B2C E-Commerce Business Analysis

Considering the level of competition in Business-to-Consumer (B2C) E-commerce environment and the investments required to attract new customers, firms are focusing on reducing their customer churn rate. Churn rate is the ratio of customers who part away with the firm in a specific time period. One of the best mechanism to retain current customers is to identify any potential churn and respond fast. Detecting early signs of a potential churn, recognizing what the customer is looking for by the switch over and automating personalized win back campaigns are essential to sustain business in this era of competition. E-Commerce firms normally possess large volume of data pertaining to their existing customers like past transactions, search history,
According to Forrester Research, as on 2014 E-Commerce is contributing 5.9% of the overall retail revenue amounting to $1.3 trillion. E-Commerce share is expected to grow to $2.5 trillion by 2018 reaching 8.8% contribution to retail revenue. While E-Commerce is having such a great growth potential, there are many challenges for the firms in this area. In a seller perspective customer retention is the key for their profitability. Most of the initial transactions are not profitable in B2C E-commerce business while accounting the average cost for new customer acquisition. A customer relationship will start making profit only after a few repeated business, when the average cost per serving the customer comes down. This underlines the need of customer retention and reduction of customer
According to a survey conducted by the Rockefeller Foundation, majority of customers mentioned that they move on from sellers as they are not being cared [Fig. 1]. The real challenge is to identify which customer is moving to the competitor and which customer is going idle for a while. Historical data can be mined in such a scenario to identify different purchasing patterns of customers. For example, some shoppers might do their purchases on every alternate weeks, some might do near to their salary day and some might purchase only around holidays. Of course this has a dependency on what is the tem being purchased as well. But when a consumer deviate from the purchase pattern which was observed for a while, it may be a potential case of churn.
Once a potential parting away customer is identified, the retailer can try out personalized retention strategies. Individualized offers may do excellent results in such scenarios. For example, a customer who orders a particular brand products on every school opening, but shows signs of parting away with recent purchase patterns may get excited and come back when he get a call/intimation from the shopper on the availability of his preferred items at a discount