A day in the life of a profiler

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

Learn how to estimate the risk of churn in a customer database with Alteryx (part1)

This model will estimate the risk of churn of telco customers and can be used to set up a retainment policy. Furthermore, we will do it together.

Mapping geographic variations of income with Alteryx

We would like to visualise the variations of the average income in Belgian municipalities. We also want to see clearly which municipality of every region has the highest mean income.

Learn how to calculate and visualise local variances of your market share with Alteryx.

In our previous article, we measured how the market share of a Belgian company evolved between 2016 and 2017. In that analysis we concluded that there was no significant difference between the market share of both years at national level. Now we want to have a closer look at these evolutions with a local approach.

How to measure the increase of the market share with Alteryx

We will analyse two consecutive years (2016 and 2017) and see how the market share has increased. First of all we load the files of the sales by customer and by year. We also have access to the sales potential by postal code and by year.