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Part of Ovum's Connected Car Consumer Services report series, this report identifies the opportunities for connected car data monetization and the key challenges ahead.


  • Connected car data is valuable to auto OEMs and third parties across a range of verticals, including retail, insurance, and health. It can provide a feedback loop to enhance product and service development and encourage proactive customer engagement and support.
  • Connected car data brokering platforms will aid monetization. Drawing on a standardized open platform that aggregates data from multiple connected car brands is a lot easier than having to negotiate and interface with potentially dozens of individual auto OEM data platforms.
  • Data privacy issues and regulatory scrutiny loom large. Data privacy in the connected vehicle domain is coming under increasing regulatory scrutiny, particularly as most existing data protection frameworks have not been designed with connected vehicles in mind.

Features and Benefits

  • Identify the key monetization scenarios and use cases for connected car and user data.
  • Learn about the best practices needed to maximize connected car data monetization opportunities.

Key questions answered

  • What types of connected car data sets are available?
  • What are the most promising use cases for monetizing connected car data?
  • What are the challenges in monetizing connected car data?

Table of contents


  • In brief
  • Ovum view
  • Recommendations

Market status

  • Connected cars are a data treasure trove
  • Connected car data needs advanced analytics – at scale
  • The rise of brokering platforms

Market dynamics: data monetization scenarios

  • Marketing engagement
  • Service development and cost reductions
  • Consumer vertical markets
  • Digital advertising

Market outlook

  • Not all players are created equal in the arms race for data
  • Collaborating and sharing data is critical – but difficult
  • Consumer willingness to share data is not a given
  • New complexity for digital advertising
  • Data privacy issues loom large


  • Methodology
  • Further reading
  • Author

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