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行銷市場中的人工智慧 - 全球產業規模、佔有率、趨勢、機會和預測，按產品、部署類型、技術、按應用、最終用戶產業、地區和競爭細分，2018-2028 年
市場調查報告書
商品編碼
1379565

行銷市場中的人工智慧 - 全球產業規模、佔有率、趨勢、機會和預測，按產品、部署類型、技術、按應用、最終用戶產業、地區和競爭細分，2018-2028 年

Artificial Intelligence in Marketing Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Offering, By Deployment Type, By Technology, By Application, By End User Industry, By Region, and By Competition, 2018-2028
出版日期: | 出版商: TechSci Research | 英文 171 Pages | 商品交期: 2-3個工作天內

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簡介目錄

隨著組織越來越認知到人工智慧技術徹底改變其行銷工作的潛力，全球行銷市場中的人工智慧正在經歷顯著的成長和轉型。行銷中的人工智慧涵蓋了廣泛的應用，從資料分析和客戶細分到個人化內容推薦和預測分析。

人工智慧在行銷領域發展的關鍵驅動力之一是其利用大量資料並提取可行見解的能力。人工智慧驅動的工具可以以前所未有的規模和速度分析客戶行為、偏好和互動，使行銷人員能夠做出數據驅動的決策。這會帶來更有效、更有針對性的行銷活動，與客戶產生共鳴。

個人化是人工智慧在行銷的另一個關鍵面向。人工智慧演算法可以根據個人消費者的歷史互動和偏好，為他們量身定做行銷訊息、產品推薦和廣告。這種程度的個人化增強了客戶參與度，提高了轉換率，並最終推動收入成長。

市場概況
預測期 2024-2028
2022 年市場規模 106.7億美元
2028 年市場規模 442.5億美元
2023-2028 年CAGR 25.78%
成長最快的細分市場 雲
最大的市場 北美洲

由人工智慧支援的預測分析使行銷人員能夠預測未來趨勢和客戶行為，使他們能夠主動調整策略並在競爭中保持領先地位。行銷自動化、聊天機器人和虛擬助理正在成為客戶服務和參與的一部分，提供 24/7 支援並改善客戶體驗。

主要市場促進因素

增強的個人化和客戶參與度：

人工智慧 (AI) 是行銷工作日益個人化的驅動力。人工智慧演算法可以分析大量資料集，以了解個人客戶的偏好、行為和購買歷史。這種數據驅動的方法使行銷人員能夠向消費者提供高度個人化的內容、產品推薦和廣告。增強的個人化可以提高客戶參與度，因為消費者更有可能與與其興趣產生共鳴的內容互動並做出積極回應。因此，人工智慧驅動的個人化是轉換率、客戶忠誠度和品牌親和力的強大驅動力。

數據驅動的決策：

人工智慧使行銷人員能夠以以前無法達到的規模和速度做出數據驅動的決策。機器學習演算法可以分析大量行銷資料，包括客戶互動、網站流量和活動績效。透過識別這些資料中的模式和趨勢，人工智慧使行銷人員能夠最佳化行銷策略，有效分配資源，並以正確的訊息瞄準正確的受眾。數據驅動的決策不僅可以提高行銷投資報酬率，還可以提供有價值的見解，為長期行銷策略提供資訊。

重複任務的自動化：

人工智慧驅動的行銷自動化是效率和生產力的主要驅動力。行銷人員可以自動化日常任務，例如電子郵件行銷、社群媒體發布和廣告活動管理。由人工智慧支援的聊天機器人和虛擬助理可以處理客戶詢問並提供即時支援。透過自動化這些流程，行銷人員可以騰出時間和資源，專注於行銷活動中更具策略性和創造性的方面。自動化還確保訊息傳遞的一致性並降低人為錯誤的風險。

改善客戶體驗：

人工智慧在增強整體客戶體驗方面發揮關鍵作用。聊天機器人和虛擬助理提供 24/7 客戶支持，及時解決查詢和問題。人工智慧驅動的推薦引擎推薦符合個人客戶偏好的產品和服務，促進無縫交叉銷售和追加銷售。此外，人工智慧可以分析客戶回饋和情緒，以確定產品或服務需要改進的領域。透過根據人工智慧洞察優先考慮客戶體驗改進，組織可以建立更牢固的客戶關係並提高品牌忠誠度。

即時分析與最佳化：

人工智慧使行銷人員能夠存取即時分析和最佳化功能。機器學習演算法可以持續分析產生的資料，使行銷人員能夠立即調整行銷活動和策略。例如，人工智慧可以根據即時效果資料調整廣告競價策略，以最大限度地提高投資報酬率。即時分析還可以洞察消費者行為，使行銷人員能夠即時回應趨勢和新出現的機會。這種敏捷性和回應能力在當今快節奏的行銷環境中至關重要。

主要市場挑戰

資料隱私和合規性：

行銷市場中的人工智慧面臨的最重大挑戰之一是資料隱私和合規性的複雜情況。由於人工智慧演算法依賴大量資料來做出明智的決策和個人化行銷工作，因此公司必須了解一系列法規，包括《一般資料保護規範》(GDPR) 和《加州消費者隱私法案》(CCPA)。確保遵守這些法規，同時有效利用客戶資料進行行銷目的是一個微妙的平衡。違規行為可能會導致嚴厲的罰款並損害品牌聲譽，從而使資料隱私成為行銷人員面臨的首要挑戰。

道德問題和偏見：

行銷中圍繞人工智慧的道德考量越來越受到重視。人工智慧演算法可能導致偏見、歧視或意外後果長期存在，這是一個值得關注的問題。例如，有偏見的演算法可能會向某些人口群體提供歧視性廣告或推薦。解決這些道德挑戰需要開發公平、透明且無偏見的人工智慧模型。此外，公司必須制定人工智慧使用道德準則，並確保持續監控和審計，以防止道德違規。

