NRI Papers
No. 186 June 1, 2013
  New Customer Management Technique:CRM by "RFM + I" Analysis  
Katsutoshi MURAKAMI and Shigeki NATORI

Traditional customer management analysis has mostly focused on the "purchasing power of customers themselves," as typified by RFM (recency, frequency and monetary) analysis. However, given the increasing importance of information disseminated by customers such as through word-of-mouth communication, a need arises for incorporating the perspective of a "customer's ability to disseminate information = I (influence)" into customer management.

In 2012, as part of its research activities to develop new customer management analysis techniques, Nomura Research Institute (NRI) undertook an experiment in cooperation with a consumer goods manufacturer. This experiment revealed that (1) by making use of social media, it is possible to determine a "customer's ability to disseminate information," (2) information dissemination activities originate from only a small percentage of customers (influencers) and (3) by implementing measures that leverage the information dissemination ability of individual customers, a better marketing effect than that which has been possible in the past can be obtained.

The use of the perspective of "RFM + I" analysis that is proposed by NRI will add an expanse of new landscapes to the concept of customer management. For example, even when a customer himself or herself has low purchasing power, if that customer strongly recommends the purchase of a company's products to people around him/her, the company must give importance to this customer in its marketing activities. NRI's RFM + I analysis adds this perspective to traditional customer management. In addition, the company needs to build relationships with customers having high RFM + I scores in terms of two aspects: making them promoters of the company's products and preventing them and those who are influenced by them from defecting to competitors.

With traditional customer management, the focus was on maximizing profits generated from customers themselves. However, with RFM + I analysis, which takes information dissemination ability into account, in addition to maximizing profits, it can be expected to acquire new customers based on the connections between customers. As such, RFM + I analysis offers a vast expanse of new marketing possibilities that can drive increased sales.

Contents
I Differences between Traditional RFM Analysis and "RFM + I" Analysis Proposed by Nomura Research Institute
II Impact of Customer Connections on Consumption
III NRI's Experiment to Identify Influencers and Its Results
IV Use of RFM + I Analysis for CRM

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