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Lifetime Value
by David M. Raab
Relationship Marketing Report
April, 1997
Lifetime value
is one of those concepts that are easy to understand but hard to
execute. The challenge is a practical one—how do you gather the
information needed to calculate a customer's profitability?
Think of the data required:
- promotion
costs. Not just the initial media expense, but also the
cost to handle replies, fulfill any premiums, and provide
ongoing communications. And don't forget to allocate costs
related to non-respondents, bad debt, and returns. Bear in
mind the allocated figure can change as you get more
responses or fewer payments.
- gross profit
margins. Total purchases are just the start; you also
need to know what you paid for each item, packing and
shipping expenses, and costs for customer service and
billing. If you're in an industry with high fixed costs,
such as airlines or telecommunications, you have to deal
with allocations yet again.
- projected
future behavior. Cumulative past purchases are not
enough; you really need to predict future purchases as well.
This means looking at how similar customers have already
behaved—assuming you can figure out who is truly "similar"
in the ways that count. This takes still more data, on
demographics, lifestage and behavior patterns, as well as
the tools and techniques to analyze it.
- projected
changes in behavior. Lifetime value is anything but
static: the more you watch it, the more you will attempt to
change it through adjustments in pricing, service,
promotions, and so on. So you need still more tools to
measure the impact of past policies and estimate the impact
of new ones.
If you're not
worried by now, you haven't been paying attention. Clearly where
so much data is involved there has to be a computer somewhere
nearby. But just as clearly, a process this complex will not
have a simple software solution.
In fact, there
is no single "solution" to the challenge of lifetime value
calculations. Instead, different industries have evolved
solutions that make sense given the data they have available and
the economics of their business. These solutions are embedded in
those industries' marketing and operational software.
Consider the
magazine industry, where fulfillment service bureaus like
Neodata and CDS capture transaction statistics from the
subscription systems and feed them into models that project
future circulation levels. These models are organized primarily
by subscription source, which circulators have found are the
most meaningful predictors of subscriber behavior. Each source
has a set of assumptions regarding renewal and payment rates, as
well as the number of bills, renewal notices and bad debt copies
per subscriber. Add some unit costs for the magazines, bills and
renewals, and maybe an assumption about advertising revenue per
paid subscriber, and the lifetime value per new subscriber by
source is a mechanical byproduct of the modeling process.
Magazine circulators have made this a science for decades—in
fact, they did it by hand before computer models were widely
available.
Catalog
marketers also speak in terms of circulation, but they share
little else with their magazine cousins. Most catalog
fulfillment systems maintain a running total of purchases for
each customer, primarily for Recency-Frequency-Monetary Value
segmentation. This is often labeled "lifetime value," although
it does not usually incorporate any projection for the future.
At best, the magazine systems provide a report of that groups
customers by their initial order date and shows each cohort's
lifetime purchases. This gives some sense of the flow of
purchases over time, although it's usually left to the marketer
to build any type of projection curves. The magazine systems
generally do not record the cost of catalogs sent per customer,
let alone other expenses such as customer service or billing.
They often contain actual merchandise costs and frequently can
show profit margins (that is, revenue less cost of goods) by
catalog or product line. But they generally do not calculate
margin on a per customer basis.
Margins are a
much greater concern—bordering on obsession—to retailers.
General merchandisers and grocery stores both use price
adjustments as a major marketing tool, to attract traffic during
sales and to move excess merchandise. As a result, their
database marketing systems often do track the difference between
what each item cost and what the customer actually paid. These
systems also record the costs of promotions and calculate
profitability, net of both promotion and merchandise costs, per
campaign. Products in this group include Retail Target Marketing
Systems Archer (414-798-1705), RMS MarketExpert (203-656-3411),
S2 Systems CRM (972-458-3800) and STS Systems Open MarketWorks
(514-426-0822). These systems also will often divide customers
into segments based on lifetime purchases and show the
profitability by segment. They still do not project future
purchases by customer, however.
Perhaps the most
advanced lifetime value calculations belong to portfolio
management systems such as Fair-Isaacs TRIAD (800-999-2955), AMS
Strata (703-267-8760) and CCN-MDS Strategy Management/PROBE
(404-841-1400). Customer Management Services Customer Portfolio
Manager (919-969-5233) and Exchange Applications ValEX
(617-737-2244) also arguably fit into this category. Originally
built for credit card marketers, these products are now applied
throughout financial services, in telecommunications and
elsewhere. They include statistical modeling to predict customer
behavior, consulting to define contact strategies and policies,
and software to integrate the strategies and models with
business operations such as billing and pricing decisions.
Implementation generally involves identification of key business
decisions—which might be credit limits, collection policies,
and interest rates in a credit card situation—and development
of models to predict the results of applying different policies
at each decision point to each individual customer. Because the
value of earlier decisions can be affected by later
decisions—for example, accepting high-risk customers may be
profitable only if aggressive collection policies are
applied—marketers must define "strategies" that are sets of
decisions or options to be applied as a package.
The portfolio
management systems also provide extensive support for testing
alternative strategies over time, which they typically refer to
as "champion/challenger". The systems gather a combination of
operational data, such as account balances and payment rates,
and user-provided assumptions for promotion and contact costs.
The
comprehensive nature of the portfolio management systems makes
them arguably the most complete implementation of the lifetime
value concept. They explicitly incorporate models to predict
future behavior and, even more important, they attempt to change
lifetime value through business actions. This
understanding—that lifetime value is is something to manage,
not measure—is the key to customer-centered marketing.
David M. Raab is president of ClientXClient, a consulting
and software firm specializing in customer value optimization.
He can be reached at
draab@clientxclient.com.
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