25 Key Ecommerce Metrics to Track in 2026

An ecommerce metric is a measurable data point that shows how part of your online business is performing.

For example, more traffic can produce more sales, but it can also send shoppers into an ecommerce sales funnel that’s already losing them. As Sway Copy Founder Josh Garofalo says, too many businesses spend money trying to “fill their leaky bucket.” 

When there are holes in the sales funnel, patching them makes more sense than bringing in new visitors. Ecommerce metrics help you decide whether to attract more visitors, fix conversion friction, improve retention, or do all three in the right order. This article covers 25 of them to track.

What are ecommerce metrics and KPIs?

Ecommerce metrics are quantifiable data points that help store owners track performance, profitability, and where the business is gaining or losing money across marketing spend, digital customer experience, checkout, customer retention, and inventory.

A metric records something happening in the business, such as website traffic, conversion rate, average order value, return rate, or inventory turnover. On the other hand, a key performance indicator (KPI) is a metric chosen to measure progress toward a specific business goal. So all KPIs are metrics, but not every metric is a KPI. 

For example, website sessions are an ecommerce metric. They become a KPI when increasing qualified web traffic is a defined priority, and the business has set a target and timeframe for it.

Why is tracking ecommerce metrics important for your online business?

According to Statista, worldwide ecommerce revenue was modelled to reach $3.64 trillion in 2025—$2.29 trillion more than in 2017—and is forecast to grow by another $1.41 trillion by 2030.

But a growing market doesn’t guarantee that every online store or campaign is profitable. In a Q4 2025 Shopify survey of store owners,* 42% named ensuring profitability as their top business goal. 

In this context, ecommerce metrics help you determine whether revenue growth is translating into profit. And they also show where to investigate. For example, marketing metrics reveal whether spend attracts qualified visitors, whereas inventory metrics reveal which products sell through and where working capital is tied up.

Diagnose what's happening now

Baymard Institute's meta-analysis of 50 studies puts average cart abandonment at 70.22%. In other words, around 7 in 10 online shopping carts are abandoned before purchase.

You may not realize interventions are blocked if you don't measure them. 

Take the French beauty retailer, Oh My Cream. Their original custom platform required a workaround to aggregate customer data from their online and physical stores. 

They spent years trying to answer a basic question: what’s a customer worth across both channels?

But moving their in-store checkout to Shopify POS finally gave the company a 360-degree view of their customers, which they used to develop a loyalty program around their behavior. Over two years, revenue grew 2.6 times, customer lifetime value increased by 50%, and the average online basket size rose by 25%.

Forecast what happens next

IHL Group puts the annual global cost of inventory distortion—out-of-stocks plus overstocks—at $1.73 trillion, around 6.5% of all retail sales.

The largest single slice, $690.9 billion in out-of-stocks, traces back to failures in demand sensing and planning horizons that are too short. Here, your sell-through rate (STR), product-level sales over time, and inventory turnover can tell you which products earn reorder budget and which are absorbing capital. 

These forecasts can also inform decisions about hiring, advertising budgets, promotions, and cash flow. 

25 essential ecommerce metrics to make more informed decisions 

Shopify’s Analytics overview dashboard organizes its metrics library into categories such as Acquisition, Behavior, and Customers. The wider reports cover areas including sales, marketing, inventory, products, and orders.

The metrics below are drawn from Shopify’s Top 30 most helpful analytics fields and the wider set of metrics available natively in Shopify Analytics reports. They’ve been grouped here by business goal area, so you can focus on the numbers that support your current objective:

Acquisition metrics

Your ecommerce customer acquisition metrics show whether your marketing brings qualified people to your store and converts enough of them into first-time customers at a sustainable cost.

1. Online store sessions

Online store sessions count visits to your storefront, including visits from new and returning shoppers. Shopify treats activity as part of the same session when visits occur less than 30 minutes apart.

Formula: No formula needed. Shopify counts the number of qualifying visits during the selected period.

