Last month we discussed the cost of getting a customer, a key measurement for the “front end,” or the prospecting side of the business. Now, we look at a corresponding analytical marketing variable: lifetime value, a “back end” marketing metric, which is applied to the house list to determine the value of a customer or group of customers over time. These tools work in tandem to improve a cataloger’s mailing efficiency. By identifying repeat customers who are more valuable to a mailer — and altering front-end strategies to better target similar types of customers — you can improve your bottom line.
Why you should bother
By calculating the value of buyers during one-, two-, and three-year periods, segmented by source, you can determine where the best long-term customers are coming from and adjust the front end or new customer acquisition strategy accordingly.
Determining LTV also lets you know how much you can spend to obtain a customer and still break even. Most catalogers like to be able to recoup any investment for new customers in the first year.
A less-obvious reason to calculate LTV is to help assign a value to your house file. If you are buying or selling a catalog company, your primary asset is your customer list. The LTV calculation can accurately project what the future value of the customer list is.
The importance of coding
To assess LTV, you need to assign to every new buyer an original source code indicating where the customer came from: what mailing list, space ad, or trade show the buyer first responded to, or if the name came from the Internet or another source. You’ll maintain that original source code on the buyer file for the life of the customer. When assigning source codes, build some logic into your system, such as ending every code with the year and the promotional event, so that you don’t duplicate codes from year to year. For example, source code B011A can be broken down as follows:
B = buyer
01 = buyer segment
1 = 2001
A = the first promotional event of the year. (Subsequent efforts are B, C, D, and so forth.)
By tracking customers by original source code and following the promotions sent to and the sales that result from each group of customers, it is easy to determine the value of a customer after one, two, and three years. Three years will give you a reasonable number to compare LTV among customer sources.
Get out your calculators
The chart below shows the LTV calculation of a group of customers from a specific source code.
Year 1 starts with 1,000 buyers who spend an average of $500 each, or $500,000 in total sales. When cost of goods (50% of total sales, or $250,000), fulfillment (12% of total sales, or $60,000) and advertising (25% of total sales, or $125,000) are subtracted from total sales, $65,000 is the remaining profit contribution. This represents a first-year LTV of $65 per customer ($65,000 divided by the 1,000 initial buyers.)
Year 2 shows that 50% of the original 1,000 customers made repeat purchases. Again, the average spent per customer was $500, for total sales of $250,000. From those sales, the cost of goods, fulfillment, and advertising are tallied (the sum: $217,500) and again subtracted from the total sales, leaving a year 2 profit from those customers of $32,500.
But then you need to discount that profit 20% (divide the sum by 1.20). By doing so you’re accounting for the past year in which you did not have the original costs of selling to these customers on hand. The true net-present value profit, then, is $27,083, or $27.08 for each of the original 1,000 customers. When the second year’s profit is added to the first year’s profit, there is a cumulative LTV of $92.08 per original customer.
Year 3 shows some improvement in the percentage of people buying — 60% of the buyers from year 2, or 300 in all — have returned to buy again. Again the average expenditure per customer is $500. When cost of goods, fulfillment, and advertising are again subtracted, $19,500 remains. This time, to obtain the discount factor you’ll divide the sum by 1.44 (1.20 squared). The net present value profit for the third year is $13,542, or $13.54 for each original customer. The cumulative LTV of each of the original 1,000 customers is $105.62.
Keys to success
To effectively measure LTV, you must track results tenaciously. If you can’t capture the source codes, forget about measuring LTV. Working with properly ink-jetted mailings on the address label and attentive order-takers, you should be able to capture up to 95% of source codes. Business mailers have historically had problems tracking source codes because purchase orders may not be coded or there may be multiple people involved in the buying decisions. But by retaining a copy of the mailing tape, you can look up uncoded orders.
The Internet poses another source code capture problem. With more and more consumers and companies placing orders online, even though a catalog mailing might have stimulated the sale, it is critical that your site asks for a source code during the ordering or address capture process. Another solution is to amend the URL to reflect specific offers; if your URL is www.buyme.com, you could create a URL of www.buyhere.com/offer for a specific promotion.
You’ll also want to measure the LTV of every prospecting effort. Ascertaining the cost of a new buyer is the first step. The second step is knowing how buyers perform over time. With great regularity we see examples where list or space ad performance looked subpar from the initial mailing, only to have a solid back-end response, good average order history, and a better-than-average lifetime value. Yes, response may have been lower than expected, but those customers who did respond proved to be repeat buyers with high LTV.
Good luck in your tracking and measuring. Next month’s column will look at alternative ways of assigning a value on your customer list.
Jack Schmid is president of J. Schmid & Associates, a Shawnee Mission, KS-based catalog consulting firm.