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未來的數位廣告市場 (2019-2023年):AI、廣告詐騙

Future Digital Advertising: Artificial Intelligence & Advertising Fraud 2019-2023

出版商 Juniper Research 商品編碼 328287
出版日期 內容資訊 英文
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未來的數位廣告市場 (2019-2023年):AI、廣告詐騙 Future Digital Advertising: Artificial Intelligence & Advertising Fraud 2019-2023
出版日期: 2019年05月21日內容資訊: 英文
簡介

本報告套組,提供全球數位廣告市場展望調查,數位廣告的概要與各種途徑,數位廣告AI趨勢,數位廣告的廣告詐騙趨勢,各種途徑的數位廣告的支出額的預測,數位廣告AI市場定量分析、預測,廣告詐騙的損失額的預測,競爭環境,主要企業的簡介,相關利益者的策略性建議等資料。

提供內容

  • 「Deep Dive Strategy & Competition (策略、競爭分析)」(PDF)
  • 「5-Year Deep Dive Data & Forecasting (5年市場資料&預測)」(PDF&Excel)
  • 摘要整理、主要調查結果 (PDF)
  • 線上資料平台的存取 (12個月)

Deep Dive Strategy & Competition (策略、競爭分析)

第1章 數位廣告途徑:參與度和有效半徑

  • 未來的數位廣告
  • 服務的有效半徑和注意的不足
  • Amazon:對未來的數位廣告市場的影響
  • 數位廣告對相關利益者的策略性建議

第2章 數位廣告AI

  • 廣告業的AI
  • 數位廣告用AI:供應商的地位目錄
  • 數位廣告用AI的影響:定量分析
  • 5年藍圖

第3章 數位廣告的廣告詐騙

  • 簡介:廣告詐騙
  • 廣告詐騙造成的損失的定量分析
  • 未來的策略分析
  • 廣告詐騙、對策的貓捉老鼠

第4章 數位廣告:競爭環境

  • 簡介:廣告歸因平台
  • 供應商的分類
  • 規定、解釋
  • 數位廣告:有影響力的經營者
  • 企業簡介
    • Adjust
    • Affle
    • App Samurai
    • AppsFlyer
    • ClickGUARD
    • Codewise
    • Comscore
    • Impact Technologies
    • Kochava
    • Machine Advertising
    • Pixalate
    • Singular
    • Telecoming
    • TrafficGuard
    • TUNE

「Dive Data & Forecasting (市場資料&預測)」(PDF&Excel)

第1章 數位廣告市場:摘要

  • 數位廣告的生態系統
  • 市場預測:摘要
    • 總支出額
    • 總支出額:各途徑

第2章 市場資料、預測:線上數位廣告

  • 線上數位廣告
    • 總支出額:桌上型電腦/筆記型電腦展示廣告
    • 總支出額:桌上型電腦/筆記型電腦搜尋廣告
    • 總支出額:桌上型電腦/筆記型電腦視訊廣告

第3章 市場資料、預測:行動瀏覽數位廣告

  • 行動瀏覽數位廣告
    • 行動廣告
    • 總支出額:行動瀏覽展示廣告
    • 總支出額:行動瀏覽搜尋廣告

第4章 市場資料、預測:行動應用程式內數位廣告

  • 行動應用程式內數位廣告
    • App內廣告Methodology
    • 總支出額:App內展示廣告

第5章 市場資料、預測:數位廣告AI

  • 數位廣告AI
    • AI或機器學習演算法的線上廣告
    • AI或機器學習演算法的行動顯示器廣告
    • AI或機器學習演算法的行動搜尋廣告

第6章 數位廣告的廣告詐騙

  • 簡介:數位廣告的廣告詐騙
    • 線上廣告詐騙點選
    • 線上廣告詐騙造成的損失額
    • 行動瀏覽廣告欺詐的損失額
    • 行動應用程式內廣告詐騙點選數
    • App內廣告詐騙的喪失額

本網頁內容可能與最新版本有所差異。詳細情況請與我們聯繫。

目錄

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?