數據品質和可訪問性：

人工智慧模型在很大程度上依賴資料的品質和可訪問性。不準確或不完整的資料可能會導致錯誤的預測和低於標準的行銷工作。確保資料品質涉及資料清理和預處理，這可能非常耗時且佔用資源。此外，並非所有組織都能獲得訓練有效人工智慧模型所需的大量高品質資料。較小的公司和新創公司可能在獲取和管理人工智慧驅動的行銷計劃所需的資料方面面臨挑戰。

人才短缺和技能差距：

行銷領域對人工智慧專業知識的需求遠遠超過熟練專業人員的供應。尋找並留住人工智慧專家、資料科學家和機器學習工程師是組織面臨的重大挑戰。人工智慧領域正在迅速發展，公司必須不斷投資於培訓和開發，以使其團隊掌握最新技術和最佳實踐。此外，對頂尖人工智慧人才的競爭推高了薪資和招募成本，使一些組織難以組建有能力的團隊。

與遺留系統整合：

許多組織擁有遺留的 IT 系統和行銷技術，這些系統和行銷技術最初並不是為適應人工智慧而設計的。將人工智慧整合到這些現有系統中可能非常複雜且成本高昂。相容性問題、資料遷移挑戰以及對額外基礎設施的需求可能會阻礙人工智慧在行銷中的無縫採用。實現全面整合通常需要策略方法以及投資技術升級和現代化工作的意願。

主要市場趨勢

超個性化和以客戶為中心：

超個人化是全球人工智慧行銷市場的一個重要趨勢。隨著消費者被資訊和選擇淹沒，行銷人員擴大轉向人工智慧來創造高度個人化的體驗。人工智慧演算法分析大量客戶資料，以了解偏好、行為和人口統計數據，從而提供量身定做的內容、推薦和廣告。這種程度的個人化不僅可以提高客戶參與度，還可以提高轉換率和品牌忠誠度。此外，人工智慧驅動的聊天機器人和虛擬助理提供即時幫助，進一步增強以客戶為中心的能力。

預測分析與預測：

由人工智慧支援的預測分析正在改變行銷策略。行銷人員正在利用機器學習演算法來預測未來趨勢、客戶行為和市場需求。這種數據驅動的方法可以幫助組織有效地分配資源、最佳化定價策略並預測消費者偏好的變化。透過準確預測市場動態，人工智慧使行銷人員能夠在競爭中保持領先並做出明智的決策，最終提高投資回報。

人工智慧增強的內容創作：

人工智慧正在徹底改變內容創建和行銷自動化。自然語言處理 (NLP) 和生成對抗網路 (GAN) 使人工智慧能夠生成高品質的、類似人類的內容，包括文章、產品描述和社交媒體貼文。人工智慧產生的內容可以針對不同的受眾和平台進行客製化，為行銷人員節省時間和資源。此外，人工智慧驅動的工具可以分析內容效能，為最佳化未來內容策略提供見解。這種趨勢簡化了內容行銷工作，增強了一致性並確保了相關性。

語音和視覺搜尋最佳化：

Siri、Alexa 和 Google Assistant 等聲控虛擬助理的興起帶動了語音搜尋的成長。同樣，視覺搜尋（使用者可以使用圖像搜尋產品或資訊）也越來越受歡迎。人工智慧在最佳化這些新興搜尋方法的網站和內容方面發揮關鍵作用。行銷人員正在調整他們的 SEO 策略來解決語音和視覺搜尋查詢，因為他們需要不同的關鍵字最佳化和內容格式。人工智慧驅動的圖像辨識和語音辨識技術正在融入電子商務平台，使消費者更容易找到和購買產品。

道德人工智慧和透明度：

道德人工智慧正成為行銷產業的一個重要考慮因素。由於人工智慧演算法影響決策過程和消費者互動，因此透明度和問責制至關重要。行銷人員越來越關注負責任的人工智慧實踐，確保人工智慧驅動的行銷活動沒有偏見並遵守道德準則。這包括解決與資料隱私、同意和公平使用相關的問題。各組織也努力透明地傳達他們的人工智慧實踐，以建立與消費者的信任。監管機構開始對人工智慧道德製定指導方針，這使得行銷人員必須採用符合道德的人工智慧實踐並提高營運透明度。

細分市場洞察

提供見解

到 2022 年，軟體領域將在全球人工智慧行銷市場中佔據主導地位。人工智慧驅動的軟體工具擅長快速、準確地處理和分析大量資料。行銷人員依靠這些解決方案從客戶行為、偏好和互動中提取有價值的見解。透過利用人工智慧軟體，企業可以更深入地了解目標受眾並做出數據驅動的決策，從而進行更有效的行銷活動。

人工智慧軟體的突出特點之一是能夠向個人消費者大規模提供高度個人化的行銷內容和建議。人工智慧演算法分析客戶資料，根據每個客戶的獨特偏好和歷史客製化訊息、產品建議和優惠。這種程度的個人化增強了客戶參與度並增加了轉換的可能性。

人工智慧驅動的軟體擅長預測分析，根據歷史資料預測未來趨勢和消費者行為。行銷人員依靠預測分析來預測客戶需求和趨勢，使他們能夠主動調整行銷策略。這種預測能力使企業能夠在競爭中保持領先地位並快速回應市場變化。

部署類型見解

到 2022 年，雲端細分市場將在全球人工智慧行銷市場中佔據主導地位。基於雲端的人工智慧行銷解決方案提供無與倫比的可擴展性，使企業能夠擴展業務並無縫適應不斷變化的需求。無論公司的行銷需求是快速成長還是季節性波動，雲端都可以靈活地根據需要擴展或縮減資源。

