Luminis Apeldoorn is experienced in building large-scale e-commerce platforms. Through the years we have seen how these systems changed from providing the customer with a static routine in which they search for and potentially buy products to the use of recommender systems that provide a personalized experience.
Our systems could perhaps be improved if we apply predictive analytics to select the ‘next-best-action’ and personalize the way our systems engage with customers. With this, the focus is not directly on recommending some product within the current transaction, but to increase the total customer lifetime value by, for example, reducing customer churn.
This internship is an opportunity to lean about the possibilities of predictive analytics. You conduct a literate review to increase your breadth of knowledge of state of the art analytics techniques with a view to applying them in the context of e-commerce.
At the same time, you start building a prototype e-commerce platform to experiment with and demonstrate various predictive analytics techniques.
Depending on your education the emphasis could be more on the research part and/or on the implementation of the prototype.
Does this assignment appeal to you? Please contact Jorg Hollenberg, email@example.com