GFK Norm focuses on understanding consumer behavior and the process that leads to a purchase decision. A proprietary virtual store environment, Simstore has the ability to predict the impact of marketing activities at the point of purchase based on solid shopping simulations. In short, Simstore allows for providing of quantitative shopper research that supports business decisions. Using new technology and new research methods, GFK Norm is looking for an understanding of the decision makings process.
Our task was to create a survey data processing and visualizing system with microservice structure. The project was aimed at receiving raw data provided by GFK Norm and making a number of extensive Powerpoint presentations and Excel spreadsheets fully ready, editable and adjusted for working with them for those interested in such data. We parsed aggregated jsons, aggregated raw json and then parsed aggregated json in other microservices, created dataclasses, added metadata, created templates and filled them with the data.
An interesting point is that the developed system aggregates the data with the use of complex statistic analysis algorithms, thus separating random fluctuations and finding the most valid statistical differences.
WRIM and National Representation Weighters
Weighters are the first part of system that is used for counting the weight of each respondent based on his answers to other anchor questions
Aggregates the raw data based on anchor questions and applies statistical techniques to understand correlations
Creates a human readable Powerpoint presentation based on results of the aggregator with graphs and tables added. Supports custom pptx templates. Uses AWS storage to store and retrieve different templates
Another way of creating a human readable output. Creates excel tables that allows specialists to apply different data analysis techniques as required