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市場調查報告書

未來的數位廣告市場

Future Digital Advertising

出版商 Juniper Research 商品編碼 328287
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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未來的數位廣告市場 Future Digital Advertising
出版日期: 2017年09月25日 內容資訊: 英文
簡介

本報告提供未來的數位廣告市場相關調查分析,行動廣告,線上廣告,智慧型手錶廣告,戶外廣告為對象,主要流通管道的機會相關的系統性資訊。

策略與競爭

第1章 數位廣告生態系統

  • 數位廣告:市場更新
  • 行動廣告市場趨勢

第2章 數位廣告預測

  • 未來的經營模式
  • 廣告攔截的未來

第3章 廣告的人工智能 (AI)

  • 廣告的AI
  • AI廣告企業分析

第4章 數位廣告:競爭情形

  • 簡介
  • 供應商評估
  • 限制、解釋
  • 數位廣告:產業的有勢力者
  • 企業簡介

資料與預測

第1章 數位廣告:未來預測

  • 數位廣告產業預測
  • 行動廣告
  • 數位廣告生態系統

第2章 數位廣告:市場預測摘要

  • 數位廣告摘要預測

第3章 線上數位廣告:市場預測和要點

  • 線上廣告

第4章 行動廣告:市場預測和要點

  • 行動市場
  • 行動網際網路瀏覽 (閱覽) 廣告
  • 行動應用程式內、SMS廣告支出

第5章 廣告定位掩護:市場預測和要點

  • 廣告定位掩護
  • 線上廣告定位掩護
  • 行動廣告Broker

第6章 廣告的AI

  • 簡介
  • 廣告的AI
  • 廣告詐騙
  • 減少廣告詐騙的AI

第7章 數位戶外廣告:市場預測和要點

  • 數位戶外廣告

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目錄

Overview

Juniper Research's highly regarded Future Digital Advertising research provides actionable insights, market intelligence and strategic recommendations for stakeholders on the swiftly changing digital advertising markets covering:

  • Mobile Advertising
  • Online Advertising
  • Smartwatch Advertising
  • Out of Home Advertising

It investigates the opportunities across key channels, considering the adoption of ad blocking technologies and the role that Artificial Intelligence will play in the future of the market. It identifies ad targeting strategies and the prevention of advertising fraud, to present a comprehensive outline of the next 5 years of the digital advertising industry.

This research suite includes:

  • Deep Dive Strategy and Competition (PDF)
  • 5 Year Deep Dive Data and Forecasting (PDF)
  • Executive Summary & Core Findings (PDF)

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, targeting strategies and chatbots
    • Future opportunities in Mobile, Online, and Digital Out-of-Home Advertising
    • Evaluation of the impact of Ad Blocking technologies
    • Key market trends, drivers and constraints acting on the digital advertising market
  • Juniper Positioning Index: A comparative assessment of AI advertising services from 14 platform providers in the Digital Advertising market, categorised in terms of the depth of their hardware offerings. Vendors in our Positioning Index include:
    • Affectiva
    • Alphabet
    • Antvoice
    • Baidu
    • Cognitiv
    • Dentsu
    • drawbridge
    • Dynamic Yield
    • Facebook
    • IBM
    • Microsoft
    • Reflektion
    • Rocket Fuel
    • Salesforce
  • 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 the 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)
    • Message-Based (SMS)
    • Ad Blocking & Fraud
    • AI In Advertising
  • Interviews: Unique insight into how each player is competing in this market, including:
    • Dynamic Yield
    • Eyeo
    • Mitto
    • Reflektion
    • Rubicon Project
    • Salesforce
  • Juniper Leaderboard: 12 leading digital advertising platform vendors compared, scored and positioned on the Juniper Leaderboard matrix.

Key Questions

  • 1. Which strategies and technologies will be the most effective on diminishing ad fraud?
  • 2. How is artificial intelligence disrupting the digital advertising industry?
  • 3. How much will the digital advertising industry be worth by 2022?
  • 4. What steps have been taken by the ad industry to combat ad blocking technology?
  • 5. Which area of advertising will be the most lucrative over the next 5 years?