雲端部署消除了對硬體和基礎設施進行大量前期投資的需求。相反，企業可以以即用即付或訂閱的方式訂閱雲端服務，從而減少資本支出。這種經濟高效的模式使人工智慧行銷工具的使用變得民主化，使各種規模的組織都可以使用它們。

與本地替代方案相比，基於雲端的人工智慧行銷解決方案可以快速部署。實施通常涉及配置軟體設定並與現有系統整合，從而使企業能夠開始利用人工智慧功能，而無需延長設定時間。

基於雲端的平台可以透過網路連線從任何地方訪問，促進行銷團隊之間的遠端工作和協作。團隊成員可以協作開展活動、分析資料並存取人工智慧工具，而無需局限於實體辦公地點。

區域洞察

北美在2022年全球人工智慧行銷市場中佔據主導地位。北美，特別是美國，是全球技術創新和研究中心。加州的矽谷是一些世界上最大的科技公司和新創企業的所在地。這些公司一直處於開發人工智慧技術的前沿，並積極將人工智慧融入行銷實踐。他們的創新為全球行銷中人工智慧的採用奠定了基礎。

北美的風險投資和投資機會推動了人工智慧新創公司和計劃的發展。該地區為人工智慧驅動的行銷企業吸引了大量資金，使這些企業能夠開發和擴展其解決方案。這種資金支持使北美公司在人工智慧行銷技術方面具有競爭優勢。

北美培育了豐富的人工智慧研究機構、大學和智庫生態系統。這些機構與私營部門密切合作，共享知識和資源以推動人工智慧技術。這種協作環境創造了人工智慧人才和專業知識的穩定流動，推動了行銷應用的創新。

北美龐大且多樣化的消費者群體對人工智慧驅動的行銷解決方案產生了巨大的需求。該地區的企業熱衷於利用人工智慧，透過個人化客戶體驗、最佳化廣告活動和提高行銷投資回報率來獲得競爭優勢。這種需求刺激了人工智慧行銷工具的開發和採用。

目錄

第 1 章：服務概述

  • 市場定義
  • 市場範圍
    • 涵蓋的市場
    • 研究年份
    • 主要市場區隔

第 2 章：研究方法

  • 基線方法
  • 主要產業夥伴
  • 主要協會和二手資料來源
  • 預測方法
  • 數據三角測量與驗證
  • 假設和限制

第 3 章：執行摘要

第 4 章：COVID-19 對全球人工智慧行銷市場的影響

第 5 章：客戶之聲

第 6 章：全球人工智慧行銷市場概述

第 7 章：全球人工智慧行銷市場展望

  • 市場規模及預測
    • 按價值
  • 市佔率及預測
    • 依產品提供（硬體、軟體、服務）
    • 依部署類型（雲端、本機）
    • 依技術分類（機器學習、情境感知計算、自然語言處理、電腦視覺）
    • 按應用（社群媒體廣告、搜尋廣告、內容規劃、銷售行銷自動化、分析平台等）
    • 按最終用戶產業（BFSI、零售、消費品、媒體娛樂、企業、其他）
    • 按地區（北美、歐洲、南美、中東和非洲、亞太地區）
  • 按公司分類 (2022)
  • 市場地圖

第 8 章：北美人工智慧行銷市場展望

  • 市場規模及預測
    • 按價值
  • 市佔率及預測
    • 透過提供
    • 依部署類型
    • 依技術
    • 按應用
    • 按最終用戶產業
    • 按國家/地區

第 9 章：歐洲人工智慧行銷市場展望

  • 市場規模及預測
    • 按價值
  • 市佔率及預測
    • 依產品類型
    • 按電源類型
    • 按提升高度
    • 按應用
    • 按國家/地區

第10章 ：南美洲人工智慧行銷市場展望

  • 市場規模及預測
    • 按價值
  • 市佔率及預測
    • 依產品類型
    • 按電源類型
    • 按提升高度
    • 按應用
    • 按國家/地區

第 11 章：中東和非洲人工智慧行銷市場展望

  • 市場規模及預測
    • 按價值
  • 市佔率及預測
    • 依產品類型
    • 按電源類型
    • 按提升高度
    • 按應用
    • 按國家/地區

第12章：亞太地區人工智慧行銷市場展望

  • 市場規模及預測
    • 按價值
  • 市場規模及預測
    • 透過提供
    • 依部署類型
    • 依技術
    • 按應用
    • 按最終用戶產業
    • 按國家/地區

第 13 章：市場動態

  • 促進要素
  • 挑戰

第 14 章：市場趨勢與發展

第 15 章：公司簡介

  • 奧多比公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services Offered
  • 字母公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services Offered
  • 亞馬遜網路服務公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services Offered
  • IBM公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services Offered
  • 微軟公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services Offered
  • Salesforce.com 公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services Offered
  • SAS 研究所公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services Offered
  • 天睿公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services Offered
  • 甲骨文公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services Offered
  • SAP系統公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services Offered

第 16 章：策略建議

第 17 章：關於我們與免責聲明

簡介目錄
Product Code: 17043

The global Artificial Intelligence in Marketing market is experiencing remarkable growth and transformation as organizations increasingly recognize the potential of AI technologies to revolutionize their marketing efforts. AI in marketing encompasses a broad spectrum of applications, from data analysis and customer segmentation to personalized content recommendations and predictive analytics.

One of the key drivers behind the growth of AI in marketing is its ability to harness vast amounts of data and extract actionable insights. AI-powered tools can analyze customer behavior, preferences, and interactions at an unprecedented scale and speed, enabling marketers to make data-driven decisions. This leads to more effective and targeted marketing campaigns that resonate with customers.

