自動內容識別市場（按組件、技術、內容、平台、應用和垂直領域）—2025-2030 年全球預測

預計自動內容識別市場在 2024 年將達到 38.4 億美元，在 2025 年將成長至 44.5 億美元，在 2030 年將達到 96.2 億美元，複合年成長率為 16.50%。

主要市場統計數據
基準年2024年	38.4億美元
預計2025年	44.5億美元
預測年份 2030	96.2億美元
複合年成長率（%）	16.50%

開啟自動內容辨識的新時代：在動態數位生態系統中推動媒體智慧和受眾參與

數位轉型的推進和串流媒體服務的不斷擴展，將自動內容識別推到了媒體智慧的前沿。廣告、測量和內容傳送相關人員正在利用自動內容識別 (ACR) 來即時識別音訊、影像和廣播訊號。將 ACR 功能整合到互聯設​​備和 OTT 平台中，使提供者能夠提供個人化體驗並深入了解消費行為。此外，整合先進的指紋識別和數位浮水印可以提高識別準確性，為進階分析和有針對性的商業化戰略鋪平道路。

揭示影響自動內容識別的變革性變化：重新定義市場軌跡的技術創新、夥伴關係和監管動態

近年來，人工智慧和邊緣運算領域的突破顯著改變了音訊辨識（ACR）的格局。用於音訊和視訊指紋識別的深度學習模型如今能夠以無與倫比的精度實現亞秒級識別，而雲端基礎的數位浮水印服務則確保了在不同串流媒體環境中的彈性檢測。 5G 網路的推出進一步加速了這些功能的發展，它降低了延遲，並能夠將豐富的元資料即時傳輸到下游分析系統。因此，服務提供者可以根據即時環境來協調動態內容定位，從而將觀眾參與度提升到新的高度。

評估美國2025年關稅對自動內容辨識的累積影響：供應鏈、成本結構與競爭優勢

美國將於2025年對進口硬體和專用組件徵收新關稅，這將為自動內容識別提供者及其供應鏈帶來巨大的複雜性。關鍵感測器模組、數位訊號處理器和專有半導體晶片現在都需要繳納進口關稅，這會導致製造成本上升。因此，目標商標產品製造商和平台供應商被迫重新評估籌資策略，並尋找具有成本效益的替代方案。

自動內容識別的關鍵細分洞察：按組件、技術、內容、平台、應用、垂直促進因素

按組件細分，可以發現專業服務和軟體產品之間存在差異。在專業服務領域，隨著部署的日益複雜，對構建ACR策略的諮詢專家、負責將識別引擎整合到現有基礎設施的整合團隊以及確保系統性能不間斷的維護專家的需求正在成長。在軟體方面，承包指紋辨識和數位浮水印套件、雲端託管OCR引擎以及語音辨識模組正在打包成開發人員友善的API，從而幫助企業縮短產品上市時間。

揭示美洲、歐洲、中東和非洲以及亞太地區自動內容識別的關鍵區域洞察和成長模式

隨著美洲生態系統持續擁抱數位轉型，美國和加拿大在應用自動內容辨識方面處於領先地位。這些市場的串流媒體巨頭、廣播公司和廣告網路正在利用即時指紋和數位浮水印來最佳化動態廣告插入並監控授權合約的合規性。此外，高電視普及率正在刺激家庭機上盒和智慧電視的需求，而汽車資訊娛樂系統正在整合識別引擎，以在行駛過程中提供情境音訊體驗。

分析競爭格局中塑造自動內容識別未來的主要企業的策略和創新

多家領先的技術供應商和專業服務供應商正在透過差異化創新和策略聯盟來塑造自動內容識別的格局。知名元資料專家 Gracenote 正在透過增強其指紋識別功能並與主要目標商標產品製造商建立夥伴關係關係，將其識別引擎嵌入韌體級別，從而擴大其業務範圍。 Audible Magic 憑藉其強大的音樂識別平台脫穎而出，該平台利用龐大的內容資料庫和對音訊串流服務的全面覆蓋。

