Using customer lifetime value equations is a proven foundation of many database marketing strategies. As database marketers, we all use "extend the lifetime value of the customer" as justification for our customer retention programs. But in reality, only some marketers understand lifetime value and even fewer have actually used these calculations and applied them to marketing strategies.

To simplify this process, let's start by defining exactly what lifetime value means to us as marketers. Customer lifetime value is the net profit that your company can realize on the average customer over a given number of years.

Let's calculate lifetime value for a fictitious company; Ron's Cleaners, using the spreadsheet below:

The figures being used in this fictitious example are exactly that, fictitious. Of course, in order to perform lifetime value calculations, you must have a method of capturing customer and respective transaction information and the ability to link the two. Your numbers should be real, as dictated by your data. Further, for this example we are focusing on the round number of 1,000 customers. Your number can be 1,000, 10,000, 100,000 or any number you choose as representative or statistically significant depending upon the size of your database. The only requirement is that you focus on the performance of a specific segment of customers.

This table shows a group of 1,000 customers over a five-year period. The second line of the spreadsheet shows the retention rate after the first year as 50%. In addition, each subsequent year the remaining customers have an increased retention rate by 5%. This is reflected in the first line (Customers) in subsequent years. Both of these are reasonable percentages.

The third line of the spreadsheet reflects the average amount spent by each customer that year. For our example, Ron's Cleaners' annual sales per customer are projected as being a flat $150 per year. That doesn't mean that there isn't sales growth, only that the sales per customer is remaining the same. The fourth line (Total Revenue) is the average annual sales number multiplied by the number of customers remaining for that year.

Once the revenue numbers are calculated, it's time to determine your cost percentage involved with serving these customers. The first line under the header "COSTS" shows a 50% cost percentage and is multiplied by the Total Revenue figure to calculate the Total Calculated Costs number.

Gross Profits under the "PROFITS" heading then is the Total Revenue minus the Total Calculated Costs. Now to figure the Discount Rate, which is the most mathematically challenging part of the spreadsheet. Discount Rate accounts for the fact that today's dollar is not worth the same in future years, but less. To discount future revenue, simply use the market rate of interest and multiply it for a risk factor. For example, let's use 10% (a nice round number) as the market rate of interest. Now to account for risk we'll double that to get 20%.

Now that we've settled on an interest rate of 20%, we need to compute the discount rate to be applied to amounts to be received in future years. This formula is:

D=(1+i)

Where D = Discount Rate, i = interest rate, and n = number of years that you are using in your spreadsheet (which is 4 years from now to reach Year 5 in our example). Therefore, our equation works out to be:

D = (1.20) = 2.07

To calculate Net Present Value (NPV) of future revenues simply divide your Gross Profits by the Discount Rate. In our example, the NPV of $20,625 in Year 3 is $14,323 ($20,625/1.44). The Cumulative NPV Profit is then all the NPV Profit from the present year plus each previous year.

If you made it this far in the column without having to take some pain relief I commend you! Stick with me, we're almost there.

Lifetime value is calculated by taking the Cumulative NPV Profit and dividing it by the original (Year 1) number of customers (1,000 in our example). The NPV Lifetime Value is the true representation of the average profit you can expect, after a given number of years, from every new customer that you acquire.

The present lifetime value of the average new customer for Ron's Cleaners after four years is $127.73.

Now that you've calculated your customers lifetime value, you need to apply it to a proposed marketing strategy, in theory. You will need to make some assumptions about these strategies. In other words, "If we execute this tactic, the customer will respond thusly". This will lead to a number of "What If" scenarios which will assist you in making your projection assumptions.

Some of these assumptions are that your marketing initiative will impact the following variables:

• Gains in customer referral rate
• Increased customer retention rate
• Increased sales rate
• Reduced marketing costs

You can play with these rate percentages to reasonably project how your marketing strategies will effect them. Will your customer contact marketing strategy increase referral rates by 3%? How does it look at 5%? Will it increase customer retention by 5% or is it powerful enough to boost retention by 10%?

Play with the numbers. Make your projections. But always consider the increased cost percentage by implementing the marketing strategy.

Smart database marketers always apply prospective marketing strategies to their lifetime value calculations to understand what the reasonable gains could be. If your projections make money, test it (never roll-out on assumptions). And if your test works, run with it. If not, then it's time to test another marketing strategy based upon your enhanced knowledge.

Good luck and good marketing!

Ariss Kahan Database Marketing Group, Inc. assists clients build customer relationships through proven and innovative database marketing techniques and marketing database technologies. They specialize in customer acquisition, retention, cross-sell and up-sell initiatives and can be reached at (303) 368-9800 or via e-mail at rkahan@dbmktg.com.