Lifetime Value in a Retail Setting
by Arthur Middleton Hughes

 

Lifetime Value in a Retail Setting


By Arthur Middleton Hughes


This article explains the computation of the lifetime value of a customer of a retail store. To make the story interesting, it explores the effect on lifetime value of the introduction of a Birthday club, in which the store writes to husbands suggesting gifts for their wives on the wives birthdays. Prior to the club, the wives have signed up for the club giving their preferences in clothing styles, colors and sizes.


Definition of Lifetime Value


First, a definition: Lifetime value is the net present value of the profit that you will realize on the average new customer during a given number of years. Lifetime value can be used in the development of marketing strategy and tactics. At any given time it is a specific number, but it will change from month to month. There are many different things that cause lifetime value to change, some of which are under your control, many of which are not.



What a lifetime value table looks like


Let’s begin with a basic lifetime value table. After you understand it, we will explain:





For this table, we are going to look at Ridgeway Fashions before and after they adopted the new strategy of writing letters to husbands before their wife's birthday. We will see how they costed out the Birthday Club, and determined whether the strategy would work, using a lifetime value table. While this is a retail example, the principles apply to any type of industry: financial services, telecommunications, business-to-business situations, as well as consumer marketing. Lifetime value is a universal measurement system. This book contains more than a dozen different lifetime value tables for a variety of industries. You will probably find your business represented on one of more of these charts. For now, however, study this particular table, because you will learn the basic principles of lifetime value from it.



Figure 01 Customer Lifetime Value


In this table we are looking at a group of 200,000 Ridgeway Fashions customers over a three-year period. Let us assume that prior to this time, Ridgeway Fashions issued a plastic membership card to many of their customers, or with customer permission, recorded customer’s credit card numbers so that they could find out who was buying what, and could store that data in a simple database. This chart is based on the data available on these customers in the database. It does not include other Ridgeway Fashions customers who pay cash, or otherwise cannot be tracked. The first year is the acquisition year of the 200,000 customers. We are following these specific people over three years. The store will be acquiring other customers during this time. We are not tracking them on this chart. This is the way lifetime value tables are constructed.


The Retention Rate

You will note that of the 200,000 customers who were acquired in Year 1, only 80,000 of them came back to make purchases in the second year. That means that Ridgeway retained only 40% of the customers that they acquired in Year 1. The retention rate is the single most important number in a lifetime value table. It is a measure of customer loyalty, and is something that you, as a marketer, can modify by your marketing strategy and tactics.


The retention rate is easily calculated by a simple formula:


RR = Year X Customers / Previous Year Customers

RR = 80,000 / 200,000 = 40%


Year X Customers represent those previous year customers who are still buying in the later year.


What do we do with new customers who wander in to the store and begin shopping in the second year? We can develop a LTV table for them. That is their acquisition year. In your table, you don't need to select 200,000 as your group for study. You could select 59,102, or any number that you might have in the database. The only requirement is that we are taking snap shots of the performance of a specific group of consumers or companies over their first several years as a customer. Later, we will be developing the lifetime value of customer segments, not of all customers, as we are doing here. For now, however, let’s stick with looking at all the customers in the database who were acquired together, to see what we can learn about them.


What do we do with lapsed customers who did not buy in Year 2, but came back in Year 3? They are in there. They are part of the 36,000 who are shopping in Year 3. The fact that some of the lapsed customers may be reactivated, leads companies to keep these customers on their books for a couple of years. There is always hope. Of course, since they are on the database, we will have to keep track of them and send them occasional messages. This costs money. Database marketing is not free.


In this chart we have shown the cost of the card database as $2 per card holder per year. We keep this database going for the three years, even though more than half of the customers have left us forever. The reason is that we still have hope that they will return to shop again.


The Visits per Year and Spending per Visit.


We are tracking each visit to the store. Many come once, and never come again. Some come many times. In the first year this averages out to 1.1 visits per year. We are also tracking the spending per visit. Both of these numbers tend to go up over time. The disloyal customers have left, and the loyal ones who remain visit more often and spend more per visit. You will have the same experience. Typically, the longer customers are with you, the more they will spend per year, per visit, per order. The second year represents the activity from the customers who are still active out of the original group acquired in the Acquisition Year.


