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Our work

VR — towards an even better customer experience

Loihde Factor’s professionals designed and implemented a big data and data analytics platform for VR.

The challenge

The competition in cargo and commercial transportation is intense. In order to succeed in such a challenging market the service providers must identify their customers’ needs faster and better – automatically and proactively. For example, effortless purchasing and personalised customer experience are essential competitive advantages and their significance is growing even further in the future. VR develops its products, pricing and customer loyalty program based on data.

In addition to creating a better customer experience, more real-time and accurate data was needed for leadership and operations management. In order to make quick decisions based on knowledge, the data must flow seamlessly and in real time from different sources. This enables, for example, the optimization of equipment based on more accurate, customer segment-specific predictions. Moreover, VR wanted to increase their sales in additional services by targeting the right products for the right customers and by estimating the purchase probability based on data.

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The solution

Our solution included building a traditional business intelligence system and a platform for digital service analytics and API development. Data from various systems, including the web store, VR Mobile, train route information and conductors’ application, is collected in a data warehouse. The data flows from different sources through a completely automated mechanism. 

Advanced analytics tools make working pleasant and effective for VR’s data scientists. The solution utilizes AWS cloud’s capabilities and enables sufficient capacity even for heavy analytics use. VR uses the Microsoft PowerBI tool for internal reporting and for following their business operations. A real time data flow, directly from the source to the report, was implemented in the project. It enables using up to date knowledge for daily business decisions.

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