Shopify analytics: which reports show where sales come from

What is Shopify analytics?

Shopify analytics is the set of dashboards and reports built into every Shopify store. You open it from Analytics in your Shopify admin. It answers the questions every business owner has at the end of a month: what sold, how many people visited, and which channels brought the buyers.

Shopify’s help center says the main Shopify Analytics features are available to merchants on any subscription plan. As of September 2026, Shopify’s pricing page lists more than 200 real-time reports, plus custom analytics, on every plan from Basic up. It has three parts:

• The Analytics dashboard: a page of metric cards, such as sessions by device type. It opens on the last 90 days and is up to date within about a minute, according to Shopify’s guide to using the Analytics overview dashboard.
• Reports: a graph plus a table for one set of metrics, grouped into categories such as Acquisition, Marketing and Inventory.
• Live View: a map of what is happening on the store right now.

What sets it apart from every other dashboard you use: Shopify records the orders themselves. Your email platform, your ad account and Google Analytics each report on their own share of the credit. Shopify is where the orders actually land.

Where do you find Shopify reports?

From your Shopify admin, go to Analytics, then Reports. Click the Category filter to narrow the list to Acquisition, Sales, Marketing or another group. A few facts about Shopify reports save a lot of confusion:

• Default reports are built by Shopify. Filter the list by Created by, then Shopify, to see only those.
• Every report is a query. Shopify’s overview of the new reports explains that each default report shows a pre-written ShopifyQL query, so you can read exactly how its metrics are built.
• Edits are temporary until you save. A change to a default report does not override it. Save the exploration as a custom report to keep it, which you can do regardless of your plan.
• Tables stop at 1,000 rows on screen. Shopify’s reports guide says totals still cover every row, and you can export the full report.

Sidekick, Shopify’s built-in AI assistant, can also build a report from a plain-language request. Check the query it writes before you trust the answer, the same way you would check a new hire’s spreadsheet.

Which Shopify reports show where sales come from?

Three of them. Together they answer three questions: how much the store sold, which site sent each buying visit, and how many visits each site sent. Read them in this order:

Shopify documents the first two with its sales report definitions and the third with its acquisition reports. Put the referrer reports side by side and you get the performance figure ad dashboards leave out: how many visits each channel needs to produce one order.

What is the difference between gross, net and total sales?

Each figure builds on the one before. Gross is the price of what you sold before anything comes off, net takes out discounts and reversals, and total adds back what customers paid on top. Shopify defines all three in its glossary:

A sales reversal is any order adjustment with a negative value: a return, a cancellation, an edit, or an adjustment to shipping, taxes, fees or discounts. Pending, unpaid and canceled orders are included. Test orders are not, and deleted orders disappear from the reports entirely.

Two more rules catch owners out. These reports track the value of goods sold, not the money that has reached your bank. Chargebacks are not included either, so for cash, use the payments finance reports.

How do you read the Total sales by referrer report?

It lists revenue by the site that sent the buying visit. Shopify groups each referrer as Direct, Search, Email, Social or Unknown, and the report shows the last interaction referrer: the site the customer used just before placing the order.

Shopify’s own example on its marketing reports page makes the rule plain. A shopper finds you on Google, comes back several times that week, then buys after clicking an email.

Google was the first interaction. Email gets the credit.

Search covers the unpaid clicks as well as the paid ones, so once your products sit in Google’s free listings, those orders land in this row too.

Why is so much of it Direct?

Direct is the catch-all for visits whose origin Shopify cannot see. According to Shopify’s glossary, that happens when a link is clicked from some email products, a mobile app, an instant message or a bookmark. It also happens when the browser has Do Not Track on, when a proxy or firewall blocks referrer data, or when a shortened URL was used.

The fix is tagging. Add UTM parameters, a source, a medium and a campaign name, to the links in your emails, posts and ads. Shopify’s guide to measuring marketing performance says traffic that arrives with utm_campaign parameters is attributed to marketing, so it stops hiding inside Direct.

On one store, for August 17 to September 15, 2026, Klaviyo credited email with 23 orders. Shopify’s referrer report traced 10 to an email click.

Both numbers are defensible. They count differently, and only one of them comes from the store itself.

Why do Klaviyo, Meta and Google Analytics claim more than Shopify?

Because each tool counts its own credit by its own rules, and none of them is counting the others. Shopify counts each order once. Every tool grades its own homework, and a store should not fund its channels on the strength of their self-assessments.

