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行销市场中的人工智慧 - 全球产业规模、份额、趋势、机会和预测，按产品、部署类型、技术、按应用、最终用户产业、地区和竞争细分，2018-2028 年
市场调查报告书
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1379565

行销市场中的人工智慧 - 全球产业规模、份额、趋势、机会和预测，按产品、部署类型、技术、按应用、最终用户产业、地区和竞争细分，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个工作天内

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简介目录

随着组织越来越认识到人工智慧技术彻底改变其行销工作的潜力，全球行销市场中的人工智慧正在经历显着的成长和转型。行销中的人工智慧涵盖了广泛的应用，从资料分析和客户细分到个人化内容推荐和预测分析。

人工智慧在行销领域发展的关键驱动力之一是其利用大量资料并提取可行见解的能力。人工智慧驱动的工具可以以前所未有的规模和速度分析客户行为、偏好和互动，使行销人员能够做出数据驱动的决策。这会带来更有效、更有针对性的行销活动，与客户产生共鸣。

个人化是人工智慧在行销的另一个关键面向。人工智慧演算法可以根据个人消费者的历史互动和偏好，为他们量身定制行销讯息、产品推荐和广告。这种程度的个人化增强了客户参与度，提高了转换率，并最终推动收入成长。

市场概况
预测期 2024-2028
2022 年市场规模 106.7亿美元
2028 年市场规模 442.5亿美元
2023-2028 年CAGR 25.78%
成长最快的细分市场 云
最大的市场 北美洲

由人工智慧支援的预测分析使行销人员能够预测未来趋势和客户行为，使他们能够主动调整策略并在竞争中保持领先地位。行销自动化、聊天机器人和虚拟助理正在成为客户服务和参与的一部分，提供 24/7 支援并改善客户体验。

主要市场驱动因素

增强的个人化和客户参与度：

人工智慧 (AI) 是行销工作日益个人化的驱动力。人工智慧演算法可以分析大量资料集，以了解个人客户的偏好、行为和购买历史。这种数据驱动的方法使行销人员能够向消费者提供高度个人化的内容、产品推荐和广告。增强的个人化可以提高客户参与度，因为消费者更有可能与与其兴趣产生共鸣的内容互动并做出积极回应。因此，人工智慧驱动的个人化是转换率、客户忠诚度和品牌亲和力的强大驱动力。

数据驱动的决策：

人工智慧使行销人员能够以以前无法达到的规模和速度做出数据驱动的决策。机器学习演算法可以分析大量行销资料，包括客户互动、网站流量和活动绩效。透过识别这些资料中的模式和趋势，人工智慧使行销人员能够优化行销策略，有效分配资源，并以正确的讯息瞄准正确的受众。数据驱动的决策不仅可以提高行销投资报酬率，还可以提供有价值的见解，为长期行销策略提供资讯。

重复任务的自动化：

人工智慧驱动的行销自动化是效率和生产力的主要驱动力。行销人员可以自动化日常任务，例如电子邮件行销、社群媒体发布和广告活动管理。由人工智慧支援的聊天机器人和虚拟助理可以处理客户询问并提供即时支援。透过自动化这些流程，行销人员可以腾出时间和资源，专注于行销活动中更具策略性和创造性的方面。自动化还确保讯息传递的一致性并降低人为错误的风险。

改善客户体验：

人工智慧在增强整体客户体验方面发挥关键作用。聊天机器人和虚拟助理提供 24/7 客户支持，及时解决查询和问题。人工智慧驱动的推荐引擎推荐符合个人客户偏好的产品和服务，促进无缝交叉销售和追加销售。此外，人工智慧可以分析客户回馈和情绪，以确定产品或服务需要改进的领域。透过根据人工智慧洞察优先考虑客户体验改进，组织可以建立更牢固的客户关係并提高品牌忠诚度。

即时分析与优化：

人工智慧使行销人员能够存取即时分析和优化功能。机器学习演算法可以持续分析产生的资料，使行销人员能够立即调整行销活动和策略。例如，人工智慧可以根据即时效果资料调整广告竞价策略，以最大限度地提高投资报酬率。即时分析还可以洞察消费者行为，使行销人员能够即时回应趋势和新出现的机会。这种敏捷性和回应能力在当今快节奏的行销环境中至关重要。

主要市场挑战

资料隐私和合规性：

行销市场中的人工智慧面临的最重大挑战之一是资料隐私和合规性的复杂情况。由于人工智慧演算法依赖大量资料来做出明智的决策和个人化行销工作，因此公司必须了解一系列法规，包括《一般资料保护规范》(GDPR) 和《加州消费者隐私法案》(CCPA)。确保遵守这些法规，同时有效利用客户资料进行行销目的是一个微妙的平衡。违规行为可能会导致严厉的罚款并损害品牌声誉，从而使资料隐私成为行销人员面临的首要挑战。

