What Is CLTV? How to Calculate Customer Lifetime Value in Ecommerce

CLTV, or customer lifetime value, is what a customer is worth to your brand from the first order to the last. It decides how much you can spend to acquire a customer, which channels deserve budget, and whether a subscription offer is worth its discount. This guide gives the formulas for repeat buyers and for subscriptions, works each one through with numbers, and shows how Shopify, Klaviyo, Stripe and Chargebee calculate it.

What is CLTV?

Customer lifetime value (CLTV, CLV or LTV: the three acronyms mean the same thing) is the total value one customer brings over the whole time they buy from you. A customer who places a 60 USD order and never returns is worth 60 USD. A customer who reorders the same 60 USD product every two months for three years is worth 1,080 USD in revenue. Same first order, very different customer.

If you searched "CLTV" and landed here by mistake: in mortgage lending, CLTV means combined loan-to-value ratio, the total of all loans secured by a property divided by its value. This article covers the ecommerce metric only.

The word "value" hides two choices that change the number completely:

Revenue CLTV is fine for comparing customers with each other. Gross-margin CLTV is the one to put next to customer acquisition cost, because acquisition is paid out of margin, not revenue. Historical CLTV is a fact. Predictive CLTV is an estimate, and only as good as its assumptions. Whatever mix you choose, write it next to the number.

How to calculate CLTV for repeat purchases

For a brand selling one-off orders that customers may repeat, the standard formula multiplies three averages:

CLTV = average order value × purchase frequency × customer lifespan

Average order value and frequency come straight from your order export. Lifespan is the weak input. The 1 ÷ (1 − retention) shortcut assumes the same share of customers comes back every year, forever. A brand less than two years old can't observe that, and a long guessed lifespan inflates CLTV faster than anything else. If you have to guess, use a fixed window instead: "12-month CLTV" is less flattering and much harder to get wrong.

Use net sales, not gross sales: returns and refunds aren't revenue you kept. Count unique customers by email or customer ID, not by order, or guest checkouts will look like new customers every time.

Revenue vs gross-margin CLTV

Revenue CLTV overstates what a customer is worth, sometimes by half. Gross margin per order is what's left after every cost that grows with the order. Here's the 60 USD order from the example:

Keep fixed costs out (salaries, software, rent): they don't change with one more customer. Keep acquisition cost out too, so you can compare CLTV with it. Some guides subtract CAC from CLTV and still call it CLTV; that's a different metric, closer to profit per customer.

How to calculate LTV for a subscription

A subscription has a cancellation date, so lifespan comes from churn. If a constant share of subscribers leaves every month, the average subscriber stays 1 ÷ monthly churn months. That gives the subscription formula:

Subscription LTV = ARPU × gross margin ÷ monthly churn rate

ARPU is average monthly revenue per subscriber. Illustrative example: ARPU of 40 USD, gross margin of 60% (24 USD a month), monthly churn of 6%. The average subscriber stays 1 ÷ 0.06 = 16.7 months. Revenue LTV is 40 ÷ 0.06 = 667 USD, and gross-margin LTV is 24 ÷ 0.06 = 400 USD.

Billing tools publish their own versions:

• Stripe Billing: subscriber lifetime value = ARPU ÷ subscriber churn rate, where ARPU is total MRR ÷ active subscribers. Stripe's example: an ARPU of 500 USD and a 9% monthly churn give 5,555 USD. There's no margin in it, so it's revenue LTV.1Stripe Docs, Billing analytics: metric definitions (ARPU, subscriber lifetime value, subscriber churn rate, retention by cohort)
• Chargebee RevenueStory: LTV = subscription lifetime × average revenue per paid subscription, with lifetime as the inverse of the average churn of the last three months, and churn divided by active paid customers at the end of the month.2Chargebee Docs, How is the lifetime value metric calculated in RevenueStory

The formula's weakness is the churn rate itself. LTV is divided by it, so small changes in churn move LTV a lot:

Three more limits to keep in mind:

• Churn isn't constant. Subscribers leave fastest in the first months, then the ones who stay are stickier. A blended monthly rate mixes both, so the formula can be off in either direction. A cohort table shows the real curve.
• ARPU moves. Upgrades, add-ons and price increases raise it; downgrades and longer delivery intervals lower it. Net revenue retention, covered in gross vs net retention, captures that.
• Very low churn breaks it. At 1% monthly churn the formula assumes a 100-month average lifetime, longer than most brands have existed. Cap the horizon at what you can observe, or use a 24- or 36-month window.

