From Data To Insights: How to Infer Valuable Insights from Big Data in Business?
“From Data to Insights” is a research area of the Chair of Quantitative Marketing and Consumer Analytics at the University of Mannheim. Due to the digitization of the value chain, companies have access to huge amounts of various types of “Big” data which provide the opportunity to analyze and answer strategic questions in management and marketing. In our research we show, how individual-level consumption data or unstructured information from social media, online networks, and brand perceptions can be transformed into insights and key performance indicators. Furthermore, we show how this consequently results in more effective corporate and marketing strategies.
Based on research insights, we teach students and executives various types of methods and tools to analyze and to utilize big data. In our courses we train participants how they can deduce relevant management implications and sustain competitive advantages from various types of data which are available today in companies.
Exemplary research “From Data to Insights”
- Communications and Diffusion Strategies in Social Media: In this day and age, companies face decreasing effectiveness of mass media. On the other hand, online social networks have become ubiquitous in everyday life. Therefore, companies try to increase their brand awareness by exploiting the vast potential that online social networks offer. Within this domain, we analyze communications, seeding and diffusion strategies and suggests policies on how to capitalize on online social networks in order to increase brand awareness.
- Digital Customer Management - Insights from your Customer’s Digital Footprint: The application of digital technologies allows to improve customer knowledge tremendously. Tracking the consumer journey and analysing the consumption of free and/or paid digital offers are of utmost importance in order to develop a successful strategy for the profitable acquisition and retention of customers on websites, in apps or online shops. In our research, we develop key metrics and tools on how to gain insight and derive implications from big data on consumer behavior.
- Revenue Models in the Digital Age - How to Maximize Profits of Digital Goods? Classic business models and marketing approaches cannot be transferred directly, but have to be adapted to the characteristics of the digital market, especially when it comes to pricing or product management, e.g. off apps or websites). Oftentimes, revenues come from multiple sources (e.g. customers of paid content and advertisers on the website, and in addition, are interdependent. The focus of our research is to find insights on how to determine the optimal price strategy for paid content, how to decide on how much content should be paid and how to ultimately maximize revenues from users and advertisers.
- Consumer Behavior in the Era of User Generated Content: Over the past years the amount of content that is generated by consumers such as consumer product reviews has increased tremendously and their relevance consumer behavior such as their purchase decisions has been clearly established. In this project we aim at analyzing the impact of user generated content on key consumer metrics such as purchase behavior on an aggregate as well as on an individual level and to identify key drivers of the relationship between consumer reviews and sales in order to better predict their impact in the future.
Are you interested in getting more information about how to turn data into insights?
Your contact for more information:
Prof. Dr. Florian Stahl
L 5, 2 | 68161 Mannheim | Germany
Email: florian.stahl(at)uni-mannheim.de | Phone: +49 621 181-1563