Customer lifetime value (LTV) – an introduction
Customer lifetime value (LTV) is the contribution (or margin) made on your service or product, for each customer, throughout their entire relationship.
What is customer lifetime value (LTV)?
LTV is a measure of the margin estimated to be generated from an individual customer from your entire relationship with them.
LTV helps consider the long-term value of a customer’s repeat business. It’s often used in conjunction with customer acquisition cost (CAC) to calculate LTV:CAC ratio. This is often more meaningful as it compares the lifetime value with the cost of customer acquisition.
It’s typically assessed on a 'cohort' basis, where customers are grouped across a common characteristic (month, geography, sector, marketing event etc). The LTV of all customers aggregated avoids customer by customer variations and gives a more meaningful view of customer lifetime value.
While calculating LTV for different cohorts is valuable to decision-making, averaging out LTV is commonplace when forecasting and modelling growth. However, if the population size isn’t big enough then lifetime value conclusions from the data could be misleading.
LTV is often looked at on a historical basis, what did we achieve? And on a forecast basis, what do we expect to achieve? These will likely differ as you're likely considering this because within your forecast you're looking to improve customer lifetime value as you implement new strategies.
Lifetime value can quickly become relatively complex to calculate and understand as there are several ways of calculating LTV, and different views on what should be excluded when calculating contribution/margin.
LTV is also sometimes referred to as CLV - customer lifetime value.
Why is customer lifetime value (LTV) important?
Unless you know how much contribution you will make from each customer, you won’t know how much you can spend on customer acquisition or how aggressively you can grow.
Once you understand your LTV, which in isolation isn't always that useful, you can begin to use it alongside other metrics, such as CAC. Looking at your LTV:CAC ratio will help you monitor how aggressively you can grow your customer base, especially as most fast-growth businesses are loss-making, at least in the early stages of acquiring customers. If your CAC is higher than your LTV, you won't make any money.
A common pitfall is to use revenue as the lifetime value, whereas gross profit (or contribution) is actually the right marker to calculate value.
For example, if LTV is calculated using customer revenue of £100 with a CAC of £50, the business looks profitable. But if gross profit is actually 50%, the real value is £50. With a CAC of £50, the business would make no contribution after the cost of acquiring the customer. In this example, the CAC:LTV ratio is actually 1 which, all other things being equal, would significantly impact the sustainability of the business. In practice, early stage businesses often operate with metrics like this to expand customer base before realising economies of scale.
How can I improve my LTV?
Increasing lifetime value can have one of the biggest impacts on the valuation of a business. There are a number of levers to pull to increase LTV, for example:
Reducing churn/extending customer lifetime/repeat purchase rate
For a SaaS business, reducing monthly churn or extending the number of months a customer is with you will increase overall LTV. In an e-commerce business, the increase of frequency of purchases from customers will also improve LTV.
Increasing your MRR for SaaS businesses, or AOV for e-commerce businesses, will drive a higher absolute contribution (even with the same gross profit %) for each customer.
Increasing gross profit/contribution margin
Contribution margin itself has a number of levers that can be managed but taking it as an input to LTV, if all other things remain equal (sales price, length of customer lifetime etc.), increasing contribution margin each month will increase the lifetime value generated.
Practical examples to improve LTV include focusing on customer experience/support, actively introducing new functionality to move customers to new plans and nurturing customers with other products/services.
How do you calculate LTV?
There are a number of widely accepted formulae to calculate LTV, which have varying degrees of accuracy depending on the size of your dataset and accuracy of your inputs. The formulae below use ARPA in their calculations.
Lifetime value = ARPA × Gross profit % x Customer lifetime
The alternative method uses churn rate:
Lifetime value = ARPA x Gross profit % / Churn rate
In addition to the above, the method most often used in e-commerce businesses that has historic data is:
Lifetime value = CM in month 1 + (CM month 2 x Repeat purchase rate month 2) + … + (CM month n x Repeat purchase rate month n)
Where CM is contribution margin and n is the final, or capped, month of the customer lifetime.
It’s common to cap the long-tail at 36, 48 or 60 months to show the LTV:CAC ratio as a comparable ratio. In practice, the longer the tail, the more valuable impact it will have on the LTV.
LTV worked example
If a company has the following, it’s LTV can be calculated across the two methods as follows:
- ARPA (per month): £800
- Gross profit: 80%
- Customer lifetime: 36 months
- Churn rate: 3.0% monthly
LTV = £800 x 80% x 36 months = £23,040
Or using the alternate approximation method:
LTV = £800 x 80% / 3.0% = £21,333
As mentioned above, lifetime is often capped at 3, 4 or 5 years which can create differences compared to using churn rate, which calculates an uncapped lifetime value. The more data available will give a more accurate churn rate.
Like all metrics, it’s interesting to ask, what can you learn or do from understanding your LTV? Establish the reasons for specific cohorts with high LTV to replicate across other cohorts.
LTV is a key metric used for modelling, predicting future revenue, and understanding how aggressive you can be on acquiring customers. For understanding performance and profitability it should be used alongside other metrics to get most value from it.