為行業領導者提供切實可行的建議，以推動不斷發展的自動內容識別市場的競爭優勢和永續成長

想要抓住自動內容辨識機會的產業領導者，應優先開發隱私優先的架構，以實現設備端處理和分散式資料處理。減少對集中式伺服器進行指紋辨識和數位浮水印處理的依賴，有助於企業遵守日益嚴格的資料保護條例，並提升使用者信任度。此外，與區域代工廠和硬體供應商建立策略聯盟，可以減少因關稅導致的供應鏈中斷風險，並透過協同設計解決方案加快產品上市時間。

透過結合初步訪談、二次資料分析和高級三角測量技術的強大調查方法來獲得深入的市場洞察

此項市場分析背後的調查方法是嚴格結合二手資料和一手資料收集技術。首先，我們會全面審查產業白皮書、監管文件、專利資料庫和公司簡介，以便對技術進步和市場動態有基本的了解。此階段也會結合全球監管文件和橫向報告，以確保對合規制度和業務促進因素有全面且客觀的觀點。

自動內容識別演進的全面觀點：關鍵發現及其對產業相關人員的策略意義

隨著自動內容辨識市場的不斷發展，先進的指紋辨識、數位浮水印、光學字元辨識 (OCR) 和語音辨識技術的融合正在重塑內容的辨識、收益和保護方式。軟體供應商、系統整合商和專業服務公司之間複雜的相互關係凸顯了端到端夥伴關係關係的必要性，這種合作夥伴關係既能解決技術複雜性問題，又能滿足法規合規性要求。同時，基礎設施成熟度和法律規範在地區間的差異也凸顯了客製化部署策略的重要性。

目錄

第1章：前言

第2章調查方法

第3章執行摘要

第4章 市場概述

第5章市場動態

• 自動內容識別引擎與串流分析平台的整合實現了即時觀眾測量
• 水印和指紋技術的進步增強了跨裝置的內容識別和追蹤
• 引入人工智慧和機器學習模型，提高自動內容辨識的準確性和速度
• 將內容感知應用程式擴展到零售環境，以實現個人化的店內廣告和分析。
• 監管和消費者的擔憂推動了對自動內容識別中符合隱私的資料處理的需求
• 廣播公司和廣告科技公司合作利用ACR數據進行動態可尋址電視廣告最佳化
• 將自動內容辨識功能整合到智慧家庭設備中，實現語音啟動的內容搜尋和個人化

第6章 市場洞察

• 波特五力分析
• PESTEL分析

第7章 2025年美國關稅的累積影響

第 8 章 自動內容辨識市場（按組件）

• 服務
  • 諮詢服務
  • 整合服務
  • 維護服務
• 軟體

第9章 自動內容辨識市場（依技術）

• 音訊和視訊指紋識別
• 音訊和視訊浮水印
• 光學字元辨識 (OCR)
• 語音辨識

第 10 章 自動內容辨識市場（按內容）

• 聲音的
• 影像
• 句子
• 影片

第 11 章：按平台分類的自動內容識別市場

• 連接裝置
• OTT平台
• 智慧電視

第 12 章 自動內容辨識市場（按應用）

• 廣告定位和定價
• 廣告和行銷
• 受眾測量
• 廣播級監控
• 內容管理
• 版權保護

第 13 章：按行業垂直分類的自動內容識別市場

• 車
• 家電
• 資訊科技/通訊
• 媒體與娛樂
• 零售與電子商務

第 14 章：美洲自動內容辨識市場

• 美國
• 加拿大
• 墨西哥
• 巴西
• 阿根廷

第 15 章歐洲、中東和非洲自動內容識別市場

• 英國
• 德國
• 法國
• 俄羅斯
• 義大利
• 西班牙
• 阿拉伯聯合大公國
• 沙烏地阿拉伯
• 南非
• 丹麥
• 荷蘭
• 卡達
• 芬蘭
• 瑞典
• 奈及利亞
• 埃及
• 土耳其
• 以色列
• 挪威
• 波蘭
• 瑞士