There’s no meaningful universal sessions benchmark because traffic volume varies with business size, market, season, and marketing budget. But compare sessions with your own previous periods, then segment them by traffic source, conversion rate, and order value. Remember to allot for seasonality when comparing periods. 

Note: On Shopify, sessions only count where visitors consent through the cookie banner. If session counts look unexpectedly low, check that the banner is displaying and functioning correctly.

2. New customer share

New customer share tells you what proportion of a period's revenue came from them, which shows whether growth is arriving from an expanding customer base or from repeat orders off the existing one.

Formula: New customer share = (Revenue from first-time customers / Total revenue) x 100.

The new-to-returning customer mix reads differently depending on whether you're counting people or money. Decile's H1 2026 benchmarks put net new customers at 61% of revenue in home goods and 45% in food and beverage—the only category where repeat buyers generate the majority. 

In Shopify, the New vs returning customers report separates shoppers who placed their first order from those whose order history already contains a purchase. 

3. Customer acquisition cost (CAC)

Customer acquisition cost (CAC) measures the full sales and marketing cost of gaining one new customer.

Formula: CAC = Total sales and marketing costs / Number of new customers acquired.

Polar Analytics’ July 2026 medians put CAC at $36.09 for apparel and accessories, $41.60 for beauty and personal care, $49.90 for food and beverage, and $59.38 for home and garden. The right ceiling still depends on your margins and how much the customer spends after the first order.

4. Cost per acquisition (CPA)

Cost per acquisition (CPA) measures how much a specific campaign or channel spends to produce a defined conversion, usually an attributed order. And unlike CAC, it typically focuses on direct campaign spend rather than the business’s complete acquisition costs.

Formula: CPA = Campaign spend / Number of attributed acquisitions.

Across more than 30,000 ecommerce brands using Triple Whale, the median paid-ad CPA was $32.74 in 2025, up 8.64% from 2024. 

5. Return on ad spend (ROAS)

Return on ad spend (ROAS) compares the revenue attributed to an advertisement or campaign with its advertising cost. This metric helps you compare channel performance, but it doesn’t account for product costs, fulfilment, returns, or wider marketing expenses.

Formula: ROAS = Revenue attributed to ads / Advertising spend.

Polar Analytics’ July 2026 benchmarks ranged from 1.59 times for pet brands and 1.61 times for food and beverage to 4.09 times for apparel and accessories and 5.16 times for consumer electronics.

Conversion metrics

Your conversion metrics show how effectively your online store moves visitors from browsing to buying. Shopify’s Online store conversion report presents this as a funnel report: sessions that land on the store, add a product to cart, reach checkout, and complete a purchase.

6. Bounce rate

Bounce rate is the percentage of online store sessions that end after the visitor views only one page. A high rate can suggest that the landing page, traffic source, or offer does not match search intent, or what visitors expected. Sometimes, however, some single-page visits may still accomplish their purpose and satisfy the customer intent, like providing product pricing or store hours.

Formula: Bounce rate = (Single-page sessions / Total sessions) x 100.

According to data from CXL, the average bounce rate for ecommerce websites is 45.68%.

7. Added-to-cart rate

Added-to-cart rate measures the percentage of online store sessions in which a visitor places at least one item in their cart. This is an early indication that shoppers find the products, prices, and product-page information compelling enough to consider purchasing.

Formula: Added-to-cart rate = (Sessions with cart additions / Total sessions) x 100.

Dynamic Yield reports a global average add-to-cart rate of 6.07%. Their 12-month rolling benchmarks vary considerably by category, from 10.19% for food and beverage to 1.72% for luxury and jewelry. The rate also varies by region and device—EMEA averaged 6.48%, compared with 6.1% in the Americas and 3.16% in APAC. 

Note: Dynamic Yield calculates the benchmark based on items added after product-page views, while Shopify measures sessions with cart additions relative to all online store sessions. 

8. Reached-checkout rate

Reached-checkout rate is the percentage of online store sessions in which a shopper proceeds to checkout. Compare it with the added-to-cart rate to see how effectively your cart moves interested shoppers toward payment.

