Value creation through innovative statistical methods and AI solutions for customer and user data
| Reference number | |
| Coordinator | JUPEL AB |
| Funding from Vinnova | SEK 300 000 |
| Project duration | August 2020 - December 2020 |
| Status | Completed |
| Venture | Innovative Startups |
| Call | Innovative Startups step 1 spring 2020 |
Important results from the project
Jupel develops innovative analysis methods for customer, user and behavioral data for efficient data-driven decision-making processes. During the project, we have taken a significant step towards commercializing our analysis methods based on our research experience in statistics. The project has had four sub-goals; develop a strategy for data processing and interconnection of data sources, investigate market conditions, develop routines to ensure ethical and legal handling of personal data as well as prototype development and preparations for major user tests in step 2.
Expected long term effects
Jupel has - acquired insights on required pre-analysis work, how data from different CRM systems is extracted and developed solutions to combine different data sources. - concretized the need of data analysis for different customers and decision-making processes. - produced necessary agreements and documentation required for Jupel´s operations. - programmed a comprehensive base of algorithms for a variety of analyzes and purposes. The project has provided valuable conditions for user tests on a larger scale in step 2 and for development of a software solution for our services.
Approach and implementation
The project included 3 main work activities. In-depth interviews were conducted with public and private actors, including consulting firms. The interviews provided valuable insights into potential customers´ data structure, analysis needs and attitudes to data-driven decision-making. An investigation was conducted to ensure that Jupel complies with applicable laws and regulations with focus on GDPR legislation. A large part of the project has been spent programming algorithms for a variety of analyzes that have been tested in two pilot projects; an authority and a company.