LTV
LTV is the total revenue — or, more usefully, contribution margin — a customer generates across their full relationship with your store. It sets the ceiling on CAC.
LTV (Lifetime Value)
Total revenue or contribution margin a customer generates over their full relationship with your store.
LTV — Lifetime Value, sometimes written CLV or CLTV — measures the cumulative value a customer delivers from first order to last. In online retail it is usually expressed as revenue per customer, but the more defensible version is contribution-margin LTV: revenue minus COGS, payment fees, shipping, and returns. That is the number that can actually fund acquisition.
LTV is most useful when broken down by acquisition cohort, channel, or first product purchased — not as a single sitewide average. A blended LTV hides the fact that paid-social buyers, email subscribers, and search visitors behave very differently over 12 months.
The reason LTV matters is simple: it is the ceiling on what you can spend to acquire a customer. If a buyer is worth €120 in contribution margin over two years, paying €90 in CAC leaves €30 to fund overhead and growth — paying €130 quietly destroys value, even if the first order looks profitable.
Most teams overstate LTV because they extrapolate from a small number of loyal repeat buyers. A cleaner approach is to track LTV by monthly acquisition cohort and let the curve mature — 30-day, 90-day, 12-month — so paid teams can bid against a number that has actually been observed, not one projected from a best-case retention assumption.
LTV = AOV × Purchase Frequency × Gross Margin × Customer Lifespan
AOV
Average Order Value
Average revenue per order across the cohort.
Purchase Frequency
Orders per year
How many times an average customer orders in a year.
Gross Margin
Contribution margin %
Revenue minus COGS, fees, shipping, and returns, expressed as a decimal.
Customer Lifespan
Active years
Average number of years a customer continues to purchase.
A Shopify apparel brand calculating 2-year LTV for its paid-social cohort.
AOV: €75
Purchase Frequency: 1.8 orders/year
Gross Margin: 0.55
Customer Lifespan: 2 years
→ €148.50
With LTV at roughly €149, this cohort can sustain a CAC up to about €50 to hit a healthy 3:1 LTV:CAC ratio. Anything above €75 starts eroding the contribution after acquisition costs.
Segment before you average. LTV varies dramatically by first-touch channel, first product SKU, and discount depth at acquisition — customers acquired through a 30%-off welcome code rarely match the lifetime value of those who paid full price. If your platform supports it, model LTV by acquisition month and channel, then compare against blended CAC for the same window.
Typical 12-month contribution-margin LTV by vertical and AOV tier
| Vertical | AOV €30-60 | AOV €60-120 | AOV €120+ |
|---|---|---|---|
| Beauty & skincare | €55-90 | €110-180 | €220-380 |
| Apparel & accessories | €45-75 | €95-160 | €180-320 |
| Home & lifestyle | €35-65 | €85-140 | €160-280 |
| Consumer electronics | €25-50 | €60-110 | €120-220 |
| Food & supplements (subscription-leaning) | €90-160 | €180-300 | €340-560 |
Subscription-leaning categories like supplements and coffee sit at the top of the table because repeat cadence is structural, not earned each time. Electronics sit lowest because replacement cycles are long and customers tend to comparison-shop on the next purchase. Use the table as a sanity check on your own cohort curves — if your 12-month LTV is materially above the band, confirm you are using contribution margin, not gross revenue.
Frequently asked questions about LTV
3:1 is the widely cited healthy target — three euros of lifetime contribution margin for every euro of acquisition cost. Below 2:1 you are likely under-pricing or over-spending on paid; above 5:1 you are probably under-investing in growth and leaving market share on the table.
Contribution-margin LTV is the defensible number for budgeting CAC, because that is the cash actually available after COGS, payment fees, shipping, and returns. Revenue LTV is fine for trend tracking but will overstate what you can afford to pay for a customer.
Pick a window your cohorts have actually completed. 12-month LTV is the most common operational number because it lines up with annual planning and most retention curves flatten by then. 24-month LTV is more accurate but you can only measure it on customers acquired two years ago.
A sitewide average mixes high-value repeat buyers with one-and-done discount-code customers, and it shifts as your channel mix changes. Cohort LTV — by acquisition month and channel — gives you a number that paid teams can actually bid against.
Deeply discounted first orders consistently produce lower LTV than full-price acquisitions, often 20-40% lower over 12 months. The discount also eats directly into contribution margin on order one, so the gap between revenue LTV and margin LTV widens for these cohorts.
Yes — LTV, CLV, and CLTV are used interchangeably and all refer to Customer Lifetime Value. Some teams reserve CLV for a predicted/modelled value and LTV for the observed historical number, but there is no industry-wide convention.
Use ARPU × gross margin ÷ monthly churn rate as the steady-state approximation. For example, €25 monthly ARPU at 60% margin and 5% monthly churn implies an LTV of about €300. Validate this against actual cohort curves once you have 6-12 months of data.
Partially. First-order AOV, product category, and acquisition channel are strong early signals. Most teams build a simple model that segments new customers into 3-4 predicted-LTV bands within 30-60 days of first purchase, then use those bands to tier post-purchase flows and paid bidding.
LTV is the long-horizon counterpart to AOV, purchase frequency, and retention rate — it rolls them up into a single euro figure. It sits opposite CAC on the unit-economics ledger, and together LTV and CAC determine whether your acquisition spend is building or destroying value.
Refresh cohort LTV curves monthly so paid teams have a current bidding ceiling, and review the full LTV model quarterly when margins, shipping costs, or return rates shift. Major changes to product mix or pricing should trigger an immediate recalculation.
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