Variable Costs


Direct costs are computed in a wide variety of ways in different industries. To determine costs in your industry, you should consult the finance department in your company. These costs include the cost of the products or services provided, plus the variable administrative costs such as customer service, debt collection, deliveries, returns, credits, etc.

What you will notice, and will be true of your situation as well, is that the costs of servicing a customer tend to decrease with the number of years that the customer has been buying from you. This is true in business-to-business as well as in most forms of consumer marketing situations. If you are selling software, for example, the customers are likely to tie up your customer service lines during the first sixty days until they learn how your software works. For the next sixty months, you may never hear from them again. This is true in a wide variety of industries, and helps to reduce costs and increase lifetime value.


Computation of costs should not be made into a major problem. If you develop a consistent system and stick to it consistently, that is all you need. The reason? We are going to look at the effect of a new strategy on lifetime value. If both tables use the same cost percentages, what that percentage is may not be of crucial importance. So don’t worry whether your costs are 50% or 60% or 70%. If you come up with a good number, stick with it, and use it in all your LTV charts.


The Acquisition Cost


Most companies are geared for acquisition. They spend a lot of money to get customers. To compute the acquisition cost, simply add up all the money you spend on your advertising and marketing efforts during the year (exclusive of retention programs, which we will discuss later). These marketing efforts can include advertising, sales commissions, sales salaries, etc. Then divide this total by the number of new customers who actually make purchases from you each year. That is your cost of acquisition.


Computing this number is very important. It may drive your whole marketing strategy. You will find that money spent on acquisition does not pay as well as money spent on retention. Lifetime value computation is the first opportunity most companies have to find that out.


Gross Profits.


Gross profits are easy to compute. They are equal to the total revenue less the total costs. We need to spend some time on the discount rate, however, since that is the most complicated part of the entire lifetime value analysis.


The Discount Rate


The reason why we need a discount rate is simple: the profits you receive from your customers come in over several years. Money received in future years is not worth as much today as money received today.


If I owe you $1,000 right now, but pay you the $1,000 a year from now, I have gypped you out of the interest you could have earned on that $1,000 if I had paid you right away. Future money is worth less than present money. To estimate the value of future money, we must discount it by a certain amount, so we can equate it to present money, and add the two totals together.


How much should you discount future revenue? There is an easy answer: you use the market rate of interest. As I write this today, 7% seems like a reasonable market interest rate. Ten years ago, 12% was what businesses were paying. The amount varies with the general market conditions. You should use a number which corresponds with your current situation. In this book, I am using 8% throughout, as being a nice round average number.


In reality, however, I am doubling that 8% to get 16%. Why is that? Because I am including risk. In any long-term business transaction, like lifetime customer value, there is always a serious risk. What are the risks?






For these reasons, in this example, I have doubled the interest rate to get the discount rate. The risk factor (rf) is two. You may be able to develop more sophisticated risk factors than (rf = 2), based on your business history.


Computing the discount rate from the interest rate


Once you have decided on a market interest rate -- such as the 8% that I have used -- you need to compute the discount rate that applies to amounts to be received in each year. There is a simple formula that is used to compute the discount rate. It is:


D = (1 + (i x rf))n


Where D = Discount rate, i = interest rate , rf = the risk factor, and n = number of years that you have to wait. The discount rate in Year 3, for example, (two years from now) is computed like this:


D = (1 + (.08 x 2))2

D = (1.16)3 = 1.35


It is possible to be much more precise in your discount rate calculation. You can worry about whether you have to wait several weeks or months, on the average, to be paid. This is true in most business-to-business operations. In this case, we can make "n" into a fractional amount, like 3.25. We will use this type system in calculating lifetime value for a business-to-business situation.


Net Present Value (NPV) Profits


Once you have the discount rate, each of your expected profits must be discounted so as to arrive at the Net Present Value of these future profits. The process is a simple one:


Net Present Value (NPV) Profits = Gross Profits / Discount rate


The Net Present Value of the $3,002,000 profits expected in Year 3 is $2,223,704 which is the result of dividing $3,002,000 by the discount rate of 1.35.


Cumulative NPV Profit

We must now add together the net present value of all the profits in the present year, and each previous year. The net present value of profits realized by the third year, for example, is equal to sum of the net present value of the profits in the Acquisition year + Year 2 + Year 3.


