Lifetime value is widely recognized as important, but more than a few managers will admit in private that they don't really know what to do with it. This naturally makes them reluctant to invest the considerable resources required to come up with a meaningful lifetime value model.
It is possible to argue that what you do with lifetime value doesn't matter; assembling the data for the calculation will by itself bring enough new insight to justify the effort. Regardless of whether or not this is true, this rationalization isn't necessary. Lifetime value has many practical applications that fall into several broad categories. In rough order of increasing complexity, they are:
ROI Calculations. This includes the most common lifetime value application: determining what you can spend for a new customer. It also covers the second most common use, which is deciding how much to invest in existing customers. The general idea is that you can spend an amount proportional to the customer's value or, more precisely, an amount that leaves enough profit for an acceptable ROI.
Sadly, these common ideas are incorrect. If spending money on a customer doesn't change their lifetime value, then the money is wasted and return on that investment is zero. What matters is the incremental impact on lifetime value of incremental investments. For customer acquisition, this means any analysis must consider the marginal cost of acquiring new customers. This is usually much higher than the average cost, assuming companies harvest their most efficient sources first. With existing customers, the error is more common and subtler. Although it seems reasonable to invest more money in your most valuable customers, it's actually quite easy to spend money on them with little added return. Conversely, you may be underinvesting in your least valuable customers. There is no particular reason that the optimal ratio of spending to value should be the same for all customers. Therefore, setting a spending budget based on lifetime value is a very bad idea.
The focus on incremental results extends beyond customer treatments. Given a proper lifetime value model, any business investment can be assessed in terms of its net impact on the combined lifetime values of all affected customers.
Segment Value. Average lifetime value is interesting, but few companies deal with their customers as an undifferentiated mass. Rather, they make decisions about customer segments based on any number of differentiators: source of business, products purchased, usage patterns, significant events and so on. Once a company can calculate lifetime value for its entire customer base, it should also be able to calculate separate values for different segments within that base. This puts it in a position to evaluate relative ROIs in each of those segments - always keeping in mind, of course, that incremental returns may not equal the average.
Value Components. Many factors contribute to lifetime value, including transaction volume, revenue per transaction, profit margin, product mix, acquisition cost, retention costs, service costs and referrals. These will be identified and quantified within the lifetime value model. Breaking them out for analysis lets managers see where value is actually being added or lost, giving them a better understanding of the dynamics of their business and highlighting areas worth closer attention.
Value components can be further subdivided by time as it relates to the customer's tenure with the company. That is, managers can look at how much value is received during the first period, second period, third period, and so on during the customer's lifetime. The appropriate period might be days, months, years or decades, depending on the business. This longitudinal perspective on customer behavior is often unavailable from other sources and can help companies affirm or correct widely held assumptions about how their business works. Examining past behavior of today's customers over time can also help companies predict their future business, assuming tomorrow's customers follow similar patterns.
Trends. Customer behavior never remains exactly the same. An ongoing lifetime value analysis can look at how behaviors are changing over time, identifying both opportunities and weaknesses for management review. Trends can be evaluated at all levels: by total lifetime value, by segment, by component within segment and by time within component. The amount of detail could be overwhelming, but automated techniques can identify exceptions and analyze variances to save managers the drudgery of plowing through raw data.
Business Value. The value of a business can be simply defined as the sum of the lifetime values of all present and future customers. Whether the results of such a calculation match the stock prices or other real-world valuations is questionable. However, aggregate lifetime value, and, in particular, analysis of changes in aggregate lifetime value, gives managers another productive technique for understanding events within their business.
In short, lifetime value is not an exotic beast to be hunted for its own sake, then stuffed into a trophy case and ignored. It is more like a school of colorful tropical fish that can only be understood by both examining individual members and watching them move as a group. This is a more painstaking process than a simple hunting expedition, but ultimately, it is more rewarding.
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