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市場調查報告書

數位廣告詐騙:市場展望 & 未來的策略 (2019-2023年)

Digital Advertising Fraud: Market Prospects & Future Strategies 2019-2023

出版商 Juniper Research Ltd 商品編碼 901444
出版日期 內容資訊 英文
商品交期: 最快1-2個工作天內
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數位廣告詐騙:市場展望 & 未來的策略 (2019-2023年) Digital Advertising Fraud: Market Prospects & Future Strategies 2019-2023
出版日期: 2019年05月29日內容資訊: 英文
簡介

本報告提供目前數位廣告生態系統,為了降低未來的數位廣告詐騙及詐騙活動的損失的市場策略的相關調查,詐騙的各類型,未來的詐騙策略的演進化,及主要詐騙建議平台等相關之全面性評估。

第1章 數位廣告流通管道:參與度 & 有效半徑

  • 數位廣告的未來
  • 服務有效半徑 & 關注的不足
  • 未來,Amazon帶給數位廣告市場的影響
  • 對數位廣告相關利益者的策略建議

第2章 數位廣告詐騙

  • 廣告詐騙的簡介
  • 廣告詐欺造成的損失的定量化
  • 未來策略分析
  • 廣告詐騙的貓捉老鼠的性質 & 未來的詐騙防止策略

第3章 數位廣告:競爭情形

  • 廣告歸因平台的簡介
  • 數位廣告歸因平台供應商分類
  • 限制事項 & 說明
  • 數位廣告:主要企業
  • 企業簡介
    • Adjust
    • Affle
    • App Samurai
    • AppsFlyer
    • ClickGUARD
    • Codewise
    • Comscore
    • Impact Technologies
    • Kochava
    • Machine Advertising
    • Pixalate
    • Singular
    • Telecoming
    • TrafficGuard
    • TUNE

第4章 市場預測 & 要點:數位廣告詐騙

  • 數位廣告詐騙的簡介
    • 預測手法
    • 線上詐騙點擊總數
    • 線上廣告詐欺造成的總損失額
    • 行動瀏覽廣告詐騙數
    • 行動瀏覽廣告詐欺造成的總損失額
    • 行動應用程式內點擊詐騙數
    • App內廣告詐欺造成的總損失額
目錄

Overview

Juniper's ‘Digital Advertising Fraud research’ provides a must-read analysis of the current digital advertising ecosystem, the future of digital advertising fraud and market strategies for mitigating the loss to fraudulent activities. The research also provides a comprehensive evaluation of the types of fraud, future innovation in fraud tactics and the leading fraud mitigation platforms.

This research suite includes:

  • Market Trends & Opportunities (PDF)
  • 5 Year Market Sizing & Forecast Spreadsheet (Excel)
  • 12 months' access to harvest online data platform

Key Features

  • Market Landscape: Extensive analysis of the future outlook of the digital advertising market, and the role emerging technologies will play in its development.
    • Future opportunities in Mobile, Online and OTT TV Advertising
    • Key market trends, drivers and constraints acting on the digital advertising market
  • Benchmark Industry Forecasts: Market forecasts for the prevalence of fraud in the industry and total potential loss to advertising fraud. Forecasts also include the amount of ad spend that can be recovered through the adoption of fraud mitigation solutions. This is split across:
    • Online advertising
    • Mobile browsing advertising
    • In-app advertising
    • Install attribution fraud
  • Digital Advertising Platform Analysis: 5 year forecasts for digital advertising platform revenues and market share analysis for leading advertising networks, including:
    • Amazon
    • Baidu
    • Bing
    • Facebook
    • Google
    • Tencent
    • Twitter
  • Juniper Leaderboard: 15 leading MMPs (Mobile Measurement Platforms) and anti-fraud solution providers compared, scored and positioned on the Juniper Leaderboard.
  • Interviews with leading players across the value chain, including:
    • App Samurai
    • ClickGUARD
    • Codewise
    • GumGum
    • Kochava
    • mGage
    • Pixalate
    • Singular
    • Telecoming
    • TrafficGuard

Key Questions

  • 1.How much will the digital advertising ecosystem be worth by 2023?
  • 2.Who are the leading digital advertising platforms?
  • 3.Who are the leading mobile measurement platforms and fraud mitigation solutions?
  • 4.How much will advertisers lose to digital advertising fraud over the next 5 years?
  • 5.Which strategies can be adopted to maximise the mitigation of losses to advertising fraud?

