Shopify customer lifetime value: what one customer is worth

What lifetime value is

Customer lifetime value (LTV) is the revenue one customer brings you over the time they keep buying. It matters because a first order can look expensive in ads and still be a good one to buy, if that customer comes back. Judging ads on the first sale alone makes anything people reorder look unprofitable.

The simple version is three numbers multiplied together: average order value, orders per year, and the number of years a customer stays. The result is revenue, not profit, so it is a ceiling for what you can spend to win a customer, not a target.

How to work it out

1. Find average order value in your Shopify reports for a period long enough to smooth out sales spikes.
2. Work out orders per year: orders divided by customers over twelve months. Use customers who ordered at least once, not visitors.
3. Estimate years they stay from your returning-customer data. If the store is under a year old, enter 1 and treat anything beyond that as upside.
4. Open the Shopify lifetime value calculator and enter the three numbers.
5. Read lifetime value, orders over that time, and revenue per year.

Worked example

These are example figures, not a real store. A $42 average order, 1.8 orders a year and 2.2 years gives:

• Orders over that time: 1.8 × 2.2 = 3.96
• Lifetime value: $42 × 3.96 = $166.32 of revenue
• Revenue per year: $42 × 1.8 = $75.60

A one-time $42 customer and this customer look the same on the first order. They are worth very different amounts.

Now turn revenue into something you can spend against. If each order leaves $26.98 after product cost, shipping and fees (see the margin guide), the lifetime contribution is 3.96 × $26.98 = $106.84. The first order alone can only support $26.98 of ad cost. The whole relationship supports four times that, though the later orders arrive over years.

You decide how much of that to spend. Say you choose a third of lifetime contribution as a cap. That is a rule you picked, not a standard. It gives $35.61 per customer, above the $26.98 the first order breaks even at. So the first sale loses about $8.60 and later orders repay it. That plan needs cash to wait for the repeat orders and customers who actually return, so it should only be used with real repeat data.

Getting the inputs right

• Average order value. Use a window that includes at least one quiet month and one sale, so a single promotion does not inflate it.
• Orders per year. Count only customers who have had a full year to reorder. A customer who joined last month has not yet had the chance, and including them drags the average down.
• Years they stay. This is the weakest input in any store under two or three years old. Look at how many customers from your oldest cohort bought in the most recent year. If half of them did, an estimate of two years is not unreasonable. If almost none did, use one.

Split new from returning customers if your reports allow it. The blend hides how different they are, and the returning group is the one that tells you how long relationships last.

A second check: if you sell something people use up (coffee, skincare, pet food), compare your orders per year with how long one purchase lasts. A bag that lasts a month implies up to twelve orders a year, and an actual 1.8 means most customers drop out early, which is where the work is.

How to use the number in your ads

• Set two targets. Break-even on the first order (see the break-even ROAS guide), and a looser target you accept only if repeat purchases are proven.
• Cap acquisition cost by lifetime contribution, not lifetime revenue.
• Judge a campaign on its cohort. Look at what customers from a campaign bought in the months after, not just the first order.
• Use it to compare products. A consumable with frequent reorders can justify more ad cost than a durable item bought once.

Ways to raise it

• Raise order value. A bundle or a free-shipping threshold lifts every future order too. See the average order value lesson.
• Raise frequency. Replenishment emails timed to when the product runs out, subscriptions for consumables, and a reason to come back such as a new release.
• Extend the years. Good support, easy returns and fixing the first-order experience. A customer who has a bad first delivery rarely returns.
• Make the second order easy. A product page that works on mobile, saved payment, and an order you can edit after checkout.

Two products, two ceilings

This example uses invented figures to show why LTV changes how you buy ads. Product A is a $42 serum people reorder, at 1.8 orders a year for 2.2 years, leaving $26.98 per order. Product B is a $120 desk lamp that most people buy once, at 1.1 orders a year for 1 year, leaving $55 per order after costs.

• Product A: 3.96 orders, $106.84 lifetime contribution, about $26.98 on the first order
• Product B: 1.1 orders, $60.50 lifetime contribution, about $55 on the first order

Product B has the larger first-order contribution, so it can afford more ad cost on the first sale. Product A has the larger lifetime contribution, so it can afford more over the relationship, provided the repeat orders arrive. Both products are fine at the right acquisition cost. Applying B's logic to A leaves money on the table, and applying A's logic to B loses it.

Common mistakes

• Treating revenue as profit. Multiply by your contribution margin before you set a ceiling.
• Using a long lifespan with no data. A three-year guess for a store that is eight months old is a hope, not an input.
• Averaging everyone. Customers who buy twice are not like customers who buy once. If you can, split them.
• Counting orders from discount-only buyers as repeat customers. If they only come back with a code, the margin on those orders is lower.
• Spending the whole ceiling. Leave room for returns, churn and the cash you have to carry while you wait.

What to check next

LTV tells you how much a customer is worth. To see whether a given campaign recovered its cost, read ROI versus ROAS. To see whether the store is on the right plan for the revenue those customers produce, use the plan comparison guide.

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