Data driven sustainable lifestyle

Important results from the project

The purpose of the project was to use data-driven analysis to analyze the user´s consumption in order to continuously calculate the persons climat impact, and propose personalized areas of improvement with the aim of continuously reducing the individual´s climate impact through changing consumption and lifestyle habits. The project has resulted in methods, technical platform and knowledge to do this. The methods and functionality also leads to increased retention among the users, which is the basis for a long-term sustainable business model.

Expected long term effects

The results of the project are new methods, technical platform, and knowledge for data-driven analysis, including prerequisites for continued machine learning of data collected. The project has also resulted in extended collaborations with partners and insights that have meant improvements and new features in addition to the project´s objective. The effect of the project´s results is expected to be further increased retention among existing, as well as new, users. With increased retention, the platform also becomes more attractive to partners and a sustainable business model.

Approach and implementation

The project´s setup was partly based on collaboration with partners, where some partnerships became less important than initially planned while some turned out to be much more significant. The initial approach to calculating an individual´s climate footprint based on transactions also decreased in importance after user testing and personal recommendations based on lifestyle and consumption became more important. Data-driven recommendations also pose a greater challenge in terms of methodology, and collecting and analyzing sufficient amounts of relevant data was a challenge.