How to work out your customer's Lifetime Value (LTV)?
Working out how much profit an average customer will deliver over the lifetime of their relationship with you is a crucial step in understanding the profitability of your business - and in particular in assessing the return on investment (ROI) of your marketing spend.
Cost of acquisition
Here is a simple worked example. If you spend $1,000 on Google advertising or Facebook advertising, and that campaign delivers 100 new customers, you can loosely say that your cost of acquisition is $10 per customer.
You might then look at some statistics on your customer churn rate - put simply, if today you are still actively trading with 400 out of the 500 customers you had 12 months ago, you might conclude your churn rate is 20%. In other words, you retain 80% of your customers in a given year. Extending that over time, you might reasonably estimate that your customers stay with you, on average, for about five years. Some may stay longer, some may leave sooner, but it's a rough average.
You would then look at average sales per customer in a year (say, $500), and allowing for cost of goods sold (say, $450), work out the average gross margin per customer per year ($50). Multiply this number out by five (based on the above assumption of an average five year customer lifecycle), and this gives you the lifetime value of your customers ($250).
Pulling it all together
If the LTV of a customer is, on average, less than your cost of acquisition, you're in trouble. You're investing more in acquiring each customer than they are making you over their lifetime. It's time to start looking at each of the above variables, and working out which one(s) you can tweak.
In the above worked example, you're paying $10 to acquire a customer who, on average, will make you $250. The ROI on that marketing investment would be 25x: a fantastic result.
Here is a link to a great post which explores the subtleties of working out the lifetime value of your customers, in particular for startups and younger companies. Most startups I've worked with were making all three of the mistakes mentioned in the post, and ended up significantly over-stating their LTV.