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デジタル広告の未来　2019-2023年：AI＆広告詐欺


Future Digital Advertising

このレポートは世界の電子広告（デジタル広告）市場を調査し、主要企業10社へのインタビューや、ベンチマーク産業ごとの予測を掲載しています。 主な掲載内容 地域別市場予測 米国 ... もっと見る

　

　

出版社 出版年月 電子版価格 言語
Juniper Research
ジュニパーリサーチ社 		2019年5月21日 GBP4,090
完全版(PDF+Excel)
ライセンス・価格情報
注文方法はこちら 		英語

「Deep Dive Strategy & Competition」「Deep Dive Data & Forecasting」のみの購入も可能です。詳しくはお問合せ下さい。


　

サマリー

このレポートは世界の電子広告（デジタル広告）市場を調査し、主要企業10社へのインタビューや、ベンチマーク産業ごとの予測を掲載しています。

主な掲載内容

地域別市場予測

  • 米国
  • カナダ
  • 英国
  • ドイツ

オンライン広告収益予測

  • インターネットディスプレイ広告の収益
  • インターネット検索の広告収益
  • インターネットのビデオ広告の収益

モバイルインターネット広告の収益予測

  • インターネットディスプレイ広告の収益
  • インターネット検索の広告収益

モバイル向けアプリ内広告収益予測

  • ディスプレイ広告
  • リッチメディア広告

OTT TV広告収益予測

  • コネクテッドTV
  • スマートフォン
  • タブレット
  • デスクトップPC
  • SMS広告

オンライン広告ブロックでの収益損失予測

  • インターネットディスプレイ広告の収益
  • インターネット検索の広告収益
  • インターネットのビデオ広告の収益

モバイルインターネット広告ブロックでの収益損失予測

  • インターネットディスプレイ広告の収益
  • インターネット検索の広告収益

広告詐欺予測

  • オンライン広告
  • モバイル広告
  • アプリ内広告
  • インストールアトリビューション詐欺

AIプラットフォーム収益予測

  • モバイル検索の広告
  • モバイルディスプレイ広告
  • オンライン広告

 

Overview

Juniper Research’s Future Digital Advertising research provides a complete evaluation of the digital advertising system; assessing opportunities across key channels in the ecosystem, including:

  • Online
  • Mobile
  • In-app
  • OTT TV
  • Smartwatches
  • DOOH (Digital-Out-of-Home)

The research identifies key use cases of AI in the digital advertising industry; evaluating future disruptive impacts in areas including programmatic advertising and combatting advertising fraud. It identifies ad targeting and advertising fraud prevention strategies to present a comprehensive outline of the next 5 years of the digital advertising industry.

This research suite includes:

  • Deep Dive Strategy & Competition (PDF)
  • 5-Year Deep Dive Data & Forecasting (PDF)
  • Executive Summary & Core Findings (PDF)
  • 12 months' access to harvest online data platform

Key Features

  • Market Landscape: Extensive analysis of the future outlook of the market, and the role emerging technologies will play in the development of the market.
    • Future benefits of AI, including fraud detection and programmatic advertising
    • Future opportunities in mobile, online, OTT TV and digital out-of-home advertising
    • Key market trends, drivers and constraints acting on the digital advertising market
  • 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 Positioning Index: A comparative assessment of AI advertising services from 19 digital advertising service providers, categorised in terms of the depth of their service offerings. Vendors in our Positioning Index include:
    • Affectiva
    • Amazon
    • Amplero
    • Baidu
    • Bidalgo
    • Congnitiv
    • Conversica
    • Dynamic Yield
    • Facebook
    • Google
    • GumGum
    • IBM
    • Influential
    • InsideSales.com
    • Invoca
    • Microsoft
    • Quantcast
    • SalesForce
    • Sizmek
  • Benchmark Industry Forecasts: Understand the size of the digital advertising market and where the growth will take place with our highly granular dataset. We identify key opportunities; covering theoretical savings and costs, adoption of the various technologies, revenues from these technologies and more, for 8 global regions and 4 key country markets, covering these segments:
    • Online (Display, Search)
    • Mobile Internet (Display, Search)
    • In-App (Display, Rich Media)
    • OTT TV (Connected TV, Smartphone, Tablet, Desktop PC)
    • Message-Based (SMS)
    • Advertising Fraud
    • AI-based Programmatic Advertising
  • Interviews with leading players across the value chain, including:
    • App Samurai
    • ClickGUARD
    • Codewise
    • GumGum
    • Kochava
    • mGage
    • Pixalate
    • Singular
    • Telecoming
    • TrafficGuard.
  • Juniper Leaderboard: 15 leading MMPs (Mobile Measurement Platforms) and anti-fraud solutions providers compared, scored and positioned on the Juniper Leaderboard.

Key Questions

  1. How is AI being used in digital advertising?
  2. How much will the digital advertising ecosystem be worth by 2023?
  3. How much are advertisers losing to digital advertising fraud?
  4. What strategies can advertisers and publishers implement to recover some of this lost spend?
  5. Who are the leading digital ad fraud detection and mitigation platforms?