Personalization is another pivotal aspect of AI in marketing. AI algorithms can tailor marketing messages, product recommendations, and advertisements to individual consumers based on their historical interactions and preferences. This level of personalization enhances customer engagement, boosts conversion rates, and ultimately drives revenue growth.

Market Overview
Forecast Period2024-2028
Market Size 2022USD 10.67 Billion
Market Size 2028USD 44.25 Billion
CAGR 2023-202825.78%
Fastest Growing SegmentCloud
Largest MarketNorth America

Predictive analytics, powered by AI, empowers marketers to anticipate future trends and customer behavior, enabling them to proactively adjust strategies and stay ahead of the competition. Marketing automation, chatbots, and virtual assistants are becoming integral to customer service and engagement, providing 24/7 support and improving customer experiences.

Content generation and optimization, facilitated by AI, help businesses produce high-quality, relevant content efficiently, enhancing their online presence and SEO rankings. Real-time insights enable marketers to monitor campaign performance and make instant adjustments for optimal results.

The market is primarily dominated by cloud-based deployment models due to their scalability, cost-efficiency, accessibility, and integration capabilities. Furthermore, leading cloud providers offer a wide array of AI services that empower businesses to harness advanced AI capabilities for marketing purposes.

As the global AI in Marketing market continues to evolve, businesses across industries are expected to increasingly adopt AI technologies to gain a competitive edge, enhance customer engagement, and achieve greater ROI on their marketing investments. This market promises innovation and disruption, with AI at the forefront of the marketing landscape's future.

Key Market Drivers

Enhanced Personalization and Customer Engagement:

Artificial Intelligence (AI) is a driving force behind the increasing personalization of marketing efforts. AI algorithms can analyze vast datasets to understand individual customer preferences, behaviors, and purchase histories. This data-driven approach enables marketers to deliver highly personalized content, product recommendations, and advertisements to consumers. Enhanced personalization leads to higher customer engagement, as consumers are more likely to interact with and respond positively to content that resonates with their interests. As a result, AI-powered personalization is a powerful driver of conversion rates, customer loyalty, and brand affinity.

Data-Driven Decision-Making:

AI empowers marketers with the ability to make data-driven decisions at a scale and speed that was previously unattainable. Machine learning algorithms can analyze massive amounts of marketing data, including customer interactions, website traffic, and campaign performance. By identifying patterns and trends within this data, AI enables marketers to optimize marketing strategies, allocate resources effectively, and target the right audience with the right message. Data-driven decision-making not only enhances marketing ROI but also provides valuable insights that inform long-term marketing strategies.

Automation of Repetitive Tasks:

AI-driven marketing automation is a major driver of efficiency and productivity. Marketers can automate routine tasks such as email marketing, social media posting, and ad campaign management. Chatbots and virtual assistants powered by AI can handle customer inquiries and provide real-time support. By automating these processes, marketers can free up time and resources to focus on more strategic and creative aspects of their campaigns. Automation also ensures consistency in messaging and reduces the risk of human error.

Improved Customer Experience:

AI plays a pivotal role in enhancing the overall customer experience. Chatbots and virtual assistants provide 24/7 customer support, resolving inquiries and issues promptly. AI-driven recommendation engines suggest products and services that align with individual customer preferences, facilitating seamless cross-selling and upselling. Additionally, AI can analyze customer feedback and sentiment to identify areas for improvement in products or services. By prioritizing customer experience improvements based on AI insights, organizations can build stronger customer relationships and drive brand loyalty.

Real-Time Analytics and Optimization:

AI enables marketers to access real-time analytics and optimization capabilities. Machine learning algorithms can continuously analyze data as it is generated, allowing marketers to make immediate adjustments to campaigns and strategies. For example, AI can adjust ad bidding strategies based on real-time performance data to maximize ROI. Real-time analytics also provide insights into consumer behavior as it happens, enabling marketers to respond to trends and emerging opportunities in real time. This agility and responsiveness are crucial in today's fast-paced marketing landscape.

Key Market Challenges

Data Privacy and Compliance:

One of the most significant challenges facing the AI in Marketing market is the complex landscape of data privacy and compliance. As AI algorithms rely on vast amounts of data to make informed decisions and personalize marketing efforts, companies must navigate a web of regulations, including the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Ensuring compliance with these regulations while effectively utilizing customer data for marketing purposes is a delicate balance. Violations can result in severe fines and damage to a brand's reputation, making data privacy a top challenge for marketers.

Ethical Concerns and Bias:

Ethical considerations surrounding AI in marketing are gaining prominence. The potential for AI algorithms to perpetuate bias, discrimination, or unintended consequences is a significant concern. For example, biased algorithms may deliver discriminatory advertisements or recommendations to certain demographic groups. Addressing these ethical challenges involves developing AI models that are fair, transparent, and free from bias. Additionally, companies must establish guidelines for ethical AI use and ensure ongoing monitoring and audits to prevent ethical breaches.

Data Quality and Accessibility:

AI models rely heavily on the quality and accessibility of data. Inaccurate or incomplete data can lead to erroneous predictions and subpar marketing efforts. Ensuring data quality involves cleaning and pre-processing data, which can be time-consuming and resource-intensive. Moreover, not all organizations have access to the vast amounts of high-quality data required to train effective AI models. Smaller companies and startups may face challenges in acquiring and managing the necessary data for AI-driven marketing initiatives.

Talent Shortages and Skill Gaps:

The demand for AI expertise in marketing far exceeds the supply of skilled professionals. Finding and retaining AI specialists, data scientists, and machine learning engineers is a major challenge for organizations. The AI field is rapidly evolving, and companies must continually invest in training and development to keep their teams up to date with the latest technologies and best practices. Additionally, competition for top AI talent has driven up salaries and hiring costs, making it challenging for some organizations to assemble capable teams.

