Shopify Analytics: A Store Owner’s Guide

Shopify Analytics shows your store’s sales, customers, products, and online shopping activity. Open Analytics in your Shopify admin for the dashboard, then Reports to investigate a change. Start with a business question, compare matching periods, and finish with a decision someone can act on.

You might want to know why sales fell, whether a promotion attracted returning customers, or which products need stock. Each question needs a different report. This guide explains where to start, what the main numbers mean, and when another tool earns its place.

What Shopify Analytics shows and where to find it

Use the dashboard to spot a change and a detailed report to understand where it happened. Live View serves a different purpose: watching current store activity during a launch or promotion.

Shopify describes its analytics dashboard and reports as a connected reporting experience. Dashboard cards summarize measures such as sales by channel or sessions by device. Opening a related report gives you a chart and a table you can explore further.

In your admin, select Analytics, then choose Reports when you need a breakdown. A staff member needs the relevant Analytics permissions. If someone cannot open a report, check their access before assuming your store needs another subscription.

Dashboard, report, or Live View?

The dashboard answers, “What deserves attention?” Keep the measures tied to your current priorities visible there. A store preparing a promotion might emphasize orders, sales, and conversion, while another focuses on fulfillment.

A report answers a narrower question, such as which products account for a sales decline. Use its date range, filters, and grouping choices to separate the parts of the business involved. A total tells you the size of a change; the breakdown helps locate it.

Live View helps you watch activity as it happens. It can be useful while checking a campaign launch, but it offers little evidence about longer buying cycles. Use a completed comparison period for decisions about retention or product demand.

Is analytics included in your Shopify plan?

Shopify says its main Analytics features are available on its subscription plans. Its current documentation includes custom explorations, customer cohorts, and RFM customer analysis. Check the report in your admin and the current help page before paying to solve a supposed limitation.

Older guides sometimes reserve custom reporting for higher plans or say Shopify has no customer analysis. Those claims can send you toward an unnecessary upgrade. Judge an additional tool by the question it answers and the work it saves in your store.

Start with a question and a fair comparison

Write the question before changing the dashboard. “Which collection explains the fall in online sales?” is more useful than “How is the store doing?” It names a result, a part of the business, and a reason to investigate.

Choose the period that matches the decision. Compare complete weeks with complete weeks, and allow for promotions, holidays, and stock availability. A partial current week can look weak beside a completed previous week even when daily performance is steady.

Then follow a short reporting workflow:

1. Open the report for the result you want to understand.
2. Set the date range and comparison period.
3. Add a relevant breakdown, such as product, channel, or customer type.
4. Apply the filter that matches your question.
5. Check the detailed rows before saving or sharing the result.

Shopify lets you customize reports as data explorations. Start from a nearby report rather than adding unrelated measures to a blank view. Give the saved report a name that describes its purpose, such as “Online sales by collection.” The separate view keeps a temporary investigation from cluttering the main dashboard.

Before exporting, check whether the output includes the columns and rows you need. Keep the period, filters, currency, and measure names beside the figures when sharing them. A spreadsheet without those labels is hard for someone else to interpret correctly.

This sequence keeps the review focused on evidence rather than the appearance of a chart.

1. 1Ask a store question
2. 2Match the comparison
3. 3Find the change
4. 4Check an explanation
5. 5Choose an action

Read sales, orders, traffic, and conversion together

Read these measures together because each tells a different part of the sales story. More traffic can accompany fewer orders. More orders can accompany lower order value, heavier discounts, or weaker profit.

Sales show the value recorded under the report’s sales definition. Pay attention to whether you are reading gross sales, net sales, or total sales. Discounts, returns, shipping, and taxes can make those totals differ.

Orders show purchase activity, while units sold describe how many items moved. A customer buying several products in one order affects these measures differently. Use the measure that matches the stock or demand question you are asking.

Average order value, or AOV, describes the average value of an order under the report’s definition. A change can reflect product prices, basket size, discounts, or a different mix of customers. It does not tell you which explanation applies.