道德问题和偏见：

行销中围绕人工智慧的道德考量越来越受到重视。人工智慧演算法可能导致偏见、歧视或意外后果长期存在，这是一个值得关注的问题。例如，有偏见的演算法可能会向某些人口群体提供歧视性广告或推荐。解决这些道德挑战需要开发公平、透明且无偏见的人工智慧模型。此外，公司必须制定人工智慧使用道德准则，并确保持续监控和审计，以防止道德违规。

数据品质和可访问性：

人工智慧模型在很大程度上依赖资料的品质和可访问性。不准确或不完整的资料可能会导致错误的预测和低于标准的行销工作。确保资料品质涉及资料清理和预处理，这可能非常耗时且占用资源。此外，并非所有组织都能获得训练有效人工智慧模型所需的大量高品质资料。较小的公司和新创公司可能在获取和管理人工智慧驱动的行销计划所需的资料方面面临挑战。

人才短缺和技能差距：

行销领域对人工智慧专业知识的需求远远超过熟练专业人员的供应。寻找并留住人工智慧专家、资料科学家和机器学习工程师是组织面临的重大挑战。人工智慧领域正在迅速发展，公司必须不断投资于培训和开发，以使其团队掌握最新技术和最佳实践。此外，对顶尖人工智慧人才的竞争推高了薪资和招募成本，使一些组织难以组建有能力的团队。

与遗留系统整合：

许多组织拥有遗留的 IT 系统和行销技术，这些系统和行销技术最初并不是为适应人工智慧而设计的。将人工智慧整合到这些现有系统中可能非常复杂且成本高昂。相容性问题、资料迁移挑战以及对额外基础设施的需求可能会阻碍人工智慧在行销中的无缝采用。实现全面整合通常需要策略方法以及投资技术升级和现代化工作的意愿。

主要市场趋势

超个性化和以客户为中心：

超个人化是全球人工智慧行销市场的一个重要趋势。随着消费者被资讯和选择淹没，行销人员越来越多地转向人工智慧来创造高度个人化的体验。人工智慧演算法分析大量客户资料，以了解偏好、行为和人口统计数据，从而提供量身定制的内容、推荐和广告。这种程度的个人化不仅可以提高客户参与度，还可以提高转换率和品牌忠诚度。此外，人工智慧驱动的聊天机器人和虚拟助理提供即时帮助，进一步增强以客户为中心的能力。

预测分析与预测：

由人工智慧支援的预测分析正在改变行销策略。行销人员正在利用机器学习演算法来预测未来趋势、客户行为和市场需求。这种数据驱动的方法可以帮助组织有效地分配资源、优化定价策略并预测消费者偏好的变化。透过准确预测市场动态，人工智慧使行销人员能够在竞争中保持领先并做出明智的决策，最终提高投资回报。

人工智慧增强的内容创作：

人工智慧正在彻底改变内容创建和行销自动化。自然语言处理 (NLP) 和生成对抗网路 (GAN) 使人工智慧能够生成高品质的、类似人类的内容，包括文章、产品描述和社交媒体贴文。人工智慧产生的内容可以针对不同的受众和平台进行客製化，为行销人员节省时间和资源。此外，人工智慧驱动的工具可以分析内容效能，为优化未来内容策略提供见解。这种趋势简化了内容行销工作，增强了一致性并确保了相关性。

语音和视觉搜寻优化：

Siri、Alexa 和 Google Assistant 等声控虚拟助理的兴起带动了语音搜寻的成长。同样，视觉搜寻（使用者可以使用图像搜寻产品或资讯）也越来越受欢迎。人工智慧在优化这些新兴搜寻方法的网站和内容方面发挥关键作用。行销人员正在调整他们的 SEO 策略来解决语音和视觉搜寻查询，因为他们需要不同的关键字优化和内容格式。人工智慧驱动的图像辨识和语音辨识技术正在融入电子商务平台，使消费者更容易找到和购买产品。

道德人工智慧和透明度：

道德人工智慧正成为行销产业的一个重要考虑因素。由于人工智慧演算法影响决策过程和消费者互动，因此透明度和问责制至关重要。行销人员越来越关注负责任的人工智慧实践，确保人工智慧驱动的行销活动没有偏见并遵守道德准则。这包括解决与资料隐私、同意和公平使用相关的问题。各组织也努力透明地传达他们的人工智慧实践，以建立与消费者的信任。监管机构开始对人工智慧道德製定指导方针，这使得行销人员必须采用符合道德的人工智慧实践并提高营运透明度。

细分市场洞察

提供见解

到 2022 年，软体领域将在全球人工智慧行销市场中占据主导地位。人工智慧驱动的软体工具擅长快速、准确地处理和分析大量资料。行销人员依靠这些解决方案从客户行为、偏好和互动中提取有价值的见解。透过利用人工智慧软体，企业可以更深入地了解目标受众并做出数据驱动的决策，从而进行更有效的行销活动。

