Customer Retention and LifeCycle Modeling  
 in the High Ticket / Durable
          Goods Business
          First published 9/17/01
           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 a
          long time ago.   
          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 a long time ago.  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 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 and is not intrusive. 
          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
          my book. 
         
        
        What would you like to
        do now? 
        Get
        the book with Free customer scoring software at: 
        Booklocker.com    
        Amazon.com     Barnes
        & Noble.com 
        Find
        Out Specifically What is in the Book 
        Learn
        Customer Marketing Models and Metrics (site
        article list)
        
           
     |