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Automotive Data Monetisation Pricing and Business Models

  • ID: 4431568
  • Report
  • October 2017
  • Region: Global, Global
  • 91 Pages
  • Frost & Sullivan
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By 2025, Data Monetisation is Expected to Unravel ~$33 Billion in Opportunity for OEMs, With the Potential to Monetise $100 Per Car Across 140 Unique Use Cases


  • BMW
  • Delphi
  • IBM Watson
  • Manheim
  • Otonomo
  • Tom Tom
  • MORE

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. The publisher 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?
Note: Product cover images may vary from those shown
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  • BMW
  • Delphi
  • IBM Watson
  • Manheim
  • Otonomo
  • Tom Tom
  • MORE

1. Executive Summary

  • Executive Summary - Key Findings
  • Evolving Data Monetisation Business Models in the Auto Industry
  • Automotive Data-as-a-Service Types
  • Key Consumers of Vehicle Data
  • Automotive Data Monetisation Market - Data Types and Definitions
  • Total Addressable Market in 2017
  • Key Elements of a Data Monetisation Business Model
  • Automotive Data Monetisation - Use Case Grouping
  • Use Case Grouping Snapshot - UBI Focus on a Data-driven Future
  • Use Case Grouping Snapshot - Crash Reconstruction Role in AVs
  • BMW CarData Platform Case Study
  • Otonomo’s Data Exchange Platform
  • Commercial Data Types Tracked by Otonomo
  • Automotive Data Monetisation - Pricing Variables

2. Research Scope, Objectives, Methodology, and Background

  • Research Scope
  • Research Aims and Objectives
  • Key Questions this Study will Answer
  • Research Background
  • RelatedVideo Content Available for Support
  • Research Methodology
  • Snapshot of Frequently Used Input Streams for Data Capture

3. Best Practice Assessment from the Non-automotive Industry

  • Data Monetisation Use Cases across Industries
  • Data Format and IoT Data Types
  • Data Monetisation Business Models - Non-automotive
  • Data Monetisation - Non-automotive Industry Highlights
  • Data Monetisation - Non-automotive Industry Examples
  • Case Study - Barclays Market and Customer Insight Service Offering

4. Key Challenges, Regulations, and Revenue Opportunities

  • Automotive Data Monetisation - Key Challenges
  • EU General Data Protection Regulation (GDPR) - Key Principles
  • GDPR Principles and Compliances
  • GDPR Principles and Compliances (continued)
  • Data Monetisation - Direct and Indirect Revenue Opportunities
  • Snapshot of Direct Revenue Opportunities
  • Snapshot of Indirect Revenue Opportunities

5. Highlights/Examples Based On Use Case Grouping and Ecosystem Partners

  • Automotive Data Monetisation - Use Case Grouping
  • Use Case 1 - UBI and Contextual Behaviour Intelligence
  • Use Case 1 - Contextual Driver Behaviour Score
  • Use Case 1 - Contextual Driver Behaviour
  • Use Case 2 - Crash Reconstruction in a Virtual Driving Environment
  • Use Case 2 - Proactive FNOL
  • Use Case 2 - TSPs’ Crash Reconstruction Solutions
  • Use Case 3 - Location and Mapping Services
  • Use Case 3 - Harnessing Location Data
  • Use Case 3 - HAD Maps for Autonomous Cars
  • Use Case 3 - HERE’s Real-time Traffic Service
  • Use Case 4 - Dealerships and Ecosystem Datasets and Initiatives
  • Use Case 4 - Dealership Data Monetisation
  • Use Case 4 - Vauxhall OnStar Portal
  • Use Case 4 - Auction Companies
  • Use Case 5 - Autonomous Vehicles
  • Use Case 5 - Insurance Opportunity in AVs

6. Key OEM/Tier 1 Initiatives

  • Car Connectivity Consortium (CCC) - Car Data Solution Architecture
  • IBM Connected Solutions
  • GM Partnership with IBM Watson to Handle Data-Business In-house
  • Mercedes Benz - Leveraging OBD to Connect Legacy Vehicles
  • Ford Invests in AI and ML Companies
  • Ford Partnership with Pivotal
  • Volkswagen Data Lab Competencies
  • Volkswagen Digital Lab and Enhanced Digital Platform
  • Bosch Investments in Iguazio, a Data-driven Innovative Company
  • Bosch and Tom Tom - Radar Road Signature
  • Delphi Automotive Software Suite
  • Delphi Offers a Holistic Connected Vehicle Platform

7. Data Aggregators and UBI Company Profiles

  • Dash Labs’ Business Model
  • Octo Telematics’ Business Model
  • Nexar’s Vision-based Driver Scoring
  • LexisNexis UBI Capability
  • The Floow - Helping OEMs Monetise Data

8. Growth Opportunity Analysis

  • Automotive Data Monetisation Companies
  • Growth Opportunity - Partnerships and Business Models

9. Key Conclusions and Future Outlook

  • New Business Models in Mobility will be Data-driven
  • Automotive Data Monetisation Recommendations
  • The Last Word - 3 Big Predictions
  • Legal Disclaimer

10. Appendix

  • Table of Acronyms Used
  • Market Engineering Methodology
Note: Product cover images may vary from those shown
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  • BMW
  • Bosch
  • Car Connectivity Consortium (CCC)
  • Copart Inc.
  • Dash Labs
  • Delphi
  • Ford
  • GM
  • HERE
  • IBM Watson
  • Iguazio
  • KAR
  • LexisNexis
  • Manheim
  • Mercedes Benz
  • Nexar
  • Octo Telematics
  • Otonomo
  • Pivotal
  • Tesla
  • The Floow
  • Tom Tom
  • Toyota
  • TSPs
  • Vauxhall
  • Volkswagen
Note: Product cover images may vary from those shown