Automotive Data Monetisation Pricing and Business Models
This study analyses the strategies, growth analysis, competitive landscape, business models, and future focus areas of OEMs, data aggregators, usage-based insurance (UBI) companies, and tier 1 suppliers. OEMs, tier 1s, insurance companies, and data aggregators must focus on data services around smart mobility, connected cars, and autonomous vehicles (AVs) and must introduce new business models between 2022 and 2030. UBI companies, data aggregators, and aftermarket OBD II companies and the rise of Uber, Apple, and Google in the automotive market are pushing OEMs to finally realise the true potential of harnessing data and turning the same into successful business models.
OEMs and tier 1 suppliers have realised that digitisation along with IoT, technology partnerships, software capabilities, and customised solutions will be the way forward for the global automotive industry. The growing number of digitalisation initiatives and pilot projects with a software-centric focus by automotive OEMs and tier 1s will increase automotive IT spending from $37.9 billion in 2015 to $168.8 billion in 2025 (CAGR of 16.1%). Connected cars, AVs, and ride sharing provides more use cases for data monetisation.
Over the next decade, OEMs, data consumers, and ecosystem participants must focus on business models around location data, driving behaviour, HD mapping, vehicle usage, and environmental data types. In addition to OEM, tier 1 supplier, and technology company initiatives, this study covers a detailed list of start-ups and technology companies focusing on analytics and data aggregation. The total number of connected vehicles, activation rate, and consent rate are some of the key factors that help determine the automotive data monetisation market across various data types. Frost & Sullivan expects UBI to be the most mature use case that brings in more value from a car/year for OEMs (ever since it transitioned from an aftermarket to an OEM data-enabled service).
In addition, this study analyses and answers the following key questions:
• What are the different data monetisation business models being discussed in the automotive industry and which ones will garner more value in
the current and future ecosystem?
• What are the various use cases and data types expected to create value in the automotive industry?
• What are the different pricing models being evaluated? What is the expected price per use case?
• What is the addressable opportunity from data monetisation in 2017 and in 2025?
• Who are the key stakeholders involved? What are the key partnerships that need to be built to be successful?
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