Programming and predicting the future with big data

Big data, machine learning, artificial intelligence ‒ those are the buzzwords in many companies when it comes to marketing. Still, the programming skills needed to work on these concepts are not commonly taught in marketing programmes. That is why Rotterdam School of Management, Erasmus University (RSM) offers the elective Big Data Analytics for Marketing Insight for master students of the MSc in Marketing Management.

Data are all around us, for example on social media or reviews on web stores. These data sets can tell you a lot about people, for example which groups of people bought a certain product and which people didn’t.

“Marketing is about predicting the future,” says Dr Pieter Schoonees. The assistant professor from RSM’s Department of Marketing Management continued: “And the best way to predict the future is to learn from the past. If you bought this brand before, it’s likely that you’ll buy it again.”

For his course Big Data Analytics for Marketing Insight, Dr Schoonees trains marketing students to use machine-learning algorithms to mine unstructured data and predict future behaviour of new customers.

No technical background

Along with the elective Marketing Analytics, the course leans heavily on the use of R, an open-source programming language for statistical analysis and data visualization. The elective aims at marketing students, but is open to other RSM master students, and may be especially useful to students who want to work with data on a deeper level.

According to Dr Schoonees, RSM is one of very few universities that offers such a course for students without a technical background. “It helps to have some prior experience with programming, but it’s not required,” he said.

“Programming is a useful skill for marketing students, because companies are increasingly looking for people who can apply data – lots of data – to solve business problems,’ said Dr Schoonees.

Students are taught, for example, how to build a model that predicts which Amazon reviews are most useful to consumers. Or a model that can predict which emails should be marked as spam. ”Unfortunately there is no one method which is best at solving all problems. Every problem has unique aspects, so during the course we talk about different strategies and we provide various tools for various situations.”

Hard work

Saad Maqsood (26) took the elective when he was enrolled in RSM’s MSc Marketing Management.

“It was a great experience overall and it really helped to learn more advanced forms of predictive modelling that very few courses teach you.” Although the course was quite intensive, Maqsood said he highly recommends it for students pursuing a more quantitative field within marketing, such as search engine advertising, conversion rate optimisation or business intelligence (BI).

Saad Maqsood is now employed as a web analyst at International Bike Group. “This elective, as well as my thesis with Dr Pieter Schoonees, helped set up a strong foundation. It greatly helped me enhance my analytical skills and think more quantitatively. In marketing, having good quantitative skills helps you stand out from the competition. So ultimately, it helped me find the job I really liked.”

More information

Rotterdam School of Management, Erasmus University (RSM) is one of Europe’s top 10 business schools. RSM provides ground-breaking research and education furthering excellence in all aspects of management and is based in the international port city of Rotterdam – a vital nexus of business, logistics and trade. RSM’s primary focus is on developing business leaders with international careers who can become a force for positive change by carrying their innovative mindset into a sustainable future. Our first-class range of bachelor, master, MBA, PhD and executive programmes encourage them to become critical, creative, caring and collaborative thinkers and doers. Study information and activities for future students, executives and alumni are also organised from the RSM office in Chengdu, China.

For more information about RSM or this release, please contact Marianne Schouten, communications manager for RSM, on +31 10 408 2877 or by email at

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