Cohort-based CLTV: what customers actually spent

A cohort is every customer whose first order fell in the same month. Instead of multiplying averages, you add up what the cohort really spent, month after month, and divide by the number of customers it started with, including those who never came back.

Cohort CLTV at month n = cumulative gross margin from the cohort through month n ÷ customers in the cohort at the start

Compare this with the formula. The averages promised 132 USD of margin over 2.5 years; the cohort has produced 72 USD after 12 months. Both can be right, but only the cohort number is observed. Lay several cohorts side by side and you'll see whether newer customers are worth more or less than older ones at the same age, which no single average shows. The full method is in what is cohort analysis.

Shopify builds this table for you. Its customer cohort analysis report groups customers by the date of their first order, lets you choose number of customers, customer retention rate, gross sales, net sales or average order value as the metric, and can show projections of future amount spent per customer, which Shopify notes "aren't a guarantee of future sales."5Shopify Help Center, Customers reports (customer cohort analysis) Stripe Billing does the same for subscriptions, with cohorts by the month a subscriber first generated MRR, and both subscriber and revenue retention.1Stripe Docs, Billing analytics: metric definitions (ARPU, subscriber lifetime value, subscriber churn rate, retention by cohort)

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Historical vs predictive CLTV: how Shopify, Klaviyo and Stripe compute it

Your dashboard probably already shows a lifetime value. Before you act on it, check which kind it is:

Predictive models need data. Klaviyo shows predictive analytics only when at least 500 customers have placed an order, with at least 180 days of order history, orders in the last 30 days, and some customers with three or more orders. It retrains the model at least once a week and warns that predictions "work best when averaged over many customers and are not expected to be exact for any single individual."3Klaviyo Help Center, Understanding Klaviyo's predictive analytics Shopify's predicted spend tier requires a store with over 100 sales and only covers customers who have bought.4Shopify Help Center, Predicted spend tier

So use predicted CLV to rank and segment customers (VIP flows, win-back targets, who gets a discount), not as the input to your acquisition budget. For budgets, use cohort data you have observed.

LTV:CAC and payback

CLTV only becomes a decision when you compare it with what a customer costs to acquire. Two numbers do that:

• LTV:CAC = gross-margin LTV ÷ customer acquisition cost. CAC is acquisition spend for a period divided by new customers in the same period.
• Payback period = the number of months before a customer's cumulative gross margin covers their CAC.

Back to the subscription example, with a CAC of 90 USD:

For the repeat-buyer cohort above, with a CAC of 45 USD, cumulative margin crosses 45 USD between month 1 (39.05 USD) and month 3 (47.30 USD). Its 12-month LTV:CAC is 72.05 ÷ 45 = 1.6, while the formula LTV gives 132 ÷ 45 = 2.9. The gap is the part of the value you're still waiting for. The step-by-step method, with variants, is in the CAC payback formula.

Is there a "good" ratio? Rules of thumb such as 3:1 circulate widely, mostly from software-industry content, without a published dataset behind them or any account of cash timing. A brand with cheap capital and a sticky subscription can grow on a lower ratio; a brand paying for inventory up front may need fast payback whatever the ratio. Track your own ratio and payback by channel and by offer, and watch the trend.

How to increase customer lifetime value

CLTV has four inputs, and each one has its own levers. Work on the one that's weakest in your cohort table.

Two of these levers get underestimated. The first is involuntary churn: a subscriber whose renewal is declined and never recovered stops paying without ever deciding to leave, and every recovered renewal adds a full month to their lifespan. The second is the moment right after checkout: a one-click post-purchase offer raises order value without a second acquisition cost, which lifts CLTV and LTV:CAC at the same time.

Be careful with discounts. A deep first-order discount brings in customers who buy at that price. Compare the cohort it produces with a full-price cohort at month 6 before you call it a win.

Common CLTV mistakes

A few more that don't show up as a pattern:

• Counting new customers twice. Guest checkouts and different emails split one customer into several, which lowers frequency and CLTV. Deduplicate before you calculate.
• Forgetting refunds and chargebacks. Klaviyo nets refunds and returns out of historic CLV;3Klaviyo Help Center, Understanding Klaviyo's predictive analytics do the same in your own numbers.
• Mixing subscribers and one-time buyers. They have different lifespans and different formulas. Calculate each, then weight them by their share of new customers.

Where Tagada fits

Whatever stack you use, the method doesn't change: calculate CLTV on gross margin, check the formula against cohorts, say which tool and which method produced each number, and judge it against acquisition cost and payback, not on its own.