Did that make it clear? OK, I am as puzzled by that formula as you probably are but, believe it or not there is not just one formula to answer the the CLV question. As you see, it can be very complex. I don't think it has to be that complex. There are many sources of information on both CLV and well as how to determine the cost to acquire a new customer, what is often referred to as Cost per Acquisition (CPA). Some of you have tools in your POS to help you with these questions, but you need to know how the POS is calculating this.

For today, we will look at just one simple approach to the Customer Lifetime Value (CLV) question. It is called Recency, Frequency, and Monetary (RFM). One of the best references I found on this is available from Shopify and available HERE. This approach suggests you take your current customer list and subdivide it into these three categories.  

• Recency refers to the last time that a customer made a purchase. A customer who has made a purchase recently is more likely to make a repeat purchase than a customer who hasn’t made a purchase in a long time.

• Frequency refers to how many times a customer has made a purchase within a given time frame. A customer who makes purchases often is more likely to continue to come back than a customer who rarely makes purchases.

• Monetary Value refers to the amount of money a customer has spent within that same time frame. A customer who makes larger purchases is more likely to return than a customer who spends less.

By segmenting your customers with RFM, you’ll be able to analyze each group individually and determine which set of customers has the highest CLV.

To use RFM to organize your customers, you’ll need to grab three pieces of data about every individual customer: The date of their most recent transaction, the number of transactions they’ve made within a consistent timeframe (a year will work best), and the total amount that they’ve spent during that same timeframe.

For RFM calculations, each of these variables needs to given a scale. The simplest way is to use a scale of 1 to 3. This might seem a bit confusing, but don’t worry, it’s not as complicated as it looks. Remember: This scale is just a way to help you visualize which groups of customers are most valuable.You’ll be assigning your customer’s recency, frequency, and monetary value each a value on your scale of 1 to 3. Think of these three values as categories: 1 being the least valuable, 2 being somewhat valuable, and 3 being the most valuable.So, when you sort your data, your least valuable ⅓ of customers will get assigned a score of 1, the ⅓ above that will get a 2, and so on. Here's a graph to illustrate:

Finally, sort your chart by RFM Score and divide your results by highest (shown here in red), middle (orange), and lowest score (yellow). This is starting to look like Steve Bailey's Most Profitable Items spreadsheet.

Your highest scoring results will be your most valuable customer segment—be sure to dive into the data to try and find common threads between these customers that could indicate why they provide more value and how you can target them better.

There certainly is a lot more details shared in the Shopify article, but at least you have some basics. There are probably as many ways to calculate all of this as people figuring it, but you have to start somewhere and when you or your staff are dealing with customers and making decisions how to handle customer complaints, it will be very important.

In closing I would like to end by passing along a few words of wisdom from my early management training days in retail at Sears Roebuck & Co....