MIT Sloan Management Review
July 23, 2013 Reading Time: 16 min
Is it better to reward existing
customers for loyalty — or spend your marketing dollars on attracting new ones?
Here is a framework to help you decide.
Clothing retailers, the
authors argue, should focus on retaining high-value customers because different
customers may spend vastly different amounts, and customers can switch from
store to store easily.
Charlie, a
loyal customer of his local bank, had never thought of taking his business
elsewhere, but the offer from a competing bank to refinance his mortgage at an
extremely low interest rate seemed too good to pass up. He asked Rick, the loan
officer he had been dealing with for years, if the bank could match the offer.
Rick knows lowering Charlie’s mortgage rate won’t be good for the bank’s bottom
line, but he thinks making a long-time customer happy is worth the investment.
Should the bank match the offer, or should it let Charlie go?
This anecdote,
while fictional, represents a real customer management dilemma faced by many
companies nowadays: Should we offer better deals to current customers or to new
ones? In particular, at what cost should we keep current customers, as opposed
to seeking out new ones? The question is simple, but the answer is not.
A quick scan of
offers found in the marketplace does not reveal obvious commonalities and
provides little insight. While airlines give lavish frequent-flyer packages to
their most loyal customers, wireless carriers generally focus on wooing new
customers through introductory deals. Hotels often do both. Apparel catalog
retailers send special discount “value” catalogs to existing customers, whereas
magazines, newspapers and software companies often offer discounts to new
customers by offering them lower introductory prices.
But would it,
for example, be more profitable for a newspaper to offer a better price for
subscription renewal rather than new subscriptions? Should a wireless carrier
instead offer lower rates to its high-volume customers who have stayed with the
carrier for a long time? Should a hotel, airline or retailer offer better rates
to new customers it aims to acquire? Ultimately, how can a manager reconcile
the demands of current customers with the need to
attract new customers?
attract new customers?
Expert opinions
on this subject conflict. On one side, you can find people who argue that
careful attention to the needs of existing customers like Charlie deepens the
relationship between customer and company. That, in turn, leads to continuous
increases in customer satisfaction, loyalty and company profitability in a
virtuous cycle of mutual benefits. Customers get better rewards, and the
companies get more business from those customers.1People who take this
position are quick to point out the basic and well-established fact that
customer retention is notably less expensive than acquisition. This
consumercentric view presumes that a loyal customer is a good customer
deserving of rewards.
On the other
side, you can find people who take a company-centric perspective, one that is
skeptical of customer-centric narratives and conventional wisdom. Essentially,
their argument is this: Simply by virtue of purchasing from and being loyal to
a company, existing customers have revealed that they much prefer the company’s
products or services to those of competitors. Therefore, they argue, existing
customers should be “punished” with higher prices than new customers receive,
given their willingness to pay them in the past, and companies should focus
their rewards and incentives on new customers in an attempt to increase sales
and earnings.2
Our view is
that to create an artificially stark dichotomy — you should always reward
or punish your own customers or new customers — is a misleading black-and-white
simplification. Both arguments have merit; the appropriateness of each strategy
depends on the circumstances a company faces. What this means is that
executives need a framework for deciding the best way to increase maximum
profitability. Our recent research provides one.3 (See “About the
Research.”)
ABOUT
THE RESEARCH
The ideas in
this article are based on a series of academic research papers jointly
undertaken by the authors in the past decade.i In addition, we used
game theory as an analytic tool to gain insights into the complexities of
customer reward program design. Game theory provides a set of techniques to
analyze interdependency of strategies between companies and customers in a
disciplined fashion. The framework helps to develop, test and explain intuition
about strategic interactions and has become the basis of significant
intellectual progress in many areas, including business, economics and
political science.