Data & Interactive Forecast

Juniper’s Future Digital Advertising forecast suite includes:
  • Regional data splits for 8 key regions as well as country level splits for:
    • US
    • Canada
    • UK
    • Germany
  • Online advertising revenues, split by:
    • Internet display advertising
    • Internet search advertising
    • Internet video advertising
  • Mobile Internet advertising revenues, split by:
    • Internet display advertising
    • Internet search advertising
  • Mobile in-app advertising revenues, split by:
    • Display advertising
    • Rich media advertising
  • OTT TV Advertising, split by:
    • Connected TV
    • Smartphone
    • Tablet
    • Desktop PC
    • SMS Advertising
  • Online ad blocking and lost revenues, split by:
    • Internet display advertising
    • Internet search advertising
    • Internet video advertising
  • Mobile Internet ad blocking, split by:
    • Internet display advertising
    • Internet search advertising
  • Advertising fraud, split:
    • Online advertising
    • Mobile advertising
    • In-app advertising
    • Install attribution fraud
  • AI Platform Revenues, split by:
    • Mobile search advertising
    • Mobile display advertising
    • Online advertising
  • Interactive Excel Scenario tool allowing the user the ability to manipulate Juniper’s data for 10 different metrics.
  • Access to the full set of forecast data of 360 tables and over 30,400 data points.
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.

 



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目次

Table of Contents

1. Deep Dive Strategy & Competition

1. Digital Advertising Channels: Engagement & Reach

1.1 The Future of Digital Advertising . 6
Figure 1.1: Total Spend on Desktop/Notebook Advertising ($bn) in 2023 . 6
1.2 Service Reach & Scarcity of Attention. 7
Figure 1.2: Global Reach of Select Consumer Devices for Advertising by 2023. 7
1.2.1 The Reach of SMS Advertising . 7
1.3 The Future Impact of Amazon on the Digital Advertising Market . 8
Figure 1.3: Amazon’s Annual Revenue Attributable to Other Services (including
Advertising Services) ($m) 2016-2018. 8
Case Study: Amazon’s Advertising Services . 9
1.3.1 The Impact on Google & Facebook.10
Figure & Table 1.4: Total Digital Advertising Ad Spend ($m), Split by Leading
Advertising Platforms 2018-2023. 10
i. Google’s Advertising Activities . 11
Figure 1.5: Leading Advertising Netw ork Ad Revenues ($bn) by 2023. 11
ii. Facebook’s Advertising Activities . 11
iii. Baidu ’s Advertising Activities. 12
1.4 Strategic Recommendations for Digital Advertising Stakeholders.12
Figure 1.6: Net In-App OTT TV Advertising Spend in 2023, Split by 8 Key Regions. 13

2. AI in Digital Advertising

2.1 Artificial Intelligence in the Advertising Space.16
Figure 2.1: AI Use Cases in the Advertising Industry .16
2.2 Artificial Intelligence in Digital Advertising: Vendor Positioning Index .17
Table 2.2: Juniper Vendor Positioning Index - Vendor Assessment Criteria .17
Figure 2.3: Juniper Research Vendor Positioning Index - Artif icial Intelligence
Providers in Advertising .18
2.2.1 Established Leaders .19
Figure 2.4: Alphabet’s Advertising Revenues ($m) 2016-2018 .19
Table 2.5: Sizmek Acquisitions 2012-present .23
2.2.2 Challenging Providers .24
2.2.3 Niche Providers.28
2.3 Quantifying the Impact of AI in Digital Advertising.30
Figure 2.6: Global Proportion of Ads Delivered Using AI or Machine Learning
Services, (%) Split by Ad Channel 2018-2023 .30
2.4 AI in Digital Advertising: The 5 Year Roadmap .31
2.4.1 Legislation will Impact Future Digital Advertising Strategies 31
2.4.2 AI-created Content for Advertising .31
Figure 2.7: Key Global AI in Advertising Statistics in 2023.31
Figure 2.8: Artif icial Intelligence in Advertising: The 5 Year Roadmap 2019-2023.32

3. Digital Advertising Fraud

3.1 Introduction to Advertising Fraud .34
3.1.1 The Direct Cost of Digital Advertising Fraud .34
Figure 3.1: Total Loss to Mobile & Online Advertising Fraud in 2019 & 2023 ($m)
Split by 8 Key Regions .34
3.1.2 Indirect Costs of Fraudulent Advertising Spend.35
Table 3.2: Select Types of Advertising Fraud . 36
3.2 Quantifying the Loss to Advertising Fraud .37
3.2.1 Online Browsing Advertising Fraud.37
Figure 3.3: Total Potential Lost Online Brow sing Ad Spend through Advertising
Fraud w ithout AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019 & 2023 . 37
3.2.2 Mobile Browsing Fraud.38
Figure 3.4: Total Potential Lost Mobile Brow sing Ad Spend through Advertising
Fraud w ithout AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019 & 2023 . 38
3.2.3 In-app Browsing Fraud .39
Figure 3.5: Total Potential Lost In-app Ad Spend through Advertising Fraud
w ithout AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019 & 2023 . 39
3.2.4 Install Attribution Fraud Level .40
Figure 3.6: Total Potential Lost App Advertising Spend through Advertising Fraud
w ithout AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019 & 2023 . 40
3.3 Future Strategy Analysis .41
Table 3.7: High Level View of Mobile Measurement Platforms & Fraud Detection
Platform Strategies . 41
3.4 The Cat-and-Mouse Nature of Advertising Fraud & Future Antifraud Strategies.42
Figure 3.8: The Advertising Fraud Innovation Cycle & AI . 42
Figure 3.9: Attribution Window Process . 44