Companies Referenced

  • Interviewed: Dynamic Yield, Eyeo GmbH, Mitto, Reflektion, Rubicon Project, Salesforce.
  • Profiled: Airpush, Alphabet, Amobee, Baidu, Demandbase, Facebook, Fiksu, OpenX, PubMatic, Rubicon Project, Salesforce, xAd.
  • Case Studied: BroadSign, Facebook, Google, Rocket Fuel, White Ops.
  • Platform Providers Profiled in Vendor Positioning Matrix: Affectiva, Alphabet, Antvoice, Baidu, Cognitiv, Dentsu, drawbridge, Dynamic Yield, Facebook, IBM, Microsoft, Reflektion, Rocket Fuel, Salesforce.
  • Mentioned: AdBlock, Adblock Fast, AdBlock Plus, Adconian Direct, Adelphic, Adenyo, Adjitsu, Adjust, Admoove, Adobe, AdRoll, Alibaba, Amazon, AMI (American Media Inc), Angel.ai, AOL, API.ai, Apple, AppNexus, Apps Flyer, Aprimo, Apsalar, Ardeeka, Associated Press, Bell Communications Research, Bell Labs, BeyondCore, Blogger, Bluekai, Born, Box, Cadreon, Captivate Network, Carnival.io, CBS, Cellmania, Chango, Charity Water, Chatflow, Cheesecake Factory, Cisco, Citigroup, Clickability, Coalition for Better Ads, Convade, Coolan, Criteo, Crownpeak, Dark Blue Labs, DeepMind, Demandware, DFKI (German Research Centre for Artificial Intelligence), Digital Marketing Magazine, DNNresearch, DocuSign, DoubleClick, DoubleVerify, Dunkin' Donuts, E.piphany, Edgecase, Ektron, Emu, Equivio, Everjobs, Exact Target, Exelate, Face.com, Finfo.com, Fox Audience Network, FreshDirect, G+J, Gander Mountain, GE, Genee, Globespan, Godiva, Gradient X, Granata Decision Systems, Green Bay Packers, Halli Labs, Hallmark Channel, Harvest.ai, HelloFresh, Hemnet, Hewlett Packard, Hubbi, Hubspot, IAB (Interactive Advertising Bureau), iAd, IAS (Integral Ad Science), Implisit, Indisys, InStranet, iSite Design, J PADTM (Japan Publisher Alliance on Digital), jetpac, Kadro, Kaggle, Kellogg's, Kiip, Kiplinger, KITT.AI, Kochave, Kontera, Krux, L90, Lamoda, Lattice, LiftDNA, LiveRamp, Liverpool Football Club, Localytics, Lucent Technologies, Magento, Magic Pony, MapSense, Marmot, Mars, Mastercard, Media 122, MediaMath, MediaOcean, Mediekompaniet Adapt, Merkle, MetaMind, Millennial Media, MinHash, Moat, Mocean Mobile, Moodstocks, Mopub, Movidius, MRC (Media Rating Council), Nanigans, Narvar, Nervana Systems, Nest, Neustar, News Corp, Nielsen, nToggle, NVIDIA, Opentext, Oracle, Orbeus, OthersOnline, Outback Steakhouse, OutFront Media, PageFair, PANTA Systems, Party, Pedowitz Group, Perceptio, Philips, Picasa, Pixalate, POST-Cereal PETA, PredictionIO, Proxama, Publicis, Qualcomm, Raven Tech, Razorfish, RealFace, ReaXions, RelateIQ, Reuters, RIM, RingRing Media, Rocketship Apps, Saatchi LA, Saffron Technology, SailThru, SAP, SDL, Sephora, Shine, Silverpop, Singtel, Site Scout, Sizmek, SonoTrend, Statiq, Stitchfix, StrongMail Systems, Strongview, Subway, SwiftKey, Synthace, Telefonica, TellApart, Tempo AI, Tencent, Timeful, TouchTunes, Triggit, tumplejump, Tune, Turi, Turn, Twitter, Ubiquity, Under Armour, Unilever, Uniqlo, Urban Outfitters, VERITAS India, Vision Factory, Vocal IQ, Vodafone, Walt Disney, Web Financial Group, Webtrends, Wit.ai, WordPress, Workday, xPerception, Yahoo, YOTTAA, YP, Zondingo, Zurich Eye.