Separate traffic from buying behavior

Sessions are visits, not distinct people. A visitor can return and create another session. Online store conversion describes how often measured sessions result in a purchase, so read it alongside traffic quality and the shopping funnel.

If traffic rises while conversion falls, look at the new traffic’s source, device, and landing page. A campaign reaching people earlier in their buying journey may change the store’s overall conversion rate. That pattern alone does not establish a checkout problem.

Review cart additions, checkout starts, and completed purchases to locate the change. Then inspect the affected experience on the device customers use. An unexpected shipping charge, missing size, or unclear delivery promise calls for a different response than irrelevant traffic.

Treat attributed sales as a reporting view

Marketing reports connect sales and sessions with recorded sources and campaigns. They help you compare marketing activity using a consistent view. They do not prove that the sale would disappear if you stopped that channel.

For example, an email promotion can bring existing customers back to buy. The attributed sales may look encouraging while the product’s margin or stock position makes another promotion unattractive. Check those constraints before repeating the offer.

Keep campaign names consistent so you can recognize the activity in your reports. When comparing channels, use the same attribution view and period. Adding together sales claimed by different advertising platforms can count the same purchase more than once.

What is a useful AOV benchmark?

A useful AOV benchmark gives context for a comparable store, rather than a universal target. Product prices and category matter, and stores within the same category can still have very different baskets.

Among clothing and fashion stores, the middle range runs from $80 to $235. Even within that category, a single basket target would describe very different businesses poorly.

For your comparison, use AOV over the same length of time and check that the revenue scope matches. The benchmark concerns order value after discounts, including tax and shipping, before refunds. A report using a different sales definition needs care before you compare it.

If your AOV is below the category median, examine whether that fits your price range and purchase model. A lower-priced replenishment product may support a different basket than a premium occasional purchase. A higher basket is useful only when the extra revenue supports the business’s margin and customer needs.

Choose the report that answers the next question

Pick the report family from the decision you need to make. The dashboard is a starting point, while customer, product, inventory, and finance reports answer different follow-up questions.

Customers: acquisition and retention

Compare new and returning customers when you need to understand who is buying. Then use customer cohorts when the question concerns what happened after the first purchase. A cohort groups customers by when their relationship with the store began.

Give cohorts equal time to mature. A recent group has had less opportunity to return than an older group. Comparing them without matching that opportunity can make healthy recent acquisition look like a retention decline.

Read the label on a retention measure carefully. A returning customer measure and a repeat purchase measure may use different customer histories and windows. Keep the name and period attached when copying the result into a report.

Customer analysis can suggest a useful next question without proving a marketing effect. If returning customers account for more sales, check whether new customer acquisition slowed. The same movement can reflect stronger retention, weaker acquisition, or both.

Products, stock, and fulfillment

Use product sales to locate demand, then inventory reports to understand available stock. A bestselling product deserves attention when it is running short. A slow seller needs a different review of demand, margin, and the stock already committed.

Compare units as well as revenue when prices or promotions changed. A discounted collection can sell more items while contributing less sales value per item. That distinction matters when choosing whether to reorder or repeat the discount.

Orders and fulfillment reports answer operational questions about volume, shipping, and delivery. Check them when a sales campaign strains the team’s capacity. Selling more than the team can fulfill reliably can create a service problem that the sales chart does not show.

Retail, profit, and finance

For a store selling in person, retail reports help compare locations, products, and staff sales. Keep online and retail activity separate when investigating a change in either channel. Their customer journeys and operating constraints can differ.

Profit reports require reliable cost information. Shopify’s report guide notes that profit reporting depends on recorded product costs at the time of sale. Missing costs deserve investigation before you use a margin figure to set an advertising budget.

Gross profit also leaves business expenses to consider. Advertising, fulfillment, payment fees, and overhead can change the amount left from a sale. Finance and payment reports serve reconciliation and bookkeeping tasks; sales totals alone do not describe cash received.

Put refund exposure beside sales growth

Check refunded revenue alongside sales before concluding that a promotion or product is performing well. The refund rate here concerns money refunded on the period’s orders. It is different from the share of items returned or orders receiving a refund.