Lifetime Value


The lifetime value is simply the Cumulative NPV Profit in each year, divided by the original group of customers (in this case 200,000). It really means this:


The NPV lifetime value represents the average profits which you can expect to receive, after a given number of years, from the average new customer that you can sign up. The lifetime value of the average new customer for Ridgeway Fashions in the third year is $45.84


LTV = CUM-NPV/ Acquired customers = $9,167,152 / 200,000 = $45.84


This is a very important number. It is the most important number in your entire database. It can be used to develop your entire marketing strategy. We will be using this number throughout this book. Built into this number are all of the other numbers in the LTV table: the retention rate, spending rate, the acquisition cost, marketing costs, product costs, and discount rate.



Strategy Development


Developing your customer lifetime value table is the first step in the development of strategy. The second step is to get a great idea, and test it out -- in theory –using your lifetime value table as the measuring stick. Let’s do this right now.


Strategy always begins with some assumptions. “If we do this, then the customer will do that.” We will learn that customer relationship building strategy can affect five (and only five) basic things:


1. Retention Rate. Building relationships increases customer loyalty, and augments the retention rate. Increases in the retention rate will reduce the costs of servicing customers, and increase the revenue per customer.


2. Referrals. Relationship building activities can turn your customers into advocates and lead them to suggest your company to their friends, co-workers, or relatives. This works in business-to-business as well as consumer marketing. Referrals typically have higher retention rates and spending rates than other newly acquired customers.


3. Increased Sales. Database activities can lead to increased visits, larger average purchases, cross-selling, or upgrades.


4. Reduced Direct Costs. Database activities can reduce costs, in some cases, by changing the channel of distribution. Once you have customers on your database, you can learn more about them, and can increase your channels to reach them. You can send them emails. You can call them on the phone.


5. Reduced Marketing Costs. Well planned database activities are often much more cost effective than mass advertising. Once you have your customers on a database, you will develop innovative ways to market to them. For example, you will find that some customers have a negative lifetime value. They are costing you profits. Why spend a lot of money trying to build a relationship with these losers? Save your marketing money for people who can do you some good.


For Ridgeway Fashions, let’s imagine a creative Director of Database Marketing whom we will call Robin Baumgartner. Robin decides to test out the idea of a Birthday Club: to ask women customers to provide information about their sizes and preferences, their birthday, and their husband’s business address. This information will be put into the database, and supplied to the merchandise buyers who have to buy what the customers want. Then, each month, Robin will send letters to husbands about their wives birthdays providing hints on what to get.

Here is what Robin's idea might do to the lifetime value of customers who decide to join the Birthday Club:


Figure 02 Lifetime Value with the Birthday Club


Here are the changes that Robin estimates will take place as a result of the Birthday Club:


Retention Rate


In the previous example, the retention rate for Ridgeway began at 40%. In drawing up this new table for the Birthday Club, Robin makes the assumption that her programs can increase that to 50% -- with further increases as the remaining customer base becomes composed of more and more loyalists. Where did she get the 50% number from? She estimated it, based on some tests that she had conducted. One objective of any new strategy will be to make customers happier, and thus to increase their retention rate. What that increase will be you will have to estimate. Lifetime value is a forward-looking concept. You use it to predict your future revenue and profits.


What determines the retention rate? A great many things, only some of which are under the marketer's control. Factors that marketers usually cannot control include:





The factors that marketers can control that affect the retention rate, however, are quite impressive:






Certainly, the Birthday Club will appeal to some customers. It will result in some husbands, who have never bought women’s clothing before, ordering a birthday gift for their wives, based on the information which she has provided to the store. As a result of these additional sales, we can assume more visits (or orders) and a higher average order size.


The Spending Rate


Robin is assuming that the Birthday Club will increase the acquisition year average visits (or orders) from 1.1 per year to 1.2, with additional increases in the second and third years. She estimates that Birthday Club members will buy an average of $130 dollars worth of clothing in the acquisition year instead of $120. How does she know that it will be $130? She can do little tests using test and control groups. Database marketing offers a tremendous opportunity to conduct mini-experiments prior to your major rollouts. Robin has done her homework. Her estimate is, clearly, a testable proposition.


