CLTV is an important metric because it provides you with a customer-centric perspective to guide some critical marketing and sales strategies of your subscription business, such as acquisition, retention, cross-selling, upselling, and support.

It helps you decide how much to spend on acquisition

Unless you know how much money you can generate from a customer, you wouldn’t know how much to spend to acquire them. In the SaaS industry, on average, companies spend 5 to 7 times more in acquiring customers than what they would spend on retaining the existing customer base.

Before we get into the nitty-gritty, let’s understand what Customer Acquisition (CAC) is. Just as the name suggests, CAC is the amount of money you spend to acquire a customer. According to David Skok, a guideline for SaaS businesses to ensure profitability is to maintain:

LTV > 3x CAC

i.e., the cost of acquiring a customer should be considerably lower than the revenue that will be derived from the customers during the period when they remain subscribed to your service. The math seems elementary, but if you miss the implications, your SaaS business will struggle to generate profits in the long run.

It helps you understand your customer behavior better

You can segment your customer data into different categories based on their ‘lifetime’ values. You can identify customers who are likely to churn early and act proactively. To boost customer retention in specific segments, you can extend special discount rates or offers. Another significant benefit of customer segmentation is that you can use lookalike modeling to acquire more similar and high-value customers.

Types of Customer Lifetime Value

There are various ways to calculate CLV, and you can divide them into these two types:

1. Historical Customer Lifetime Value

Historical CLV calculates a customer’s lifetime value depending on what the customer has spent with a business. There are two ways of calculating historical CLV: using ARPU and using cohort analysis.

This is how you can calculate annual historical CLV using ARPU: (total revenue/number of months in the customer lifetime so far) x 12. It is a relatively simple calculation.

Cohort analysis calculates ARPU per month for all the customers who first signed up in a particular month. It is a visual representation of all variations across the months/years in the customer’s lifetime with your business.

Calculating CLV historically doesn’t take into account customer behaviors, variations, and preferences.

2. Predictive Customer Lifetime Value

The predictive CLV model is more complicated than its historical counterpart. Predictive CLV uses customers’ historical behavior and the predicted retention to estimate future customer lifetime and revenue by applying artificial intelligence and machine learning.

This model, by nature, takes into account customer trends and behaviors throughout the lifetime of customers.

Customer Lifetime Value Calculation

Now that we know the CLV metric’s key role, let’s see how to calculate it. The basic formula for calculating the CLV is:

CLV = ARPU * Gross Margin * Average duration of customer contracts

Or

CLV = ARPU / % Churn

Where,

  • ARPU is the Average Revenue Per User.
  • ARPU (monthly) = Total MRR / Total Active Subscriptions (Users)
  • Gross Margin is simply the revenue after deducting the Cost of Goods Sold (COGS). It is usually expressed as a percentage of total revenue.
  • Gross Margin (%) = (Revenue – COGS) / Revenue

   The average customer contract duration is the average value of how long your customers continue to subscribe to your product or service.

  • % churn is the rate at which you are losing customers.

Source: https://www.chargebee.com/blog/saas-metric-customer-life-time-cltv/#what-is-clv