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,
  • Included in Vendor Positioning Index: Affectiva, Amazon, Amplero, Baidu, Bidalgo, Cognitiv, Conversica, Dynamic Yield, Facebook, Google, GumGum, IBM, Influential, Insidesales.com, Invoca, Microsoft, Quantcast, Salesforce, Sizmek.
  • Mentioned: A4D, Aarki, Acquired.io, Acxiom, Adalyser, Adcolony, Adconnect, Adform, Adjust, Ad juster, Adobe, Advertisas, Aeron, Affluent, Airbnb, Alphabet, Amobee, Apartment List, API.ai, Appfuel, Appier, AppLift, AppNexus, Artisan, Associated Press, ATIS (Alliance for Telecommunications Industry), AVA.ai, BBC Worldwide, Bennett, Bing, Branch, Burger King, Button, BuzzFeed, C9, CAAF (Coalition Against Ad Fraud), Cambridge Analytica, Cassandra, CBS, Centro, Centro, Centurion Corporation, CenturyLink, Chartboost, Chewy, Citigroup, ClearPier, ClearSaleing, Coleman & Co, CreditSesame, Cricket Wireless, D2C, Dark Blue Labs, Dataxu, Demandware, Dentsu, Diply, elex, Eloqua, Epson, Eureka & Docker, Everjobs, Eyeball Division, Fiksu, Fitplan, Folloze, Forbes, Forensiq, FreeWheel, Fyber, General Mills, GFK, Goodway Group, Grammarly, Gripati Digital Entertainment, Groupon, GS Stat Counter, Halli Labs, Hallmark Channel, HelloFresh, HIS Markit, Hotel Tonight, HP, HubSpot, IAB (Interactive Advertising Bureau), IMDB, iHance, Implisit, InferSystems, InMobi, InMobi, Innovid, Innvervate, Inovalon, Instagram, Investing.com, ironSource, Itochu, Kabbage, Kaggle, Kayzen, Kellogg's, KITT.AI, Lamoda, Leadpoint, Lexus, Liftoff, LinkedIn, Liverpool Football Club, Lyft, M&C Saatchi, Managed Objects, Marketo, Markt.ooo, Marriott Hotels, Mars, Match, McDonald's, M-Code, MediaOcean, MediaRadar, Mediarails, MetaMind, Migros, MobileDevHQ, MobileRQ, Mobimasta, MoPub, mParticle, Mpire, MRC (Media Rating Council), Nestlé, Netty, Neustar, NewVoiceMedia, Nike, NinthDecimal, Nudge.Ai, Olymp Trade, Omnicom Media Group, Onavo, optimob, Oracle, Pandora, Paperclip, Pardot, Partnerize, Peer39, Pepsi, Pinterest, PlaceIQ, PLAYXPERT, Pocket Media, PointRoll, Publicis, Pubmatic, Rakuten, Rappi, Razer, Reddit, RelateIQ, RhythmOne, Rocket Fuel, Roku, runtastic, Saatchi LA, Sabre Holdings, Samsung, SAP, Savings.com, ScaleArc, Segment, Sephora, Shazam, Shoffr, Shopcom, Shopify, Simmons, Skillz, Snap, Sony, SoundCloud, Spotify, Spring Boot on Java 8, Stitchfix, StrikeAd, Sunset World, Symantec, Synthace, Tappx, Telaria, The Atlantic, The Canadian Real Estate Association, The Los Angeles Film School, Toyota, TrafficGuard, TVSquare, Tvty, Twitter, Unbotify, Under Armour, Urban Outfitters, Verizon ,Vice, Vision Factory, Vizury, Vungle, Walmart, WhiteOps, WyWy, xPerception, Yelp, Yodas.com, Zynga.

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.

Table of Contents

Deep Dive Strategy & Competition

1. Digital Advertising Channels: Engagement & Reach

  • 1.1. The Future of Digital Advertising
    • Figure 1.1: Total Spend on Desktop/Notebook Advertising ($bn) in 2023
  • 1.2. Service Reach & Scarcity of Attention
    • Figure 1.2: Global Reach of Select Consumer Devices for Advertising by 2023
    • 1.2.1. The Reach of SMS Advertising
  • 1.3. The Future Impact of Amazon on the Digital Advertising Market
    • Figure 1.2: Global Research of Select Consumer Devices for Advertising Services) ($m) 2016-2018
    • 1.2.1. The Reach of SMS Advertising
  • 1.3. The Future Impact of Amazon on the Digital Advertising Market
    • Figure 1.3: 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. Baidu'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. AI in Digital Advertising

