Customer Retention and Modeling in the High Ticket / Durable
First published 10/01/01
One might think the principles of RFM
and LifeCycle modeling would break down in the durable goods
area. For example, is a person who bought a refrigerator
Recently more likely to buy another one than a person who bought a refrigerator
a long time ago? On the surface, the answer would seem to be
no. But to ask the question this way is to set up a "trick
question" with a self-fulfilling answer. In fact, this
question is not the right question to ask.
Let's look at this from two perspectives - the perspective of the
"whole relationship" with the customer and the perspective
of a single product replacement cycle.
RFM approaches customer behavior from the perspective of a business
and the relationship of the business with a customer, not from
a product-driven view. RFM tells you the person who Recently
bought a refrigerator is much more likely to buy any product from
the business relative to a customer who bought a refrigerator at
some date further in the past.
In other words, from the perspective of the business selling the
refrigerator, the customer who Recently bought a refrigerator is
much more likely to buy a stove, a washer-dryer combo, and so forth
than a customer who bought a refrigerator further in the past. This
is RFM from the "whole relationship" perspective. It's
about the relative likelihood of customers engaging in purchase
behavior with a business, not the absolute likelihood of any
customer or non-customer on the planet to buy another refrigerator
based on last purchase date.
If you want to stretch RFM into service from the single product
perspective (the repeat purchase of another refrigerator), you have to
make adjustments to the method. With long purchase cycle
products, you have to move your threshold of measurement out in time
to account for the long product cycles. In other words, it is
Recency of purchase relative to the expected life of the product (or
some other variable) that matters, not Recency of purchase from
purchase date. To expect a re-purchase of a brand new appliance
immediately after initial purchase ignores human behavior, and RFM is
about predicting relative human behavior. You have to
"normalize" the method to account for long lifecycle
products and services.
For example, if the refrigerator has an expected life of 5 years
(perhaps the length of the warranty), a logical data point to study
would be Recency of purchase relative to warranty expiration.
A customer who is only 6 months past warranty expiration is much more
likely to purchase another refrigerator from the business who
originally sold them one than a customer who is 2 years past warranty
expiration. The more time passing into the replacement cycle,
the less likely the customer becomes to replace the unit with the
business who sold them the first refrigerator.
Here's an example from the auto industry. In the 60's, when 2
- 3 year financing was the norm, dealerships had very high repeat
customer rates. When payment terms for cars stretched to 5 years
in the 70's, repeat purchase rates at auto dealerships dropped
dramatically. Over these very long product cycles, people became
less and less loyal to the individual dealership / brand of car they
had purchased. Since buying a car is a significant (and often
traumatic) event, dealerships benefit greatly from handling customers
carefully and creating a pleasant buying experience. But over
time, customers forget the details of this experience and become more
likely to seek other sources.
With the introduction of a 2 year vehicle lease, repeat rates
soared. Early dealership and product line adopters of the 2 year
lease experienced rapidly increasing market share wins at the
individual dealership level, and these increases affected entire
product lines on a national basis, forcing a capitulation by those
dealerships at the local level and product lines at the national level
not offering short-cycle financing methods to their customers.
It became just plain easier for customers to repeat with a dealer,
because the memories of the past transaction were fresh - they had
"gone through the motions" of the decision-making process
more Recently. Familiarity breeds inertia, especially when
making high-ticket purchase decisions. And all this happened
despite the fact car leasing is generally an inferior deal relative to purchase
from an economic standpoint.
Are their other influences? Sure, just like any other
business. At a dealership, service is big business and the way
customers are handled with respect to repairs is critical. This
leads to a whole other opportunity for behavioral profiling - the
impact of Recency or Frequency of service on the new car buying
decision. My guess is they are negatively correlated - the
higher a customer scores on Recency and Frequency of repairs, the
lower their likelihood of a repeat purchase with the dealership.
This effect is seen in the service
business all the time, where profiling of non-purchase
transactions is frequently more predictive than profiling purchase
transactions. But just because the metric is inverted does not
mean it is not valid; it simply represents an inverse relationship
relative to the desired outcome.
Many companies offering long purchase cycle products actively
shorten the cycle by employing an inter-purchase contact
strategy. By actively contacting the customer between purchases,
these companies try to "bridge" the purchase cycle and
maintain Recency of contact. This approach can lead to an
increase in repeat purchase rate, if handled correctly.
In fact, this approach is not new and has nothing to do with the
Internet. State Farm Insurance has for a long time pursued this
contact strategy through the mail. Many companies have the means
to conduct an inter-purchase communication campaign though the
installment loan system, but fail to send the customer anything but a
bill and bunch of bill inserts selling unrelated products. On
the other hand, Weber-Stephen Products Co., the manufacturer of Weber
Barbecue Grills, sends a quarterly magazine full of seasonal cooking
tips and accessories to customers who buy high-end grills.
In the durable goods business, it is much more likely the data
needed to profile customer behavior has never been collected or cannot
be accessed than it
is RFM "doesn't work" for the business. If developing
a customer retention measurement and management system is on your
"to do" list this year, you might want to pick up a copy of