LTV for Subscription Business - Understanding and Calculating Customer Lifetime Value

For subscription-based businesses, understanding and harnessing the power of Customer Lifetime Value (LTV) is vital for long-term success. LTV is a metric that not only measures the financial value of your customers but also serves as a crucial tool for forecasting revenue and making strategic decisions. In this article, we will delve into what LTV is, its significance in subscription businesses, how to calculate it, and how to use it for projecting future revenues.

LTV for Subscription Business

Customer Lifetime Value (LTV) is a metric that quantifies the total revenue a business can expect to earn from a customer over their entire subscription period. In the context of subscription businesses, LTV measures the monetary worth of a customer over the entire duration of their subscription, assuming they stay subscribed for a particular period.

The formula for calculating LTV in a monthly subscription model can be expressed as follows:

LTV = (Monthly Revenue Per Customer x Average Customer Lifespan)

Here's a breakdown of the components:

• Monthly Revenue Per Customer: This represents the average monthly revenue generated from each customer. 
• Average Customer Lifespan: This is the average number of months a customer stays subscribed before churning (cancelling their subscription).

Why LTV is Important for Subscription Business

LTV is crucial for subscription businesses for several reasons:

1. Decision Making: LTV provides valuable insights for making strategic decisions. It helps identify the most profitable customer segments, allowing businesses to allocate resources effectively.
2. Churn Mitigation: By understanding how long customers typically stay subscribed, businesses can take proactive measures to reduce churn. Reducing churn is often more cost-effective than acquiring new customers.
3. Pricing Strategies: LTV helps determine optimal pricing strategies. Businesses can set subscription prices that align with the value they provide to customers, maximizing revenue without driving away subscribers.
4. Customer Acquisition: LTV aids in evaluating the cost of acquiring a new customer. Knowing the LTV allows businesses to make informed decisions about marketing and customer acquisition budgets.
5. Growth and Forecasting: LTV plays a critical role in projecting future revenue and growth. It helps businesses make more accurate financial forecasts and set realistic growth targets.

How to Calculate LTV for Subscription Business

Calculating LTV for subscription businesses requires a deep understanding of customer behaviour and subscription dynamics. Let's break it down step by step 

Step 1: Gather data

Total_monthly_revenue = Total Money EarnedTotal_month_active_customers = Total Active Customers

Step 2: Calculate Monthly Revenue Per Customer

Calculate Monthly Revenue Per Customer

Monthly_revenue_per_customer = Total_monthly_revenue / Total_month_active_customers

Step 3: Determine Average Customer Lifespan

Calculate Average Customer Lifespan

Churn_rate = (Number of customers churned / Total_customers_last_month) # Churn rate as a decimalAverage_customer_lifespan = 1 / churn_rate # Average customer lifespan in months

Here number of customers churned is customers who were active in the last month but did not continue the subscription in the current month.

Step 4: Finally Get LTV

Calculate LTV

LTV = monthly_revenue_per_customer * average_customer_lifespan

With these steps, you can calculate LTV for your subscription business. It's essential to periodically update this metric as customer behaviour and business dynamics change over time.

#This method is a pretty simple way to calculate the LTV.

Advanced & Accurate LTV Calculation

One issue in the above method is that the churn rate is considered the same for the whole active customer base. This assumption though is not always correct. The impact of the same will be lowest if the addition of new customers have been similar for last 6 or more months. 

In a scenario where there has been a drastic increase or decrease in customer addition in the last few months, the effective churn rate might be different. If less subscription customers have been added lately the overall churn rate will be lower, if new customers have been added lately the overall churn rate will be higher. In such cases the cohort of the customers should be created and churn should be calculated. 

Overall Retention in that case will be 

Overall Retention = (New Users added in month * new users retention) + (1 month ago addition * retention of 1 month cohort) + (2 month ago addition * retention of 2 month cohort).... / Total Users

And churn is (1 - retention). Lets take an example - 

Say there are 100 new customers in a particular month. And next month 20 of them have cancelled their subscription. So here the retention will be = 80/100 as there were 80 customers active after the Month 1. It can be written as 0.8

And the churn will be 1-0.8 = 0.2 as 20% of the users did not renew their subscription, hence the churn.

The retention for new users, 1 month cohort and so on; can be calculated using heuristics data. Here is the simple way to calculate it. 

Keeping the users in cohort - 

1 month retention = 1 / (New Customers in 1 month cohort / Number of customers active in consecutive month)1 month retention = Number of customers active in consecutive month / New Customers in 1st month cohort

Similarly retention rates can be calculated for all the months and a more accurate overall retention rate can be calculated.

In this case the LTV can be calculated as - 

Overall LTV = (1st month revenue) + (1 month retention rate * 2nd month revenue) + (1 month retention rate * 2nd month retention rate * 3rd month revenue) …

Assuming the revenue is same for all the months Overall LTV will be 

LTV = (month_revenue) * (1 + 1 month retention + 1month retention * 2month retention+ 1month retention* 2month retention * 3 month retention … )

If we assume all the retention rates to be same (similar to the simple LTV calculation formulae in step 1)

LTV = (monthly_revenue) * (1 + monthly_retention + monthly_retention^2 + monthly_retention ^3 ….. )

Which makes it an infinite GP whose sum is  = a/(1-r) - where a (1 in this case) is the starting number and r is the ratio or multiplier of GP (monthly_retention in this case)

LTV = (monthly_revenue) * 1 / (1-monthly_retention)LTV = monthly_revenue / churn // (As churn = 1-monthly_retention) - Same Formula as Step #1

I recommend keeping the retention rates for the first 12 months cohorts as accurate values and after that you can use the same retention rate (12th month) for months after that. This makes the calculation a bit more complex but will ensure the LTV is accurate. 

Forecasting of Revenue in Subscription Business - 

Another benefit of subscription is that future revenue can be calculated pretty accurately due to availability of retention rates. Also most of the revenue for the month for a seasoned subscription business comes from old customers and dependence on new customers is not that huge. Which means the revenue can be forecasted pretty accurately. 

If the new customer data can be added then overall revenue can be estimated. 

Overall monthly revenue forecast = New users in that month * avg customer revenue + 1 month old user * 1 month retention * avg customer revenue + 2 month old user * 2 month retention * avg customer revenue ….Overall monthly revenue forecast = avg customer revenue * (New users in that month + 1 month old user * 1 month retention + 2 month old user * 2 month retention + …)

Doing this calculation can forecast the revenue with such ease. 

In-case you have any queries or want to share the feedback on the article, please mail me at vibhu@getlumino.co