Leveraging the entirety of point of sale and loyalty data collected across a category, as well as additional socio-economic and other supporting data sources, apply statistical modelling to identify the own-price elasticity of demand and cross-price elasticity of demand at regular and promoted price points across Unilever’s portfolio within that category. Subsequently measuring the promotional […]

Companies rely on financial reports which are generated through various transactions such as sales and expenses to understand the discrepancies between actual performance and financial forecast. Accordingly, generating commentaries on financial data might be considered as a routine operation for many companies. The previous studies indicate that machine learning algorithms can be used to automate […]

Leveraging the entirety of point of sale and loyalty data collected across a category, as well as additional socio-economic and other supporting data sources, apply statistical modelling to identify the own-price elasticity of demand and cross-price elasticity of demand at regular and promoted price points across Unilever’s portfolio within that category. Subsequently measuring the promotional […]

Currently there are no effective tools to capture and measure return on investment (ROI) in social media in conjunction with more traditional data points that come from sources such as Flyer Tracking and Point of Sale (POS) systems. Using visual analytics techniques, this project will develop and evaluate a set of ROI metrics that will […]

Planetary boundaries can be understood as limits for the Earth’s tolerance towards environmental impacts in the form of, for example, greenhouse gas emissions, water use and the release of nitrogen and phosphorous. This project aims at making planetary boundaries useful to the environmental management within companies. This will happen by developing a method that quantifies […]