Actionable Customer Analytics

Actionable customer analytics is aboutmaking data-informed or data driven business decisions.In making these decisions, managers choose from among alternative courses of action in a complex and uncertain world. Eventually, they enable the creation of business intelligence through customer insights, i.e., better decisions through a better understanding of the customer behavior.

In this master course, we will work with the most essential data analysis technique on a range of artifical and read data sets. These techniques include regression, logistic regression, and k-means. However, the focus is not on the method alone, but in particular on translating the results into recommendations for management decisions.

Using various types of data sources, models, and related exercises tied to recommended software components, course participants will develop marketing plans in various decision contexts.

The preliminary course plan is:

Week 1: Introduction + data briefing

Week 2: Descriptive analytics, regression, and JMP

Week 3: Logistic regression and actionable customer analytics

Week 4: Teamcoaching sessions & guest lecture

Week 5: Assumptions

Week 6: K-Means

Week 7:Teamcoaching sessions

Week 8: Nudging & steering customers & debriefing

In the later sessions, we will briefly look at alternative software, such as Grepsr for scrapping, python and Jupiter-files. Experience in using Excel is expected, nevertheless, this course is designed such that participants without any experience in JMP, Pythin or Gepsr will be able to complete all assignments.

Content-wise, we will apply a mixture of traditional teaching methods, hands-on assignments, applied on real-world data sets.

~45% report

~50% exam