4. Digital Advertising: The Competitive Landscape

4.1 Introduction to Advertising Attribution Platforms .46
4.1.1 Vendor Assessment Methodology.46
Table 4.1: Player Comparison Scoring Criteria - Digital Advertising Attribution Platforms.47
Figure 4.2: Juniper Leaderboard - Digital Advertising Attribution Platforms .48
Table 4.3: Juniper Leaderboard Heatmap Results - Digital Advertising Attribution Platforms.49
4.2 Vendor Groupings - Digital Advertising Attribution Platforms 50
i. Established Leaders.50
ii. Leading Challengers .50
iii. Disruptors & Emulators.52
4.3 Limitations & Interpretations .54
4.4 Digital Advertising: Movers & Shakers .55
4.5 Player Profiles .57
4.5.1 Adjust .57
i. Corporate .57
ii. Geographical Spread .57
iii. Key Clients & Strategic Partnerships .57
iv. High Level View of Offerings .58
v. Juniper View: Key Strengths & Strategic Opportunities.58
4.5.2 Affle.59
i. Corporate .59
Table 4.4: Aff le Acquisitions 2012-present.59
ii. Geographical Spread .59
iii. Key Clients & Strategic Partnerships .59
iv. High Level View of Offerings .59
v. Juniper View: Key Strengths & Strategic Opportunities.60
4.5.3 App Samurai .60
i. Corporate. 60
ii. Geographical Spread . 60
iii. Key Clients & Strategic Partnerships. 60
iv. High Level View of Offerings . 60
v. Juniper View: Key Strengths & Strategic Opportunities . 61
4.5.4 AppsFlyer .61
i. Corporate. 61
ii. Geographical Spread . 61
iii. Key Clients & Strategic Partnerships. 61
iv. High Level View of Offerings . 61
v. Juniper View: Key Strengths & Strategic Opportunities . 62
4.5.5 ClickGUARD.63
i. Corporate. 63
ii. Geographical Spread . 63
iii. Key Clients & Strategic Partnerships. 63
iv. High Level View of Offerings . 63
v. Juniper View: Key Strengths & Strategic Opportunities . 64
4.5.6 Codewise .64
i. Corporate. 64
ii. Geographical Spread . 64
iii. Key Clients & Strategic Opportunities . 64
iv. High Level View of Offerings . 64
v. Juniper View: Key Strengths & Strategic Opportunities . 65
4.5.7 Comscore .65
i. Corporate. 65
Table 4.5: Comscore Select Financial Information ($m) 2015-2018 . 65
ii. Geographical Spread .65
iii. Key Clients & Strategic Partnerships .66
iv. High Level View of Offerings .66
v. Juniper View: Key Strengths & Strategic Opportunities.66
4.5.8 Impact Technologies .67
i. Corporate .67
ii. Geographical Spread .67
iii. Key Clients & Strategic Partnerships .67
iv. High Level View of Offerings .67
v. Juniper View: Key Strengths & Strategic Opportunities.68
4.5.9 Kochava .68
i. Corporate .68
ii. Geographical Spread .68
iii. Key Clients & Strategic Partnerships .68
iv. High Level View of Offerings .68
v. Juniper View: Key Strengths & Strategic Opportunities.69
4.5.10 Machine Advertising .70
i. Corporate .70
ii. Geographical Spread .70
iii. Key Clients & Strategic Partnerships .70
iv. High Level View of Offerings .70
v. Juniper View: Key Strengths & Strategic Opportunities.70
4.5.11 Pixalate .70
i. Corporate .70
ii. Geographical Spread .71
iii. Key Clients & Strategic Opportunities.71
iv. High Level View of Offerings . 71
v. Juniper View: Key Strengths & Strategic Opportunities . 72
4.5.12 Singular .72
i. Corporate. 72
Table 4.6: Singular’s Funding Rounds July 2014-present. 72
ii. Geographical Spread . 72
iii. Key Clients & Strategic Partnerships. 72
iv. High Level View of Offerings . 73
v. Juniper View: Key Strengths & Strategic Opportunities . 73
4.5.13 Telecoming .74
i. Corporate. 74
ii. Geographical Spread . 74
iii. Key Clients & Strategic Partnerships. 74
iv. High Level View of Offerings . 74
v. Juniper View: Key Strengths & Strategic Opportunities . 74
4.5.14 TrafficGuard .75
i. Corporate. 75
ii. Geographical Spread . 75
iii. Key Clients & Strategic Opportunities . 75
iv. High Level View of Offerings . 75
v. Juniper View: Key Strengths & Strategic Opportunities . 76
4.5.15 TUNE .76
i. Corporate. 76
Table 4.7: TUNE Acquisitions 2012-present . 76
ii. Geographical Spread . 76
iii. Key Clients & Strategic Opportunities . 76
iv. High Level View of Offerings .76
v. Juniper View: Key Strengths & Strategic Opportunities.77