What does each tool count?

• Klaviyo counts a conversion when someone opens or clicks a message and then orders within its attribution window. Its help center on message conversion tracking says that window defaults to 5 days for email on newer accounts. Automatic Apple Mail Privacy Protection opens count too.
• Ad platforms attribute sales by their own rules too. Shopify’s marketing performance page warns that a Facebook ad created in Shopify can show different results in Shopify and in Facebook, because the two credit interactions differently and data takes time to sync.
• Shopify offers five attribution models when a report pairs a revenue metric with a marketing dimension: last non-direct click, last click, first click, any click and linear. Any click hands out more credit than you have orders, so use it to study one channel, not to add channels up.

“the last-click rarely represents the complete consumer journey”

Avinash Kaushik, author of Web Analytics 2.0, Marketing Analytics: Attribution Is Not Incrementality

That cuts both ways: Shopify’s last-interaction view undercounts the ad that introduced a buyer, while each platform’s own view overcounts itself, so compare the two and trust neither alone.

Here is what one store’s own attribution report showed when its two biggest sources of visits were put next to each other:

Google search brought in more than 3.5 times the sales of the paid ads, from under a fifth of the traffic.

Source: Shopify’s sales attribution report for the 90 days before September 3, 2026. Google search brought $8,316 in sales and paid Facebook and Instagram $2,322, as charged. What it does not prove: the report credits each order to the visit it came from, so an ad that first introduced a buyer who later searched Google gets no credit.

How do you read the Sessions by referrer report?

It counts visits by where they came from, not revenue. Shopify’s acquisition reports say a session ends after 30 minutes of no activity, and at midnight UTC. One visitor can have many sessions, so sessions usually run higher than visitors.

The useful number comes from dividing. Take a channel’s orders from the referrer report above and its sessions from this one, for the same dates. That gives you visits per order, the figure no ad dashboard volunteers.

Sessions are also the denominator for a number most stores never check: how many of those visits you can email later, which is your visitor identification rate.

On one store, only 1 in 1,793 visits from cold Facebook and Instagram campaigns completed checkout (August 3 to 25, 2026). On warm audiences it was 1 in 179 (August 26 to September 15, 2026).

Both periods fall inside the work. That store’s Facebook checkout rate had ranged from 1 in 71 (March 2026) to 1 in 811 (December 2025), so treat it as one reading, not a rule.

Which sessions should you leave out?

• Bots. Shopify’s page on bot filtering says every session is labeled human or bot, and a Human or bot session filter removes the bots. It applies only to data from October 7, 2025 on.
• You. Viewing the store from your desktop admin counts as a session unless you open it with View store. Views from the Shopify app on a phone always count.

What does Shopify Live View show?

Shopify Live View is a real-time map of your store: who is on it right now, what has sold since midnight, and what shoppers did in the last 10 minutes. Open it from Analytics, then Live View. Blue dots are recent visitor sessions and purple dots are orders.

What does each Live View number mean?

Shopify’s Live View guide defines the metrics:

• Visitors right now: people active on the online store in the past 5 minutes. To stay active, a visitor has to view a page or click a button.
• Total sales, total sessions and total orders: counted since midnight in your store’s time zone. Orders and revenue include your other channels too.
• Customer behavior: sessions in the last 10 minutes with active carts, sessions checking out, and sessions that purchased.
• Top locations and top products: where visitors are, and which product has earned the most since midnight.

Why do visitors show up in the middle of the country?

When Live View cannot place a US visitor from their IP address, it puts the dot at 38°N 97°W, roughly the geographic center of the United States. Search engine bots, crawlers and VPN users land there, so a cluster of dots in the middle of the map is not a surprise market.

Use the map on launch days, during an email send or over Black Friday, to see a spike arrive. Do not judge a channel on it. Five minutes of dots tells you nothing about what a month of that traffic is worth.

Can you trust Shopify's conversion rate?

Trust it as a trend, not a verdict. Conversion rate is the share of sessions that ended in an order, so anything that inflates or hides sessions moves it without a single order changing.

• Cookie rotation. Shopify’s page on session cookie rotation says a script or consent app that keeps regenerating the session cookie makes one visit count as several. Conversion rate looks lower. Orders, revenue and customer counts are untouched.
• Consent banners. Where a cookie banner is active, Shopify collects data only after a visitor consents, so session counts and other session-based metrics can drop. That is on its page about customer and session discrepancies.
• Bots. Filtering them out often raises the rate, because bots browse product pages and rarely buy.