Comprehensive analysis
of reward programs requires modeling of a variety of interactions between
competing companies and between a company and its customers. It is further
complicated by the fact that the companies’ strategies are dynamically evolving
over time under competition. Given the dynamics in customer choice, we analyzed
the customer choices as a dynamic programming problem. Given the dynamics of
competition between companies, we also analyzed the companies’ choices in a
dynamic game framework. In sum, we embedded the dynamic program of consumer
choice within a dynamic game of competition between businesses under a variety
of marketing environments. This allows us to explain the diversity of reward
program designs in the marketplace and to provide advice on when companies
should reward current or new customers.
Flexibility and Value Concentration
In structuring
our framework, we introduce two basic rules characterized by simple but often
ignored features of customer behavior. First, consumers’ preferences for a
product often change depending on the purchase occasion. Such changes in
preferences can happen independent of marketing or pricing, because consumers’
needs or wants depend on the specifics of each purchase occasion.
For example, a
customer may generally prefer a Lowe’s store for home improvement products
because it is closer to her home and, in her opinion, offers superior quality
offerings. However, she may still prefer to go to The Home Depot on the drive
home from the office because it is more convenient to her route. We define this
fluidity of customer preferences as shopping flexibility.
This
flexibility is not restricted to store choice and geographic location. Consider
a college student who lives in New York. He generally prefers American Airlines
because he likes its service and it flies a direct route to his hometown.
However, when he needs to visit a friend in Houston, Texas, he may prefer
United Airlines because it has more direct flights for that route.
The second
feature of customer behavior that is important to understand in resolving the
“reward or punish” dilemma is the fact that, in many markets, not all customers
are equally valuable. Some contribute far more to a company’s profits than
others. An American Express executive, for example, once reported that the best
customers outspent others by 16 to 1 in retailing, 13 to 1 in restaurants, 12
to 1 in airlines and 5 to 1 in hotel/motels.4 These are examples of
the widely known (and empirically supported) 80-20 rule, with a small number of
customers (20%) contributing a large amount of profit (80%).5 We define this
imbalance as value concentration.
Over the past
two decades, massive investment in organizational resources (human, technical
and financial) to build information infrastructures that store and analyze data
about customer purchase behavior has helped unearth the details of value
concentration. Armed with this data, companies can pursue fine-grained
microsegmentation and customer management strategies. However, even with all
this data, companies continue to differ on whether they offer a lower price to
their own customers or competitors’ customers, and the question of when such
segmentation and differential pricing is profitable remains open.
When to Reward or Punish
In our
research, we found that these two basic customer dimensions of shopping
flexibility and value concentration provide insight into how managers might
best balance customer retention and acquisition. Specifically, we discovered
that, most of the time, rewarding and acquiring new customers creates the most
value. Under select circumstances, however, attention should shift to the
retention of existing high-value customers. We recommend that managers choose
their approach based on these two features. (See “Identifying the Best Customer
Management Strategy.”) In markets that have a high degree of both flexibility
and value concentration, companies should focus on rewarding their own
customers — in particular, their best customers. If either of these
characteristics is not in place — that is, either the value concentration is
low, shopping flexibility is low or both are low — then managers should focus
on rewarding new customers or those drawn from the competition.
Identifying the Best Customer Management Strategy
In markets where consumer preferences are highly fluid and where the highest-value customers are much more valuable than others, companies should focus on rewarding their best existing customers. If either of these characteristics is not in place — that is, either the degree to which value is concentrated in the best customers is low, customers’ shopping flexibility is low or both are low — then managers should focus on rewarding new customers
Returning to
some of our specific examples in the introduction will help us to understand
the logic behind these recommendations. Consider magazine subscriptions, where
both value concentration and shopping flexibility are quite low: Most subscribers
buy only one subscription per periodical (low value concentration), and they
typically purchase subscriptions for an extended length of time, often six
months or a year (low shopping flexibility). Given the combination of low value
concentration and low shopping flexibility, the camp that advocates investing
in customer acquisition is indeed right, and we recommend that managers focus
on rewarding new customers with introductory offers.
