New Ways of Digitalization: Smart Data in Sales

Public transportation is subject to a constant process of transformation by digitalization. Transportation companies have to deal with increasing passenger volumes and meet the needs of individual customers, all while working sustainably and economically. The Hamburger Hochbahn AG recognized this transformation in public transportation early on and, together with Lufthansa Industry Solutions, is treading new paths in digitalization in the reseach project “Smart Data in Sales”.

Norderstedt, December 21, 2018 – Together with Lufthansa Industry Solutions, the Hamburger Hochbahn AG, operator of the underground rail network and a large part of the bus network in the Hanseatic city of Hamburg, analyzed the potential of Smart Data in a sales context. For ten months, a team of data experts and specialists worked together to collect internal sales data from the transportation company as well as external data such as weather information, vacation dates, or events. This data was analyzed in the Data Insight Lab at Lufthansa Industry Solutions. The results it produced will provide the transportation company with new regional and temporal insights into the data, allowing a greater understanding of the process and tools for data-based research projects.

Forecasting passenger volumes

In the scope of the first Use Case cluster, the project team visualized passenger volumes of the Hamburger Hochbahn in terms of times, rail lines, and stations. This made it clear which stops at which times experience especially high passenger volumes, for example, during the Haspa marathon. This knowledge allows the Hamburger Hochbahn to optimize its product range and provide better information to its customers.

This forecast for future passenger volumes is possible from thoroughly analyzing historical data. Among other things, the experts simulated Hamburg’s public transportation network with traveling passengers, which allowed them to be able to assess the redistribution in passenger volumes in the case of a sudden change in the network, e.g. because of delays or construction works.

Forecasting demand for service points and Hotlines

In the second Use Case cluster the project team analyzed ticket data from the different sales channels: sales in the online shop and purchases from conductors, at ticket machines and at the service points. From this data, the Hamburger Hochbahn AG was able to better evaluate regional sales, recognize social-demographic features, and directly compare sales in buses and at stops. Furthermore, the experts were able to predict the number of customers at the service points and calls to the hotlines on the basis of this data. This knowledge enables the Hamburger Hochbahn to adjust their service range to customer requirements and publish customer information in a targeted manner.