by Arthur Middleton Hughes

Marketers have been using the three terms, ROI (Return on Investment), Profitability and Lifetime Value as if they were synonymous. They aren’t. Each has its own special use in database marketing. The purpose of this article is to explain each term to show how they differ, and how they are related.

Return on Investment

Return on Investment is usually used for marketing campaigns. The basic idea is that you invest a certain amount in a specific campaign to sell a group of products or services. You make a certain net profit from the activity. The ROI is determined by the basic formula:

ROI = (Net profit – Amount Invested) / (Amount Invested)

Suppose, for example, you invest \$40,000 in mailing a catalog to 100,000 people. You get a 2% response rate. 2,000 people buy an average of \$100 each, spending a total of \$200,000. If the average cost of each order (including the cost of the goods sold, the fulfillment, telesales, credit, returns, etc.) is \$40, then your net profit on your average order is \$60, multiplied by 2,000, or \$120,000 in all. Your ROI is:

ROI = (\$120,000 – \$40,000) / \$40,000 = 2 = 200%

Unfortunately, most customer acquisition programs are not as successful as this example. Typically, many direct marketing companies make very little money on their first sale to a customer. Their profit comes from subsequent sales to the buyers acquired in the first sale. This is true of banks recruiting credit card customers, non-profit fund-raisers, and companies selling books by mail, to mention only three. A bank may spend \$80 to acquire a credit card customer whose lifetime value at that moment is only about \$25. As soon as the customer begins to use her card, however, she may build up a big balance, pay interest and annual fee charges, and increase her lifetime value by multiple amounts. There are really two ways of computing ROI:

1. ROI from the initial acquisition which can be negative

2. ROI from the lifetime value of the customer, which is usually positive

Profitability

Profitability is usually computed by financial institutions such as banks. Profitability applies to customers, rather than to campaigns. The idea in profitability is to estimate the profit that you will receive per year from a given customer, if the customer continues to maintain her product portfolio in the same way in the future that she has been doing in the recent past. Let’s take an example.

Suppose that a customer has a credit card which she uses to purchase items which cost about \$1,000 per month, maintaining an average unpaid balance of \$300 each month. We can calculate her profitability in this way:

 Merchant processing fees (2.8% x \$1,000) = \$28.00 Interest on unpaid balance (17.9% * \$300 / 12) = \$ 4.48 Total \$32.48 Annualized monthly revenue \$389.76 Annual fee \$40.00 Total Annual revenue \$429.76 Annual maintenance, processing, mailing costs - \$256.00 Annual Profitability \$173.76

We can say, therefore, that her profitability is \$173.76. Profitability calculations can become quite complex if customers have many different accounts (savings, checking, money market, auto loans, home mortgages, etc.). Computers can be programmed to determine the profitability of every customer in a bank based on the customer’s current products, balances, and past performance. It is possible to go back more than one year to factor in trends. If this customer, for example, bought an average of \$500 per month the year before last, and \$1,000 per month last year, we might assume that she will be buying more than \$1,000 per month next year. Her profitability would be greater than \$173.76 On the other hand, she might be spending less than in the past, which might lead us to predict a continuation of this behavior, with a lower profitability in the future.

There is a lot of guesswork built in to profitability estimates. Return on investment is a backward looking concept, and can be determined with a great deal of accuracy and assurance. Profitability is a forward-looking concept. It is based on projecting future behavior based on the present and the past. It can be, and often is, wrong. It is subject to swings in the market. Usually missing from profitability calculations are such factors as the retention rate, the referral rate, the marketing costs, and sunk costs such as the acquisition cost, and the effect on behavior of various relationship building activities. For these, we must look to lifetime value.

Lifetime value (LTV) is calculated initially for groups (segments) of customers. Once determined, it can be attributed back to individual members of the group. To understand LTV, let’s look at a typical lifetime value table calculated for a group of 50,000 bank customers who have the same credit card performance as that shown by the previous example.

 Year 1 Year 2 Year 3 a Referral Rate 6.0% 8.0% 10.0% b Referred Customers - 3,000 3,240 c Retention Rate 75.0% 80.0% 85.0% d Retained Customers - 37,500 32,400 e Total Customers 50,000 40,500 35,640 f Average Balance \$300.00 \$300.00 \$300.00 g Revenue per Customer \$389.76 \$429.76 \$429.76 h Total Revenue \$19,488,000 \$17,405,280 \$15,316,646 I Direct Costs \$256 \$12,800,000 \$10,368,000 \$9,123,840 j Acquisition Cost \$80 \$4,000,000 0 0 k Marketing Costs \$25 \$1,250,000 \$1,012,500 \$891,000 l Total Costs \$18,050,000 \$11,380,500 \$10,014,840 m Profit \$1,438,000 \$6,024,780 \$5,301,806 n Discount Rate 1.00 1.14 1.30 o Net Present Value \$1,438,000 \$5,284,895 \$4,078,313 p Cumulative NPV \$1,438,000 \$6,722,895 \$10,801,207 q Lifetime Value \$28.76 \$134.46 \$216.02

Lifetime value calculations are more complex than simple profitability. For this reason, let's look at this chart line by line. For convenience, we will refer to each line by its letter (a) as we go.