The clothing and fashion median is 2.5%, compared with 0.4% for food and drink. These are category observations, not acceptable-loss targets for an individual store.

A higher refund rate is a reason to investigate the products and orders involved. Look for issues such as sizing, damage, delivery expectations, or a recent promotion. The benchmark cannot tell you which explanation applies to your store.

Allow time for refunds to arrive before assessing a recent campaign. Record when you reviewed its results and revisit the decision if later refunds change the picture. Keep this check separate from the question of whether a customer physically returned an item.

Why do Shopify and other tools disagree?

Different totals often reflect different definitions, dates, or records. Start by aligning those settings before deciding that a report is wrong. Shopify’s analytics discrepancy guidance is a useful reference when reconciling tools.

Check the date range, time zone, currency, sales definition, and treatment of refunds. Compare the same sales channel and attribution view. A store-wide order total and an online traffic report may describe different parts of the business.

Orders recorded by the commerce platform and activity measured in a browser have different limitations. Consent choices, blockers, and tracking configuration can affect browser measurements. A missing visit in a web analytics tool does not establish that the underlying order is missing.

If a gap appeared after a tracking change, investigate that change before making a marketing decision. An older installation and a newer app can send overlapping events. Ask whoever manages tracking to check for missing or duplicate purchases using the current setup guidance.

GA4 is useful when you need custom event analysis, reporting across other sites or apps, or Google advertising connections. It adds configuration and a reporting model to maintain. Choose it because you need those answers, then follow Shopify’s current Google Analytics setup instructions.

When should you add another analytics tool?

Add a tool when you can name an important question your current workflow leaves unanswered or makes costly to answer. Test that question with your store data before committing. A larger report library is useful only when it supports decisions you need to make.

A reporting app might help with a specific export, recurring customer analysis, or a view the team uses often. A separate web analytics tool might help with traffic across a storefront and another site. Those are different requirements, so evaluate them separately.

Write down the required output, who uses it, and how often they need it. Check the available history, filters, sharing controls, and current price. Include setup and ongoing review effort when comparing the options.

For example, By the Numbers provides a report library covering sales, customers, products, and marketing. Its ecommerce reporting overview is a place to assess that fit. Check the particular report before assuming it supports a filter or comparison you need.

During a trial, reproduce a familiar result and investigate a real open question. Ask a colleague to read the output without your explanation. If they cannot tell what changed or what the labels mean, fix the report before automating its delivery.

Finish the review with one action

End the review with an action, an owner, and a condition for checking the result. This can be a test or a request for more evidence. Keep a possible explanation separate from something the reports establish.

Suppose a promoted collection gained orders while its AOV fell. Inspect the discount and product mix, then check margin, stock, and later refunds. You might test a different bundle instead of extending the discount across the collection.

Record the decision in a short note:

• Observation: The promoted collection gained orders while order value fell.
• Possible explanation: More customers bought the discounted entry product.
• Next action: Review basket contents and test a relevant bundle.
• Owner: The person responsible for the collection’s merchandising.
• Review condition: Compare the next completed campaign period and check refunds again.

Share the saved report or checked export with that note. Include the dates and filters so the next review uses the same basis. If you schedule a report through another tool, confirm the delivered output before relying on it.

Keep the dashboard tied to these decisions. Remove cards the team does not use, and retain a small set that leads to useful follow-up questions. The value comes from the action the review supports.

Methodology

These benchmarks use anonymized, aggregated data from Shopify stores in the By the Numbers network. No individual store is identifiable from any figure. Stores that use an analytics app are not a random sample of all Shopify stores, so read the figures as a reference point, not as an average for the whole market.

Related guides

• Create custom Shopify reports when you need a focused saved view.
• Track items sold when units and stock matter more than sales totals.
• Prepare a Shopify client report when someone else needs the results and next decision.

Related guides

More on this topic from the By the Numbers team:

• The New By the Numbers Arrives December 8
• Monthly Ecommerce Report: A Board Pack
• When To Upgrade Reporting Tools In Shopify
• Limited Reporting Tools on Shopify Cost You Later

By the Numbers builds this into the dashboard. See Shopify analytics reporting.