eCommerce

After having obtained a detailed profile of the shopper’s behavior, the manager of the online area at a retail company easily recognized “proximity” sales segments within seconds. Taking these segments as a basis, he selected a sample of the customers who were delivering better response and readjusted the sample’s profile. Finally, this profile was applied on the universe of customers and prospects and in the end, the process was automated into bimonthly cycles.

A CRM manager on an ecommerce company crossed data coming from the website, from already-made transactions and from campaigns, and additionally he tracked the path to purchase in real time. Through predictive techniques, he quickly identified the best product to recommend to each customer and immediately launched cross selling campaigns.

A marketing director used Quiterian’s visual data mining techniques to forecast the profile of respondents to marketing actions, and thus increased 20% the effectiveness in customers acquisition campaigns.

A sales manager used Quiterian DDWeb both to develop a first purchase matrix to get to know activations and average expenditure per shopper, and also to predict the customers’ base churn. Not only did he improve effectiveness in retention campaigns, but he also managed to spread the customers value and lifecycle.