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
  • 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 & AI Platform Revenues, split by:
    • Mobile advertising
    • Online advertising
  • Interactive Excel Scenario tool allowing user the ability to manipulate Juniper's data for 36 different metrics.
  • Access to the full set of forecast data of 325 tables and over 18,400 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. The Digital Advertising Ecosystem

  • 1.1. Digital Advertising: A Market Update
    • 1.1.1. Notable Market Movements
      • Figure 1.1: Digital Advertising MarTech & AdTech Notable Market Movements
  • 1.2. Mobile Advertising Market Trends
    • 1.2.1. Reach & Engagement
      • Figure 1.2: Number of Hours Spent Internet Browsing by US Consumers (211-2016), Split by Device
    • 1.2.2. A2P & P2A Advertising
    • 1.2.3. Advances in Programmatic Advertising & Real-time Bidding
      • i. Privacy Issues
      • ii. Inexplicable AI Algorithms
    • 1.2.4. Digital Advertising: Market Drivers, Trends & Constraints
      • Figure 1.3: Digital Advertising: Trends, Drivers & Constraints
    • 1.2.5. DOOH Avertising
      • Figure 1.4: Digital Signate Unit
        • i. Case Study: BroadSign
        • ii. Digital Signate Strategies & Opportunities
      • Figure 1.5: The DOOH Advertising Environment

2. The Outlook for Digital Advertising

  • 2.1. Future Business Models
    • 2.1.1. The Current Mobile Market
  • 2.2. The Future of Ad Blockers
    • Figure 2.2: Total Number of Global Ad Block Users 2009-2016(m)
    • 2.2.1. Motivation for Ad Blocker Adoption
      • Figure 2.3: Motivation behind Ad Blocker Adoption
    • 2.2.2. Ad Blocking Publisher Strategies
      • ii. Case Study: Google to Develop Ad Blocker Built into Chrome
    • 2.2.3. Combative Strategies

3. Artificial Intelligence in Advertising

  • 3.1. AI (Artificial Intelligence) in Advertising
    • Figure 3.1: Select AI Acquisitions
    • 3.1.1. AI's Role in Advertising
    • 3.1.2. AI for Fraud Detection
      • i. Case Study: White Ops & Methbot
        • Figure 3.2: Total Revenue Loss through Advertising Fraud ($bn) 2017 & 2022
    • 3.1.3. Machine Learning & RTB
      • i. AI Disruptor: Case Study - Rocket Fuel
    • 3.1.4. Ad Fraud Detection Strategies
      • Figure 3.3: Juniper Research Phased Evolution Model - AI in Ad Fraud Detection
      • Figure 3.4: Proportion of Online Ad Click Through Ads that are Due to Fradulent Clicks in 2022
    • 3.1.5. Gaining Access to the 'Walled Gardens'
      • Figure 3.5: Proportion of Advertising Spend Saved by AI & ML Algorithms of Total Ad Spend Lost to Ad Fraud (%)- Selected Regions 2017-2022
    • 3.1.6. Ad Blockers as a Combatant to Advertising Fraud
    • 3.1.7. AI Enabling Cognitive Advertising
      • Figure 3.6: Global Proportion of Digital Ad Spend Leverage by AI &ML Platforms
    • 3.1.8. AI in Chatbots
      • i. Benefits of Implementing AI Chatbots
      • ii. Chatbot Advertising Opportunity & Hurdles
        • Figure 3.7: Total Number of Chatbots Accessed per Annum (m), Split by eCommerce & Retail & Other Uses - 2017 & 2022
      • iii. Case Study: Facebook Messenger Chatbots
  • 3.2. AI Advertising Player Analysis
    • Table 3.8: Juniper Vendor Positioning Index - Vendor Assessment Criteria
    • Figure 3.9: Juniper Vendor Positioning Index - AI Advertising Platforms
    • 3.2.1. AI Advertising Player Commentary
      • i. Affectiva
      • ii. Alphabet
      • iii. Antvoice
      • iv. Baidu
      • v. Cognitiv
      • vi. Dentsu
      • vii. drawbridge
      • viii. Dynamic Yield
      • ix. Facebook
      • x. IBM
      • xi. Microsott
      • xii. Reflektion
      • xiii. Rocket Fuel
      • xiv. Salesforce