2. Deep Dive Data & Forecasting

1. Digital Advertising Market Summary

1.1 The Digital Advertising Ecosystem . 4
1.1.1 Reach, Engagement & Scarcity of Attention . 4
1.1.2 Mobile Subscriber Growth . 4
Figure 1.1: Share of Mobile Advertising Spend (%) Split by 8 Key Regions in 2023 . 4
1.1.3 Downward Price Pressure of Applications. 5
1.1.4 Improvements in Retargeting Strategies & Identifying High Value Users . 5
Figure 1.2: Digital Advertising Forecast Summary by 2023 . 5
1.1.5 The Digital Advertising Ecosystem . 6
Figure 1.3: The Digital Advertising Ecosystem . 6
1.2 Market Summary Forecasts . 7
1.2.1 Total Digital Advertising Spend. 7
Figure & Table 1.4: Total Spend on Digital Advertising - Online, Mobile,
Wearables, OTT TV & DOOH ($m) Split by 8 Key Regions 2018-2023. 7
1.2.2 Total Digital Advertising Spend, Split by Channel . 8
Figure & Table 1.5: Total Spend on Digital Advertising - Online, Mobile,
Wearables & DOOH ($m), Split by Advertising Channel 2018-2023 . 8

2. Online Digital Advertising

2.1 Online Digital Advertising . 10
2.1.1 Online Digital Advertising Forecast Methodology . 10
Figure 2.1: Online Advertising Forecast . 11
2.1.2 Total Spend of Desktop/Notebook Display Advertising . 12
Figure & Table 2.2: Net Desktop/Notebook Display Advertising Spend ($m) Split
by 8 Key Regions 2018-2023 . 12
2.1.3 Total Spend of Desktop/Notebook Search Advertising . 13
Figure & Table 2.3: Net Desktop/Notebook Search Advertising Spend ($m) Split
by 8 Key Regions 2018-2023 . 13
2.1.4 Total Spend of Desktop/Notebook Video Advertising . 14
Figure & Table 2.4: Net Desktop/Notebook Video Advertising Spend ($m) Split by
8 Key Regions 2018-2023 . 14

3. Mobile Browsing Digital Advertising

3.1 Mobile Browsing Digital Advertising . 16
3.1.1 Mobile Advertising . 16
Figure 3.1: Mobile Browsing Digital Advertising Forecast Methodology . 17
3.1.2 Total Spend on Mobile Browsing Display Advertising . 18
Figure & Table 3.2: Net Spend on Mobile Internet Display Advertising ($m) Split
by 8 Key Regions 2018-2023 . 18
3.1.3 Total Spend on Mobile Browsing Search Advertising . 19
Figure & Table 3.3: Total Spend on Smartphone Internet Search Advertising ($m)
Split by 8 Key Regions 2018-2023 . 19

4. Mobile In-app Digital Advertising

4.1 Mobile In-app Digital Advertising . 21
4.1.1 In-app Advertising Methodology . 21
Figure 4.1: Mobile In-app Advertising Forecast Methdology . 22
4.1.2 Total Spend on In-app Display Advertising . 23
Figure & Table 4.2: Net In-App Display Advertising Spend on Smartphones ($m)
Split by 8 Key Regions 2018-2023 . 23
Table 4.3: Net In-App Display Advertising Spend on Smartphones ($m) Split by
Ad Format 2018-2023 . 23

5. AI in Digital Advertising

5.1 AI (Artificial Intelligence) in Digital Advertising . 25
5.1.1 Methodology. 25
Figure 5.1: AI in Advertising Forecast Methodology . 26
5.1.2 Total Online Advertisements Delivered via AI or Machine
Learning Alogrithms . 27
Figure & Table 5.2: Total Spend on Online Advertising Delivered through
AI/Machine Learning Advertising ($m) Split by 8 Key Regions 2018-2023 . 27
5.1.3 Total Mobile Display Advertisements Delivered via AI or
Machine Learning Alogrithms . 28
Figure & Table 5.3: Total Spend on Mobile Display Advertising Delivered through
AI/Machine Learning Advertising ($m) Split by 8 Key Regions 2018-2023 . 28
5.1.4 Total Mobile Search Advertisements Delivered via AI or
Machine Learning Alogrithms . 29
Figure & Table 5.4: Total Spend on Mobile Search Advertising Delivered through
AI/Machine Learning Advertising ($m) Split by 8 Key Regions 2018-2023 . 29

6. Digital Advertising Fraud

6.1 Introduction to Digital Advertising Fraud . 31
6.1.1 Digital Advertising Fraud Forecast Methodology . 31
Figure 6.1: Digital Advertising Fraud Forecast Methodology . 32
6.1.2 Total Online Fraudulent Clicks . 33
Figure & Table 6.2: Number of Online Ad Clickthrough Ads that are Due to
Fraudulent Clicks (m) Split by 8 Key Regions 2018-2023 . 33
6.1.3 Total Loss to Online Advertising Fraud . 34
Figure & Table 6.3: Total Actual Lost Online Browsing Ad Spend through
Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Splut by 8
Key Regions 2018-2023 . 34
6.1.4 Mobile Browsing Advertising Fraud . 35
Figure & Table 6.4: Number of Mobile Ad Clickthrough Ads that are Due to
Fradulent Clicks (m) Split by 8 Key Regions 2018-2023 . 35
6.1.5 Total Loss to Mobile Browsing Advertising Fraud . 36
Figure & Table 6.5: Total Actual Lost Mobile Browsing Ad Spend through
Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Split by 8 Key
Regions 2018-2023 . 36
6.1.6 Number of Fraudulent Mobile In-app Clicks . 37
Figure & Table 6.6: Total Number of In-App Ad Impressions that are Delivered
Fraudulently (m) Split by 8 Key Regions 2018-2023 . 37
6.1.7 Total Loss to In-app Advertising Fraud . 38
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 . 38