Companies Referenced

  • Interviewed: Adjust, Affle, App Samurai, ClickGUARD, Codewise, GumGum, Kochava, mGage, Pixalate, Singular, Telecoming, TrafficGuard.
  • Profiled: Adjust, Affle, App Samurai, AppsFlyer, ClickGUARD, Codewise, Comscore, Impact, Kochava, Machine Advertising, Pixalate, Singular, Telecoming, TrafficGuard, TUNE.
  • Case Studied: Amazon.
  • Mentioned: A4D, Aarki, Acquired.io, Acxiom, Adalyser, Adcolony, Adconnect, Adform, Ad juster, Adobe, Adveritas, Aeron, Affluent, Airbnb, Alphabet, Altitude, Amobee, Apartment List, Appfuel, Apple, Appier, AppLift, AppNexus, Apsalar, Artisan, ATIS (Alliance for Telecommunications Industry), Baidu, BBC Worldwide, Bennett, Bing, Branch, Button, CAAF (Coalition Against Ad Fraud), Cassandra, CBS, Centro, Centurion Corporation, Chartboost, Chewy, ClearPier, ClearSaleing, Coleman & Co, CreditSesame, D2C, Dataxu, elex, Eureka & Docker, Eyeball Division, Facebook, Fiksu, Fitplan, Forbes, Forensiq, FreeWheel, Fyber, GFK, Goodway Group, Google, Grammarly, Gripati Digital Entertainment, Groupon, GS Stat Counter, HIS Markit, Hotel Tonight, IMDB, InferSystems, InMobi, Innovid, Innvervate, Inovalon, Investing.com, ironSource, Itochu, Kabbage, Kayzen, Leadpoint, Liftoff, LinkedIn, Lyft, M&C Saatchi, Managed Objects, Markt.ooo, Marriott Hotels, Match, McDonald's, M-Code, MediaOcean, MediaRadar, Mediarails, Microsoft, Migros, MobileDevHQ, MobileRQ, Mobimasta, MoPub, mParticle, Mpire, MRC (Media Rating Council), Netty, Neustar, Nike, NinthDecimal, Olymp Trade, Omnicom Media Group, Onavo, optimob, Oracle, Pandora, Paperclip, Partnerize, PlaceIQ, PLAYXPERT, Pocket Media, Pubmatic, Rakuten, Rappi, Razer, RhythmOne, Roku, runtastic, Sabre Holdings, Savings.com, Segment, Shazam, Shoffr, Shopcom, Shopify, Simmons, Sizmek, Skillz, Snap, SoundCloud, Spotify, Spring Boot on Java 8, Symantec, Tappx, Telaria, TVSquare, Tvty, Twitter, Unbotify, Verizon, Vizury, Vungle, WyWy, Yelp, Yodas.com, Zynga.

Data & Interactive Forecast

Juniper's ‘Digital Advertising Fraud’ forecast suite includes:

  • Regional data splits for 8 key regions and country level splits for:
    • US
    • Canada
    • UK
    • Germany
  • Total number of fraudulent ads delivered, and total advertiser loss to fraud, split by
    • Online advertising
    • Mobile browsing advertising
    • In-app advertising
    • Install attribution fraud
  • Total potential recovered ad spend via fraud mitigation solutions
  • Interactive Excel Scenario tool allowing user the ability to manipulate Juniper's data for 3 different metrics.
  • Access to the full set of forecast data of 44 tables and over 3,600 datapoints.

Juniper Research's highly granular interactive Excels enable clients to manipulate Juniper's forecast data and charts to test their own assumptions using the Interactive Scenario Tool, and compare select markets side by side in customised charts and tables. IFxls greatly increase clients' ability to both understand a particular market and to integrate their own views into the model.

Table of Contents

1. Digital Advertising Channels: Engagement & Reach

  • 1.1. The Future of Digital Advertising
    • Figure 1.1: Total Spend on Desktop/Notebook Advertising ($bn) in 2023
  • 1.2. Service Reach & Scarcity of Attention
    • Figure 1.2: Global Reach of Select Consumer Devices for Advertising by 2023
    • 1.2.1. The Reach of SMS Advertising
  • 1.3. The Future Impact of Amazon on the Digital Advertising Market
    • Figure 1.1: Amazon's Annual Revenue Attributable to Other Services (Including - Advertising Services) ($m) 2016-2018
    • Case Study: Amazon's Advertising Services
    • 1.3.1. The Impact on Google & Facebook
      • Figure & Table 1.4: Total Digital Advertising Ad Spend ($m), Split by Leading Advertising Platforms 2018-2023
      • i.Google's Advertising Activities
        • Figure 1.5: Leading Advertising Network Ad Revenues ($bn) by 2023
      • ii. Facebook's Advertising Activities
      • iii. Baudu's Advertising Activities
  • 1.4Strategic Recommendations for Digital Advertising Stakeholders
    • Figure 1.6: Net In-App OTT TV Advertising Spend in 2023, Split by 8 Key Regions

