Understanding The Business Value Of Customer Data From Connected Services - An exploratory case study of what business value an emerging automotive OEM can create from customer data generated by connected services

The rapid development of connectivity accelerated by a myriad of emerging technologies contribute to an ever-growing volume of data in which companies have realized the need for, and value of, becoming data-driven. Data, and more specifically, customer data, is thus a promising area for transforming insights into actions which identifies new value creation opportunities to enhance business performance. In the automotive industry, being in an era of accelerated digital transformation, the number of connected cars and its associated data is growing exponentially. Hence, turning customer data into valuable insights is key to successfully withstand competition and changing customer preferences. However, how automotive OEMs can leverage these developments have previously been unclear. Through an exploratory single-case study, this thesis therefore shows what business value can be created by customer data from connected services and its associated challenges and risks. This was operationalized through semi-structured interviews with internal respondents at the case company and external experts within academia, consultancy firms, and other automotive companies. The empirical findings were analyzed iteratively through themes found in previous literature to highlight similarities and differences between various views. Through the analysis process, the findings were reduced to four main value creation use cases; personalization, service innovation, decision-making, and data monetization, in which the combination of internal and external data is important. These value creation use cases create business value for a company in terms of enhancing and differentiating the customer experience, thus improving customer satisfaction and loyalty, leading to long-term profitability if managed successfully. Subsequently, four main challenges and risks were identified; privacy concerns and providing value to customers, data collection and analysis, connected service development and adoption, and creating a sustainable competitive advantage