What is Customer Lifetime Value (LTV or CLTV)?

  • SaaS

Customer Lifetime Value estimates the total revenue your SaaS business can expect from a single customer throughout their entire relationship with your company. You calculate LTV by multiplying your average revenue per account by your average customer lifespan.

For example, if customers pay $100 monthly and stay for 24 months on average, your LTV equals $2,400. This metric helps you understand how much you can spend on customer acquisition while remaining profitable.

A strong LTV supports sustainable growth by justifying higher marketing investments. Companies typically aim for an LTV-to-CAC ratio between 3:1 and 5:1. When your LTV reaches $3,000, you can spend up to $600-$1,000 acquiring each customer.

Improving LTV requires focusing on two areas: reducing customer churn through better onboarding and support, and increasing revenue per customer through upgrades and feature expansion.

R&D Offer Quiz

Step 1 of 3

Answer to find out if you're eligible for R&D tax credits.

Do the activities performed relate to a new or improved business component’s function, performance, reliability, quality, or composition?(Required)
For Example: A mid-sized packaging company develops a slightly modified cardboard box design to improve its stacking strength (reliability) for warehouse storage, involving minor adjustments to the corrugation pattern to reduce collapse under standard weight loads.
Is your company trying to discover information to eliminate uncertainty concerning the capability or method for developing or improving a business component?(Required)
For Example: A furniture manufacturer investigates whether a cheaper wood adhesive can hold joints as effectively as the current one during assembly, testing bond strength to resolve doubts about its capability in standard production lines.
Do the activities performed constitute a process of experimentation?(Required)
For Example: An auto parts supplier runs a series of bench tests on different lubricant formulations to find one that reduces friction in engine bearings more effectively, systematically comparing wear rates over simulated operating cycles.