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市場調查報告書

汽車資料的收益化:2015年

The Automotive Data Monetization Report 2015-2016

出版商 TU Automotive 商品編碼 336964
出版日期 內容資訊 英文 58 Pages; 14 Figures
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汽車資料的收益化:2015年 The Automotive Data Monetization Report 2015-2016
出版日期: 2015年08月31日 內容資訊: 英文 58 Pages; 14 Figures
簡介

汽車回收的資料的數量飛躍性地增加,如何有效利用這個資料,成為汽車產業的下個課題。

本報告提供汽車回收的各種資料的有效利用法的相關調查、學習資料的有效利用及收益化的經營模式、聯盟關係範例、案例研究、其他產業的教訓等彙整資料。

第1章 簡介

  • 汽車製造商支出的擴大
  • 集中資料擁有
  • 複雜資料的收益化
  • 市場機會的收益化

第2章 汽車的連接服務和資料業務的基礎

  • 汽車資料的價值鏈和流通量
  • 有效的資料管理、資料收益化的重要性
  • 對汽車經營者來說,目前策略實行的重要性
  • 汽車資料的收益化趨勢
  • 地區的差異

第3章 商業、聯盟模式

  • 生態系統地圖
  • 聯盟模式

第4章 商業模式的選擇

  • 無償內建式客戶
  • 內建式客戶的許可證費用
  • 無償服務
  • 服務費:月、年度
  • 每個利用功能的費用

第5章 障礙與課題

  • 資料的法律上的責任
  • 品牌形象
  • 資料隱私

第6章 案例研究的類別

  • 車內行銷&廣告
  • CRM (Customer Relationship Management)
  • 駕駛輔助 / 交通管理
  • 車輛的健全性/VRM (Vehicle Relationship Management)
  • 車輛設計
  • 售後服務/零件商務
  • 汽車保險、UBI (Usage Based Insurance)
  • 資訊娛樂

第7章 案例研究

  • Aupeo
  • Hortonworks
  • INRIX
  • Nissan
  • Parkopedia
  • ParkTag
  • Tera Data
  • Vinli
  • WirelessCar
  • Xtime
    • 經營模式
    • 教訓
    • 分析、評論等

第8章 關注的利用案例

  • 運費管理的車載資通系統
  • 內部資料的有效利用
  • 汽車的評估和定價
  • 零件管理
  • 資料的集中與中介

第9章 富有魅力的B2B的機會

第10章 其他的產業吸取的經驗

  • 電子商務
  • 行動社群媒體

第11章 最後分析、評論

第12章 調查手法

第13章 簡稱

第14章 文獻

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目錄

Industry Overview

The volume of data being generated and collected from cars is growing exponentially. How to capitalize on this data is the next challenge the automotive industry has to face. This report looks into the opportunities to monetise data through an overview of use-cases and case studies. The report also maps the monetization eco-system, presenting partnership options of how data analytics companies and content companies can work with OEMs.

Key Takeaways

Key topics include:

  • Industry Case Studies: Gain key industry insight with 10 case studies exploring the different approaches to monetizing data and pitfalls to avoid
  • Business Models: What are the most compelling data use cases? A look at in-car marketing and advertising to auto-insurance to vehicle design
  • Partnership Options: Discover how companies are working together to derive increased revenue from car data
  • Revenue Potential: FInd out how industry players are leveraging and capitalizing on vehicle data for new services and creating new revenue streams

Your Key Questions Answered

Data Use Cases:

  • What are the most compelling data use cases?
  • What are the challenges and opportunities in each case?

Use cases analysed include:

  • In-car marketing and advertising
  • Customer Relationship Management (CRM)
  • Vehicle Health/Vehicle Relationship Management (VRM)
  • Vehicle Design
  • After Sales/Parts Business
  • Auto Insurance
  • Infotainment

Partnership Options:

  • How does the automotive industry respond to this huge amount of data?
  • What does the monetization eco-system look like? What types of companies are involved in the process, and what are their services?
  • What do they provide etc.?
  • Who can you work with and how? What are the compelling B2B opportunities? How can data analytics companies and content companies work with OEMs? Do OEMs outsource/go in house?
  • What are benefits and drawbacks of each option?

