Purchase Triggers
It is essential that an e-commerce website, at the end of the day, incites purchase. A combination of clickstream analysis, purchase driver analysis to understand customer drivers and user experienced based design can do that. A fast growing field within this realm is something very similar to the retail Market Basket Analytics- analytical algorithms to determine what else the customer is most likely to purchase provided he has purchased product B.
A prime example of this is the Netflix Prize. The world’s leading online rental delivery, Netflix announced a prize of $1 Million for the team which most improved upon their algorithm to recommend movies to a customer based on his previous viewing preferences. The winning algorithm improved on Netflix’s own algorithm by a little over 10%, which was considered significant enough for a $1 million prize in terms of its impact on customer loyalty and basket size
Retention and Loyalty
Akin to consumer banks and large retailers, web analysts also use customer segmentation and clustering based on Recency (when did the customer last visit the website), Frequency ( how often does the customer visit the website) and Monetization (what is the size of transaction/length of visit) to reward loyalty, attract profitable but infrequent customers and retain those who were once profitable but now seem to be leaving
Customer Engagement
The first step towards enabling customer engagement is placing analytically developed content on the website, most likely to appeal to the target segment. Some other analytical techniques used to help companies at this stage include:
• Clickstream Analysis- to understand user traffic, landing pages, most frequently visited pages and most traversed path, ensuring that all the content in these pages is geared towards creating a purchase
• User Experience Design- Using the insights developed through click stream and traffic analysis to create a seamless user experience in the website, reducing the number of clicks to desired outcomes (hence dissonance) and ultimately enabling purchase.
2.Social Media Marketing based buzz analytics:
What is the customer saying about your traditional brick or mortar product online? Customers talk: in their online reviews and Facebook statuses and their Twitter feeds, and they listen- to industry experts, their blogs, web searches and discussion forums. It is essential for companies to be able to understand what the overall buzz about their product/brand is and to leverage it to create stronger brand resonance. Text and sentiment mining, conducted in an analytical framework can help us greatly really understand what a customer feels about the brand