E-Commerce Metrics That Matter: LTV, CAC and Contribution Margin

Revenue is a vanity metric on its own

A store can grow sales every single month and quietly go broke doing it. It happens when each marginal order costs more to win and fulfil than it contributes, and a top-line revenue chart hides that completely. Ad platforms make it worse by reporting ROAS against revenue, a number that flatters everything.

The antidote is three numbers: contribution margin (what each order really earns), customer acquisition cost (what each new customer really costs) and lifetime value (what a customer is really worth over time). None of them needs an analyst or new software. All three fit in one spreadsheet you update monthly, and together they answer the only strategic question that matters: can you afford to grow?

Contribution margin: what an order really earns

Contribution per order is average order value minus every cost that scales with the order. Be ruthless about what counts as variable:

• Cost of goods sold, including inbound freight and duty allocated per unit
• Pick, pack and packaging (yes, including the nice tissue paper)
• The shipping you subsidise: if you charge £3.99 and pay the courier £5.20, that £1.21 gap is your cost
• Payment processing fees, typically in the 1.5% to 3% range depending on provider and card mix
• A returns allowance based on your actual return rate, not your hoped-for one

Contribution margin percentage is contribution per order divided by average order value. This one number sets your advertising ceiling, because break-even ROAS equals 1 divided by contribution margin. At a 40% margin, any ROAS below 2.5 loses money on every order, whatever the platform dashboard is celebrating. Most owners who run this sum for the first time discover their real ceiling is higher than they feared or lower than they assumed, and both discoveries are worth the hour.

CAC without the self-deception

Customer acquisition cost is everything you spent to acquire customers in a period, divided by the number of new customers gained in that period. Two honesty rules keep it useful. First, count new customers only; letting returning buyers into the denominator flatters the figure badly. Second, include all of the spend: ad budgets, agency fees, influencer gifting, affiliate commissions and the discount cost of your welcome code.

Track two versions. Paid CAC (paid-channel spend over customers from those channels) tells you whether campaigns work. Blended CAC (all acquisition spend over all new customers) tells you whether the business works. If blended CAC creeps up towards paid CAC, your organic, referral and repeat engine is weakening underneath the ads, and that is a strategy problem no media buyer can fix.

LTV: measured, not hoped

Lifetime value is the most abused number in e-commerce, usually pressed into service to justify losing money today. Keep it honest by measuring rather than projecting: a practical 12-month LTV is average contribution per order multiplied by the average number of orders a customer places in their first twelve months. Use contribution, not revenue; a £200 revenue LTV on 30% margins is £60 of actual money.

Work in cohorts: everyone acquired in January 2026, tracked forward month by month. Shopify's cohort reports or an app such as Lifetimely will do the tracking automatically, and at small scale a spreadsheet built from an order export works fine. Cohorts also reveal the trend that matters most: whether the customers you acquired this quarter are better or worse than last quarter's.

Three ratios to run the business by

Once the three base numbers exist, the ratios do the strategic work:

• LTV to CAC: the long-standing rule of thumb is around 3:1. Well below that, growth is expensive; far above it, you are probably under-investing in acquisition.
• CAC payback: how many months of contribution it takes to earn back the cost of a customer. Shorter payback means less cash tied up in growth; anything beyond a year is demanding for a small brand's cash flow.
• MER (marketing efficiency ratio): total revenue divided by total marketing spend, the whole-business sense check that survives all the attribution arguments between ad platforms.

Benchmarks vary too much by category for universal targets, but the patterns are consistent. Consumables such as coffee, supplements, beauty and pet food repeat often, so LTV runs at several multiples of first-order value and you can afford to break even, or lose a little, on acquisition. Big-ticket one-off purchases such as furniture must make their profit on the first order, because there may never be a second. Apparel sits in between, with returns quietly eating contribution, so model them explicitly rather than averaging them away.

Build the spreadsheet this week

A workable unit-economics model is four tabs and an afternoon:

• Tab 1, unit costs: every SKU with landed COGS, packaging cost and average shipping subsidy
• Tab 2, orders: a monthly export with AOV, order counts and the new-versus-returning split (Shopify and WooCommerce both report this natively)
• Tab 3, marketing: all spend by month, including fees, tools and discount costs
• Tab 4, outputs: contribution per order, blended and paid CAC, 12-month cohort LTV, and the three ratios
• Review monthly and change one thing each time: raise a price, cut a cost, shift budget between channels, or invest in retention

Once the sheet exists, arguments about whether Meta is 'working' become arithmetic instead of opinion, and pricing decisions stop being guesses. If you would rather have the model built properly and wired to your store data, our analytics team does exactly that.