This course provides a deeper insight into the following three data-driven contributions to marketing and sales, enabled by social media and modern big data technologies:
Customer Analytics: As a recent study revealed that customer analytics are dominating big data use in sales and marketing (Datameer 2015). Among other things, it aims to improve conversion rates and lower customer acquisition costs. In this course, R (a well-known and free statistical programming language) will be used to analyze customer demographics and behavior. To provide an adequate setting, a real-world data set will be investigated in detail.
Contextual Marketing: Social media platforms know a lot about their customers by gathering huge amounts of data. For example, the video streaming service Netflix uses this information in combination with a personalized recommendation engine to reach high customer satisfaction. In this course, a consumer database will be used to build such a recommendation system. The engine will be based on collaborative filtering, a method of making automatic predictions of the interests of users based on users’ preferences.
Online Communication Management: Social networks have revolutionized communication, providing a public channel where customers can contact businesses, organizations or people directly. On the one hand, these channels allow companies to gain a better understanding of the general market and of their own as well as their competitors' customers. On the other hand, they also pose a threat to any company’s reputation, because they may be used for customer attacks. Nowadays bigger companies are prepared for social media crises (also known as “shitstorms”) by using modern prediction and analysis methods. In this part of the course, students will have to create a small scraper, which loads data from a so-called social media application programming interface (API). In a second stage, basic text mining techniques will be used to determine the sentiment of the collected data, which in turn can be used to analyse and detect anomalies.