　

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Summary

このレポートは世界の電子広告（デジタル広告）市場を調査し、主要企業10社へのインタビューや、ベンチマーク産業ごとの予測を掲載しています。

主な掲載内容

地域別市場予測

  • 米国
  • カナダ
  • 英国
  • ドイツ

オンライン広告収益予測

  • インターネットディスプレイ広告の収益
  • インターネット検索の広告収益
  • インターネットのビデオ広告の収益

モバイルインターネット広告の収益予測

  • インターネットディスプレイ広告の収益
  • インターネット検索の広告収益

モバイル向けアプリ内広告収益予測

  • ディスプレイ広告
  • リッチメディア広告

OTT TV広告収益予測

  • コネクテッドTV
  • スマートフォン
  • タブレット
  • デスクトップPC
  • SMS広告

オンライン広告ブロックでの収益損失予測

  • インターネットディスプレイ広告の収益
  • インターネット検索の広告収益
  • インターネットのビデオ広告の収益

モバイルインターネット広告ブロックでの収益損失予測

  • インターネットディスプレイ広告の収益
  • インターネット検索の広告収益

広告詐欺予測

  • オンライン広告
  • モバイル広告
  • アプリ内広告
  • インストールアトリビューション詐欺

AIプラットフォーム収益予測

  • モバイル検索の広告
  • モバイルディスプレイ広告
  • オンライン広告

 

Overview

Juniper Research’s Future Digital Advertising research provides a complete evaluation of the digital advertising system; assessing opportunities across key channels in the ecosystem, including:

  • Online
  • Mobile
  • In-app
  • OTT TV
  • Smartwatches
  • DOOH (Digital-Out-of-Home)

The research identifies key use cases of AI in the digital advertising industry; evaluating future disruptive impacts in areas including programmatic advertising and combatting advertising fraud. It identifies ad targeting and advertising fraud prevention strategies to present a comprehensive outline of the next 5 years of the digital advertising industry.

This research suite includes:

  • Deep Dive Strategy & Competition (PDF)
  • 5-Year Deep Dive Data & Forecasting (PDF)
  • Executive Summary & Core Findings (PDF)
  • 12 months' access to harvest online data platform

Key Features

  • Market Landscape: Extensive analysis of the future outlook of the market, and the role emerging technologies will play in the development of the market.
    • Future benefits of AI, including fraud detection and programmatic advertising
    • Future opportunities in mobile, online, OTT TV and digital out-of-home advertising
    • Key market trends, drivers and constraints acting on the digital advertising market
  • 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 Positioning Index: A comparative assessment of AI advertising services from 19 digital advertising service providers, categorised in terms of the depth of their service offerings. Vendors in our Positioning Index include:
    • Affectiva
    • Amazon
    • Amplero
    • Baidu
    • Bidalgo
    • Congnitiv
    • Conversica
    • Dynamic Yield
    • Facebook
    • Google
    • GumGum
    • IBM
    • Influential
    • InsideSales.com
    • Invoca
    • Microsoft
    • Quantcast
    • SalesForce
    • Sizmek
  • Benchmark Industry Forecasts: Understand the size of the digital advertising market and where the growth will take place with our highly granular dataset. We identify key opportunities; covering theoretical savings and costs, adoption of the various technologies, revenues from these technologies and more, for 8 global regions and 4 key country markets, covering these segments:
    • Online (Display, Search)
    • Mobile Internet (Display, Search)
    • In-App (Display, Rich Media)
    • OTT TV (Connected TV, Smartphone, Tablet, Desktop PC)
    • Message-Based (SMS)
    • Advertising Fraud
    • AI-based Programmatic Advertising
  • Interviews with leading players across the value chain, including:
    • App Samurai
    • ClickGUARD
    • Codewise
    • GumGum
    • Kochava
    • mGage
    • Pixalate
    • Singular
    • Telecoming
    • TrafficGuard.
  • Juniper Leaderboard: 15 leading MMPs (Mobile Measurement Platforms) and anti-fraud solutions providers compared, scored and positioned on the Juniper Leaderboard.

Key Questions

  1. How is AI being used in digital advertising?
  2. How much will the digital advertising ecosystem be worth by 2023?
  3. How much are advertisers losing to digital advertising fraud?
  4. What strategies can advertisers and publishers implement to recover some of this lost spend?
  5. Who are the leading digital ad fraud detection and mitigation platforms?