Next, consider
the case of cellphone contracts. Here, there is low shopping flexibility but a
greater degree of value concentration. Cellphone contracts often run for one to
two years, but consumer usage varies substantially. Phone service providers
offer different plans at different tiers, and users contribute very different
amounts of revenue to a company. In this case, despite the higher levels of
concentration, the low degree of shopping flexibility ensures that it is
optimal for cellphone companies to focus on acquiring new customers, since it
is not easy for their existing customers to switch to the competition.
Indeed, this
tactic is generally on display in the introductory contract deals offered by
cellphone companies: reduced monthly rates for a fixed period of time, free
phones and often an offer to pay the contractual fees incurred by customers who
leave their current carriers. On the other hand, cellphone companies are quick
to punish existing customers by raising monthly rates midcontract, and
customers renewing a contract typically do not get the lower introductory
rates. They might get a small discount on a new phone, but even here, the
discount is less than a new customer typically receives.
Finally,
consider the case of retail stores, which typically are characterized by high
degrees of both shopping flexibility and value concentration. In retail, for
example, different people spend vastly different amounts on clothes and can
switch from store to store at the drop of a hat. As per our framework, with
both conditions (a high degree of shopping flexibility and a high degree of
value creation) met, retailers should reward and focus on retaining existing
customers by providing discount value catalogs or membership club cards to
frequent, high-value shoppers. When there is a high degree of value
concentration, it is important to retain those high-value customers; otherwise,
you are endangering profitability.
That’s
especially true where there is a good chance of customer switching due to high
shopping flexibility, such as exists in the rental car industry, another industry
in which the best customers can outspend the rest substantially. Indeed, the
best incentives and rewards in the car rental markets are reserved for existing
customers. The same is also true of airlines, where it is generally agreed that
the top customers fly disproportionately more and pay higher prices, creating a
substantial concentration in customer value.
Which Customers Should You Reward?
If you decide
to reward existing customers in markets with high shopping flexibility and high
value concentration, another series of important, related questions remains:
Should every existing customer be rewarded? And, if not, then which existing
customers should be rewarded, and how might one select them?
The answer to
the first question fits business intuition: To make sure their most profitable
customers stay with them, companies should selectively reward the most
profitable customers, as they contribute most to the customer value
concentration. And indeed, business practices are consistent with implications
from our analysis: Retailers, car rental companies and airlines selectively
reward their most profitable customers, who are at the core of customer value
concentration. These are industries with tiered loyalty programs — like the
airlines’ frequent flyers clubs — where there is substantial differentiation in
the services and incentives provided to higher-loyalty tiers.
While
selectively rewarding the most profitable customers makes intuitive sense, it
is not necessarily obvious how to identify those customers, or what to do about
customers who are not particularly profitable. Consider the following examples:
·
a Netflix customer who is paying a modest fee to receive DVDs by
mail, yet rents many DVDs per month;
·
a bank customer who insists on visiting the bank multiple times
a month and never uses ATMs or online services;
·
a retail customer who buys numerous items with the intent to
return most of them; and
·
a business customer who exploits free delivery to order small
quantities and thus minimize his inventory costs.
In all these
examples, revenues and profits may not necessarily be correlated. In the
examples above, a customer can receive a suite of services as part of a
purchase. Customers who use these services excessively can be very
unprofitable, while those who use these services sparingly can be highly
profitable. This raises the obvious question: Does it make sense to retain
those high-volume customers who also demand a great deal of service? It is not
only possible that high-volume customers may not be as valuable as they seem,
but, in some settings, they may be downright unprofitable. One study found
that, in business-to-business companies, the top 20% of customers are generally
responsible for 150%-300% of total profits, while the company breaks even on
the middle 70% of customers and the bottom 10% of customers cause losses.6 Similarly, a
multi-industry study by McKinsey & Co. found that bad customers might
account for 30%-40% of a typical company’s revenue.7
As an
illustration, we provide the cumulative profits curve at a bank with which the
second author has worked. (See “Many Customers Aren’t Profitable.”) This type
of curve is often referred to as the “whale curve” because of the profit
curve’s humpback, inverse-U shape.8 In this bank’s case,
about 50% of customers contribute negatively to profits. In fact, the top 5% of
customers contribute almost 75% of the bank’s profits.