第16章：亞太地區自動內容辨識市場

• 中國
• 印度
• 日本
• 澳洲
• 韓國
• 印尼
• 泰國
• 菲律賓
• 馬來西亞
• 新加坡
• 越南
• 台灣

第17章競爭格局

• 2024年市場佔有率分析
• 2024年FPNV定位矩陣
• 競爭分析
  • ACRCloud Limited
  • Amazon Web Services, Inc.
  • Apple Inc.
  • ArcSoft Corporation Limited.
  • Audible Magic Corporation
  • Beatgrid Media BV
  • Beatgrid Media BV
  • Clarifai Inc.
  • DataScouting
  • Digimarc Corporation
  • Google LLC by Alphabet, Inc.
  • Gracenote by Nielsen Holdings
  • International Business Machines Corporation
  • ivitec GmbH
  • Kudelski Group
  • Microsoft Corporation
  • Oracle Corporation
  • Samba TV, Inc.
  • Valossa Labs Ltd.
  • Verbit Inc.
  • Viscovery Pte Ltd
  • VoiceBase, Inc.
  • VoiceInteraction
  • Zapr Media Labs
  • Gameopedia AS

第18章 研究人工智慧

第19章 研究統計

第20章 研究聯絡人

第21章 研究報導

第22章 附錄

The Automatic Content Recognition Market was valued at USD 3.84 billion in 2024 and is projected to grow to USD 4.45 billion in 2025, with a CAGR of 16.50%, reaching USD 9.62 billion by 2030.

KEY MARKET STATISTICS
Base Year [2024]	USD 3.84 billion
Estimated Year [2025]	USD 4.45 billion
Forecast Year [2030]	USD 9.62 billion
CAGR (%)	16.50%

Introducing the New Era of Automatic Content Recognition: Catalyzing Media Intelligence and Audience Engagement in Dynamic Digital Ecosystems

The march of digital transformation and the relentless expansion of streaming services have propelled automatic content recognition into the forefront of media intelligence. Stakeholders across advertising, measurement, and content delivery are leveraging ACR to harness real-time identification of audio, video, and broadcast signals. By embedding ACR capabilities into connected devices and OTT platforms, providers can deliver personalized experiences and gain granular insights into consumer behavior. Furthermore, the integration of advanced algorithms for fingerprinting and watermarking has augmented the precision of identification, paving the way for sophisticated analytics and targeted monetization strategies.

As market dynamics evolve, the interplay between software solutions and professional services is shaping new partnership models. Consulting firms are guiding enterprises through the complexities of system integration and maintenance, while specialized software vendors continue to advance optical character recognition and speech recognition modules. This synergy underpins the operational scalability and performance reliability demanded by global media enterprises.

Moreover, industry-specific deployments within automotive, consumer electronics, and retail environments are extending ACR beyond traditional media. Smart TVs integrated into connected vehicles and in-store digital signage leverage fingerprinting and watermarking to deliver contextually relevant content and verify authenticity. Concurrently, evolving data privacy regulations are driving the adoption of privacy-centric architectures and consent management protocols. Through this interplay of innovation and compliance, automatic content recognition is solidifying its role as the linchpin for future media ecosystems

Unveiling Transformative Shifts Reshaping Automatic Content Recognition: Innovations, Partnerships, and Regulatory Dynamics Redefining Market Trajectory

In recent years, the ACR landscape has been reshaped by breakthroughs in artificial intelligence and edge computing. Deep learning models for audio and video fingerprinting now deliver sub-second recognition with unparalleled accuracy, while cloud-based watermarking services ensure resilient detection across diverse streaming environments. The rollout of 5G networks has further accelerated these capabilities by reducing latency and enabling real-time delivery of enriched metadata to downstream analytics systems. As a result, service providers can now orchestrate dynamic content targeting based on live context, elevating audience engagement to new heights.

Strategic alliances between semiconductor manufacturers, software vendors, and media conglomerates are fostering end-to-end ACR solutions optimized for various hardware platforms. This convergence has given rise to modular toolkits that streamline integration and expedite deployment cycles. System integrators and maintenance partners play a pivotal role in customizing these solutions for enterprise-scale operations, ensuring that evolving performance demands are consistently met.

Simultaneously, tightening data privacy regulations and heightened consumer expectations have driven the development of privacy-first frameworks. Techniques such as on-device processing and anonymized data aggregation are now standard, safeguarding user information without compromising recognition accuracy. Governance protocols and consent management platforms have emerged as integral components, enabling transparent control over data flows.