Data & Interactive Forecast

Juniper’s Future Digital Advertising forecast suite includes:
  • Regional data splits for 8 key regions as well as country level splits for:
    • US
    • Canada
    • UK
    • Germany
  • Online advertising revenues, split by:
    • Internet display advertising
    • Internet search advertising
    • Internet video advertising
  • Mobile Internet advertising revenues, split by:
    • Internet display advertising
    • Internet search advertising
  • Mobile in-app advertising revenues, split by:
    • Display advertising
    • Rich media advertising
  • OTT TV Advertising, split by:
    • Connected TV
    • Smartphone
    • Tablet
    • Desktop PC
    • SMS Advertising
  • Online ad blocking and lost revenues, split by:
    • Internet display advertising
    • Internet search advertising
    • Internet video advertising
  • Mobile Internet ad blocking, split by:
    • Internet display advertising
    • Internet search advertising
  • Advertising fraud, split:
    • Online advertising
    • Mobile advertising
    • In-app advertising
    • Install attribution fraud
  • AI Platform Revenues, split by:
    • Mobile search advertising
    • Mobile display advertising
    • Online advertising
  • Interactive Excel Scenario tool allowing the user the ability to manipulate Juniper’s data for 10 different metrics.
  • Access to the full set of forecast data of 360 tables and over 30,400 data points.
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.

 



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Table of Contents

Table of Contents

1. Deep Dive Strategy & Competition

1. Digital Advertising Channels: Engagement & Reach

1.1 The Future of Digital Advertising . 6
Figure 1.1: Total Spend on Desktop/Notebook Advertising ($bn) in 2023 . 6
1.2 Service Reach & Scarcity of Attention. 7
Figure 1.2: Global Reach of Select Consumer Devices for Advertising by 2023. 7
1.2.1 The Reach of SMS Advertising . 7
1.3 The Future Impact of Amazon on the Digital Advertising Market . 8
Figure 1.3: Amazon’s Annual Revenue Attributable to Other Services (including
Advertising Services) ($m) 2016-2018. 8
Case Study: Amazon’s Advertising Services . 9
1.3.1 The Impact on Google & Facebook.10
Figure & Table 1.4: Total Digital Advertising Ad Spend ($m), Split by Leading
Advertising Platforms 2018-2023. 10
i. Google’s Advertising Activities . 11
Figure 1.5: Leading Advertising Netw ork Ad Revenues ($bn) by 2023. 11
ii. Facebook’s Advertising Activities . 11
iii. Baidu ’s Advertising Activities. 12
1.4 Strategic Recommendations for Digital Advertising Stakeholders.12
Figure 1.6: Net In-App OTT TV Advertising Spend in 2023, Split by 8 Key Regions. 13

2. AI in Digital Advertising

2.1 Artificial Intelligence in the Advertising Space.16
Figure 2.1: AI Use Cases in the Advertising Industry .16
2.2 Artificial Intelligence in Digital Advertising: Vendor Positioning Index .17
Table 2.2: Juniper Vendor Positioning Index - Vendor Assessment Criteria .17
Figure 2.3: Juniper Research Vendor Positioning Index - Artif icial Intelligence
Providers in Advertising .18
2.2.1 Established Leaders .19
Figure 2.4: Alphabet’s Advertising Revenues ($m) 2016-2018 .19
Table 2.5: Sizmek Acquisitions 2012-present .23
2.2.2 Challenging Providers .24
2.2.3 Niche Providers.28
2.3 Quantifying the Impact of AI in Digital Advertising.30
Figure 2.6: Global Proportion of Ads Delivered Using AI or Machine Learning
Services, (%) Split by Ad Channel 2018-2023 .30
2.4 AI in Digital Advertising: The 5 Year Roadmap .31
2.4.1 Legislation will Impact Future Digital Advertising Strategies 31
2.4.2 AI-created Content for Advertising .31
Figure 2.7: Key Global AI in Advertising Statistics in 2023.31
Figure 2.8: Artif icial Intelligence in Advertising: The 5 Year Roadmap 2019-2023.32

3. Digital Advertising Fraud

3.1 Introduction to Advertising Fraud .34
3.1.1 The Direct Cost of Digital Advertising Fraud .34
Figure 3.1: Total Loss to Mobile & Online Advertising Fraud in 2019 & 2023 ($m)
Split by 8 Key Regions .34
3.1.2 Indirect Costs of Fraudulent Advertising Spend.35
Table 3.2: Select Types of Advertising Fraud . 36
3.2 Quantifying the Loss to Advertising Fraud .37
3.2.1 Online Browsing Advertising Fraud.37
Figure 3.3: Total Potential Lost Online Brow sing Ad Spend through Advertising
Fraud w ithout AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019 & 2023 . 37
3.2.2 Mobile Browsing Fraud.38
Figure 3.4: Total Potential Lost Mobile Brow sing Ad Spend through Advertising
Fraud w ithout AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019 & 2023 . 38
3.2.3 In-app Browsing Fraud .39
Figure 3.5: Total Potential Lost In-app Ad Spend through Advertising Fraud
w ithout AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019 & 2023 . 39
3.2.4 Install Attribution Fraud Level .40
Figure 3.6: Total Potential Lost App Advertising Spend through Advertising Fraud
w ithout AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019 & 2023 . 40
3.3 Future Strategy Analysis .41
Table 3.7: High Level View of Mobile Measurement Platforms & Fraud Detection
Platform Strategies . 41
3.4 The Cat-and-Mouse Nature of Advertising Fraud & Future Antifraud Strategies.42
Figure 3.8: The Advertising Fraud Innovation Cycle & AI . 42
Figure 3.9: Attribution Window Process . 44