That is why sales per visit, total sales divided by sessions, is often the better health check. On one store, sessions went from 4,276 in the 30 days before the work began (May 5 to June 3, 2026) to 7,970 in the 30 days about three months in (August 17 to September 15, 2026). Conversion rate went from 0.9% to 0.9%, almost flat, while sales per visit went from $2.13 to $2.95.

Bigger orders and better traffic drove that, not more checkouts per visit. It is one store, and its Facebook ads ran in both periods. Judged on conversion rate alone, the work would have looked like a failure.

More on what moves the rate is in the guide to Shopify conversion rate optimization.

Is Shopify analytics broken, or just counting differently?

Usually it is counting differently. When Shopify analytics looks broken, start with the rules about access, cookies, bots and report versions, because each one has a quick check.

If you have spent an evening trying to make the numbers line up, you know how exhausting it is. Match the symptom first, then run its check:

Then put a full week of sales next to a full week of sessions. If sales hold steady while sessions swing, suspect the counting before you suspect the store.

What do Shopify reports show on two more stores?

The same reports on a store that also sells in person, and on a store that added GA4, show what the case study cannot. A register puts counter sales into the same reports as web sales, and analytics data needs cleaning before it is read.

One store sells at a counter and online through one Shopify account, with Shopify POS on the counter. In the 90 days to September 18, 2026, its register recorded 518 orders and $20,063, up from 80 orders and $2,859 in the 90 days before.

The caveat travels with that number: the register was being adopted during the window, so the jump mixes real growth with the adoption itself. Its online store took 20 orders and $2,218 in the same 90 days, down from 27 orders and $2,981.

Two more lines from the same admin matter for email. The average register order was $38.73 against $110.88 online, and only 113 of the 541 orders the store took in those 90 days carried a customer email address. Source: the store’s Shopify admin, pulled September 18, 2026.

A second store showed why Google Analytics comes after these reports, not before. Its GA4 numbers did not mean anything until a cleaning rule was in place: one country only, with two states marked as internal traffic and the data-center cities filtered out. Source: the store’s GA4 account, checked September 23, 2026.

Shopify’s order and sales figures need no such rule, because an order is recorded whether or not a browser ran a tag. What neither store proves: 90 days on one and one filter on the other say nothing about what your reports will show.

Shopify analytics vs Google Analytics: which should you trust?

Trust Shopify analytics for revenue and orders, Google Analytics for how visitors move around the site, and Search Console for what happened on Google before the click. They measure different things, so they will never match exactly.

Shopify’s page on analytics discrepancies lists why its numbers differ from Google’s. Google can only count visitors with JavaScript and cookies turned on, browser extensions can block it, and the two may use different reporting time zones.

“GA tracks what happens when a user goes to a site.”

John Mueller, Search Advocate at Google, Search Engine Roundtable

Shopify is the only one of the three that also records what the visitor paid, which is why it settles arguments between the other two.

The setup and the gaps are covered in how to set up GA4 on Shopify and read it right. The search side is in which Shopify SEO tools are worth paying for.

How do you run a 15-minute Shopify analytics check?

Pull the same 30 days from each report and keep track of the numbers side by side. This is the first stage of The Traffic to Sales Method, and it needs nothing but your Shopify admin and the dashboards you already pay for:

1. Open Total sales over time for the last 30 days. Compare it with the previous period and the same period last year, then note revenue and orders.
2. Open Total sales by referrer for the same dates. Write down the share from Search, Email, Social and Direct.
3. Open Sessions by referrer. Divide each channel’s orders by its sessions to get visits per order.
4. Add the Human or bot session filter and see whether any number changes much.
5. Open three recent orders and read each conversion summary: where the first visit came from, and how many visits came before the order.
6. Put each platform’s claim next to Shopify’s count: attributed orders in Klaviyo, purchases in your ad account, purchases in GA4.
7. Circle the biggest gap. That is where to start.

The conversion summary in step 5 sits on every order page. Shopify’s page on the order conversion summary says it shows the customer’s visits over the last 30 days and the origin of their first visit. The details can take up to 48 hours to appear.

If the gaps are bigger than you expected, the free Traffic to Sales Check walks through the same comparison. A Shopify store audit reads Shopify, Klaviyo, Google and your ad account together, inside your own logins. The email side of the check is in five checks for whether your email is really working.