We will begin with 50,000 customers (e) who were acquired at an average cost of \$80 each (j), or \$4 million. These customers are not static. They tend to drift away. A year later, only 75% of them are still using their card. Their retention rate is 75% (c). Of those who remain, the retention rate increases to 80% in Year 2 and 85% in Year 3.

Some of these customers are encouraged by marketing efforts of \$25 per customer per year (k) to become advocates and get their relatives and friends to take out the card. This results in a referral rate (a) and three thousand referred customers in Year 2 (b).

The revenue per customer (g) is the same as in the profitability example (\$389.76). In the following two years, it goes up by \$40 because the annual fee kicks in. The direct costs (i) are the same (\$256), but in addition we have the acquisition cost of \$80 (j) and the annual marketing costs of \$25 (k).

We are showing three years here: Year 1, Year 2, and Year 3. Year 1 is not a calendar year. Instead, it is the "year of acquisition". Year 2 is the year after acquisition, and Year 3 is the year after that. For these reasons, Year 1 may contain people who have been acquired in various years (such as 1995, 1996, and 1997). Year 2 would represent the performance of these people in their second year (1996, 1997 and 1998).

The profit (m) is the total revenue minus the total costs. Particular attention should be paid to the Discount Rate (n). Discounting is required because we will be adding together profit generated in several different years. Future money is not as valuable as money in hand today. For this reason, if we are to add these amounts from various years together, we must discount future monies to give them values comparable to current money. The formula for the discount rate is:

D = (1 + i )n

i = the market rate of interest plus a factor for risk

n = the number of years for which you have to wait

If the market rate of interest is 7% and the risk factor is 2, then the discount rate in the third year is:

D = (1 + .14)2

D = 1.30

Dividing the net profit in each year (m) by the discount rate (n) results in the Net Present Value profit (o). The NPV profit in each year is added to that in the previous year to get the cumulative Net Present Value profit (p). Dividing this figure in each year by the original 50,000 customers gives you the lifetime value (q).

Instead of being a simple profitability figure like \$173.76, lifetime value is a complex set of numbers, some of which are under the bank’s control, and some of which depend on external factors such as the market, interest rates, competitive offers, marketing effectiveness, etc. For example, the retention rate – line c – reflects the fact that some customers are always leaving. They may die, or defect to another card. They may move away, or stop using their card. Some of these actions can be influenced by the way the bank treats the customer. This depends on the way the marketing budget (k) is used. The bank can also use their best efforts to increase the average balance (f), or the spending rate which determines the revenue per customer (g).

From this chart, we have determined that the average lifetime value of the fifty thousand customers in this segment is only \$28.76 in the first twelve months, rising to \$202.81 in the third year. If we want to convert these numbers into the lifetime value of an individual, we can do so by attributing the expected behavior of an individual to the average of the group to which he belongs.

Comparison of the three measures

Which is the best measure of marketing success? ROI, profitability, or lifetime value. Actually, they all have their uses. ROI is a vital measurement of the success of any direct marketing campaign. When we compare several campaigns, we can look at the response rate and the return on investment of each campaign. ROI is usually a more valid measure than response rate, because it takes into account the money spent to acquire the responses. Every direct marketing campaign should be measured by ROI.

Profitability is a good short hand method for determining the worth of a particular customer.

Arthur Middleton Hughes is Vice President of The Database Marketing Institute. Ltd. (Arthur.hughes@dbmarketing.com) which provides strategic advice on relationship marketing. Arthur is also Senior Strategist at e-Dialog.com (ahughes@e-Dialog.com) which provides precision e-mail marketing services for major corporations worldwide. Arthur is the author of Strategic Database Marketing 3rd ed. (McGraw Hill 2006). You may reach Arthur at (954) 767-4558 .

The articles on this web site are available to the general public to read, enjoy and for limited business use. If you want to reprint more than one or two of them for resale or use in a business or educational environment, send an email to Arthur Hughes at arthur.hughes@dbmarketing.com. He will give you permission by return email. The cost, depending on the number of copies you want to reprint, is very inexpensive.

 Top Search Back Next Home