Online Shoppers Purchasing Intention [SPKK19]¶

Since past few years, the e-commerce merket has seen a huge surge in their number. Online presence has become important for companies to improve their relationship with the consumers. A e-commerce website is a platform where the campanies can engage with customers in order to improve their sales. Though a large number of e-commerce paltforms have emerged, there is no equivalent rise in the conversion rates. Hence, there is rise in investment by the companies in order to deal with the problem. It is extremely difficult for the companies to convience users to buy their products and one of the reason for such difficulty is the lack of customized solution as per the need of the user.

In order to provide customized solutions in the online environment, it is first necessary for the companies to understand the intention of users. Machine learning played a crucial role in identification user intention. A lof of studies were conducted to classify the visits by users based on navigational patterns. A set of commonly visted set of navigational patterns are identified and customized actions were taken depending on the choice of navigation pattern a user follows. This help in extending time user spend on the website and increase the probability to purchase. Some studies also used user transactions and pageviews to derive aggregate usage profiles which were used by recommender systems to take customized actions in real-time. One of the research also used association rule mining to compute probability of purchase by the visitor.

With all these research, it is confirmed that it is extremely important to monitor user behavior in the virtual shopping environment which can be utilized to take customized action in order to provide personalized solutions to the clients. This helps in increasing the conversion rates and decrease in the abandonment of cart.