What is LTV?

LTV, or Lifetime Value (Customer Lifetime Value), refers to the estimated amount a customer will spend on your product over the total anticipated duration of their subscription, including renewals.

It lets you estimate the total value of each subscriber based on the revenue they will generate over their "lifetime".

It is a synthetic metric, often used in the following contexts:

• Assessing the profitability of a channel or customer segment
• Tracking the overall performance of a business model (particularly in SaaS or e-commerce)
• Calculating the LTV/CAC ratio, a key indicator to judge whether the acquisition cost is sustainable

Since the total planned duration of a customer's subscription is generally not directly observable, LTV is estimated using your customers' ARPA and churn rate.

How does Fincome calculate LTV?

At each data point date, LTV is calculated using the following formula:

LTV = (Average ARPA over the rolling window) / (Average churn rate over the rolling window)

Concretely:

• Averaged ARPA: Fincome takes the average of the ARPA (Average Revenue Per Account) observed over the X months preceding the data point's date, where X corresponds to the duration of the chosen rolling window.
• Averaged churn rate: in the same way, Fincome takes the average of the churn rate (in value) observed over those same X months preceding the data point's date.

What is the rolling window?

The rolling window defines the number of months over which Fincome calculates the ARPA and churn averages for each LTV data point.

💡 Concrete example: with a 6-month rolling window, the LTV data point on June 30th will be calculated as follows:

• Averaged ARPA = average of the ARPA for January, February, March, April, May, and June
• Averaged churn rate = average of the churn rate for January, February, March, April, May, and June
• LTV on June 30th = Averaged ARPA ÷ Averaged churn rate

The July 31st data point will follow the same principle, but over the February → July window, and so on.

This rolling window mechanism smooths out one-off variations (seasonality, churn spikes, promotions…) and provides a more stable, representative estimate at each date.

Practical example: calculating LTV in SaaS

Let's take an example to illustrate the LTV calculation with a 6-month rolling window, at the June 30th data point.

Here is the data observed over the previous 6 months:

Step 1 – Calculate the averaged ARPA over the rolling window

Average ARPA = (13.00 + 13.10 + 13.20 + 13.30 + 13.10 + 12.90) / 6 = €13.10

Step 2 – Calculate the averaged churn rate over the rolling window

Average churn = (2.8 + 3.1 + 2.9 + 3.2 + 3.0 + 3.0) / 6 = 3.0%

Step 3 – Calculate the LTV on June 30th

LTV = 13.10 / 0.03 = €436.67

The estimated customer lifetime value on June 30th for this SaaS company is therefore €436.67.

The importance of the LTV/CAC ratio

The LTV/CAC ratio (Lifetime Value / Customer Acquisition Cost) is a key strategic indicator in SaaS for assessing the profitability of your acquisition model. It relates:

• LTV: the average value of a customer over their entire lifetime (average revenue generated before cancellation).
• CAC: the average cost of acquiring a new customer, including marketing, sales, tools, and human resource expenses associated with acquisition.

LTV/CAC ratio

Analysis best practices (in Fincome)

• Segment the LTV (by plan, country, industry, acquisition channel) to identify where to invest and where to optimize (pricing, packaging, onboarding).
• Adjust the rolling window according to your context: a longer window stabilizes the indicator against seasonality; a shorter window detects a trend change faster (e.g.: companies with usage spikes, seasonal reactivations).
• Interpret LTV together with GRR/NRR and churn for a complete view of retention and expansion.

FAQ

→ LTV, CLV, CLTV: what is the difference?
None in common usage: these three terms are synonyms for Customer Lifetime Value. Fincome uses LTV for consistency.

→ Why can the LTV vary from one month to the next?
The variations come from:

• changes in ARPA within the rolling window (upsells, discounts, changes in the customer mix),
• the evolution of the churn rate over the same window,
• or seasonality effects entering or leaving the rolling window.

💡 Lengthening the rolling window can reduce these fluctuations in your reporting.

→ What is the rolling window and how to choose it?
The rolling window defines the number of months preceding each data point over which Fincome averages the ARPA and the churn rate. A shorter window (e.g. 3 months) reacts quickly to recent changes; a longer window (e.g. 12 months) smooths out seasonality effects. Choose according to the volatility of your business.

→ Does Fincome's LTV include gross margin?
No, by default. Fincome's standard formula is: LTV = Averaged ARPA (rolling window) / Averaged churn rate (rolling window). You can nevertheless manually calculate a post-margin LTV: Post-margin LTV = (ARPA × gross margin) / churn, for a "post-direct-costs" reading.

→ Which churn is used in the LTV?
The value churn (MRR lost following the termination of a customer's last active subscription), averaged over the selected rolling window — i.e. the average of the monthly churn rates over the X months preceding each data point.

→ Why does my Fincome LTV differ from an internal Excel calculation?
Several possible reasons:

• your Excel uses logo churn (number of customers lost) and not value churn (MRR lost),
• the duration of the rolling window differs (e.g. 3 months vs 6 months vs 12 months),
• the ARPA is not calculated on the same scope (discounts, excluded customers, etc.),
• your Excel uses a single month's churn instead of the average over the rolling window.

→ What to do if my LTV/CAC is low?
Act on the three main levers:

1. Increase ARPA: upsell, cross-sell, pricing optimization;
2. Reduce churn: onboarding, activation, proactive customer success;
3. Improve acquisition targeting: prioritize the segments with the best payback.

These analyses are available in Fincome via analytical segmentation.

→ Edge case: churn averaged over the rolling window ≈ 0%
Mathematically, the LTV tends to infinity and becomes hard to interpret. In this case, lengthen the rolling window and/or complement the reading with GRR / NRR.

Updated on: 03/07/2026