Conversion paths of online consumers: A sequential pattern mining approach

Abstract

As the number and variety of online channels increase, businesses and advertisers must realize efficient marketing strategies and marketing mix. Customers' online channel usage patterns can be heterogeneous depending on various variables. If they understand this behavior correctly and use them for channel inflow or advertisement toward customers, they can establish an effective marketing strategy. In this paper, we utilize sequential pattern mining to find homogeneous patterns in customer's conversion paths by using conversion path data of customers who purchase diapers and find related insights. Furthermore, by analyzing the customer's channel movement pattern by dividing it into demographic information, we examine how demographic factors affect customer's online channel usage behavior.