What do Shopify reports not prove?

They prove what sold and which visit came right before each order. They do not prove why a customer bought, or what would have happened without a campaign. Keep these limits in view when you make business decisions:

• First interactions expire. If a visitor goes 30 days without buying, Shopify resets the first interaction to the next referrer.
• History has edges. Session-based metrics only go back to October 1, 2022, and Shopify updated its analytics framework in October 2024. Older exported reports can differ from today’s.
• Edits split rows. Rename a product and a report covering both dates can list it twice, once under each product title.
• One order can move a month. A single large order can double a channel’s revenue for a month, so check order counts before celebrating.

“I love that the analyst is segmenting the data rather than showing the aggregate trend”

Avinash Kaushik, author of Web Analytics 2.0, Data Analysis 101: Seven Simple Mistakes That Limit Your Salary

A store-wide total hides everything that matters, so split every report by channel, by new or returning customer and by device before you draw a conclusion.

Do you need a Shopify analytics app?

Most stores do not need one to see where orders come from. The built-in reports, custom reports and ShopifyQL already cover it. A reporting app earns its fee when you need something Shopify does not track, such as ad cost from several platforms in one view.

On the developer side, Shopify’s documentation on building with Shopify Analytics says ShopifyQL is the query language behind it. The metric cards, dashboards and reports in the admin all run on it, and apps can query the same data through the GraphQL Admin API. That is what most people searching for a Shopify analytics API are after.

Two cautions before you start paying for one:

• Cost data still lives in the ad platforms’ own reporting. Shopify’s Growth page does not show cost, ROAS, CPA or clickthrough rate for Facebook and Google campaigns, so you still need Ads Manager and Google Ads to track spend. The math is in the ROAS formula guide.
• An app that credits itself is one more tool grading its own homework. Whatever it reports, check it against Shopify’s referrer report for the same dates.

If an app’s numbers never reconcile with Shopify’s, question the app, not the store.

What does good Shopify analytics look like for your store?

You open three reports and know, in minutes, what sold, which channels brought the buying visits, and where the other tools disagree. That is Shopify’s reporting doing its job. Decisions about ad budgets and email get made from Shopify analytics, not from whichever dashboard is loudest that week.

On the store in the case study, reading Shopify’s own reports this way came first. Its total went from $9,110 in the 30 days before the work began (May 5 to June 3, 2026) to $23,532 in the 30 days about three months in (August 17 to September 15, 2026). It is one store, and its Facebook ads ran in both periods.

The full numbers, with what they do not prove, are in the case study. The moves that lifted revenue without more ad spend are in how to grow a Shopify store without more ad spend, and the ad math is in whether Facebook ads are worth it. Left alone, the loudest dashboard keeps deciding where the next dollar goes.

The proof, from one store

Straight from the case study, with the source and what it does not prove. See all five results.

Result 2 · Email

Sales from email: $987 to $4,308 in about 90 days

Before the work$987

→

About 90 days in$4,308

4.4x

Baseline: the 30 days before the work began

$987 from 7 orders that came in through an email, 11% of sales, May 5 to June 3, 2026.

The work: what changed

Built welcome, abandoned cart, browse abandonment, win-back and high-ticket follow-up emails in Klaviyo (live July 28). Found that the weekly email only went to people who joined the list after it was switched on, so it reached 13 people in six weeks. Replaced it with a scheduled weekly email (September 4) that reached 484 people on its first send (September 8).

Result: about three months in

$4,308 from 10 orders that came in through an email, 18% of sales, August 17 to September 15, 2026, 4.4 times the baseline.

Evidence source

Shopify Analytics, Total sales by referrer, Klaviyo row, pulled September 18, 2026.

What this does not prove

One deposit order, worth $2,080, was placed 17 minutes after the buyer clicked a welcome email. Without it, email brought in $2,228, still 2 times the baseline. Klaviyo credits email with more, 23 orders for the same dates, because it counts any order placed within days of someone opening or clicking an email.

Test it on your store

In Klaviyo, open each flow and compare recipients over the last 30 days with the size of the list it should reach. Then open Total sales by referrer in Shopify for the same 30 days and find the Klaviyo row. A flow reaching a fraction of its list, or a Klaviyo row near zero, is the place to start.

Does this sound like your store?

If it does, the service that fixes it is Shopify store audit. You can see the before and after on one store in the case study.