4. Digital Advertising: The Competitive Landscape

  • 4.1. Introduction
    • Table 3.1O: Salesforce.com AI Acquisitions (2014onwards)
  • 4.2. Vendor Assessment
    • 4.2.1. Vendor Assessment Methodology
      • Table 4.1: Player Capability Criteria - Digital Advertising Platform Providers
      • Figure 4.2: Juniper Leaderboard - Digital Advertising Platform Providers
      • Table 4.3: Juniper Heatmap Results - Digital Advertising Platform Providers
    • 4.2.2. Vendor Groupings - Digital Advertising Platform Providers
      • i. Established Leaders
        • Figure 4.4: Digital Advertising Platform Providers - Established Leaders Revenues 2016
      • ii. Leading Challengers
      • iii. Disruptors & Emulators
  • 4.3. Limitations &Interpretations
  • 4.4. Digital Advertising: Industry Movers & Shakers .
  • 4.5. Player Profiles
    • 4.5.1. Airpush
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Development Opportunities.
    • 4.5.2. Alphabet
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Development Opportunities
    • 4.5.3. Amobee
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Development Opportunities
    • 4.5.4. Baidu
      • i. Corporate Profile
        • Table 4.7: Notable Baidu AI-related Acquisition (2017 onwards)
        • Table 4.8: Baidu Financial Snapshot ($bn) 2013-2015
      • ii. Geographic Spread
      • iii. Key Clients & Partnerships
      • iv. Products & Services
      • v. Juniper's View: Key Strengths & Opportunities
    • 4.5.5. Demand base
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Development Opportunities
    • 4.5.6. Facebook
      • i. Corporate
    • 4.5.7. Fiksu
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Development Opportunities
    • 4.5.8. Salesforce.com
      • i. Corporate Profile
        • Table 4.10: Salesforce.com Financial Snapshot ($m) FY 2015-2017
        • Table 4.11: Salesforce.com AI Acquisitions (2014 onwards)
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. Products & Services
      • v. Juniper's View: Key Strengths & Opportunities
    • 4.5.9. OpenX
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Development Opportunities
    • 4.5.10. PubMatic
      • Table 4.13: PubMatic Series Funding (2008 onwards)
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Strategic Opportunities
    • 4.5.11. Rubicon Project
      • i. Corporate
        • Table 4.14: Rubicon Project Selected Financial Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Development Opportunities
    • 4.5.12. xAd
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper View: Key Strengths & Development Opportunities

Deep Dive Data & Forecasting

1. Digital Advertising: The Future 0utlook

  • 1.1. The Outlook for the Digital Advertising Industry
    • 1.1.1. Mobile Subscriber Growth
    • 1.1.2. Reach & Engagement
    • 1.1.3. Downward Price Pressure of Applications
    • 1.1.4. Improvements in Retargeting Strategies
  • 1.2. Mobile Advertisements
  • 1.3. The Digital Advertising Ecosystem
    • Figure 1.1:Juniper Research Digital Advertising Ecosystem

2. Digital Advertising: A Market Forecast Summary

  • 2.1. Digital Advertising Summary Forecasts
    • 2.1.1. Total Spend on Digital Advertising: Mobile, 0nline, Wearab & DOOH
      • Figure & Table 2.1: Total Spend on Digital Advertising ($m) Split by 8 Key Regions 2017-2022
    • 2.1.2. Total Spend on Desktop/Notebook Advertising
      • Figure & Table 2.2: Total Spend on Desktop/Notebook PC Advertising ($bn) Split by 8 Key Regions 2017-2022
    • 2.1.3. Total Spend on Mobile Advertising
      • Figure & Table 2.3: Total Spend on Mobile (Smartphones, Feature phones, & Tablets) Advertising ($m) Split by 8 Key Regions 2017-2022
    • 2.1.4. Total Spend on Smartwatch Advertising
      • Figure & Table 2.4: Total Spend on Smartwatch Advertising ($m) Split by 8 Key Regions 2017-2022

3. Online Digital Advertising: Market Forecasts & Key Takeaways

  • 3.1. 0nline Advertising
    • 3.1.1. Methodology
      • Figure 3.1: Online Advertising Forecast
    • 3.1.2. Total Spend on Desktop/Notebook Display Advertising
      • Figure & Table 3.2: Total Spend on Desktop/Notebook Display Advertising ($b) Split by 8 Key Regions 2017-2022
    • 3.1.3. Total Spend on Desktop/Notebook Search Advertising
      • Figure & Table 3.3: Total Spend on Desktop/Notebook Search Advertising ($b) Split by 8 Key Regions 2017-2022
    • 3.1.4. Total Spend on Desktop/Notebook Video Advertising
      • Figure & Table 3.4: Total Spend on Desktop/Notebook Video Advertising ($bn) Split by 8 Key Regions 2017-2022