Integration with Legacy Systems:

Many organizations have legacy IT systems and marketing technologies that were not originally designed to accommodate AI. Integrating AI into these existing systems can be complex and costly. Compatibility issues, data migration challenges, and the need for additional infrastructure can hinder the seamless adoption of AI in marketing. Achieving full integration often requires a strategic approach and a willingness to invest in technology upgrades and modernization efforts.

Key Market Trends

Hyper-Personalization and Customer-Centricity:

Hyper-personalization is a significant trend in the global AI in Marketing market. As consumers are inundated with information and choices, marketers are increasingly turning to AI to create highly personalized experiences. AI algorithms analyze vast amounts of customer data to understand preferences, behaviors, and demographics, enabling the delivery of tailor-made content, recommendations, and advertisements. This level of personalization not only enhances customer engagement but also drives conversion rates and brand loyalty. Moreover, AI-driven chatbots and virtual assistants provide real-time assistance, further enhancing customer-centricity.

Predictive Analytics and Forecasting:

Predictive analytics powered by AI is transforming marketing strategies. Marketers are leveraging machine learning algorithms to forecast future trends, customer behavior, and market demand. This data-driven approach helps organizations allocate resources effectively, optimize pricing strategies, and anticipate shifts in consumer preferences. By accurately predicting market dynamics, AI enables marketers to stay ahead of the competition and make informed decisions, ultimately leading to improved ROI.

AI-Enhanced Content Creation:

AI is revolutionizing content creation and marketing automation. Natural Language Processing (NLP) and Generative Adversarial Networks (GANs) enable AI to generate high-quality, human-like content, including articles, product descriptions, and social media posts. Content generated by AI can be customized for different audiences and platforms, saving time and resources for marketers. Additionally, AI-powered tools analyze content performance, providing insights for optimizing future content strategies. This trend streamlines content marketing efforts, enhances consistency, and ensures relevance.

Voice and Visual Search Optimization:

The rise of voice-activated virtual assistants like Siri, Alexa, and Google Assistant has led to the growth of voice search. Similarly, visual search, where users can search for products or information using images, is gaining traction. AI plays a pivotal role in optimizing websites and content for these emerging search methods. Marketers are adapting their SEO strategies to account for voice and visual search queries, as they require different keyword optimization and content formats. AI-driven image recognition and voice recognition technologies are being integrated into e-commerce platforms, making it easier for consumers to find and purchase products.

Ethical AI and Transparency:

Ethical AI is becoming a critical consideration in the marketing industry. As AI algorithms influence decision-making processes and consumer interactions, transparency and accountability are paramount. Marketers are increasingly focusing on responsible AI practices, ensuring that AI-driven campaigns are devoid of bias and adhere to ethical guidelines. This includes addressing issues related to data privacy, consent, and fair usage. Organizations are also making efforts to communicate their AI practices transparently to build trust with consumers. Regulatory bodies are beginning to impose guidelines on AI ethics, making it essential for marketers to adopt ethical AI practices and foster transparency in their operations.

Segmental Insights

Offering Insights

Software segment dominates in the global Artificial Intelligence in Marketing market in 2022. AI-powered software tools excel in processing and analyzing vast amounts of data quickly and accurately. Marketers rely on these solutions to extract valuable insights from customer behavior, preferences, and interactions. By leveraging AI software, businesses can gain a deeper understanding of their target audience and make data-driven decisions, resulting in more effective marketing campaigns.

One of the standout features of AI software is its ability to deliver highly personalized marketing content and recommendations to individual consumers at scale. AI algorithms analyze customer data to tailor messages, product suggestions, and offers to each customer's unique preferences and history. This level of personalization enhances customer engagement and increases the likelihood of conversions.

AI-driven software excels in predictive analytics, forecasting future trends and consumer behaviors based on historical data. Marketers rely on predictive analytics to anticipate customer needs and trends, enabling them to proactively adjust their marketing strategies. This predictive capability allows businesses to stay ahead of the competition and respond to market changes swiftly.

Deployment Type Insights

Cloud segment dominates in the global Artificial Intelligence in Marketing market in 2022. Cloud-based AI marketing solutions offer unmatched scalability, allowing businesses to expand their operations and adapt to changing demands seamlessly. Whether a company experiences rapid growth or seasonal fluctuations in marketing needs, the cloud provides the flexibility to scale resources up or down as required.

Cloud deployment eliminates the need for extensive upfront investments in hardware and infrastructure. Instead, businesses can subscribe to cloud services on a pay-as-you-go or subscription basis, reducing capital expenses. This cost-efficient model democratizes access to AI marketing tools, making them accessible to organizations of all sizes.

Cloud-based AI marketing solutions can be deployed quickly compared to on-premises alternatives. Implementation typically involves configuring software settings and integrating with existing systems, allowing businesses to start leveraging AI capabilities without extended setup times.

Cloud-based platforms are accessible from anywhere with an internet connection, facilitating remote work and collaboration among marketing teams. Team members can collaborate on campaigns, analyze data, and access AI tools without being tethered to a physical office location.

Regional Insights

North America dominates the Global Artificial Intelligence in Marketing Market in 2022. North America, particularly the United States, is a global hub for technological innovation and research. Silicon Valley, in California, is home to some of the world's largest tech companies and startups. These companies have been at the forefront of developing AI technologies and have actively integrated AI into marketing practices. Their innovation has set the pace for AI adoption in marketing across the globe.

The availability of venture capital and investment opportunities in North America has fueled AI startups and initiatives. The region attracts substantial funding for AI-driven marketing ventures, enabling these businesses to develop and scale their solutions. This financial support has given North American companies a competitive edge in AI marketing technology.