4. Digital Advertising: The Competitive Landscape

4.1 Introduction to Advertising Attribution Platforms .46
4.1.1 Vendor Assessment Methodology.46
Table 4.1: Player Comparison Scoring Criteria - Digital Advertising Attribution Platforms.47
Figure 4.2: Juniper Leaderboard - Digital Advertising Attribution Platforms .48
Table 4.3: Juniper Leaderboard Heatmap Results - Digital Advertising Attribution Platforms.49
4.2 Vendor Groupings - Digital Advertising Attribution Platforms 50
i. Established Leaders.50
ii. Leading Challengers .50
iii. Disruptors & Emulators.52
4.3 Limitations & Interpretations .54
4.4 Digital Advertising: Movers & Shakers .55
4.5 Player Profiles .57
4.5.1 Adjust .57
i. Corporate .57
ii. Geographical Spread .57
iii. Key Clients & Strategic Partnerships .57
iv. High Level View of Offerings .58
v. Juniper View: Key Strengths & Strategic Opportunities.58
4.5.2 Affle.59
i. Corporate .59
Table 4.4: Aff le Acquisitions 2012-present.59
ii. Geographical Spread .59
iii. Key Clients & Strategic Partnerships .59
iv. High Level View of Offerings .59
v. Juniper View: Key Strengths & Strategic Opportunities.60
4.5.3 App Samurai .60
i. Corporate. 60
ii. Geographical Spread . 60
iii. Key Clients & Strategic Partnerships. 60
iv. High Level View of Offerings . 60
v. Juniper View: Key Strengths & Strategic Opportunities . 61
4.5.4 AppsFlyer .61
i. Corporate. 61
ii. Geographical Spread . 61
iii. Key Clients & Strategic Partnerships. 61
iv. High Level View of Offerings . 61
v. Juniper View: Key Strengths & Strategic Opportunities . 62
4.5.5 ClickGUARD.63
i. Corporate. 63
ii. Geographical Spread . 63
iii. Key Clients & Strategic Partnerships. 63
iv. High Level View of Offerings . 63
v. Juniper View: Key Strengths & Strategic Opportunities . 64
4.5.6 Codewise .64
i. Corporate. 64
ii. Geographical Spread . 64
iii. Key Clients & Strategic Opportunities . 64
iv. High Level View of Offerings . 64
v. Juniper View: Key Strengths & Strategic Opportunities . 65
4.5.7 Comscore .65
i. Corporate. 65
Table 4.5: Comscore Select Financial Information ($m) 2015-2018 . 65
ii. Geographical Spread .65
iii. Key Clients & Strategic Partnerships .66
iv. High Level View of Offerings .66
v. Juniper View: Key Strengths & Strategic Opportunities.66
4.5.8 Impact Technologies .67
i. Corporate .67
ii. Geographical Spread .67
iii. Key Clients & Strategic Partnerships .67
iv. High Level View of Offerings .67
v. Juniper View: Key Strengths & Strategic Opportunities.68
4.5.9 Kochava .68
i. Corporate .68
ii. Geographical Spread .68
iii. Key Clients & Strategic Partnerships .68
iv. High Level View of Offerings .68
v. Juniper View: Key Strengths & Strategic Opportunities.69
4.5.10 Machine Advertising .70
i. Corporate .70
ii. Geographical Spread .70
iii. Key Clients & Strategic Partnerships .70
iv. High Level View of Offerings .70
v. Juniper View: Key Strengths & Strategic Opportunities.70
4.5.11 Pixalate .70
i. Corporate .70
ii. Geographical Spread .71
iii. Key Clients & Strategic Opportunities.71
iv. High Level View of Offerings . 71
v. Juniper View: Key Strengths & Strategic Opportunities . 72
4.5.12 Singular .72
i. Corporate. 72
Table 4.6: Singular’s Funding Rounds July 2014-present. 72
ii. Geographical Spread . 72
iii. Key Clients & Strategic Partnerships. 72
iv. High Level View of Offerings . 73
v. Juniper View: Key Strengths & Strategic Opportunities . 73
4.5.13 Telecoming .74
i. Corporate. 74
ii. Geographical Spread . 74
iii. Key Clients & Strategic Partnerships. 74
iv. High Level View of Offerings . 74
v. Juniper View: Key Strengths & Strategic Opportunities . 74
4.5.14 TrafficGuard .75
i. Corporate. 75
ii. Geographical Spread . 75
iii. Key Clients & Strategic Opportunities . 75
iv. High Level View of Offerings . 75
v. Juniper View: Key Strengths & Strategic Opportunities . 76
4.5.15 TUNE .76
i. Corporate. 76
Table 4.7: TUNE Acquisitions 2012-present . 76
ii. Geographical Spread . 76
iii. Key Clients & Strategic Opportunities . 76
iv. High Level View of Offerings .76
v. Juniper View: Key Strengths & Strategic Opportunities.77