4. Mobile Advertising: Market Forecasts & Key Takeaways

  • 4.1. The Mobile Market
    • 4.1.1. Mobile Advertising
      • Figure 4.1: Mobile Advertising Forecast Methodology
    • 4.1.2. In-App & Messaging Advertising
      • Figure 4.2: The Components of Mobile Advertising
        • i. SMS Advertising
        • ii. In-App Advertising
          • Figure 4.3: In-Application Forecast Methodology
  • 4.2. Mobile Internet Browsing Advertising
    • 4.2.1. Total Spend on Mobile Internet Browsing Advertising, Split by Regions
      • Figure & Table 4.4: Total Mobile Internet Browsing Ad Spend ($m) Split by 8 Key Regions 2017-2022
    • 4.2.2. Total Mobile Browsing Internet Spend, Split by Ad Format
      • Figure & Table 4.5: Total Mobile Internet Ad Spend Split by Ad Format ($bn) Split by Display & Search Advertising 2017-2022
  • 4.3. Mobile In-App &SMS Ad Spend
    • 4.3.1. In-Application Mobile Ad Spend, Split by Region
      • Figure & Table 4.6: Total Mobile In-App Ad Spend ($bn) Split by 8 Key Regions 2017-2022
    • 4.3.2. Total SMS Advertising Spend
      • Figure 4.7: Total SMS Advertising Spend ($m) Split by 8 Key Regions 2017-2022

5. Ad Blocking : Market Forecasts & Key Takeaways

  • 5.1. Ad Blocking
    • 5.1.1. 0nline Ad Blockers
    • 5.1.2. Mobile Ad Blockers
    • 5.1.3. Methodology
      • Figure 5.1: Desktop and Mobile Ad Blocking Forecast Methodology
    • 5.1.4. Mobile & 0nline Ad Blocking Summary
      • Figure & Table 5.2: Total Revenue Lost due to Ad Blocking ($bn)Split by Online & Mobile Devices 2017-2022
  • 5.2. 0nline Ad Blocking
    • 5.2.1. Number of Desktop/Notebook Internet Display Adverts Blocked by Ad Blockers
      • Figure & Table 5.3: Number of Desktop/Notebook Internet Display Adverts Blocked by Ad Blockers (bn) Split by 8 Key Regions 2017-2022
    • 5.2.2. Total Desktop/Notebook Internet Display Ad Revenue Lost Due to Ad Blockers
      • Figure & Table 5.4: Total Desktop/Notebook Internet Display Ad Revenue Lost Due to Ad Blockers ($bn) Split by 8 Key Regions 2017-2022
    • 5.2.3. Number of Desktop/Notebook Internet Search Adverts Blocked by Ad Blockers
      • Figure & Table 5.5: Number of Desktop/Notebook Internet Search Adverts Blocked by Ad Blockers (bn) Split by 8 Key Regions 2017-2022
    • 5.2.4. Total Desktop/Notebook Internet Search Advertising Revenue Lost Due to Ad Blockers
      • Figure & Table 5.6: Total Desktop/Notebook Internet Search Advertising Rev(5) Lost Due to Ad Blockers ($bn)Split by 8 Key Regions 2017-2022
    • 5.2.5. Number of Desktop/Notebook Internet Video Adverts Block by Ad Blockers
      • Figure & Table 5.7: Number of Desktop/Notebook Internet Video Adverts Blocked by Ad Blockers (bn) Split by 8 Key Regions 2017-2022
    • 5.2.6. Total Desktop/Notebook Internet Video Advertising Revenue Lost Due to Ad Blockers
      • Figure & Table 5.8: Total Desktop/Notebook Internet Video Advertising Revenue Lost Due to Ad Blockers ($m) Split by 8 Key Regions 201 7-2022
  • 5.3. Mobile Ad Blockers
    • 5.3.1. Number of Smartphone & Tablet Internet Display Adverts Blocked by Ad Blockers
      • Figure & Table 5.9: Number of Smartphone & Tablet Internet Display Adverts Blocked by Ad Blockers (bn) Split by 8 Key Regions 2017-2022
    • 5.3.2. Total Smartphone & Tablet Internet Display Ad Revenues Lost Due to Ad Blocking
      • Figure & Table 5.1O: Total Smartphone & Tablet Internet Display Ad Revenues Lost Due to Ad Blocking ($m) Split by 8 Key Regions 2017-2022
    • 5.3.3. Number of Smartphone & Tablet Internet Search Adverts Blocked by Ad Blockers
      • Figure & Table 5.11: Number of Smartphone & Tablet Internet Search Adverts Blocked by Ad Blockers (m)Split by 8 Key Regions 2017-2022
    • 5.3.4. Total Smartphone & Tablet Internet Search Ad Revenues Lost Due to Ad Blocking
      • Figure & Table 5.12: Total Smartphone & Tablet Internet Search Ad Revenues Lost Due to Ad Blocking ($m) Split by 8 Key Regions 2017-2022