Formula: Reached-checkout rate = (Sessions that reached checkout / Total sessions) x 100.

In Q2 2026, an average of 4.46% of sessions reached checkout according to DTC Pages, compared with a 5.95% added-to-cart rate. That represents a 25% drop between adding an item and beginning checkout.

9. Shopping cart abandonment rate

Cart abandonment rate measures the percentage of shopping sessions where a product was added to the cart, but no purchase followed. This shows how many sessions with clear purchase intent fail to become completed orders across the cart and checkout stages.

Formula: Cart abandonment rate = [1 − (Completed purchases / Carts created)] x 100.

Baymard Institute's meta-analysis across 50 studies puts the average at 70.22%. That figure has moved very little in a decade. But across 10 years of large-scale checkout testing, they've documented that the average large ecommerce site can gain a 35.26% conversion increase through better checkout process design.

Note: A single blended figure will misdirect you if most of your traffic is mobile. Dynamic Yield, measuring live sessions, reports 80.29% abandonment on mobile against 71.14% on desktop.

10. Online store conversion rate

Online store conversion rate is the percentage of storefront sessions that result in a completed purchase. This gives you the clearest top-level view of how efficiently your store converts its existing traffic into orders.

Formula: Online store conversion rate = (Sessions that completed checkout / Total online store sessions) x 100.

Dynamic Yield reports an average global ecommerce conversion rate of 2.74% over a rolling 12-month window. The performance varies by industry. For example, beauty and personal care averaged 5.37%, while luxury and jewelry averaged 0.71%.

Order value metrics

Your order value metrics show how much revenue each transaction produces, and how much of it survives discounting.

11. Average order value (AOV)

Average order value (AOV) measures what a typical order is worth before post-order adjustments. On Shopify, it reflects gross sales after discounts, but excludes taxes, shipping, and post-order adjustments such as returns, edits, and exchanges.

Formula: Average order value = (Gross sales − Discounts) / Number of orders.

Dynamic Yield reports a global average ecommerce order value of $185 over the past 12 months on a rolling basis. The category averages range from $386 for luxury and jewelry to $63 for pet care and veterinary services. 

Further, desktop orders averaged $255, compared with $164 on mobile, showing why you should compare AOV by device, product category, and customer type rather than relying on one store-wide figure.

12. Revenue per customer

Revenue per customer measures total revenue divided by everyone who bought in the period. Where AOV tells you what an order is worth, this tells you what a customer is worth across however many orders they placed.

Formula: Revenue per customer = Total revenue / Total customers who purchased in the period.

In Shopify Analytics, the corresponding native metric is the amount spent per customer. You can view it in customer cohort analysis to compare how much different customer groups spend over time; Shopify can also project the metric using up to 24 months of store data.

13. Discount rate

Discount rate measures the proportion of gross sales given back through product- or order-level discounts. AOV can rise while discounting becomes less efficient, so review the two together rather than assuming a larger basket always contributes more revenue.

Formula: Discount rate = (Total discounts / Gross sales) x 100.

Shopify reports the monetary value of discounts natively. You can calculate the rate by comparing that amount with gross sales. There’s no single year-round benchmark because discounting changes sharply by category and season.

Retention metrics

Your retention metrics show whether customers come back without you paying to reacquire them, and how much they're worth over the whole relationship rather than the first order. For this category, review these metrics by acquisition cohort and product category. For example, a coffee subscription and a furniture store shouldn’t share the same expectations for repeat buying.

14. Returning customer rate

Returning customer rate measures the percentage of repeat customers, those who have placed more than one order with your business. This gives you a quick view of how much of your active customer base has progressed beyond its first purchase.

Formula: Returning customer rate = (Returning customers / Total customers) x 100.

A 2026 BS&Co analysis of 156,110 DTC customers found that 18.8% placed a second order within 365 days. The rates also varied by what the brand sold: 30% to 40% for consumables, 12% to 17% for fashion, and 10% to 15% for durable goods.

