Understanding Customer Innovativeness: A Soft Computing Approach in the Database Marketing Context

Although innovation is the focus of business strategy nowadays, products/services innovation that deliver values, benefits, and convenience to customers may fail to cross the chasm in the process of innovation diffusion and adoption. This is because substantiation of market penetration never comes into being as the products/services attract merely customers of innovator segment in the market instead of those who are in the overall market. Therefore, understanding customer response to innovation, measuring customer innovativeness-the propensity of customers in different segments to adopt innovative products/services-and developing the attractive deliverables to them are crucial tasks for the success in commercialization. For a company, the customer database already in place enables the firm to capture customers' behavior and extract knowledge about customer innovativeness in different segments. However, the quality of segmentation task is also critical to empower the company to target the right customers. This paper makes a contribution toward the extant body of literature by presenting a novel methodology which firstly uses soft computing methods to determine the quality of segmentation task and then articulates customer innovativeness based on the best segmentation outcome. Data collected from an industry level case study is used for justification.