Our customer has a volume of 12,000 clients with an annual client exit rate of around 10% and 18% new clients. A mere reduction of the client exit rate would have a significant business impact. Our analysis tool identifies around 85% of the clients at risk of dropping out to implement customized and/or segmented marketing campaigns.
Our customer, an association, needed to know which the target companies for its advertising campaigns are. The websites of the most important 5,000 Spanish companies were analysed to detect those with the involvement at the highest level in Corporate Social Responsibility (CSR) activities and, in particular, with science. As a result, a list of 100 enterprises, a ranking and priority objectives were obtained. It greatly facilitated the contact with those companies that might show greater interest. Applied techniques: Web scraping and Text mining.
Our customer, an online store, was interested in exploiting the Google Analytics information and also the data provided by its e-business management system to be used in different areas: cross-buying, segmentation and campaigns. The Google Analytics data for the last 2 years (half million records) and our customer internal data were downloaded and analysed. The results contribute to improve cross-selling (same shopping cart and from the first to the second online purchase), to segment customers according to their purchasing profile information to perform customized marketing campaigns. Google Analytics techniques, Association rule mining and Clustering were applied to.
Our customer, an ICT sector company, needed to improve its customer acquisition strategy. A predictive model using historical sales data was designed to estimate the success rate for future sales addressed to 5,000 new potential clients. Supervised learning techniques were applied.