2. Deep Dive Data & Forecasting

1. Digital Advertising Market Summary

1.1 The Digital Advertising Ecosystem . 4
1.1.1 Reach, Engagement & Scarcity of Attention . 4
1.1.2 Mobile Subscriber Growth . 4
Figure 1.1: Share of Mobile Advertising Spend (%) Split by 8 Key Regions in 2023 . 4
1.1.3 Downward Price Pressure of Applications. 5
1.1.4 Improvements in Retargeting Strategies & Identifying High Value Users . 5
Figure 1.2: Digital Advertising Forecast Summary by 2023 . 5
1.1.5 The Digital Advertising Ecosystem . 6
Figure 1.3: The Digital Advertising Ecosystem . 6
1.2 Market Summary Forecasts . 7
1.2.1 Total Digital Advertising Spend. 7
Figure & Table 1.4: Total Spend on Digital Advertising - Online, Mobile,
Wearables, OTT TV & DOOH ($m) Split by 8 Key Regions 2018-2023. 7
1.2.2 Total Digital Advertising Spend, Split by Channel . 8
Figure & Table 1.5: Total Spend on Digital Advertising - Online, Mobile,
Wearables & DOOH ($m), Split by Advertising Channel 2018-2023 . 8

2. Online Digital Advertising

2.1 Online Digital Advertising . 10
2.1.1 Online Digital Advertising Forecast Methodology . 10
Figure 2.1: Online Advertising Forecast . 11
2.1.2 Total Spend of Desktop/Notebook Display Advertising . 12
Figure & Table 2.2: Net Desktop/Notebook Display Advertising Spend ($m) Split
by 8 Key Regions 2018-2023 . 12
2.1.3 Total Spend of Desktop/Notebook Search Advertising . 13
Figure & Table 2.3: Net Desktop/Notebook Search Advertising Spend ($m) Split
by 8 Key Regions 2018-2023 . 13
2.1.4 Total Spend of Desktop/Notebook Video Advertising . 14
Figure & Table 2.4: Net Desktop/Notebook Video Advertising Spend ($m) Split by
8 Key Regions 2018-2023 . 14

3. Mobile Browsing Digital Advertising

3.1 Mobile Browsing Digital Advertising . 16
3.1.1 Mobile Advertising . 16
Figure 3.1: Mobile Browsing Digital Advertising Forecast Methodology . 17
3.1.2 Total Spend on Mobile Browsing Display Advertising . 18
Figure & Table 3.2: Net Spend on Mobile Internet Display Advertising ($m) Split
by 8 Key Regions 2018-2023 . 18
3.1.3 Total Spend on Mobile Browsing Search Advertising . 19
Figure & Table 3.3: Total Spend on Smartphone Internet Search Advertising ($m)
Split by 8 Key Regions 2018-2023 . 19

4. Mobile In-app Digital Advertising

4.1 Mobile In-app Digital Advertising . 21
4.1.1 In-app Advertising Methodology . 21
Figure 4.1: Mobile In-app Advertising Forecast Methdology . 22
4.1.2 Total Spend on In-app Display Advertising . 23
Figure & Table 4.2: Net In-App Display Advertising Spend on Smartphones ($m)
Split by 8 Key Regions 2018-2023 . 23
Table 4.3: Net In-App Display Advertising Spend on Smartphones ($m) Split by
Ad Format 2018-2023 . 23

5. AI in Digital Advertising

5.1 AI (Artificial Intelligence) in Digital Advertising . 25
5.1.1 Methodology. 25
Figure 5.1: AI in Advertising Forecast Methodology . 26
5.1.2 Total Online Advertisements Delivered via AI or Machine
Learning Alogrithms . 27
Figure & Table 5.2: Total Spend on Online Advertising Delivered through
AI/Machine Learning Advertising ($m) Split by 8 Key Regions 2018-2023 . 27
5.1.3 Total Mobile Display Advertisements Delivered via AI or
Machine Learning Alogrithms . 28
Figure & Table 5.3: Total Spend on Mobile Display Advertising Delivered through
AI/Machine Learning Advertising ($m) Split by 8 Key Regions 2018-2023 . 28
5.1.4 Total Mobile Search Advertisements Delivered via AI or
Machine Learning Alogrithms . 29
Figure & Table 5.4: Total Spend on Mobile Search Advertising Delivered through
AI/Machine Learning Advertising ($m) Split by 8 Key Regions 2018-2023 . 29

6. Digital Advertising Fraud

6.1 Introduction to Digital Advertising Fraud . 31
6.1.1 Digital Advertising Fraud Forecast Methodology . 31
Figure 6.1: Digital Advertising Fraud Forecast Methodology . 32
6.1.2 Total Online Fraudulent Clicks . 33
Figure & Table 6.2: Number of Online Ad Clickthrough Ads that are Due to
Fraudulent Clicks (m) Split by 8 Key Regions 2018-2023 . 33
6.1.3 Total Loss to Online Advertising Fraud . 34
Figure & Table 6.3: Total Actual Lost Online Browsing Ad Spend through
Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Splut by 8
Key Regions 2018-2023 . 34
6.1.4 Mobile Browsing Advertising Fraud . 35
Figure & Table 6.4: Number of Mobile Ad Clickthrough Ads that are Due to
Fradulent Clicks (m) Split by 8 Key Regions 2018-2023 . 35
6.1.5 Total Loss to Mobile Browsing Advertising Fraud . 36
Figure & Table 6.5: Total Actual Lost Mobile Browsing Ad Spend through
Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Split by 8 Key
Regions 2018-2023 . 36
6.1.6 Number of Fraudulent Mobile In-app Clicks . 37
Figure & Table 6.6: Total Number of In-App Ad Impressions that are Delivered
Fraudulently (m) Split by 8 Key Regions 2018-2023 . 37
6.1.7 Total Loss to In-app Advertising Fraud . 38
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 . 38

　

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