Evaluating Customer Acquisition: Metrics, ROI, and LTV Calculation

Introduction

Shares the data evaluation system used by FluentSpeak for customer acquisition and the basic calculation process.

How to Evaluate Acquisition

Product Operation Goals

Internet product operation goals usually fall into two categories:

Market share perspective: active user volume.

Commercial efficiency perspective: sales or profit.

As a company grows, the weight of these goals shifts. Early‑stage startups prioritize active users to prove product‑market fit, while later stages focus on sales and profit to ensure long‑term viability.

Acquisition Metrics

Acquisition is the starting point of operations. The two goal categories correspond to the following metrics at the acquisition stage:

New users, retained users.

Acquisition ROI.

For the first metric, from a cohort view:

Retained Users = New Users * Retention Rate .

Focusing only on “new users” can attract low‑quality traffic, causing retention rate to drop while retained users may not increase.

Common solutions: constrain channel quality (e.g., require "Retention Rate ≥ x%") or directly use the "Retained Users" metric.

For the second metric (ROI):

Common definition: Cohort Revenue / CAC . Cohort Revenue is the average cumulative sales per user within the period [T+0, T+n] after acquisition. CAC (Customer Acquisition Cost) is the average cost to acquire a user.

A more comprehensive definition is ROI = LTV / CAC , where LTV (Lifetime Value) is the average lifetime sales per user.

A scalable business model requires that sales growth does not cause ROI to decline; thus ROI is the primary metric for evaluating acquisition efficiency.

LTV

How to Calculate LTV?

From the "order user" perspective

When CAC represents the cost to acquire an "order user", the numerator of ROI should use the order user's lifetime sales. Symbol definitions:

LTV_p denotes the average lifetime sales of an order user .

Assume the i‑th order's average order value is AOV_i , with AOV_0 being the first‑purchase AOV.

Assume the i‑th purchase conversion rate is R_i (i = 0,1,2,…), where R_0 = 100% and for i ≥ 1, R_i is the repeat‑purchase rate after the (i‑1)‑th order.

Each order’s per‑user sales equal R_i * AOV_i . Summing over all orders yields:

Here "per‑user" uses the number of first‑order users as the denominator.

When AOV and repeat rates are stable, we simplify:

AOV_i = AOV (constant) and R_i = R (constant for i ≥ 1). The series reduces to:

Summing the infinite geometric series gives:

This assumption fits single‑price subscription products.

When price or repeat rate varies, handle it by limiting the series until the factor becomes very small and consider a finite number of repeats.

Thus we obtain LTV_p and the ROI for order users as ROI = LTV_p / CAC .

When Only a Portion of Users Are "Order Users"

In many products, only a subset of acquired customers become order users. Symbol definitions:

LTV denotes the average lifetime sales per **all** users, not limited to order users.

C_i is the cumulative proportion of users who convert to order users within [T+0, T+i] days.

C is the lifetime conversion rate, i.e., the proportion of users who ever become order users ( C = C_{∞} ).

From these definitions:

Compared with order‑user LTV, an extra factor C appears. Since C for an infinite horizon is generally unknown, we estimate it via historical regression analysis.

For any positive integer k, fixing the intercept at 0 yields a regression coefficient a_k . Then:

Regression is imperfect because the change rates of the C_0, C_1, … sequence may vary; for example, improvements in conversion can shift later‑day conversions to earlier days, causing C to stay similar while C_k grows, introducing error.

A Typical ROI Calculation Process

Calculate CAC. Sync acquisition costs of each traffic channel to the data warehouse and compute CAC = Cost / New Users .

Calculate LTV_p . For limited repeat purchases, compute multiple LTV_p values along different purchase paths and aggregate them with weights.

If only part of the acquired users become order users, estimate the lifetime conversion rate C via regression, obtain a_k , multiply by the actual cohort conversion C_k to get C , then compute LTV = LTV_p * C .

Calculate ROI using the appropriate LTV from step 2‑3 and the CAC from step 1.

Segment ROI by dimensions (e.g., channel, user segment) to identify high‑return users and prioritize investment.

Summary

In early product stages, focus on user scale; the acquisition metric is "Retained Users". As the product matures, ROI becomes more important.

ROI = LTV / CAC ; accurate LTV calculation is the prerequisite for reliable commercial efficiency assessment.

When only a subset of users are "order users", LTV = LTV_p * C ; estimating the lifetime conversion rate C is essential.

Only with clear ROI per channel and user segment can investment be allocated efficiently.