15. Repurchase rate

Repurchase rate measures what share of your customers bought more than once within a defined period. Where returning customer rate tells you the composition of a single period's buyers, this tells you what proportion of your base is re-buying inside a window you set.

But the two metrics move independently. So a store can post a healthy returning customer rate in a strong month while its repurchase rate declines, because a small loyal group is buying repeatedly while most first-time buyers never come back.

Formula: Repurchase rate = (Customers with more than one order in the period / Total customers in the period) x 100.

Decile's H1 2026 benchmarks put supplements at 45%, food and beverage at 34%, fashion and apparel at 25%, home goods at 21%, and health and beauty at 20%. The spread tracks consumption speed; categories people finish and replace re-buy at roughly twice the rate of categories people keep.

16. Purchase frequency

Purchase frequency measures how many orders the average customer places within a defined window.

Formula: Purchase frequency = Total orders / Total customers who ordered in the period.

Decile's H1 2026 benchmarks put supplements at 2.09 orders per customer and food and beverage at 2.0, against 1.43 for fashion and apparel, 1.35 for health and beauty, and 1.27 for home goods. Further, consumables are bought roughly twice in six months; durables are bought once.

17. Customer lifetime value (LTV)

Customer lifetime value (CLV) analysis estimates the total revenue—or, in a margin-adjusted calculation, profit—a customer generates over the full relationship with your business. This connects order value, purchase frequency, and customer lifespan in one forward-looking metric.

Formula: CLV = Average order value x Purchase frequency x Average customer lifespan.

You don't have to crunch this by hand. Ask Sidekick "What's the lifetime value of customers acquired through Google last quarter?"—and it'll pull the calculation from your store data, broken down however you want it. This is worth running monthly to see whether your CAC and CLV are moving in the right direction together.

18. Net Promoter Score (NPS)

Net Promoter Score (NPS) measures how willing customers are to recommend your business. The customers answer on a scale from zero to 10: scores of nine or 10 are promoters, seven or eight are passives, and zero to six are detractors.

Formula: NPS = Percentage of promoters − Percentage of detractors.

The result can range from −100, where every respondent is a detractor, to 100, where every respondent is a promoter. CustomerGauge’s 2025 benchmarks put the typical ecommerce NPS between 40 and 55.

And unlike returning customer rate or purchase frequency, NPS records what customers say they intend to do, so it’s best reviewed alongside actual repeat purchasing and written survey feedback.

Inventory metrics

Your inventory metrics show how quickly stock converts into cash, and how much of it comes back.

19. Sell-through rate

Sell-through rate measures what proportion of the stock you received has actually sold within a period. This is perhaps the cleanest read on whether a buying decision was right, because it compares sales against what you committed to rather than against what's left.

Formula: Sell-through rate = [Inventory units sold / (Inventory units sold + Ending inventory units)] x 100.

Shopify’s product analytics calculates sell-through using the most recent available 30-day period. A healthy sell-through rate is generally 70% to 80% for in-period assortments. For short-life releases, you might need 80% within their launch window, while 40% to 60% can be good for evergreen products measured monthly or quarterly.

20. Inventory turnover rate

Inventory turnover rate measures how many times you sold and replaced your stock across a period. A low turnover means capital sitting still; very high turnover often means stockouts you never recorded, because a customer who can't find the product doesn't generate a data point.

Formula: Inventory turnover = Cost of goods sold / Average inventory value.

The closest primary benchmark is the US Census Bureau's inventories-to-sales ratio. The total business ratio stood at 1.32 at the end of March 2026, down from 1.38 a year earlier. The ratio reads as months of inventory on hand relative to a month's sales, so it inverts into turns: 1.32 implies roughly nine turns a year. 

In Shopify’s inventory reports, you can view your month-end inventory snapshot as well as month-end inventory value.

"We know exactly what we need based on real sales data, so we're not tying up cash in excess inventory or missing sales due to stockouts," says Tyler Angelos, CEO at Angelus Direct.

