---
title: "Customer Lifetime Value (LTV) — SealMetrics Glossary"
description: "LTV is the expected total margin from a customer relationship. How it is calculated, why it belongs in order data, and how biased acquisition data skews it."
canonical_url: "https://sealmetrics.com/glossary/customer-lifetime-value/"
lang: "en"
content_type: "glossary"
owner: "content"
llm_priority: "useful"
last_verified: "2026-08-09"
source: https://sealmetrics.com/glossary/customer-lifetime-value/
publisher: SealMetrics
---

Definition

# Customer Lifetime Value (LTV)

The expected total margin a customer generates over the full duration of the relationship, not just the first order. The metric that decides how much you can afford to pay for acquisition.

Quick answer

Customer lifetime value (LTV) is the total margin a business expects from a customer relationship over its whole duration. A common retail formula is average order value × purchase frequency × gross margin × expected customer lifespan; subscription businesses divide margin per period by churn. LTV matters because it sets the ceiling on acquisition cost: a customer worth €300 over three years justifies spend that a €60 first order never would. It is properly calculated from order and CRM data, where a customer identity persists across years — not from web analytics, where cookie identifiers are deleted, blocked or expired within days. Web analytics contributes the acquisition side of the equation: which channels the orders came from. That input is only reliable when it covers 100% of orders, not the consenting fraction.

## How LTV is calculated

The classic eCommerce version multiplies average order value by purchase frequency per year, gross margin, and expected years of relationship. A customer averaging €80 per order, 2.5 orders a year, at 40% margin, retained for 3 years, is worth €240. Subscription businesses use margin per period divided by churn rate. Sophisticated teams compute it per [cohort](https://sealmetrics.com/glossary/cohort/) — customers acquired in the same period, tracked together in the order database — because LTV averaged across all customers hides whether recent acquisition is getting better or worse.

## Why LTV lives in order data, not web analytics

LTV needs an identity that survives years: the same customer recognised across every purchase. Order systems have one — an email address or account. Browser-based analytics does not: cookies are capped at days in Safari, rejected outright by 40-60% of EU visitors, and never shared across devices. Any “LTV” a web analytics tool reports is really per-browser value over a cookie’s lifespan, which systematically undercounts. This is a structural limit, not a vendor flaw — and it is why SealMetrics, which measures anonymously and keeps no per-user identifier at all, does not claim to compute LTV. The order database owns the metric.

## Where analytics data still distorts LTV decisions

The operative question behind LTV is LTV by acquisition channel: which sources bring customers who reorder, so acquisition budget can follow them. The lifetime margin comes from order data, but the channel label comes from analytics — and if that analytics only observed the consenting minority, the join is biased before it starts. Orders whose acquisition source went unmeasured land in a misleading “direct” bucket, and channel-level LTV inherits the distortion. [Revenue attribution](https://sealmetrics.com/glossary/revenue-attribution/) on 100% of orders — last-click, at channel level, no consent dependency — gives the LTV model an acquisition input that reflects all customers, not the measurable ones.

## What LTV does not tell you

LTV is a projection, not a fact: it extrapolates future behaviour from past cohorts, and a pricing change, product shift or churn spike invalidates the history it rests on. It also says nothing on its own about how much profit acquisition generates — that requires pairing it with acquisition cost per channel. And a high average LTV can mask a wide spread where a small group of loyal customers subsidises many one-time buyers.

LTV by channel is only as good as the channel data under it. Feed the model acquisition sources from 100% of orders, not the consenting minority.

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### Related concepts

- [Return on Ad Spend (ROAS) Attributed revenue divided by ad spend. The numerator comes from your analytics and the denominator from the ad platform, so unmeasured conversions understate ROAS and push budget away from channels that were working.](https://sealmetrics.com/glossary/return-on-ad-spend/)
- [Revenue Attribution Connecting revenue events (purchases, subscriptions) to the marketing channels that drove them. SealMetrics uses last-click on 100% of observed events — no per-user journey tracking, no multi-touch models.](https://sealmetrics.com/glossary/revenue-attribution/)
- [Cohort A group sharing a starting characteristic, usually first visit or first purchase period, tracked over time to compare behaviour between groups rather than across a whole audience.](https://sealmetrics.com/glossary/cohort/)
- [Data Loss in Analytics The gap between actual website traffic and what analytics tools report. Caused by consent rejection, ad blockers, browser restrictions, and data sampling. Typically 70-87% in the EU.](https://sealmetrics.com/glossary/data-loss-in-analytics/)

Learn more: [Cookieless Analytics for eCommerce](https://sealmetrics.com/blog/cookieless-analytics-for-ecommerce/) · [SealMetrics Product](https://sealmetrics.com/product/)