Managing a point of sale network is a dynamic and continuous project, requiring a careful eye to be kept on numerous aspects. This year's economic crisis will strengthen the need for profitability, or even restructuring.
Analysis of this data and usage in analytical models makes it possible to improve your customer knowledge and is a real gold mine when it comes to segmenting and targeting your customers, and even predicting their next purchases.
We were recently asked to provide more information on Belgian consumers and their purchasing habits. What does the Belgian consumer look like and what drives him? What opportunities does this offer retailers?
Knowing your customers better so that you can attract new ones: that's the essence of customer profiling. Customer profiling is a technique widely used in (geo)marketing, making it possible to precisely target the customers and prospects of most interest to your business.
Learn to build a predictive model to track churn with Alteryx (part 2)
Learn to build a predictive model to track churn with Alteryx (part 2) In our previous article we prepared our data so that we can use it in a predictive model meant to estimate the risk of churn. To this aim we did some data cleansing and standardisation of categorical and numeric variables. In this article we test a predictive model that is available in Alteryx Designer: a random forest. A random forest combines hundreds or thousands of decision trees. Each decision tree is built on a random subset of the observations, considering a limited number of the features. This Continue Reading