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Methodology and Process to Increase Revenue by Optimizing Customer Experience Based on Firmographic, Behavioral, and Opportunity Data, using Predictive Analytical Models

IP.com Disclosure Number: IPCOM000238983D
Publication Date: 2014-Sep-29
Document File: 3 page(s) / 61K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a predictive model to determine the probability of customers' purchasing from a given supplier via backend business-to-business (B2B) eCommerce integration. The model analyzes firmographic data, organizational buying behavior data, opportunity data, and current eCommerce integration status with a particular supplier, to produce a rank-ordered list of customers to be boarded on eCommerce.

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Methodology and Process to Increase Revenue by Optimizing Customer Experience Based on Firmographic, Behavioral, and Opportunity Data, using Predictive Analytical Models

Companies have finite resources to invest in boarding customers onto eCommerce, specifically in the area of backend business-to-business (B2B) eCommerce integration. By picking the right customers to be boarded in the right sequence, however, companies can optimize the customers' experience of purchasing, which in turn drives wallet share, which drives incremental revenue for the supplier. Current technologies exist for predicting customers' behavior in terms of items selected for purchase; however, no technologies address predicting the customer's methods of purchase.

The novel contribution is a predictive model to determine the probability of customers' purchasing from a given supplier via B2B eCommerce integration. The model uses firmographic data, organizational buying behavior data, opportunity data, and current eCommerce integration status with a particular supplier. The model produces a rank-ordered list of customers on which a company needs to focus. This model is unique in its usage of certain types of data combined with statistical modeling in order to determine the probability of integrating with supplier via eCommerce integration.

Figure: Business solution and applied methodology

In a preferred embodiment, the process begins with an interview of sales representatives to determine key customer pain points. These interviews result in determining which data are needed later in the process. Based on the findings of the interviews, the next step is to gather the following data:


 Firmographic data: including corporate revenue, number of employees, industry sector, region, fiscal year-end month


 Buying behavior data: including total information technology (IT) spend, wallet share of that spend with the supplier in question, whether customers currently purchase from supplier via eCommerce integration, a...