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Customer value management - Analytics is a must for customer loyalty

Posted by Bala Deshpande on Wed, Feb 22, 2012 @ 09:21 AM

There is a very subtle line separating the customer retention and customer loyaltyimproving customer loyalty programs using analytics resized 600 activities that must be followed by a business. The distinction between the two was elegantly expressed by Francis Frei in her column:

" ... When companies pay customers to remain customers, it’s part of a customer retention program.  When companies invest in activities that increase customers’ willingness to pay, they have a customer loyalty program.  When a loyalty program works, it increases the chance that your customers will choose you over a lower-priced competitor."

The sophistication of effective customer loyalty programs range from redeemable points or vouchers to elaborate co-creation activities where customers are involved in product strategy and placement and get rewarded by companies if the strategy is successful. Experienced managers know that customer loyalty cannot be earned in a day, but it is a long term process. The Logic Group believes that there are three essential elements to increasing customer loyalty

  1. Understand why your customers are loyal in the first place
  2. Keep the rewards relevant
  3. Continually monitor your customer service by means of surveys

As you can see, analytics can play a very important role in all three of these elements. For example, techniques such as k-means clustering can help in properly segmenting your customers base to understand demographics and similarities. Association rules or affinity analysis can help you identify what products are normally associated with each other, so that when a customer buys one, offering a coupon or incentive to buy the other can increase cross-sell opportunities. This is all about keeping the rewards relevant. 

Customer value management is basically about ensuring that the right customers are acquired, developed and retained. Customer loyalty programs strengthened by the right analytics will help establish these objectives. 

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Topics: customer retention, k-means clustering, customer value management