Social Media Profiling to Driving Marketing Recommendations

Innovation Development
Thesis Code: 

Thesis Type: MSc Thesis in Computer Science, Data Engineering, Computer Engineering, Mathematical Engineering

• Experience with Python and/or Java
• Basic knowledge of REST API implementation
• Basic notion of artificial intelligence, data mining
• Familiar with social media
• Basic English level

Marketing practices are more and more aiming to second closely customers’ habits and needs. Leveraging the wealth of customers’ data that is disseminated through social media platforms, nowadays marketing campaigns are more personalized than ever. The Innovation Development team, grounding on a deep knowledge of automated personalization using State-of-the-Art recommender algorithms, has developed an innovative process that starting from a name of a person and an email can automatically learn person's habits and preferences, and match a target product.

The goal of the thesis will be two-fold:
- conduct a survey of algorithms enabling to build a personalized marketing campaign: this includes both algorithms able to automatically build social media personality and algorithms to automatically recommend items
- contribute to refine and design the personalized algorithm for marketing recommendations
- implement the algorithm in a working prototype. For example, the prototype, leveraging a fixed range of products, will match the social media profile automatically with one product from a given item catalogue.

The student will benefit from a immersive experience working closely with a multidisciplinary team of researchers who will help the student to strengthen his/her technical robustness while developing an entrepreneurial mindset.

Contact: interested candidates send a resume with attached the list of exams taken to specifying the thesis title and code.