North America has fostered a rich ecosystem of AI research institutions, universities, and think tanks. These institutions collaborate closely with the private sector, sharing knowledge and resources to advance AI technologies. This collaborative environment has created a steady flow of AI talent and expertise, driving innovation in marketing applications.

North America's large and diverse consumer base has created substantial demand for AI-driven marketing solutions. Businesses in the region are keen to leverage AI to gain a competitive advantage by personalizing customer experiences, optimizing advertising campaigns, and improving marketing ROI. This demand has incentivized the development and adoption of AI marketing tools.

Key Market Players

  • Adobe Inc.
  • Alphabet Inc.
  • Amazon Web Services, Inc.
  • IBM Corporation
  • Microsoft Corporation
  • Salesforce.com, Inc.
  • SAS Institute Inc.
  • Teradata Corporation
  • Oracle Corporation
  • SAP SE

Report Scope:

In this report, the Global Artificial Intelligence in Marketing Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Artificial Intelligence in Marketing Market, By Offering:

  • Hardware
  • Software
  • Services

Artificial Intelligence in Marketing Market, By Deployment Type:

  • Cloud
  • On Premises

Artificial Intelligence in Marketing Market, By Technology:

  • Machine Learning
  • Context-Aware Computing
  • Natural Language Processing
  • Computer Vision

Artificial Intelligence in Marketing Market, By Application:

  • Social Media Advertising
  • Search Advertising
  • Content Curation
  • Sales Marketing Automation
  • Analytics Platform
  • Others

Artificial Intelligence in Marketing Market, By End User Industry:

  • BFSI
  • Retail
  • Consumer Goods
  • Media Entertainment
  • Enterprise
  • Others

Artificial Intelligence in Marketing Market, By Region:

  • North America
  • United States
  • Canada
  • Mexico
  • Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
  • South America
  • Brazil
  • Argentina
  • Colombia
  • Asia-Pacific
  • China
  • India
  • Japan
  • South Korea
  • Australia
  • Middle East & Africa
  • Saudi Arabia
  • UAE
  • South Africa

Competitive Landscape

  • Company Profiles: Detailed analysis of the major companies present in the Global Artificial Intelligence in Marketing Market.

Available Customizations:

  • Global Artificial Intelligence in Marketing Market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Service Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Baseline Methodology
  • 2.2. Key Industry Partners
  • 2.3. Major Association and Secondary Sources
  • 2.4. Forecasting Methodology
  • 2.5. Data Triangulation & Validation
  • 2.6. Assumptions and Limitations

3. Executive Summary

4. Impact of COVID-19 on Global Artificial Intelligence in Marketing Market

5. Voice of Customer

6. Global Artificial Intelligence in Marketing Market Overview

7. Global Artificial Intelligence in Marketing Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Offering (Hardware, Software, Services)
    • 7.2.2. By Deployment Type (Cloud, On Premises)
    • 7.2.3. By Technology (Machine Learning, Context-Aware Computing, Natural Language Processing, Computer Vision)
    • 7.2.4. By Application (Social Media Advertising, Search Advertising, Content Curation, Sales Marketing Automation, Analytics Platform, Others)
    • 7.2.5. By End User Industry (BFSI, Retail, Consumer Goods, Media Entertainment, Enterprise, Others)
    • 7.2.6. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)
  • 7.3. By Company (2022)
  • 7.4. Market Map

8. North America Artificial Intelligence in Marketing Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Offering
    • 8.2.2. By Deployment Type
    • 8.2.3. By Technology
    • 8.2.4. By Application
    • 8.2.5. By End User Industry
    • 8.2.6. By Country
      • 8.2.6.1. United States Artificial Intelligence in Marketing Market Outlook
        • 8.2.6.1.1. Market Size & Forecast
        • 8.2.6.1.1.1. By Value
        • 8.2.6.1.2. Market Share & Forecast
        • 8.2.6.1.2.1. By Offering
        • 8.2.6.1.2.2. By Deployment Type
        • 8.2.6.1.2.3. By Technology
        • 8.2.6.1.2.4. By Application
        • 8.2.6.1.2.5. By End User Industry
      • 8.2.6.2. Canada Artificial Intelligence in Marketing Market Outlook
        • 8.2.6.2.1. Market Size & Forecast
        • 8.2.6.2.1.1. By Value
        • 8.2.6.2.2. Market Share & Forecast
        • 8.2.6.2.2.1. By Offering
        • 8.2.6.2.2.2. By Deployment Type
        • 8.2.6.2.2.3. By Technology
        • 8.2.6.2.2.4. By Application
        • 8.2.6.2.2.5. By End User Industry
      • 8.2.6.3. Mexico Artificial Intelligence in Marketing Market Outlook
        • 8.2.6.3.1. Market Size & Forecast
        • 8.2.6.3.1.1. By Value
        • 8.2.6.3.2. Market Share & Forecast
        • 8.2.6.3.2.1. By Offering
        • 8.2.6.3.2.2. By Deployment Type
        • 8.2.6.3.2.3. By Technology
        • 8.2.6.3.2.4. By Application
        • 8.2.6.3.2.5. By End User Industry

