Demand estimation in consumer-packaged goods market using BLP method

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 cannibalization of Unilever’s temporary price reduction activities across the market to assess the promotional events with the highest return on investment and revenue optimization potential.

Improved Commentary Prediction on Financial Data

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 the process of commentary generation. Specifically, such approaches use product forecasts and actuals in addition to inventory and point-of-sales data for the underlying prediction task.

Pricing model from econometric perspective and visualizing promotion cannibalization effect on promotion activities

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 cannibalization of Unilever’s temporary price reduction activities across the market to assess the promotional events with the highest return on investment and revenue optimization potential.

Trade promotion forecasting and optimization

This project addresses two specific challenges related to promotional planning in the consumer-packaged goods sector. The first output will be to develop and evaluate models that statistically predict the impact of Unilever promotions on category and product share across different retailers. This effort will lead to the creation of trade promotion optimization techniques that enables planning of promotional activities.

Social Media Impact Tool: Measuring ROI for Social Media Engagement

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.

A life cycle impact assessment methodology based on planetary boundaries

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 environmental impacts of a company in the language of planetary boundaries.