This internship example is relevant for master students in marketing, business administration, economics, communication science, or related studies.

We are a global leader in claims testing and over the past 5 years we have tested more than 5,000 claims for different product categories. Our expertise is used to develop claims which are used in various communication materials such as TV commercials, print ads, on pack, and in other collateral materials. You may have seen some of our work or their local translations: ‘Smooth beautiful underarm skin in just 5 days’ (Dove Deodorant) or ‘Double the fragrance in every drop’ (Comfort Fabric Conditioner).

All claims that have been tested over the years are gathered in a database which we utilize to generate cross-study, category and market insights, train brand management teams and publish in international magazines. We are keen to extract more insights from this database and to extract these insights in a more efficient way. Therefore the assignment will consist of two parts:

1. Theoretical – In 2009, we conducted our first meta-analysis on the claim database. It was based on approximately 500 claims in a limited number of markets. Now that the content has increased ten-fold, we would like to repeat the meta-analysis. The questions are: what is an effective claim? What are drivers of claim effectiveness? Are the results from 2009 still valid? What are trends between 2009 and 2014? Are there key differences in claim preference and effectiveness between markets?

2. Practical – How can we extract our insights from the database in a more efficient way? Our goal is to develop an interactive dashboard in the database which displays key database benchmarks.

Other tasks might include developing a presentation and/or digital archive with additional information, material and articles to extract and share knowledge among clients and SKIM people, and co-write papers on claims insights to drive market and client awareness. You may also work on an actual communications study to see how these studies work in reality.