Ecommerce metrics that matter are the ones that connect directly to profit and to a decision you can make: conversion rate, average order value, contribution margin per order, customer acquisition cost, repeat purchase rate and customer lifetime value. Traffic, followers and impressions are useful context, but they cannot tell you whether the store is healthy on their own.
A defensible metric has a clear definition, a consistent data source and a known link to money. The sections below define the core set and show how they fit together.
Which numbers form the core set?
Revenue can be broken down into a simple equation: sessions multiplied by conversion rate multiplied by average order value. Profit adds margin and costs. Almost every useful ecommerce metric is part of this equation or explains one of its parts.
- Sessions: visits to the store, from your analytics tool
- Conversion rate: orders divided by sessions
- Average order value (AOV): revenue divided by orders
- Contribution margin per order: revenue minus product cost, shipping, payment fees and returns, per order
- Customer acquisition cost (CAC): marketing spend divided by new customers
- Repeat purchase rate: share of customers who place a second order within a set period
- Customer lifetime value (LTV): margin a customer generates over a set period
How should conversion rate be measured?
Conversion rate looks simple but is often measured inconsistently. Decide whether you count sessions or users, and stick to it. Exclude internal traffic and bots. Break it down by device and traffic source, because a store-wide average hides big differences: mobile traffic from social media usually converts differently from desktop traffic from branded search.
For deeper diagnosis, use a funnel: product page views, add to cart, checkout started, purchase. In Google Analytics 4, the ecommerce purchase funnel report shows these steps if ecommerce events are set up. In Shopify, the Analytics section shows sessions converted, added to cart and reached checkout.
Why is contribution margin more important than revenue?
A store can grow revenue while losing money on every order. Contribution margin per order shows what is left after the direct costs of fulfilling that order. It is the number that tells you how much you can afford to spend to acquire a customer.
As an example with clearly made-up numbers: an order of 60 USD with 22 USD product cost, 7 USD shipping, 2 USD payment fees and an average of 3 USD in return costs leaves a contribution margin of 26 USD. If acquiring that customer costs 30 USD in ads, the first order loses money, and the business depends on repeat purchases to make a profit.
How do CAC and LTV work together?
CAC tells you what a new customer costs; LTV tells you what that customer is worth over time. The ratio between them, and how long it takes to recover CAC, are central to deciding how much to spend on growth.
Calculate LTV on margin, not revenue, and over a fixed window such as 12 or 24 months, rather than an open-ended “lifetime”. Use actual cohort data: group customers by the month of their first order and track how much margin each cohort generated over time. Projections without cohort data are often too optimistic.
- Blended CAC: all marketing spend divided by all new customers
- Paid CAC: paid media spend divided by customers from paid channels
- Payback period: months until cumulative margin from a cohort exceeds its CAC
Which metrics often mislead store owners?
ROAS reported by ad platforms is the most common example. Each platform credits itself for conversions, often counting the same order more than once across channels. Add up platform-reported revenue and it may exceed your actual revenue. Use your own sales data and a consistent attribution approach to judge channels, and look at blended metrics such as total marketing spend divided by total revenue (sometimes called MER).
Average order value can also mislead. Raising AOV with a free shipping threshold can increase order size while reducing conversion rate. Always check AOV and conversion rate together.
Bounce rate and time on site have weak links to revenue. They can help diagnose a specific page, but they should not be targets.
How should metrics be reported?
Keep one dashboard with the core set, reviewed weekly, and a monthly view with cohorts and LTV. Show each metric with the same definition every time and a comparison against the previous period and the same period last year, because seasonality affects almost every ecommerce store.
- Weekly: sessions, conversion rate, AOV, revenue, ad spend, MER
- Monthly: contribution margin, new vs returning customers, CAC, repeat rate
- Quarterly: cohort LTV, payback period, return rate by product
A note column for events such as promotions, stockouts or site changes makes the numbers much easier to interpret later.
Which supporting metrics help explain changes?
The core set tells you what happened; supporting metrics help explain why. Cart abandonment rate and checkout completion rate point to friction in checkout. Return rate by product reveals listing or quality problems. Stock availability, measured as the share of top products in stock, explains many sudden conversion drops. Site speed matters too: Google’s Core Web Vitals use thresholds such as a Largest Contentful Paint of 2.5 seconds or less for a good experience, and slow product pages tend to lose mobile shoppers.
- Checkout completion rate: purchases divided by checkouts started
- Return rate by product and reason
- In-stock rate for the top 50 products by revenue
- Core Web Vitals for product and category templates
Setting targets that teams can act on
A metric only helps when someone owns it and can influence it. Assign each core metric to a person: conversion rate to whoever runs the site and merchandising, CAC to whoever runs paid media, repeat rate to whoever runs email and retention. Set targets as ranges based on your own history, not on generic industry benchmarks, which vary too much between categories and price points to be useful.
Review targets every quarter. If a target is always met easily, it no longer guides decisions; if it is never met, the team stops paying attention to it.
Getting the data foundations right
Most metric disputes come from data, not from strategy. Make sure the store platform, analytics tool and finance system agree on what an order is: whether cancelled orders, test orders and refunded orders are included, and which date is used. Write these rules down once and apply them in every report.
Where to start this week
Write the definition and data source for each metric in the core set on one page. Then calculate contribution margin per order for last month, including returns and payment fees. This single number often changes how a team thinks about ad budgets.
Next, build a simple cohort table: customers grouped by first-order month, with cumulative margin per customer at month one, three, six and twelve. Use it to set a maximum CAC that the business can support, and share it with whoever manages paid advertising.