Looking ahead, the fusion of ACR with the Internet of Things promises to unlock untapped use cases in smart homes, connected vehicles, and public spaces. By seamlessly integrating recognition engines into networked sensors and displays, stakeholders can derive actionable intelligence from ambient media interactions, heralding a new era of contextual content delivery

Assessing the Cumulative Impact of United States Tariffs 2025 on Automatic Content Recognition: Supply Chain, Cost Structures, and Competitive Advantages

The imposition of new tariffs on imported hardware and specialized components by the United States in 2025 has introduced significant complexities for automatic content recognition providers and their supply chains. Key sensor modules, digital signal processors, and proprietary semiconductor chips now incur increased import duties, contributing to elevated production costs. Consequently, original equipment manufacturers and platform vendors face pressure to reassess procurement strategies and identify cost-effective alternatives.

In parallel, software licensing and cross-border service agreements have been affected by revised trade regulations. Service providers delivering integration and maintenance contracts with on-site hardware support are encountering higher logistical expenses due to adjustments in customs protocols. These cumulative tariff pressures have led to a reevaluation of global distribution networks, prompting several vendors to consider local manufacturing partnerships and to accelerate technological substitution through software-driven architectures.

From a financial perspective, rising unit costs are gradually being transferred down the value chain, influencing end-user pricing for connected devices, smart televisions, and enterprise monitoring solutions. Buyers in telecommunications, media, and consumer electronics sectors are adapting budget allocations to accommodate these shifts, while vendors are exploring flexible pricing models, including subscription-based services, to mitigate the impact.

To sustain competitiveness, industry players are diversifying their supplier base and pursuing nearshoring initiatives. Collaborations with domestic foundries and regional integrators are gaining momentum as a means to circumvent tariff liabilities. This strategic realignment is fostering resilience across the ACR ecosystem and encouraging innovation in modular hardware design and cloud-centric platforms that minimize dependency on imported components

Unearthing Key Segmentation Insights in Automatic Content Recognition by Component, Technology, Content, Platform, Application, and Industry Vertical Drivers

Segmentation by component reveals a bifurcation between professional services and software offerings. Within professional services, the demand for consulting experts who architect ACR strategies, the integration teams tasked with embedding recognition engines into existing infrastructures, and maintenance specialists ensuring uninterrupted system performance has been rising in tandem with escalating deployment complexities. On the software side, turnkey fingerprinting and watermarking suites, cloud-hosted OCR engines, and speech recognition modules are increasingly packaged as developer-friendly APIs, empowering organizations to accelerate time to market.

When examining the market from a technological standpoint, providers are differentiating their value propositions around core capabilities such as audio and video fingerprinting, watermarking, optical character recognition, and speech-to-text conversion. These technologies underpin diverse use cases across multiple content types-ranging from streaming audio tracks and dynamic video environments to static images and text-based media assets-facilitating real-time indexing and automated metadata generation.

Insights into platform segmentation show that recognition engines are proliferating across connected devices, over-the-top streaming platforms, and smart television environments, each presenting unique performance and interoperability requirements. Meanwhile, application-level analysis emphasizes the critical role of recognition in advertisement targeting and pricing strategies, integrated marketing campaigns, audience measurement operations, broadcast monitoring workflows, content management systems, and copyright protection mechanisms. Across these applications, industry verticals such as automotive manufacturers embedding in-vehicle entertainment, consumer electronics makers, IT and telecommunications providers, media and entertainment networks, and retail and e-commerce enterprises are adopting ACR to drive personalization, compliance, and operational efficiency

Revealing Key Regional Insights and Growth Patterns in Automatic Content Recognition Across Americas, Europe Middle East Africa, and Asia Pacific Regions

As the Americas ecosystem continues to embrace digital transformation, the United States and Canada stand at the forefront of automatic content recognition adoption. Streaming giants, broadcasters, and advertising networks in these markets leverage real-time fingerprinting and watermarking to optimize dynamic ad insertion and monitor compliance with licensing agreements. Moreover, high television penetration rates have fueled demand for in-home set-top box and smart television implementations, while automotive infotainment systems incorporate recognition engines to deliver contextual audio experiences on the road.

