12 Ecommerce Performance Metrics That Tell You What to Fix Next

The ecommerce performance metrics worth tracking are the ones that point to a specific action: restock this, promote that, fix this page. Most dashboards report dozens of numbers without ranking them by what they cost you. This list keeps 12 metrics and groups them around the three leaks that quietly drain Shopify store revenue: products that get traffic but do not convert, winners that stay buried, and stock that runs out before you reorder.

Store-wide averages tell you something is wrong. Product-level, cart-stage, and inventory-level metrics tell you exactly where and what to do about it. That is the order this list follows.

1. Store conversion rate: a warning signal, not a diagnosis

Store conversion rate is total orders divided by total sessions, multiplied by 100. It is the number most Shopify owners check first, and the least useful for deciding what to fix.

A single blended conversion rate rarely explains what to fix, because conversion rate typically varies by device, industry, and traffic source. A drop in your store-wide rate only tells you to go look somewhere else. our guide to average ecommerce conversion rate by industry breaks the number down by vertical so you know what range is realistic before you chase it.

• A falling store conversion rate with flat traffic usually points to a site-wide issue: broken checkout, payment method outage, or a pricing change.
• A falling rate with rising traffic usually means new visitors are lower-intent (new ad channel, different keyword mix) rather than something being broken.
• Store conversion rate alone cannot tell you which products or pages caused the drop. You need metric #2 for that.

2. Product conversion rate: find what is worth promoting

Product conversion rate is orders attributed to a specific product divided by sessions (or views) on that product's page, multiplied by 100. It is the single most useful metric for deciding where to spend ad budget and merchandising effort, because it isolates performance to one SKU instead of the whole store.

A product converting well above your store average is a candidate for more traffic: featured collections, retargeting, or paid spend. A product converting well below average, especially with meaningful traffic, is either priced wrong, poorly presented, or simply not in demand. Our breakdown of product conversion rate covers how to read it against your catalog average instead of a generic benchmark.

A bestseller with a 6% product conversion rate and a near-identical item converting at 1.5% is not a coincidence. It is a signal to find out why, then act on it.

3. Product traffic: find winners shoppers never see

Product traffic is simply sessions per product page. On its own it says little, but paired with product conversion rate it exposes underexposed winners: products with a high conversion rate and low traffic. Those are the items most likely to generate more revenue if you put them in front of more shoppers, before you spend another dollar acquiring new visitors.

Products with high traffic and low conversion are the opposite problem, covered in metric #4. Sorting your catalog by both numbers at once, rather than one at a time, is what turns this into an action list. This traffic-source breakdown shows how to segment traffic by channel so you know whether underexposure is a merchandising problem or an acquisition problem.

4. Revenue by product: separate volume from profitability

Revenue by product ranks SKUs by total sales dollars in a period. It is easy to read but easy to misuse: a product can rank high on revenue purely because it has been in stock the longest, not because it is your most profitable or fastest-growing item.

• Compare revenue by product against unit margin, not just topline dollars, before deciding what to push harder.
• Look at revenue trend over the last 30 and 90 days, not just the current total, to separate a rising product from one coasting on past momentum.
• A high-revenue product with declining week-over-week sales is often the first sign of a stockout risk or a fading trend, not a stable winner.

5. Add-to-cart rate: spot product-page friction

Add-to-cart rate is the percentage of product-page visitors who add the item to their cart. According to Triple Whale's 2025 ecommerce benchmark data, the global average add-to-cart rate sits around 6.5% to 7.5%, with rates above 8% considered strong and above 10% excellent. (Triple Whale, Ecommerce Benchmarks 2025).

A product page with decent traffic but an add-to-cart rate well under 5% usually has a page-level problem: unclear pricing, weak imagery, missing size or variant information, or a value proposition that does not land. This is a page to fix, not a product to abandon, especially if traffic is already showing interest by landing there.

6. Cart-to-checkout rate: find purchase-intent leakage

Cart-to-checkout rate measures how many shoppers who added an item actually start checkout. This is where genuine purchase intent either advances or stalls, separate from the broader cart abandonment number that lumps in casual browsers who never intended to buy.

Unexpected shipping costs and taxes are a leading reason shoppers stall here, though not the single most common one. The Baymard Institute's ongoing research puts the average cart abandonment rate at 70.22% across 50 studies. In its separate survey on reasons for abandonment, 42% of shoppers cited just browsing or not being ready to buy, and 40% cited extra costs like shipping and taxes being too high. (Baymard Institute, Cart Abandonment Rate Statistics). If your cart-to-checkout rate is meaningfully worse than your industry norm, showing total cost (including shipping) earlier in the flow is the first thing to test.