21. Return rate

Return rate measures what proportion of what you sold came back. This sits in inventory rather than order value because a return is an operational event before it's a revenue event: the unit has to be received, inspected, restocked, or written off.

Formula: Return rate = (Units returned / Units sold) x 100.

NRF's 2025 Retail Returns Landscape, produced with Happy Returns, puts overall retail returns at 15.8% of annual sales, or $849.9 billion—with online sales returned at an estimated 19.3%.

Shopify tracks this natively through reversed quantity, which lets you segment by product, variant, and customer group.

Profitability metrics

Your profitability metrics show what the business keeps after every cost, and whether the money you spend acquiring customers comes back.

22. Gross margin

Gross margin measures the percentage of net sales left after the cost of the goods themselves.

Formula: Gross margin = (Net sales − cost of goods sold) / Net sales x 100.

On Shopify, gross profit and gross margin both require the cost of goods sold to be set up in Shopify to calculate accurately. Use margin as a filter, flagging products below a threshold such as 20% to find where the drag is. 

“Without context, sales numbers don’t mean anything,” says Armine Alajian, founder and CEO of Alajian Group Inc.

“You can have huge sales and still lose money. Show me the numbers: How much did you spend to make that sale?”

23. Net sales

Net sales measure product revenue after discounts and sales reversals such as returns. This gives you a clearer picture of earned product revenue than gross sales, which reflects full-price demand before those adjustments.

Formula: Net sales = Gross sales − Discounts − Sales reversals.

The amount depends on company size and category. Compare net sales with previous periods and gross sales. If gross sales rise much faster than net sales, discounts or returns may be absorbing more revenue. 

24. Profit margin by order

Profit margin by order shows how much of an individual order’s revenue remains after relevant order-level costs. Shopify’s Profit margin by order report can account for product and shipping charges, duties, import taxes, product costs, shipping costs, and duties or import taxes paid by your store.

Formula: Profit margin by order = [(Order revenue − Associated order costs) / Order revenue] x 100.

Shopify’s Average profit margin by market report lets you compare international markets with your domestic market, then drill down to individual orders.

25. LTV-to-CAC ratio

The lifetime-value-to-customer-acquisition-cost ratio compares the revenue a customer is expected to generate over the relationship with what it cost to acquire them. This connects the acquisition and retention metrics you’ve already calculated.

Formula: LTV-to-CAC ratio = Customer lifetime value / Customer acquisition cost.

The standard target is 3:1, but measured data in 2026 sits well below it. Decile's H1 2026 benchmarks put home goods at 2.55, fashion and apparel at 2.47, supplements at 2.12, health and beauty at 2.03, and food and beverage at 0.6. 

For a stricter profitability view, calculate lifetime value using gross profit rather than revenue. A revenue-based ratio can look healthy even when low margins leave little money after product costs.

How do ecommerce metrics work together?

No single metric can explain whether an ecommerce business is getting healthier. For example, Contentsquare’s 2026 Digital Experience Benchmark Report, across 99 billion sessions on more than 6,500 websites, found that visits fell 3.8%, engagement fell 10%, and conversion rates fell 5.1%. 

Yet average order value rose 6%, helping revenue remain broadly stable. Meanwhile, 13% of visitors returned within 30 days. 

A more useful approach is to read the metrics in sequence. For example: 

• Revenue shows the outcome, but not what produced it.
• Customer acquisition cost shows what you paid to bring in each new customer.
• Conversion rate shows how efficiently traffic became orders.
• Average order value shows what each transaction generated.
• Revenue per visitor (RPV) combines conversion and order value to show how much each visit was worth.
• Customer lifetime value estimates the value a customer may generate over the full relationship.
• Retention shows whether customers actually return and create that longer-term value.

For example, revenue can grow while conversion falls if AOV increases enough to offset the decline. That may still be healthy, but only when acquisition costs and margins remain controlled. If CAC rises at the same time and retention weakens, the store is paying more for customers who are less likely to become profitable.