9. Europe Artificial Intelligence in Marketing Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Product Type
    • 9.2.2. By Power Type
    • 9.2.3. By Lifting Height
    • 9.2.4. By Application
    • 9.2.5. By Country
      • 9.2.5.1. Germany Artificial Intelligence in Marketing Market Outlook
        • 9.2.5.1.1. Market Size & Forecast
        • 9.2.5.1.1.1. By Value
        • 9.2.5.1.2. Market Share & Forecast
        • 9.2.5.1.2.1. By Offering
        • 9.2.5.1.2.2. By Deployment Type
        • 9.2.5.1.2.3. By Technology
        • 9.2.5.1.2.4. By Application
        • 9.2.5.1.2.5. By End User Industry
      • 9.2.5.2. France Artificial Intelligence in Marketing Market Outlook
        • 9.2.5.2.1. Market Size & Forecast
        • 9.2.5.2.1.1. By Value
        • 9.2.5.2.2. Market Share & Forecast
        • 9.2.5.2.2.1. By Offering
        • 9.2.5.2.2.2. By Deployment Type
        • 9.2.5.2.2.3. By Technology
        • 9.2.5.2.2.4. By Application
        • 9.2.5.2.2.5. By End User Industry
      • 9.2.5.3. United Kingdom Artificial Intelligence in Marketing Market Outlook
        • 9.2.5.3.1. Market Size & Forecast
        • 9.2.5.3.1.1. By Value
        • 9.2.5.3.2. Market Share & Forecast
        • 9.2.5.3.2.1. By Offering
        • 9.2.5.3.2.2. By Deployment Type
        • 9.2.5.3.2.3. By Technology
        • 9.2.5.3.2.4. By Application
        • 9.2.5.3.2.5. By End User Industry
      • 9.2.5.4. Italy Artificial Intelligence in Marketing Market Outlook
        • 9.2.5.4.1. Market Size & Forecast
        • 9.2.5.4.1.1. By Value
        • 9.2.5.4.2. Market Share & Forecast
        • 9.2.5.4.2.1. By Offering
        • 9.2.5.4.2.2. By Deployment Type
        • 9.2.5.4.2.3. By Technology
        • 9.2.5.4.2.4. By Application
        • 9.2.5.4.2.5. By End User Industry
      • 9.2.5.5. Spain Artificial Intelligence in Marketing Market Outlook
        • 9.2.5.5.1. Market Size & Forecast
        • 9.2.5.5.1.1. By Value
        • 9.2.5.5.2. Market Share & Forecast
        • 9.2.5.5.2.1. By Offering
        • 9.2.5.5.2.2. By Deployment Type
        • 9.2.5.5.2.3. By Technology
        • 9.2.5.5.2.4. By Application
        • 9.2.5.5.2.5. By End User Industry

10. South America Artificial Intelligence in Marketing Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Product Type
    • 10.2.2. By Power Type
    • 10.2.3. By Lifting Height
    • 10.2.4. By Application
    • 10.2.5. By Country
      • 10.2.5.1. Brazil Artificial Intelligence in Marketing Market Outlook
        • 10.2.5.1.1. Market Size & Forecast
        • 10.2.5.1.1.1. By Value
        • 10.2.5.1.2. Market Share & Forecast
        • 10.2.5.1.2.1. By Offering
        • 10.2.5.1.2.2. By Deployment Type
        • 10.2.5.1.2.3. By Technology
        • 10.2.5.1.2.4. By Application
        • 10.2.5.1.2.5. By End User Industry
      • 10.2.5.2. Colombia Artificial Intelligence in Marketing Market Outlook
        • 10.2.5.2.1. Market Size & Forecast
        • 10.2.5.2.1.1. By Value
        • 10.2.5.2.2. Market Share & Forecast
        • 10.2.5.2.2.1. By Offering
        • 10.2.5.2.2.2. By Deployment Type
        • 10.2.5.2.2.3. By Technology
        • 10.2.5.2.2.4. By Application
        • 10.2.5.2.2.5. By End User Industry
      • 10.2.5.3. Argentina Artificial Intelligence in Marketing Market Outlook
        • 10.2.5.3.1. Market Size & Forecast
        • 10.2.5.3.1.1. By Value
        • 10.2.5.3.2. Market Share & Forecast
        • 10.2.5.3.2.1. By Offering
        • 10.2.5.3.2.2. By Deployment Type
        • 10.2.5.3.2.3. By Technology
        • 10.2.5.3.2.4. By Application
        • 10.2.5.3.2.5. By End User Industry

11. Middle East & Africa Artificial Intelligence in Marketing Market Outlook

  • 11.1. Market Size & Forecast
    • 11.1.1. By Value
  • 11.2. Market Share & Forecast
    • 11.2.1. By Product Type
    • 11.2.2. By Power Type
    • 11.2.3. By Lifting Height
    • 11.2.4. By Application
    • 11.2.5. By Country
      • 11.2.5.1. Saudi Arabia Artificial Intelligence in Marketing Market Outlook
        • 11.2.5.1.1. Market Size & Forecast
        • 11.2.5.1.1.1. By Value
        • 11.2.5.1.2. Market Share & Forecast
        • 11.2.5.1.2.1. By Offering
        • 11.2.5.1.2.2. By Deployment Type
        • 11.2.5.1.2.3. By Technology
        • 11.2.5.1.2.4. By Application
        • 11.2.5.1.2.5. By End User Industry
      • 11.2.5.2. UAE Artificial Intelligence in Marketing Market Outlook
        • 11.2.5.2.1. Market Size & Forecast
        • 11.2.5.2.1.1. By Value
        • 11.2.5.2.2. Market Share & Forecast
        • 11.2.5.2.2.1. By Offering
        • 11.2.5.2.2.2. By Deployment Type
        • 11.2.5.2.2.3. By Technology
        • 11.2.5.2.2.4. By Application
        • 11.2.5.2.2.5. By End User Industry
      • 11.2.5.3. South Africa Artificial Intelligence in Marketing Market Outlook
        • 11.2.5.3.1. Market Size & Forecast
        • 11.2.5.3.1.1. By Value
        • 11.2.5.3.2. Market Share & Forecast
        • 11.2.5.3.2.1. By Offering
        • 11.2.5.3.2.2. By Deployment Type
        • 11.2.5.3.2.3. By Technology
        • 11.2.5.3.2.4. By Application
        • 11.2.5.3.2.5. By End User Industry