Contributors

  • Aupeo! Holger Weiss, CEO Aupeo!
  • Hortonworks Dan Daogaru, General Manager IoT, Hortonworks
  • ParkTAG Silvan Rath, CEO, ParkTAG
  • Inrix Mark Prendergast, Product Management, INRIX
  • Vinli Mark Haidar, Founder & CEO, Vin.li
  • Parkopedia Hans Puvogel, COO, Parkopedia
  • Xtime Chris Ice, VP Product Marketing and Jim Roche, Senior VP for Marketing and Managed Services, XTime
  • Nissan Toshiro Muramatsu, Director Vehicle Information Technogy Division, Nissan Motor
  • Volvo / Wireless Car - Greg Geiselhart, Director of Sales,Wireless Car and Robert Valton, Innovation Manager, Volvo
  • Teradata Starsensor Technology, Torbjorn Rosenquist, International Automotive Practice Lead, Teradata

Table of Contents

  • List of Figures
  • Key terms
  • Executive summary
  • Business models
  • Compelling B2B opportunities
  • Partnerships
  • Barriers and issues
  • Balancing benefits and risk
  • Protecting brand image
  • Lessons learned

1. Introduction

  • 1.1. Increased spending by automakers
  • 1.2. Ownership of aggregated data
  • 1.3. Data monetization is complex
  • 1.4. Capitalizing åon the opportunity

2. Automotive connected services and data business basics

  • 2.1. Automotive data value chain and flow
  • 2.2. Why efficient data management and data monetization are important
  • 2.3. Why it is crucial for automotive players to put a strategy in place now
  • 2.4. Trends in automotive data monetization
  • 2.5. Regional differences

3. Commercial and partnership models

  • 3.1. Ecosystem map
  • 3.2. Partnership models

4. Commercial model options

  • 4.1. Free embedded client
  • 4.2. License fee for an embedded client
  • 4.3. Free service
  • 4.4. Monthly or annual fee for service
  • 4.5. Fee per feature use (metered)
  • 4.6. Mixed

5. Barriers and issues

  • 5.1. Data liability
  • 5.2. Brand image
  • 5.3. Data privacy

6. Case study categories

  • 6.1. In-car marketing and advertising
  • 6.2. Customer Relationship Management (CRM)
  • 6.3. Driver assistance / traffic management
  • 6.4. Vehicle health/Vehicle Relationship Management (VRM)
  • 6.5. Vehicle design
  • 6.6. After-sales/parts business...
  • 6.7. Auto insurance / Usage Based Insurance (UBI)
  • 6.8. Infotainment

7. Case studies

  • 7.1. Aupeo: CRM disguised as infotainment
    • 7.1.1. Business model
    • 7.1.2. Partnerships
    • 7.1.3. Regional differences
    • 7.1.4. Barriers and issues...
    • 7.1.5. Analysis and commentary
  • 7.2. Hortonworks: Big data analytics across the automotive value chain
    • 7.2.1. Business model
    • 7.2.2. Analysis and commentary
  • 7.3. INRIX: Synthesizing big data to drive insights on traffic
    • 7.3.1. Business model
    • 7.3.2. Partnerships
    • 7.3.3. Analysis and commentary
  • 7.4. Nissan Motor Corporation: Real world data to accelerate market acceptance of EVs
    • 7.4.1. Business model
    • 7.4.2. Regional differences and partnering
    • 7.4.3. Analysis and commentary
  • 7.5. Parkopedia: Real-time predictive parking information
    • 7.5.1. Business model
    • 7.5.2. Analysis and conclusion
  • 7.6. ParkTag: “Everything is about conversion and the power of bridging activities.”
    • 7.6.1. Business model
    • 7.6.2. Lessons learned
    • 7.6.3. Analysis and commentary
  • 7.7. Teradata: Integrated data to increase value through analytics
    • 7.7.1. Business model
    • 7.7.2. Partnerships
    • 7.7.3. Lessons learned
    • 7.7.4. Analysis and commentary
  • 7.8. Vinli: App store for the car....
    • 7.8.1. Business model
    • 7.8.2. Partnerships
    • 7.8.3. Analysis and commentary
  • 7.9. WirelessCar: Everything from marketing to brand loyalty to internal value is obtained via data. .
    • 7.9.1. Business model
    • 7.9.2. Regional differences and partnering
    • 7.9.3. Barriers and issues...
    • 7.9.4. Lessons learned
    • 7.9.5. Analysis and commentary
  • 7.10. Xtime
    • 7.10.1. Business model
    • 7.10.2. Lessons learned
    • 7.10.3. Analysis and commentary

8. Highlighted use case examples

  • 8.1. Telematics for managing postage costs
    • 8.1.1. Millions wasted in postage
    • 8.1.2. Economic value from telematics data
  • 8.2. Internal data utilization
    • 8.2.1. Improving future designs
    • 8.2.2. Warranty costs
  • 8.3. Vehicle valuation and pricing
  • 8.4. Parts management
    • 8.4.1. Logistical challenges
    • 8.4.2. Cost savings with improved efficiencies
  • 8.5. Data aggregation and brokering
    • 8.5.1. Numerous monetization models

9. Compelling B2B opportunities

10. Lessons learned from other industries

  • 10.1. E-commerce
  • 10.2. Mobile social media

11. Final analysis and commentary

12. Methodology

13. Abbreviations

14. References

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