Yesterday I came down firmly in the middle in the great debate between Return on Investment and Lifetime Value as the primary measure for business decisions. My heart lies with Lifetime Value, but the realist in me knows you have to consider both.
The realist in me also knows that most of work with either measure is projecting future customer behavior. This provides the inputs needed for both types of calculations. I suggested yesterday that a company might build one comprehensive lifetime value model or many project-specific ROI models, but suppose on reflection that you could build comprehensive or project-specific models under either approach. The advantage of a comprehensive model is obvious: you can apply it to many projects, thereby ensuring consistent analysis and justifying the investment needed to build a sophisticated model. Sophistication is critical because making the right choice depends increasingly on understanding the long-term effects of a business decision and it takes a sophisticated model to estimate these accurately.
The good news is that a sophisticated model has many applications. I think it’s worth laying these out in some detail to encourage the required investment. These applications fall into five main groups:
- conventional LTV applications
- drill-down into LTV components
- forecasting
- optimization
- what-if modeling
Over the next few days I’ll be looking at each of these in detail. Let’s start with the conventional applications.
The conventional applications of LTV all use the value figure itself. That is, they essentially answer the question, “What is a customer worth?”
Probably the most common conventional application is setting allowable acquisition costs. These are usually applied as targets for marketing campaigns, although they can also help in setting purchase prices when acquiring a company. Indeed, cost per subscriber is a typical yardstick in evaluating acquisitions in industries including telecommunications (landline, mobile, cable) and utilities (gas, water, electric). Although attrition is a much bigger issue in communications than utilities, consumer behavior in both industries is highly predictable, so accurate lifetime value models are fairly easy to build. (This has not prevented many telecommunications firms from paying more for a company than its customers are actually worth. This is not because they can’t calculate LTV, but because they hope the value will change due to some combination of scale economies, new product sales, and perhaps higher prices made possible by reduced competition. A certain amount of corporate gamesmanship is also often involved, such as a desire to block the expansion of other potential acquirers or to grow big enough to avoid being acquired.)
Although corporate acquirers often pay more than the estimated value of a customer, most marketers take the opposite tack and set the allowable acquisition cost at considerably less than the new customers’ expected LTV. This reflects a very realistic understanding that lifetime value figures are inherently subject to risk because they include assumptions about future behavior that may or may not come true. The most conservative approach is to not rely on these behaviors at all and to justify acquisition efforts based only on the initial sale. But in many businesses this would greatly reduce long-term profits by choking off new customer acquisitions. A more common approach is to apply a fairly steep discount rate to the estimated value of future profits, or, more simply, to build in a cushion of safety through a business rule such as “acquisition cost should never exceed 60% of estimated lifetime value”.
Competent marketers also intuitively recognize that customer value can differ greatly by source. They therefore calculate lifetime value separately for each source of customers and sometimes for more subtle distinctions such as the nature of the initial offer (for example, sweepstakes vs. non-sweepstakes in magazine subscriptions). They can then set appropriate allowable acquisition costs for each group. This helps to ensure a more productive allocation of promotion budgets, yielding better long-term results even though average acquisition costs may actually increase. (Incidentally, when making these sorts of comparisons, adjusting the allowable acquisition cost by applying a fixed cushion such as 60% of estimated value does not give the same result as applying a higher discount rate. In a sample calculation, I found the fixed cushion favored a higher value source—that is, when the allowable acquisition for a lower value source was held constant, the cushion method yielded a higher allowable acquisition cost for the higher value source than the increased discount rate. Yes I know the preceding sentence may be incomprehensible. The point is that you should probably use the adjusted discount rate method, which is more theoretically justified. If you’re not comfortable with discount rates in general, at least do the calculation both ways and consider the difference.)
Lifetime value is also used as a guide to investments in retention of existing customers. The trick here is to recognize the relevant figure is future lifetime value. What a customer has already spent with you may be a good indication of their future behavior, but the value of those past sales has already been received. There are (at least) two possible errors here. One is to use past value as a measure of future value; the other is to estimate total value and then subtract past value from it, treating the difference is what’s expected in the future.
The fallacy of using past value is self-evident. The fallacy of the other error is that total lifetime value as estimated at the start of a customer’s life is an average that includes many customers who will leave over time. The estimated value of the remaining customers has to be recalculated as time progresses since those customers are part of a survivor group which have already lasted longer than some of the original starters. This calculation itself must be done correctly: if the standard lifetime value calculation looks at, say, a five year period, the projected value of these current customers should look out five years from today, not from their acquisition date.
In most cases, the expected future value of an existing customer will be higher than the expected future value of a new customer, but there can be exceptions (life insurance or, less morbidly, an auto lease). In any case, the customer’s future value indicates the amount that can be spent to retain this customer. Because acquisition costs have already been spent, the future value is usually relatively large. But while it’s technically correct to ignore the past costs, there is a danger in looking solely at the future: it’s possible to spend so much on retention that, even though you make an incremental profit on the retention effort, you lose money on the customer as a whole. Imagine, for example, that you just spent $50 to acquiring a customer with a value of $60, but just after you send them their first bill, you find you have to spend another $50 to collect it. It’s worth spending $50 to collect $60, but you will have spent $100 in total on that customer. If this happens too often, you’re out of business. So even though it’s too late for that particular customer, it’s important to consider the retention costs when estimating allowable cost for future acquisition campaigns.
A high retention cost is also hint that you should look carefully at the estimated future value of the customer at hand: will this one expenditure do it, or are they going to need similar retention incentives in the future? One good thing about current customers is you have a lot of information about them, at least relative to most prospects. This means you can predict their behavior with greater precision. A customer who needs a major retention incentive is certainly not average in that sense, so her future lifetime value is probably not average either. In fact, it’s a safe bet that many companies lose considerable amounts of money on such retention-intensive customers precisely because they set their guidelines for allowable retention costs based on average future values. Precisely the same logic applies to customer service costs, which in a way are retention costs too. It’s easy to lose money on service-intensive customers, so at some point you have to find ways to change their behavior or to charge them for what they’re costing you.
Of course, retention and service costs are components within the LTV figure. I’ll talk more about tomorrow about making use of them.
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