Her assumptions in the next two years also follow from database marketing theory. Loyal customers always buy more than new customers. As customers drop out, those who are left are the more loyal customers. It is safe to assume that the average annual purchases will go up. If you keep track of customer spending in your database, you can prove, easily, to yourself that loyal customers tend to make more purchases per year, that they buy more on each visit, and that they tend to buy higher priced items.

Birthday Club Costs


In planning her variable costs, Robin assumes the same cost structure that applied for her customers in general. The costs for the Birthday Club can be calculated with some precision. To set the club up in the first year will cost $15 per customer. This includes the cost of training the clerks to ask people to join the club, giving the clerks a commission of $5 per customer signed up, getting the survey data, keypunching the data, putting it into the database, creating the Birthday Club software, and writing one letter to each member’s husband at birthday time. In Years 2 and 3, the costs are set at $2 per year. This covers the generation of the birthday letters. You will note that she is sending out birthday letters to all club members, even though many have already stopped buying in the store. This is excellent strategy. The club communications, alone, may serve to reactivate some lapsed customers, and are well worth the investment.


Resulting Lifetime Value


Lifetime value for club members is computed exactly as it was for regular store customers. It shows that lifetime value in the third year rises to $58.16. To show what has happened, we use a third chart which compares the bottom line on both tables:



Figure 03 Gain from the Birthday Club

What this shows is that in the first year, the Birthday Club will reduce lifetime value. In old-fashioned direct marketing programs, one might use this initial loss as a reason to abandon the club as being a loser. But with database marketing we can look at the impact of a new strategy several years ahead. What this shows is that by the third year, the Birthday Club will increase Ridgeway profits by more that $2.4 million. Bear in mind that this $2.4 million is not sales, it is net profits, after all costs have been subtracted including the loss of $1 million in the acquisition year. It is a real number that can be measured. It shows that the Birthday Club is a profitable strategy for Ridgeway Fashions.


Referral Rate


Almost any company can get some satisfied customers to become advocates. It is possible that the Birthday Club will be so successful that she can persuade (or incentivize) 3% of her customers to recommend Ridgeway to their friends or relatives. As a result, we will have 3% more customers in Year 2 than we otherwise would have had. The same thing can happen in Year 3.

Is Robin correct? Can she really increase her customer base by 3% in Year 2 through a referral program? Who knows? That depends on many things, including the success of Ridgeway as a store, the execution of the marketing plan, etc. But it is certainly a reasonable goal to build in to a marketing plan. It is also a testable proposition. If the plan does produce 3% new customers, the database will show it. If it brings in 6%, or only 1%, the plan can be modified. This is the beginning of good strategy development. The MCI Friends and Family program was one of the most successful referral programs in the history of marketing. It showed what can be done.




Figure 04 LTV with 3% referrals.


Just adding these 3% referrals in the second two years has made a major change in the overall success of the Birthday Club. Look at these numbers:


Figure 05 Gains from Referrals


Our overall profits have gone from $2.4 million to $3.4 million. Generating referrals is a really valuable strategy.


There is one issue here that we should note. These referred customers are really new acquisitions. Why don’t we just tuck them into the numbers in the Acquisition year the way we do with other new acquisitions. Why do we show them as a separate category on a Lifetime Value Chart? There is a very important reason. Research shows, and your database records will prove it, that referred people are more loyal, have a higher retention and spending rate, than the average new acquisition. They are better people than the average customer. Why this is so, no one really knows. But the fact that they are linked to an existing customer results in their being more valuable than many other customers. You list them separately because you want to track them, you want to measure their purchasing habits, and devise special programs to increase their number. You may want to create a special lifetime table just for them. Don’t lose track of them. In your database, you put the ID number of the referred person in the referrer’s record, and vice versa. That way you can track referred people and those who refer them, to determine their lifetime value. Research shows that those who refer other customers are also better customers. They are advocates. They spend more, and are more loyal. If you have enough of them, you may want to create a special “advocates group”, giving them special attention



Lessons Learned


What lessons can we draw from what we have learned already?






The basic idea is to come up with strategies that increase lifetime value by as much as possible. If we set up a matrix showing lifetime value each year for three years (as we have already done), then we can use our imagination, and do "what if" analysis to see what can we do to increase lifetime value. The results of each possible action can be calculated to determine whether the effect on lifetime value is worth the effort and resources that went into it.


 


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.

 

 

 

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