Across Europe, the Middle East, and Africa, market growth is driven by a complex interplay of regulatory frameworks and diverse consumer preferences. Western European nations prioritize content protection and transparent audience measurement, prompting widespread deployment of OCR and watermarking services. Meanwhile, Middle Eastern broadcasters are investing in ACR to support live sports rights management and to combat unauthorized distribution. In Africa, entry-level deployments are emerging through partnerships between local telecommunications providers and global platform vendors, establishing foundational recognition capabilities in growing digital markets.

The Asia-Pacific region is witnessing rapid proliferation of connected devices and mobile-first content consumption, marking it as a key battleground for ACR innovation. In markets such as China, Japan, and India, streaming platforms and smart television manufacturers are integrating recognition modules to enhance user experiences and to monetize fragmented viewership through targeted advertising. Additionally, automotive OEMs and retail chains in the region are experimenting with in-store and in-car recognition use cases, underscoring the broad applicability of ACR technologies across diverse environments

Analyzing the Strategies and Innovations of Leading Companies Shaping the Future of Automatic Content Recognition in a Competitive Global Landscape

Several leading technology vendors and specialized service providers are charting the competitive landscape of automatic content recognition through differentiated innovation and strategic collaborations. Prominent metadata specialist Gracenote has been expanding its footprint by enhancing fingerprinting capabilities and securing partnerships with major original equipment manufacturers to embed recognition engines at the firmware level. Audible Magic has distinguished itself through a robust music identification platform that leverages extensive content databases to ensure comprehensive coverage across audio streaming services.

Simultaneously, Vobile has focused on enterprise-scale watermarking solutions, augmenting anti-piracy workflows for broadcasters and content owners. The emergence of cloud-native ACRCloud has introduced agile, API-driven offerings, while media intelligence leader Veritone has integrated machine learning workflows to support automated content classification across multiple formats. Google's deep investments in speech recognition and natural language processing are being leveraged to enrich advertising targeting on its streaming platforms, whereas IBM continues to develop hybrid cloud-centric architectures combining OCR and video analysis.

Moreover, Dolby Laboratories is driving the standardization of audio fingerprinting protocols to support immersive media experiences, and Shazam, now part of Apple, retains its brand recognition by extending mobile-first discovery features to smart home ecosystems. Collectively, these companies are pursuing growth through joint ventures, targeted acquisitions, and ongoing research into edge computing optimizations, signaling a robust competitive environment characterized by continuous technological advancement

Actionable Recommendations for Industry Leaders to Drive Competitive Advantage and Sustainable Growth in the Evolving Automatic Content Recognition Market

Industry leaders seeking to capitalize on the momentum of automatic content recognition should first prioritize the development of privacy-first architectures that enable on-device processing and decentralized data handling. By reducing reliance on centralized servers for fingerprinting and watermarking workloads, organizations can navigate tightening data protection regulations and enhance user trust. Additionally, forging strategic alliances with regional foundries and hardware vendors will mitigate exposure to tariff-driven supply chain disruptions and accelerate time to market through co-engineered solutions.

To deepen market penetration, firms should invest in comprehensive integration frameworks that unify OCR, speech recognition, and media fingerprinting modules under a single middleware layer. This approach simplifies deployment across connected devices, OTT platforms, and smart television environments, reducing operational complexity while delivering consistent performance. Moreover, engaging in collaborative research initiatives with academic institutions and industry consortia can foster breakthroughs in machine learning models, enabling finer granularity in content recognition and context-aware analytics.

It is also advisable to adopt flexible commercial models, including outcome-based contracts and subscription pricing, to align with evolving customer preferences and to share risk across the value chain. Finally, continuous talent development programs focused on ACR system engineering and data science competencies will equip organizations to adapt swiftly to emerging use cases in automotive, retail, and public sector environments. Collectively, these measures will position industry players to seize growth opportunities and to sustain competitive differentiation in the rapidly evolving ACR landscape

Robust Research Methodology Combining Primary Interviews, Secondary Data Analysis, and Advanced Triangulation Techniques for In-depth Market Insights

The research methodology underpinning this market analysis is anchored in a rigorous blend of secondary and primary data collection techniques. Initially, a comprehensive review of industry whitepapers, regulatory filings, patent databases, and corporate presentations was conducted to establish a foundational understanding of technological advancements and market dynamics. This phase incorporated global regulatory documents and cross-sector reports to ensure a balanced perspective on compliance frameworks and operational drivers.