2. Digital Advertising Fraud

  • 2.1. Introduction to Advertising Fraud
    • 2.1.1. The Direct Cost of Digital Advertising Fraud
      • Figure 3.1: Total Loss to Mobile & Online Advertising Fraud in 2019 & 2023 ($m) Split by 8 Key Regions
    • 2.1.2. Indirect Costs of Fraudulent Advertising Spend
      • Table 3.2: Select Types of Advertising Fraud
  • 2.2. Quantifying the Loss to Advertising Fraud
    • 2.2.1. Online Browsing Advertising Fraud
      • Figure 3.3: Total Potential Lost Online Browsing Ad Spend through Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019 & 2023
    • 2.2.2. Mobile Browsing Fraud
      • Figure 3.4: Total Potential Lost Mobile Browsing Ad Spend through Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019 & 2023
    • 2.2.3. In-app Browsing Fraud
      • Figure 3.5: Total Potential Lost In-app Ad Spend through Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019 & 2023
    • 2.2.4. Install Attribution Fraud Level
      • Figure 3.6: Total Potential Lost App Advertising Spend through Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019 & 2023
  • 2.3. Future Strategy Analysis
    • Table 3.7: High Level View of Mobile Measurement Platforms & Fraud Detection Platform Strategies
  • 2.4. The Cat-and-Mouse Nature of Advertising Fraud & Future Anti-fraud Strategies
    • Figure 3.8: The Advertising Fraud Innovation Cycle & AI
    • Figure 3.9: Attribution Window Process

3. Digital Advertising: The Competitive Landscape

  • 3.1. Introduction to Advertising Attribution Platforms
    • 3.1.1. Vendor Assessment Methodology
      • Table 4.1: Player Comparison Scoring Criteria Digital Advertising Attribution Platforms
      • Figure 4.2: Juniper Leaderboard Digital Advertising Attribution Platforms
      • Table 4.3: Juniper Leaderboard Heatmap Results - Digital Advertising Attribution Platforms
  • 3.2. Vendor Groupings Digital Advertising Attribution Platforms
    • i. Established Leaders
    • ii. Leading Challengers
    • iii. Disruptors & Emulators
  • 3.3. Limitations & Interpretations
  • 3.4. Digital Advertising: Movers & Shakers
  • 3.5. Player Profiles
    • 3.5.1. Adjust
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.2. Affle
      • i. Corporate
        • Table 4.4: Affle Acquisitions 2012-present
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.3. App Samurai
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.4. AppsFlyer
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.5. ClickGUARD
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.6. Codewise
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Opportunities
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.7. Comscore
      • i. Corporate
        • Table 4.5: Comscore Select Financial Information ($m) 2015-2018
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.8. Impact Technologies
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.9. Kochava
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.10. Machine Advertising
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.11. Pixalate
      • i.Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Opportunities
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.12. Singular
      • i. Corporate
        • Table 4.6: Singular's Funding Rounds July 2014-present
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.13. Telecoming
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.14. TrafficGuard
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Opportunities
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 3.5.15. TUNE
      • i. Corporate
        • Table 4.7: TUNE Acquisitions 2012-present
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Opportunities
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities

4. Market Forecasts & Key Takeaways: Digital Advertising Fraud

  • 4.1. Introduction to Digital Advertising Fraud
    • 4.1.1. Digital Advertising Fraud Forecast Methodology
      • Figure 6.1: Digital Advertising Fraud Forecast Methodology
    • 4.1.2. Total Online Fraudulent Clicks
      • Figure & Table 6.2: Number of Online Ad Clickthrough Ads that are Due to Fraudulent Clicks (m) Split by 8 Key Regions 2018-2023
    • 4.1.3. Total Loss to Online Advertising Fraud
      • Figure & Table 6.3: Total Actual Lost Online Browsing Ad Spend through Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Splut by 8 Key Regions 2018-2023
    • 4.1.4. Mobile Browsing Advertising Fraud
      • Figure & Table 6.4: Number of Mobile Ad Clickthrough Ads that are Due to Fradulent Clicks (m) Split by 8 Key Regions 2018-2023
    • 4.1.5. Total Loss to Mobile Browsing Advertising Fraud
      • Figure & Table 6.5: Total Actual Lost Mobile Browsing Ad Spend through Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2018-2023
    • 4.1.6. Number of Fraudulent Mobile In-app Clicks
      • Figure & Table 6.6: Total Number of In-App Ad Impressions that are Delivered Fraudulently (m) Split by 8 Key Regions 2018-2023
    • 4.1.7. Total Loss to In-app Advertising Fraud
      • Figure & Table 6.7: Total Actual Lost In-app Ad Spend through Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2018-2023
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