7. Checkout conversion rate: the final barrier

Checkout conversion rate measures shoppers who start checkout against those who complete it. This stage is heavily influenced by mechanics, form fields, available payment methods, guest checkout availability, and site speed on the final steps, but it is not only mechanics. Payment-method availability, fraud and eligibility checks, shipping constraints, and the underlying offer (price, discount, shipping cost) can also move this number.

• A low checkout conversion rate with a healthy cart-to-checkout rate is worth investigating as a possible technical or UX problem in checkout itself, though it can also reflect a payment, shipping, or offer issue that surfaces only at this stage.
• Offering accelerated checkout options and reducing required fields are two commonly tested fixes at this stage, worth testing rather than assuming they are the cause.
• Track this rate by device separately. Mobile checkout friction is usually worse than desktop and often hides in a blended number.

8. Average order value: the value of each conversion

Average order value (AOV) is total revenue divided by number of orders. It tells you how much each conversion is worth, which matters as much as the conversion rate itself: a lower conversion rate with a higher AOV can outperform the reverse.

AOV varies heavily by category and price point, so compare it against your own trend rather than a blanket industry number. A falling AOV alongside stable conversion rate and traffic often means shoppers are trading down to lower-priced items, which is worth investigating before it shows up as a revenue problem next month.

9. Inventory days remaining: protect future revenue

Inventory days remaining estimates how many days of stock are left at current sell-through velocity. Unlike the metrics above, which explain what already happened, this one is forward-looking: it tells you what will happen to revenue if you do not reorder in time.

A bestseller with 12 days of stock left and a 21-day reorder lead time is already a stockout in progress, even though every other metric on the product page still looks healthy. This is the metric that catches the leak before it shows up as lost revenue in a sales report. Our guide to setting up Shopify inventory alerts and Skymetrics' stock intelligence tools both build workflows around this exact number.

10. Sell-through rate: find slow stock before it goes dead

Sell-through rate is units sold divided by units received, over a set period. It flags the opposite risk from inventory days remaining: stock that is moving too slowly and tying up cash that could fund a bestseller's next reorder.

There is no universal cutoff for a healthy sell-through rate, and no independently verified industry benchmark applies cleanly across categories. Treat 25% over a normal selling season as an internal starting heuristic only, not a published standard, and set your own threshold from your SKU's own historical sell-through and replenishment cycle rather than importing a number from elsewhere. This breakdown of inventory-to-sales ratio walks through how to read sell-through alongside stock value to prioritize which SKUs to act on first.

11. Collection conversion rate: does merchandising help or hurt

Collection conversion rate measures how visitors convert once inside a specific collection page, as distinct from the product page metrics above. It answers a question none of the previous metrics can: is the way you have grouped and ordered products helping shoppers buy, or getting in their way?

A collection with strong individual product conversion rates but a weak collection-level conversion rate usually means the merchandising order is wrong: strong converters are buried below weaker ones, or filters make it hard to reach them. Skymetrics' collection optimization tooling and this guide to Shopify collection optimization both focus on fixing that gap directly, by resurfacing high-converters that are currently buried.

12. Traffic source by product: stop funding weak converters

Traffic source by product breaks sessions down by channel (paid, organic, email, social) for each individual SKU, not just the store as a whole. This is the metric that connects ad spend directly to product-level outcomes instead of a vague blended ROAS.

A product receiving significant paid traffic but converting well below your catalog average is spending budget it is not earning back. Cutting or reallocating that spend toward products with proven product conversion rates (metric #2) is usually a faster fix than trying to improve the weak product's page first.

A weekly metric review that ends with a ranked action list

Checking 12 metrics individually is not a workflow. The point of tracking them is to end each review with a short, ranked list of what to do next, not a longer dashboard. A practical weekly cadence looks like this:

1. Pull inventory days remaining for bestsellers first. Anything inside its reorder lead time goes to the top of the list, before anything else.
2. Cross-reference product conversion rate with product traffic to flag underexposed winners worth promoting.
3. Check traffic source by product for any SKU spending paid budget below your catalog's average conversion rate, and pause or reallocate that spend.
4. Review collection conversion rate for collections where strong individual products are not lifting the collection average, and reorder or re-merchandise.
5. Scan sell-through rate for anything trending toward dead stock, and decide on a markdown or bundle before it ties up more cash.

This is the structure Skymetrics' agents run automatically against a connected Shopify store, turning these 12 metrics into a ranked list by revenue impact rather than a report you have to interpret yourself. Whether you build the review manually in Shopify's native reports or automate it, the metric that matters is the one that tells you what to fix before it costs you a sale, not the one that just confirms it already did. Skymetrics' product analytics applies this same product-and-collection view directly to your store data.