Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/14086
Title: Using Analytics to Pitch the Right Customer with Right Product at the Right Time through Right Channel
Authors: Kumar, Salil
Arif, Mufazzal
Keywords: SMS;STM;DNC;NDNC;Logistic Regression;Product Prioritization;Multinomial;Inbound Channel;Customer Power
Issue Date: 2015
Publisher: Indian Institute of Management, Ahmedabad
Citation: Kumar, S., & Arif, M.. (2015). Using Analytics to Pitch the Right Customer with Right Product at the Right Time through Right Channel. 4th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence. Indian Institute of Management, Ahmedabad
Series/Report no.: IC 15;159
Abstract: There are various channel of communication for cross selling of Banking Products and service.Out of which SMS, Email, ATM Display, and Internet banking Display are most important Channel for Banks in order to engage customers and cross-sell their products through these channels. Most of the instances the customer is getting multiple communication from Bank for various offers or services. The Product Centric approach bombards the customer with so many communications in all channels without checking the applicability and accessibility of that information / offer to customer. With more and more customers registering for DNC and NDNC, the accessibility of such customers is also reducing. In such a challenging environment, it is most appropriate to engage with the customer which is preferred by the customer. As in the recent times there are multiple touch points (ATM, Internet Banking, Branch, Inbound/Outbound call, SMS, Social Media etc.) for a customer to connect with the bank. Given the value of these customer-led interactions, it’s equally important to put forward a relevant message to the customer at each of such interactions. There was a need to develop a solution that helps HDFC Bank identify the most relevant product / service at customer level based on all the information available at customer level.
URI: http://hdl.handle.net/11718/14086
Appears in Collections:4th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence

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