The Body Shop Case Study

Date: 8 – 9 February 2018
Place: BLOCK71 Jakarta
Participants: 15 participants

As one of the FMCG companies, The Body Shop understands that the company has abundant data which need a revolutionary treatment.

Data science allows FMCG businesses to “fail fast and learn faster”. Managers or employees could use it to visualize patterns of causality and business value from various transactional and behavioural data sources. These insights allow a company to be more relevant and responsive to customer needs, which could be a real competitive advantage in such a crowded consumer market.

On every stage in its business process, from manufacturing to delivery to marketing and sales, an FMCG company like The Body Shop faces several challenges in decision making. The only resource that can be relied upon is data.

An FMCG company is able to collect data in the form of customer demographic data, market research data, promotional campaign data, finance data, social media data, and many more. Even so, this data is often noisy, unstructured, scattered and not available in the same formats. This could be challenging for a company to make use of this data and create action items that not only cater to the present situation but also plan for the future.

Data science and machine learning could be very useful tools in that kind of situation. Optimizing data science or machine learning in FMCG industry could help the business to make use of data for developing innovative products, improve targeting and to increase revenue per customer.

Data Science Fundamentals to encourage The Body Shop’s team to use data science understanding and skills with an additional introduction to Data Visualization and Machine Learning


  • Participants are able to demonstrate data processing using R programming language
  • Practising better visualization to the data analysis output and using machine learning to predict the outcome of their objectives

Relevant Courses: Data Visualization, Machine Learning, and Executive Training