Subsequently, in-depth interviews and workshops were held with C-suite executives, system integrators, technology architects, and end users across diverse verticals, including media and entertainment, automotive, and consumer electronics. These primary interactions provided nuanced insights into deployment challenges, performance benchmarks, and evolving use cases. Complementary surveys were administered to a broader set of stakeholders to quantify adoption trends and technology preferences.

Data triangulation processes were then applied to reconcile variances between secondary findings and primary feedback, resulting in a validated dataset that informs segmentation analysis by component, technology, content, platform, application, and industry vertical. Moreover, regional penetration patterns for the Americas, EMEA, and Asia-Pacific were assessed through market entry case studies and supply chain mapping exercises. Competitive benchmarking involved evaluating strategic initiatives, product portfolios, and financial disclosures of leading players. This multi-layered approach ensures the robustness and reliability of the insights presented

Concluding Perspectives on the Evolution of Automatic Content Recognition Highlighting Core Findings and Strategic Imperatives for Industry Stakeholders

As the automatic content recognition market continues to evolve, the convergence of advanced fingerprinting, watermarking, OCR, and speech recognition technologies is reshaping how content is identified, monetized, and protected. The intricate interplay between software vendors, system integrators, and professional services firms highlights the necessity for end-to-end partnerships that can address both technical complexity and regulatory compliance. Simultaneously, regional disparities in infrastructure maturity and regulatory frameworks underscore the importance of tailored deployment strategies.

Moreover, the cumulative impact of recent trade policies has reinforced the criticality of resilient supply chains and diversified sourcing models. Organizations that proactively adapt through localization initiatives and cloud-first architectures are better positioned to navigate cost fluctuations and to harness emerging opportunities in connected devices, OTT platforms, and smart television ecosystems. Insightful segmentation by component, technology, content format, application, and industry vertical provides a roadmap for targeted investments and innovative service offerings.

Ultimately, success in this dynamic environment will hinge on the ability to integrate privacy-centric designs, to leverage real-time analytics, and to foster agile commercial models. As stakeholders across advertising, media delivery, and enterprise monitoring seek to enhance audience engagement and operational efficiency, automatic content recognition stands as a pivotal enabler of next-generation media experiences and strategic growth trajectories

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Segmentation & Coverage
• 1.3. Years Considered for the Study
• 1.4. Currency & Pricing
• 1.5. Language
• 1.6. Stakeholders

2. Research Methodology

• 2.1. Define: Research Objective
• 2.2. Determine: Research Design
• 2.3. Prepare: Research Instrument
• 2.4. Collect: Data Source
• 2.5. Analyze: Data Interpretation
• 2.6. Formulate: Data Verification
• 2.7. Publish: Research Report
• 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

• 4.1. Introduction
• 4.2. Market Sizing & Forecasting

5. Market Dynamics

• 5.1. Integration of automatic content recognition engines with streaming analytics platforms for real-time audience measurement
• 5.2. Advancements in watermarking and fingerprinting techniques enhancing cross-device content identification and tracking
• 5.3. Deployment of artificial intelligence and machine learning models to improve automatic content recognition accuracy and speed
• 5.4. Expansion of automatic content recognition applications into retail environments for personalized in-store advertising and analytics
• 5.5. Rising demand for privacy-compliant data handling in automatic content recognition to address regulatory and consumer concerns
• 5.6. Collaboration between broadcasters and adtech firms leveraging ACR data for dynamic addressable television advertising optimization
• 5.7. Integration of automatic content recognition in smart home devices to enable voice-activated content discovery and personalization

6. Market Insights

• 6.1. Porter's Five Forces Analysis
• 6.2. PESTLE Analysis

7. Cumulative Impact of United States Tariffs 2025

8. Automatic Content Recognition Market, by Component

• 8.1. Introduction
• 8.2. Services
  • 8.2.1. Consulting Services
  • 8.2.2. Integration Services
  • 8.2.3. Maintenance Services
• 8.3. Software

