136 terms from Ecommerce and CRO, each defined in a sentence or two, with a link to the calculator that works the number out where one exists.
Carts divided by product views. The first honest intent signal.
Change in average order value over time. The growth input you do not have to buy.
Open the calculator →Units divided by orders. One of two levers behind order value.
Open the calculator →Which products get bought together.
How basket composition changes profitability, not just revenue.
The early stage where people look without intent to buy today.
Another name for the same measure.
Orders cancelled before fulfilment.
The share of carts never taken further. Normal is high, so track the trend rather than the level.
What happens between adding to cart and starting checkout.
Improving the step where people review before paying.
The share of carts that start checkout.
Profitability by category rather than product.
Margin across a product group. Usually where the real differences hide.
The inverse of the above.
The share of started checkouts that finish. Shipping cost surprises kill more sales here than anything else.
The steps inside checkout. Every extra field costs completions.
Removing friction between intent and payment.
Testing steps and fields in the checkout. Test carefully, because a broken checkout costs real money.
Open the calculator →How the checkout feels to use. Small friction here is expensive.
A visual of where people click on a page.
The same after cost. Shows whether newer customers are worse than older ones.
Revenue from a group defined by when they first bought.
Money lost when existing customers downgrade.
Improving the share of visitors who buy, instead of buying more visitors.
Open the calculator →A visible deadline. Effective once, corrosive when it resets on refresh.
The share of issued codes actually used.
How often a related product gets added.
Revenue from selling adjacent products.
How long since they last bought. The strongest single predictor of buying again.
The share of customers still active at the end of a period.
Open the calculator →Splitting customers into groups worth treating differently.
Inventory turnover expressed as days rather than a count. It answers how long the current stock would last at the present rate of sale, which is the version people can actually act on.
Open the calculator →The same online, driven by rules and data rather than shelf space.
How much is taken off. Depth costs margin faster than frequency does.
Open the calculator →Margin after discounts have been applied.
The share of orders sold at a reduced price.
How often people take a cheaper alternative after refusing the first.
Revenue saved by offering something cheaper instead of losing the sale.
Selling online. The whole discipline this category describes.
What is left after goods, shipping, processing, returns and acquisition are paid.
Open the calculator →The same, specifically for email.
Detecting someone about to leave and interrupting them.
Extra money from existing customers through upgrades or add-ons.
Open the calculator →The inverse. Usually a field-count problem.
The order value that unlocks free delivery. Works best set ten to twenty percent above current average order value.
Open the calculator →The share of free users who upgrade.
A visual of attention or interaction across a page.
How many times you sell through and replace your stock in a year. Calculated from cost of goods sold divided by average inventory, never from revenue, because revenue carries margin and inventory does not.
Open the calculator →Another name again. Agree which one your team uses.
The retail habit of doubling the wholesale cost to set the shelf price, giving a 50 percent margin. A starting point rather than a method, since it ignores freight, payment fees and returns.
Open the calculator →Improving the first page traffic lands on. The cheapest lever in most accounts.
Open the calculator →Lifetime value against acquisition cost. Three to one is the common target, and it means little without payback period next to it.
Open the calculator →Deciding what to show, where and in what order.
Margin after merchandising decisions such as placement and bundling.
A first-time buyer. Costs the most to win and is worth the least so far.
Open the calculator →Testing what you sell rather than how it looks. Usually the bigger lever.
Open the calculator →The internal search box. Users who use it convert far better, and most sites ignore it.
Someone who bought once and never returned. The majority, in most stores.
Orders divided by distinct visitors.
What is left after processing fees.
How paying feels, including which methods are offered.
The share of people who complete a pop-up. Judge it against the sessions it disrupted, not on its own.
A forecast of what a customer will be worth, based on early behaviour.
Open the calculator →Testing price points. Highest impact and highest risk of any test you can run.
Open the calculator →The same relationship at product level, used for cross-sell logic.
How people find products they were not searching for.
The share of visitors who reach a product page at all.
The path from product view to purchase.
Improving the page where the buying decision happens.
How people find products they were.
Product views divided by sessions.
The extra sales a promotion caused, over what would have sold anyway. Usually smaller than it looks.
How much of revenue comes from promoted sales.
Purchases divided by intent signals.
A dormant customer who came back.
Revenue from customers who came back after lapsing.
The price a manufacturer suggests a retailer should charge. It anchors discounting and protects channel margins, but it is a suggestion, not an obligation, in most markets.
Open the calculator →The share of customers on a repeat schedule.
Predictable income you can plan around.
The share of customers who bought again. The strongest predictor of lifetime value.
Open the calculator →Revenue from customers who already bought.
Margin after returns and the cost of handling them.
The share of orders sent back. Applied after revenue and before margin, and routinely forgotten in ROAS targets.
Open the calculator →Someone buying again. Cheaper to serve and more profitable.
A combined score from recency, frequency and monetary value. Simple, and it beats most complicated models.
Limited availability as a reason to decide. Damaging when invented.
How far down people get. Content below the drop-off point may as well not exist.
The share of received stock that sold in a period. A high rate suggests you are buying too cautiously, a low one that capital is sitting on shelves instead of working.
Open the calculator →A replay of an individual visit. Useful for finding bugs, dangerous for drawing conclusions.
What is left after delivery cost. Frequently negative on small orders.
The full journey from browsing to checkout.
The same at individual variant level. Where unprofitable sizes and colours get found.
The share of buyers who choose the subscription option.
Someone on a recurring plan rather than buying one at a time.
Revenue on a recurring schedule.
The share of trials that become paying customers.
The same measure, said differently.
Elements reassuring a stranger it is safe to pay you.
The same measure, usually in physical retail.
Revenue from moving customers to a higher tier.
A reason to act now rather than later.
Structured testing of whether the interface works.
Watching real people attempt a task.
A high-value repeat buyer. Usually a small share of customers and a large share of profit.
Evidence other people already bought and were fine.