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

3. Digital Advertising Fraud

  • 3.1. Introduction to Advertising Fraud
    • 3.1.1. The Direct Cost of Digital Advertising Fraud
      • Figure 3.1: Total Loss to Mobile & Online Advertising Fraud in 2019 & 2023 ($m) Split by 8 Key Regions
    • 3.1.2. Indirect Costs of Fraudulent Advertising Spend
      • Table 3.2: Select Types of Advertising Fraud
  • 3.2. Quantifying the Loss to Advertising Fraud
    • 3.2.1. Online Browsing Advertising Fraud
      • Figure 3.3: Total Potential Lost Online Browsing Ad Spend through Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019. & 2023
    • 3.2.2. Mobile Browsing Fraud
      • Figure 3.4: Total Potential Lost Mobile Browsing Ad Spend through Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019. & 2023
    • 3.2.3. In-app Browsing Fraud
      • Figure 3.5: Total Potential Lost In-app Ad Spend through Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2019. & 2023
    • 3.2.4. 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
  • 3.3. Future Strategy Analysis
    • Table 3.7: High Level View of Mobile Measurement Platforms & Fraud Detection Platform Strategies
  • 3.4. 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

4. Digital Advertising: The Competitive Landscape

  • 4.1. Introduction to Advertising Attribution Platforms
    • 4.1.1. Vendor Assessment Methodology
      • Table 4.1: Player Comparison Scoring Criteria Platforms
      • Figure 4.2: Juniper Leaderboard - Digital Advertising Attribution Platforms
      • Table 4.3: Juniper Leaderboard Heatmap Results - Digital Advertising Attribution Platforms
  • 4.2. Vendor Groupings Digital Advertising Attribution Platforms
    • i. Established Leaders
    • ii. Leading Challengers
    • iii. Disruptors & Emulators
  • 4.3. Limitations & Interpretations
  • 4.4. Digital Advertising: Movers & Shakers
  • 4.5. Player Profiles
    • 4.5.1. Adjust
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 4.5.2. 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
    • 4.5.3. 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
    • 4.5.4. AppsFlyer
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 4.5.5. ClickGUARD
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 4.5.6. Codewise
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Opportunities
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 4.5.7. 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
    • 4.5.8. 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
    • 4.5.9. Kochava
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 4.5.10. 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
    • 4.5.11. Pixalate
      • i. Corporate
      • ii. Geographical Spread
      • iv. Key Clients & Strategic Opportunities
      • v. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 4.5.12. Singular
      • i. Corporate
        • Table 4.6: Singular's Funding Round's July 2014 - present
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 4.5.13. Telecoming
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 4.5.14. TrafficGuard
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Opportunities
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 4.5.15. TUNE
      • i. Corporate
        • Table 4.7: TUNE Acquisitions 2012-present
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Opportunities
      • vi. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities

Deep Dive Data & Forecasting

1. Digital Advertising Market Summary

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

2. Online Digital Advertising

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

3. Mobile Browsing Digital Advertising

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

4. Mobile In-app Digital Advertising

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

5. AI in Digital Advertising

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

6. Digital Advertising Fraud

  • 6.1. Introduction to Digital Advertising Fraud
    • 6.1.1. Digital Advertising Fraud Forecast Methodology
      • Figure 6.1: Digital Advertising Fraud Forecast Methodology
    • 6.1.2. 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
    • 6.1.3. 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 ($m) Splut by 8 Key Regions 2018-2023
    • 6.1.4. Mobile Browsing Advertising Fraud
      • Figure & Table 6.4: Number of Mobile Ad Clickthrough Ads that are Due to Fradulent Clicks (m) Split by 8 Key Regions 2018-2023
    • 6.1.5. Total Loss to Mobile Browsing Advertising Fraud
      • Figure & Table 6.5: Total Actual Lost Mobile Browsing Ad Spend through Advertising Fraud without AI-based Fraud Mitigation Solutions ($m) Split by 8 Key Regions 2018-2023
    • 6.1.6. 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
    • 6.1.7. 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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