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CenSE researchers: Saskia Vanden Eede, Arnout De Donick, Katja Verbeeck, Matthias De Schoenmacker
Duration: 2017-2020
Funding: PWO
The starting point in this project is that data-smart entrepreneurship forms the basis for personalized E-commerce. The central research question in this project is the following: How can we convince SMEs that data-smart entrepreneurship is also a viable card for them to optimize their online conversion?
To make a distinction as a company or organization, it is important to approach the online consumer in a very personal way (Van Belleghem, 2016). The way to achieve this is through data science, i.e. the smart use of digital data (Osseyran, 2014). By analyzing the digital traces that a website visitor leaves behind, one can get to know the (potential) customer better and approach them personally. However, the small SME has not yet taken this step towards data-smart entrepreneurship (Bloovi & Teamleader, 2017). Often the time, budget, motivation or know-how is missing.
This project is therefore fully focused on raising awareness and information on how data and data analysis can also be used for small businesses. Based on detailed real-life case studies, a data-smart pointer is developed that shows very specifically how you can handle data and which marketing decisions you can link to it. For each practical case, a complete data mining cycle (Witten, 2011) is run through: that is, to determine which data is relevant, capture this data, process it into a model, visualize and finally interpret.
It is certainly not the intention to develop a new business intelligence or data tool; rather, it is intended that the pointer, based on specific examples, reduces the threshold for data-smart business. The example cases must therefore be sufficiently representative. We limit ourselves to examining visitor data from websites that sell a product or provide a service. The specific purpose of the analysis is to increase the conversion of those sites.
In this project there will be collaboration with different target groups. In the first instance, these are SMEs that are themselves already active online. Furthermore, there will also be collaboration with web and marketing companies and professional federations such as BDMA, feweb, VOKA, UNIZO and Safeshops. This both for mapping the current data-smart entrepreneurial landscape and for disseminating the results and the services afterwards. Appropriate awareness-raising and information campaigns (lectures, workshops, etc.) will be worked out for each target group.
The idea of this project arose on the one hand from the fact that the professional field needs new knowledge profiles such as data scientists and data-driven marketers. This project therefore creates new synergies within the IT and marketing courses. On the other hand, this project is also a continuation of the PWO Social Success Meter (Verbeeck, 2015) in which data analysis is used to increase the conversion of social crowdfunding projects.