9. Automatic Content Recognition Market, by Technology

• 9.1. Introduction
• 9.2. Audio & Video Fingerprinting
• 9.3. Audio & Video Watermarking
• 9.4. Optical Character Recognition (OCR)
• 9.5. Speech Recognition

10. Automatic Content Recognition Market, by Content

• 10.1. Introduction
• 10.2. Audio
• 10.3. Image
• 10.4. Text
• 10.5. Video

11. Automatic Content Recognition Market, by Platform

• 11.1. Introduction
• 11.2. Connected Devices
• 11.3. OTT Platforms
• 11.4. Smart TVs

12. Automatic Content Recognition Market, by Application

• 12.1. Introduction
• 12.2. Advertisement Targeting & Pricing
• 12.3. Advertising & Marketing
• 12.4. Audience Measurement
• 12.5. Broadcast Monitoring
• 12.6. Content Management
• 12.7. Copyright Protection

13. Automatic Content Recognition Market, by Industry Vertical

• 13.1. Introduction
• 13.2. Automotive
• 13.3. Consumer Electronics
• 13.4. IT & Telecommunication
• 13.5. Media & Entertainment
• 13.6. Retail & eCommerce

14. Americas Automatic Content Recognition Market

• 14.1. Introduction
• 14.2. United States
• 14.3. Canada
• 14.4. Mexico
• 14.5. Brazil
• 14.6. Argentina

15. Europe, Middle East & Africa Automatic Content Recognition Market

• 15.1. Introduction
• 15.2. United Kingdom
• 15.3. Germany
• 15.4. France
• 15.5. Russia
• 15.6. Italy
• 15.7. Spain
• 15.8. United Arab Emirates
• 15.9. Saudi Arabia
• 15.10. South Africa
• 15.11. Denmark
• 15.12. Netherlands
• 15.13. Qatar
• 15.14. Finland
• 15.15. Sweden
• 15.16. Nigeria
• 15.17. Egypt
• 15.18. Turkey
• 15.19. Israel
• 15.20. Norway
• 15.21. Poland
• 15.22. Switzerland

16. Asia-Pacific Automatic Content Recognition Market

• 16.1. Introduction
• 16.2. China
• 16.3. India
• 16.4. Japan
• 16.5. Australia
• 16.6. South Korea
• 16.7. Indonesia
• 16.8. Thailand
• 16.9. Philippines
• 16.10. Malaysia
• 16.11. Singapore
• 16.12. Vietnam
• 16.13. Taiwan

17. Competitive Landscape

• 17.1. Market Share Analysis, 2024
• 17.2. FPNV Positioning Matrix, 2024
• 17.3. Competitive Analysis
  • 17.3.1. ACRCloud Limited
  • 17.3.2. Amazon Web Services, Inc.
  • 17.3.3. Apple Inc.
  • 17.3.4. ArcSoft Corporation Limited.
  • 17.3.5. Audible Magic Corporation
  • 17.3.6. Beatgrid Media B.V.
  • 17.3.7. Beatgrid Media BV
  • 17.3.8. Clarifai Inc.
  • 17.3.9. DataScouting
  • 17.3.10. Digimarc Corporation
  • 17.3.11. Google LLC by Alphabet, Inc.
  • 17.3.12. Gracenote by Nielsen Holdings
  • 17.3.13. International Business Machines Corporation
  • 17.3.14. ivitec GmbH
  • 17.3.15. Kudelski Group
  • 17.3.16. Microsoft Corporation
  • 17.3.17. Oracle Corporation
  • 17.3.18. Samba TV, Inc.
  • 17.3.19. Valossa Labs Ltd.
  • 17.3.20. Verbit Inc.
  • 17.3.21. Viscovery Pte Ltd
  • 17.3.22. VoiceBase, Inc.
  • 17.3.23. VoiceInteraction
  • 17.3.24. Zapr Media Labs
  • 17.3.25. Gameopedia AS

18. ResearchAI

19. ResearchStatistics

20. ResearchContacts

21. ResearchArticles

22. Appendix