Many Customers Aren’t Profitable
This graph shows the approximate cumulative profits curve at a bank with which one of the authors has worked. In this bank’s case, about 50% of customers contribute negatively to profits. In fact, the top 5% of customers contribute almost 75% of the bank’s profits.
Given the fact
that in some industries a select group of customers accounts for the vast
majority of profits and other customers actually detract from company profits
due to their high cost to serve, another question arises: Would it ever be
appropriate to let some consumers go, or even proactively “fire” existing customers?
Sprint Nextel
generated a flood of adverse publicity when, in 2007, it wrote a letter to some
of its high-cost customers who contacted customer service very often — in
Sprint’s view, too often. The key part of the letter stated: “The number of
inquiries you have made to us during this time has led us to determine that we
are unable to meet your current wireless needs. Therefore after careful
consideration, the decision has been made to terminate your wireless service
agreement.”9 The move created
adverse publicity after it was widely reported.
We recognize
the mix of concerns, both ethical and practical, that swirl around firing
customers. Ethically, there may be issues about the fairness of focusing
retention on the most profitable customers. Practically, there are a number of
problems immediately associated with this tactic: negative opinions passed on
to prospective customers, bad publicity, a social media firestorm and so forth.
As a result, we advocate firing customers only as a last resort.
There are many
potential steps you can take before reaching that point. Fidelity Investments,
for example, some years ago educated a group of customers to use less costly
service channels, such as the company’s website, rather than calling a customer
service representative.10 Royal Bank of Canada
simply reduced services to unprofitable customers. A check trace for profitable
customers would be prioritized and expedited in one day, for example, while for
unprofitable customers, the bank would conduct a less expensive three- to
five-day trace.11
Education,
particularly in business-to-business settings, is an especially valuable tool.
If an explicit conversation can illustrate that both parties could save money
with more economical behavior, then this is the easiest and best solution. In
business-to-business industries, it is often useful to have a conversation with
the customer, explaining which activities drive up costs and make the customer
unprofitable to the supplier. For example, a customer who often cancels orders,
requests expedited delivery or orders in very small batches can be extremely
costly to the supplier. Highlighting how these types of customer behavior
increase supplier costs and encouraging the customer to avoid such behavior can
often lead to desired and profitable behavior on the part of the customer.
If such
conversations are not effective, a supplier may need to charge separate fees
for such costly services to rein in the undesirable behavior and convert the
customer into a profitable one. And, of course, extraneous costs can be shifted
from the company balance sheet to the consumer, thereby making unprofitable
customers more valuable. For instance, some banks have started charging for
paper statements while offering e-statements for free — a pricing enticement
toward more profitable behavior among all customers.
But if these
types of measures fail, and if customer cost-to-serve is very large, then it
can pay to selectively raise prices for high-cost customers.12 That move will have
two benefits. Some “bad” customers will leave the company. They will be, in
effect, voluntarily “fired” by refusing to pay the higher price. And those bad
customers who choose to stay will become more profitable.
The common
apprehension among managers that firing customers may lead to allocating fixed
service costs among fewer customers (making them unprofitable) is misplaced.
The way around the concern is simple. Simultaneously with firing bad customers,
the company should go out and obtain new customers — customers who are on
average more profitable than the ones who were fired.
We find that
the cumulative profits curve (“whale curve”) generally becomes progressively
“flatter” over time when companies optimally manage customer acquisition and
retention — in other words, retaining their most valuable customers while
getting rid of the costliest customers and replacing them with new customers.
When the curve is flatter, it indicates more equitable contribution to profits
across customers. A company no longer suffers from bad customers generating
losses within its own customer base.
We suggest that
managers observe progressive flattening of the “whale curve” as a useful
diagnostic to assess the efficacy of a company’s customer management strategies
over time. Also, in assessing acquisition and retention strategies, managers
must direct their attention and resources to the rate at which this whale tail
flattens. Understanding how to use this analysis will help companies develop a
more effective and profitable customer management strategy.
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