eCommerce Analytics

Do you sell recreational, hobbyist, or athletic gear? Are you looking to acquire high quality customers? Well, as much as we don’t like to admit it, not everything has to be analytics and data mining. Sometimes intuition is enough to achieve our goals.

Consider that most recreational activities have high and low seasons. For example, recreational boaters and pilots are most active during the summer months. Skiiers and hockey players are most likely to be thinking about picking up new gear during the winter (or shortly before).

Our intuition tells us that if someone, say, buys a new pair of skis in the summer, they are either a) well off enough to take a summer ski trip to South America, or b) are incredibly devoted to the sport. Either way, he or she is a likely highly desirable customer.

As a result, we should be willing to spend more to acquire customers in the low season. The low season is the time to crank up the minimum cost-per-click bids on Google or spend a little extra to rent a list. Let your competitors slug it out in the peak activity months, fighting tooth and nail for the dabblers and tightwads. You’ll be sitting back collecting money from your stable of devoted high spending enthusiasts.

Last week in What is Customer Analysis? we found that the first step in a customer analysis is determining customer lifetime value across segments. Armed with this information, we can determine which customers are worth focusing our marketing efforts on and which customers should be “fired.”

The concept behind modeling customer lifetime value is relatively straightforward. We can group customers into segments which behave similarly and then based on historical data, determine how much a customer in each segment produces in profit over the course of his/her lifetime.

One thing to understand with calculating customer lifetime value is that there are many different ways to do it. Practically speaking, as long as you remain consistent in your usage across all your customer segments and across time, you should be ok using any of them.

With this in mind let’s look at one of the simpler customer lifetime value formulas:

Where,

m is the average gross margin
i is the discount rate
r is the customer retention rate

In using this simplified formula we to pick one average profit margin value and one average customer retention rate.

We can calculate m for each segment as

m = revenue - product or service costs - cost of servicing (includes acquisition and promotion costs)

over the course of a period (usually a year).

To find r, we calculate from historical data what percentage of customers in a segment repurchase in the next period (again, usually the next year). We then assume that this will also be the retention rate for subsequent years for the segment. This is generally not the case but that’s a price we’re willing to pay to keep things simple.

Finally, i is the cost of capital (sometimes called a hurdle rate). If you don’t know what your company’s discount rate is, your CFO will likely be able to give you the number. If not, you’ll usually be ok using a value between 8% and 15%.

Using the customer lifetime value formula to rank each of your customer segments will give you a solid understanding of which to court and which to forget about. In particular, any customer segment with a customer lifetime value less than zero is costing your company money. Shed yourself of these customers as quickly as possible!

Anxious to get started calculating customer lifetime value? Our customer lifetime value calculator will help you get started. If you sell online and are looking for a way to increase customer lifetime value across all your customer segments you’ll want to check out our recommendation engine.