6. Artificial Intelligence in Advertising

  • 6.1. Introduction
    • 6.1.1. Methodology
      • Figure 6.1: Online AI Advertising Forecast Methodology
      • Figure 6.2: Mobile AI Advertising Forecast Methodology
  • 6.2. AI in Advertising
    • 6.2.1. Total Number of 0nline Adverts Delivered using AI/ML Services
      • Figure & Table 6.3: Total Number of Online Adverts Delivered using AI/ML Services (bn) Split by 8 Key Regions 2017-2022
    • 6.2.2. Total Spend on 0nline Advertising Delivered through AI/ML Advertising
      • Figure & Table 6.4: Total Spend on Online Advertising Delivered through AIlM Advertising ($m) Split by 8 Key Regions 2017-2022
    • 6.2.3. Total Number of Mobile Display Adverts Delivered using AI/ML Services
      • Figure & Table 6.5: Total Number of Mobile Display Adverts Delivered using AI/ML Services (bn) Split by 8 Key Regions 2017-2022
    • 6.2.4. Total Spend on Mobile Display Advertising Delivered through AI/ML Advertising
      • Figure & Table 6.6: Total Spend on Mobile Display Advertising Delivered through AI/ML Advertising ($m) Split by 8 Key Regions 2017-2022
    • 6.2.5. Total Number of Mobile Search Adverts Delivered using AI/ML Services
      • Figure & Table 6.7: Total Number of Mobile Search Adverts Delivered using AI/ML Services (bn) Split by 8 Key Regions 2017-2022
    • 6.2.6. Total Spend on Mobile Search Advertising Delivered through AI/ML Advertising
      • Figure & Table 6.8: Total Spend on Mobile Search Advertising Delivered through AI/ML Advertising ($m) Split by 8 Key Regions 2017-2022
  • 6.3. Advertising Fraud
    • 6.3.1. Number of 0nline Ad Click-Through Ads that are due to Fraudulent Clicks
      • Figure & Table 6.9: Number of Online Ad Click-Through Ads that are Due to Fraudulent Clicks (bn) Split by 8 Key Regions 2017-2022
    • 6.3.2. Total 0nline Advertising Revenue Lost through Advertising Fraud
      • Figure & Table 6.1O: Total Online Advertising Revenue Lost Through Advertising Fraud ($m) Split by 8 Key Regions 2017 -2022
    • 6.3.3. Number of Mobile Ad Click-Through Ads that are Due to Fraudulent Clicks
      • Figure & Table 6.11: Number of Mobile Ad Click-Through Ads that are Due to Fraudulent Clicks (bn) Split by 8 Key Regions 2017-2022
    • 6.3.4. Total Mobile Advertising Revenue Lost through Advertising Fraud ($bn)
      • Figure & Table 6.12: Total Mobile Advertising Revenue Lost through Advertising Fraud ($bn) Split by 8 Key Regions 2017-2022
  • 6.4. AI in Reducing Ad Fraud
    • 6.4.1. Total Fraudulent 0nline Advertising Spend Saved through AI & ML Advertising Algorithms
      • Figure & Table 6.13: Total Fraudulent Online Advertising Spend Saved through AI & ML Advertising Algorithms ($m)Split by 8 Key Regions 2017-2022
    • 6.4.2. Total Fraudulent Mobile Advertising Spend Saved through AI & ML Advertising Algorithms
      • Figure & Table 6.14: Total Fraudulent Mobile Advertising Spend Saved through AI & ML Advertising Algorithms ($m)

7. Digital 0ut of Home Advertising: Market Forecasts & Key Takeaways

  • 7.1. Digital Out of Home Advertising
    • 7.1.1. Methodology
      • Figure 7.1: Digital Out of Home Advertising
    • 7.1.2. Number of Digital Signate Units Used for 00H Advertising that Rent Ad Space
      • Figure & Table 7.2: Number of Digital Signate Units Used for OOH Advertising that Rent Ad Space (m)Split by 8 Key Regions 2017-2022
    • 7.1.3. Total Number of Advertiser Digital Signate Subscriptions
      • Figure & Table 7.3: Total Number of Advertiser Digital Signate Subscriptions ($m) Year End Split by 8 Key Regions 2017-2022
    • 7.1.4. Total Advertiser Spend on Digital Signate 00H Advertising
      • Figure & Table 7.4: Total Advertiser Spend on Digital Signate OOH Advertising ($m)
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