Improved evaluation of customer data and optimization of personnel planning
Möbel Pfister is the leading furniture store in Switzerland and since 1882 has always been motivated to create a beautiful home for its clientele. With around 1’200 employees, it pursues a clear vision of giving everything with a passion for furnishing. In addition, the company is committed to ecological awareness and sustainable production. Möbel Pfister has 19 branches throughout Switzerland and, with over 40’000 products, is one of the largest online suppliers in the Swiss furnishing sector.
Initial Situation
Möbel Pfister used an on-premises data warehouse and deployed a dedicated data team. However, the data warehouse grew incrementally, depending on the use cases encountered. Problems were often solved independently of the overall context, which led to the implementation of different technologies and tools (Docker, Maria DB, SQL, ...) that were not ideally aligned. This made connections and automatic evaluations of data, such as from customer surveys, difficult.
Solution
In collaboration with isolutions, a new data warehouse was set up in the cloud, a connection for SAP was created, and collaboration tools were reviewed. In addition to the migration, isolutions advised Möbel Pfister AG regarding tools, coordination and onboarding of the employees. The employees underwent training to become familiar with the tools and to improve their collaboration with each other. In addition, data from existing customer customer surveys were integrated and a corresponding Power BI dashboard was set up. Through this the results of the surveys can be efficiently evaluated and used effectively.
Benefits
- Build of a data warehouse infrastructure in the cloud.
- Training of the tools for more efficient use and higher acceptance.
- Automated processing of previously handwritten customer surveys.
- Connection to Survey Monkey survey tool, automated analysis of the customer satisfaction (Sentiment-Analysis) and easy overview in the Power BI dashboard.
- Analysis and display of customer flows in stores via anonymized camera data.