12. Asia Pacific Artificial Intelligence in Marketing Market Outlook

  • 12.1. Market Size & Forecast
    • 12.1.1. By Value
  • 12.2. Market Size & Forecast
    • 12.2.1. By Offering
    • 12.2.2. By Deployment Type
    • 12.2.3. By Technology
    • 12.2.4. By Application
    • 12.2.5. By End User Industry
    • 12.2.6. By Country
      • 12.2.6.1. China Artificial Intelligence in Marketing Market Outlook
        • 12.2.6.1.1. Market Size & Forecast
        • 12.2.6.1.1.1. By Value
        • 12.2.6.1.2. Market Share & Forecast
        • 12.2.6.1.2.1. By Offering
        • 12.2.6.1.2.2. By Deployment Type
        • 12.2.6.1.2.3. By Technology
        • 12.2.6.1.2.4. By Application
        • 12.2.6.1.2.5. By End User Industry
      • 12.2.6.2. India Artificial Intelligence in Marketing Market Outlook
        • 12.2.6.2.1. Market Size & Forecast
        • 12.2.6.2.1.1. By Value
        • 12.2.6.2.2. Market Share & Forecast
        • 12.2.6.2.2.1. By Offering
        • 12.2.6.2.2.2. By Deployment Type
        • 12.2.6.2.2.3. By Technology
        • 12.2.6.2.2.4. By Application
        • 12.2.6.2.2.5. By End User Industry
      • 12.2.6.3. Japan Artificial Intelligence in Marketing Market Outlook
        • 12.2.6.3.1. Market Size & Forecast
        • 12.2.6.3.1.1. By Value
        • 12.2.6.3.2. Market Share & Forecast
        • 12.2.6.3.2.1. By Offering
        • 12.2.6.3.2.2. By Deployment Type
        • 12.2.6.3.2.3. By Technology
        • 12.2.6.3.2.4. By Application
        • 12.2.6.3.2.5. By End User Industry
      • 12.2.6.4. South Korea Artificial Intelligence in Marketing Market Outlook
        • 12.2.6.4.1. Market Size & Forecast
        • 12.2.6.4.1.1. By Value
        • 12.2.6.4.2. Market Share & Forecast
        • 12.2.6.4.2.1. By Offering
        • 12.2.6.4.2.2. By Deployment Type
        • 12.2.6.4.2.3. By Technology
        • 12.2.6.4.2.4. By Application
        • 12.2.6.4.2.5. By End User Industry
      • 12.2.6.5. Australia Artificial Intelligence in Marketing Market Outlook
        • 12.2.6.5.1. Market Size & Forecast
        • 12.2.6.5.1.1. By Value
        • 12.2.6.5.2. Market Share & Forecast
        • 12.2.6.5.2.1. By Offering
        • 12.2.6.5.2.2. By Deployment Type
        • 12.2.6.5.2.3. By Technology
        • 12.2.6.5.2.4. By Application
        • 12.2.6.5.2.5. By End User Industry

13. Market Dynamics

  • 13.1. Drivers
  • 13.2. Challenges

14. Market Trends and Developments

15. Company Profiles

  • 15.1. Adobe Inc.
    • 15.1.1. Business Overview
    • 15.1.2. Key Revenue and Financials
    • 15.1.3. Recent Developments
    • 15.1.4. Key Personnel
    • 15.1.5. Key Product/Services Offered
  • 15.2. Alphabet Inc.
    • 15.2.1. Business Overview
    • 15.2.2. Key Revenue and Financials
    • 15.2.3. Recent Developments
    • 15.2.4. Key Personnel
    • 15.2.5. Key Product/Services Offered
  • 15.3. Amazon Web Services, Inc.
    • 15.3.1. Business Overview
    • 15.3.2. Key Revenue and Financials
    • 15.3.3. Recent Developments
    • 15.3.4. Key Personnel
    • 15.3.5. Key Product/Services Offered
  • 15.4. IBM Corporation
    • 15.4.1. Business Overview
    • 15.4.2. Key Revenue and Financials
    • 15.4.3. Recent Developments
    • 15.4.4. Key Personnel
    • 15.4.5. Key Product/Services Offered
  • 15.5. Microsoft Corporation
    • 15.5.1. Business Overview
    • 15.5.2. Key Revenue and Financials
    • 15.5.3. Recent Developments
    • 15.5.4. Key Personnel
    • 15.5.5. Key Product/Services Offered
  • 15.6. Salesforce.com, Inc.
    • 15.6.1. Business Overview
    • 15.6.2. Key Revenue and Financials
    • 15.6.3. Recent Developments
    • 15.6.4. Key Personnel
    • 15.6.5. Key Product/Services Offered
  • 15.7. SAS Institute Inc.
    • 15.7.1. Business Overview
    • 15.7.2. Key Revenue and Financials
    • 15.7.3. Recent Developments
    • 15.7.4. Key Personnel
    • 15.7.5. Key Product/Services Offered
  • 15.8. Teradata Corporation
    • 15.8.1. Business Overview
    • 15.8.2. Key Revenue and Financials
    • 15.8.3. Recent Developments
    • 15.8.4. Key Personnel
    • 15.8.5. Key Product/Services Offered
  • 15.9. Oracle Corporation
    • 15.9.1. Business Overview
    • 15.9.2. Key Revenue and Financials
    • 15.9.3. Recent Developments
    • 15.9.4. Key Personnel
    • 15.9.5. Key Product/Services Offered
  • 15.10. SAP SE
    • 15.10.1. Business Overview
    • 15.10.2. Key Revenue and Financials
    • 15.10.3. Recent Developments
    • 15.10.4. Key Personnel
    • 15.10.5. Key Product/Services Offered

16. Strategic Recommendations

17. About Us & Disclaimer