More established ecommerce store owners tend to monitor this broader picture. A Q4 2025 Shopify survey* found that store owners generating more than $1 million in revenue commonly tracked revenue (85%), profit margin (57%), average order value (52%), cash flow (51%), growth rate and ROAS (44% each), conversion rate (43%), and NPS (25%).

“For example, if your goal is to increase revenue, key indicators might include conversion rate, average order value, and customer acquisition cost,” says Mark Hayes, director of Communications at Shopify. 

Read more about the ecommerce sales funnel and the metrics to track, the over 70 essential ecommerce KPIs for growth, and the top 15 ecommerce growth metrics.

Build an ecommerce metrics dashboard or report

Shopify's built-in Analytics helps you make better decisions faster with more than 60 pre-built dashboards and reports, plus Sidekick for asking questions in plain language, metric targets to track your goals, and Insights that flag trends proactively.

A dashboard tells you what changed; a report helps you investigate why. In a Q4 2025 Shopify survey*, 77% of store owners said they track sales or total revenue, making it the most commonly monitored metric. Yet fewer than half said they track profit margin, traffic, average order value, or conversion rate. 

While revenue belongs on your dashboard, it needs supporting metrics to show whether ecommerce growth is profitable and likely to continue.

Start with a small dashboard tied to your current objective. Customize Shopify’s Analytics overview dashboard by adding, removing, resizing, and rearranging metric cards. You can also organize cards into labelled sections, compare date ranges, and open any card’s corresponding report for a deeper view. The dashboard is updated within about one minute, making it useful for monitoring recent changes without rebuilding the same analysis each time. 

Your reporting should become more specific as the business grows. An early-stage store may only need to compare sales, sessions, and conversion week over week. Once it invests heavily in acquisition, the same dashboard should bring CAC, ROAS, gross margin, and LTV into view. 

"We created custom reports that show us exactly how our Charleston store is performing compared to our other sales channels. This visibility helps us monitor sweet spots in store traffic, determine optimal staffing levels, and make data-driven decisions about everything from inventory to store hours,” says Kenny Haisfield, founder at Kenny Flowers. 

A multichannel or international business may then need reports segmented by market, channel, product, location, and customer cohort.

Shopify Sidekick can help build those reports without requiring you to write the query from scratch. Ask a question in everyday language, such as which traffic source converted best, and Sidekick can generate or refine a ShopifyQL report and visualization. 

Shopify’s Winter ’26 Edition expanded this capability with custom analytics reports and data visualizations directly in the ShopifyQL query editor. Sidekick Pulse goes further, delivering recommendations and next steps based on your store's data rather than waiting to be asked.

Start with Shopify-native analytics so sales, customer, inventory, order, and profit data share the same underlying commerce record. Shopify App Store analytics tools can be useful later when you need specialist attribution, forecasting, experimentation, or reporting across systems that sit outside Shopify.

How often should I check my ecommerce metrics?

The answer depends on your store size, traffic volume, whether you’re running campaigns, and your business model. For instance, a high-volume retailer running a promotion may need to monitor performance throughout the day, while a smaller store with steadier demand may learn more from weekly trends.

Use a cadence that matches how quickly each metric can change and how soon you could act on it:

• Daily works for operational metrics like sessions, orders, revenue, and inventory alerts. 
• Weekly or monthly suits conversion rate, average order value, and add-to-cart rate.
• Quarterly is right for retention, lifetime value, cohort behaviour, and margin; Decile's data, for example, shows categories clustering indistinguishably at three months and separating clearly at six.

Campaign periods are the exception. During BFCM or a product drop, hourly monitoring earns its place because you can still act: fix a broken discount or reallocate inventory. Shopify's date and time filters now go down to the minute for exactly this.

*Based on a 2025 survey of 500 Shopify merchants conducted in English across Australia, Canada, the United Kingdom, Ireland, New Zealand, and the United States. Respondents were established merchants with two or more years on the platform. Results reflect the experiences of this specific sample and may not be representative of all merchants.