WhatsApp, or placed by you on a customer's behalf, still lands in the orders half of the sum. On a store that sells mostly by WhatsApp the conversion figure will look impossibly high.
• Most WhatsApp and Instagram traffic arrives with no source. Those apps usually strip the referring address, so real traffic from them lands in the gap rather than in Traffic sources. An empty or thin sources panel does not mean nobody is clicking your links.
• Revenue / visit divides by page views, not by people. A store where shoppers browse a lot of products will read lower than one where they land straight on a product.
• Bot filtering is not perfect. It works on the browser signature, so a scraper pretending to be a normal browser is counted as a visitor. Locations are network-level guesses too: read the city list as a pattern, not an address book.
• There are no individual visitor journeys, no advertising attribution, and no custom events. If you need those, add your own tracking code as well.

How long the data is kept

Visit records are kept for one year and then deleted automatically. The longest window the tab can show is 90 days, and it reads a further 90 days behind that for the comparison, so a year covers everything you can see with room to spare. Orders and revenue are not affected by this: your order history is kept in full.

How this differs from Google Analytics

• It knows your shop. Products, orders, revenue and the buying funnel are here without any setup. In Google Analytics, ecommerce reporting is something you have to configure, and on a store you do not own the code for, that is not always possible.
• It sets no cookies of its own and holds no address or identifier that points at a person, so there is nothing here to ask consent for.
• It cannot follow a shopper across days or across devices, which Google Analytics can. That is the price of the point above.
• It has no campaign, advert or custom-event reporting. No UTM breakdown, no goals, no audiences.
• You can run both. Paste your Google Analytics, Meta Pixel, Microsoft Clarity or PostHog snippet into Settings → Tracking & code, which is included with Starter and above. Your snippet runs on the live storefront only, and it does not change anything in this tab.