人工智慧软体的突出特点之一是能够向个人消费者大规模提供高度个人化的行销内容和建议。人工智慧演算法分析客户资料，根据每个客户的独特偏好和历史客製化讯息、产品建议和优惠。这种程度的个人化增强了客户参与度并增加了转换的可能性。

人工智慧驱动的软体擅长预测分析，根据历史资料预测未来趋势和消费者行为。行销人员依靠预测分析来预测客户需求和趋势，使他们能够主动调整行销策略。这种预测能力使企业能够在竞争中保持领先地位并快速回应市场变化。

部署类型见解

到 2022 年，云端细分市场将在全球人工智慧行销市场中占据主导地位。基于云端的人工智慧行销解决方案提供无与伦比的可扩展性，使企业能够扩展业务并无缝适应不断变化的需求。无论公司的行销需求是快速成长还是季节性波动，云端都可以灵活地根据需要扩展或缩减资源。

云端部署消除了对硬体和基础设施进行大量前期投资的需求。相反，企业可以以即用即付或订阅的方式订阅云端服务，从而减少资本支出。这种经济高效的模式使人工智慧行销工具的使用变得民主化，使各种规模的组织都可以使用它们。

与本地替代方案相比，基于云端的人工智慧行销解决方案可以快速部署。实施通常涉及配置软体设定并与现有系统集成，从而使企业能够开始利用人工智慧功能，而无需延长设定时间。

基于云端的平台可以透过网路连线从任何地方访问，促进行销团队之间的远端工作和协作。团队成员可以协作开展活动、分析资料并存取人工智慧工具，而无需局限于实体办公地点。

区域洞察

北美在2022年全球人工智慧行销市场中占据主导地位。北美，特别是美国，是全球技术创新和研究中心。加州的硅谷是一些世界上最大的科技公司和新创企业的所在地。这些公司一直处于开发人工智慧技术的前沿，并积极将人工智慧融入行销实践。他们的创新为全球行销中人工智慧的采用奠定了基础。

北美的风险投资和投资机会推动了人工智慧新创公司和计划的发展。该地区为人工智慧驱动的营销企业吸引了大量资金，使这些企业能够开发和扩展其解决方案。这种资金支持使北美公司在人工智慧行销技术方面具有竞争优势。

北美培育了丰富的人工智慧研究机构、大学和智库生态系统。这些机构与私营部门密切合作，共享知识和资源以推动人工智慧技术。这种协作环境创造了人工智慧人才和专业知识的稳定流动，推动了行销应用的创新。

北美庞大且多样化的消费者群体对人工智慧驱动的行销解决方案产生了巨大的需求。该地区的企业热衷于利用人工智慧，透过个人化客户体验、优化广告活动和提高行销投资回报率来获得竞争优势。这种需求刺激了人工智慧行销工具的开发和采用。

目录

第 1 章：服务概述

  • 市场定义
  • 市场范围
    • 涵盖的市场
    • 考虑学习的年份
    • 主要市场区隔

第 2 章：研究方法

  • 基线方法
  • 主要产业伙伴
  • 主要协会和二手资料来源
  • 预测方法
  • 数据三角测量与验证
  • 假设和限制

第 3 章：执行摘要

第 4 章：COVID-19 对全球人工智慧行销市场的影响

第 5 章：客户之声

第 6 章：全球人工智慧行销市场概述

第 7 章：全球人工智慧行销市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 依产品提供（硬体、软体、服务）
    • 依部署类型（云端、本机）
    • 依技术分类（机器学习、情境感知计算、自然语言处理、电脑视觉）
    • 按应用（社群媒体广告、搜寻广告、内容规划、销售行销自动化、分析平台等）
    • 按最终用户产业（BFSI、零售、消费品、媒体娱乐、企业、其他）
    • 按地区（北美、欧洲、南美、中东和非洲、亚太地区）
  • 按公司划分 (2022)
  • 市场地图

第 8 章：北美人工智慧行销市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 透过提供
    • 依部署类型
    • 依技术
    • 按应用
    • 按最终用户产业
    • 按国家/地区

第 9 章：欧洲人工智慧行销市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 依产品类型
    • 按电源类型
    • 按提升高度
    • 按应用
    • 按国家/地区

第10章：南美洲人工智慧行销市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 依产品类型
    • 按电源类型
    • 按提升高度
    • 按应用
    • 按国家/地区

第 11 章：中东和非洲人工智慧行销市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 依产品类型
    • 按电源类型
    • 按提升高度
    • 按应用
    • 按国家/地区

第12章：亚太地区人工智慧行销市场展望

  • 市场规模及预测
    • 按价值
  • 市场规模及预测
    • 透过提供
    • 依部署类型
    • 依技术
    • 按应用
    • 按最终用户产业
    • 按国家/地区

第 13 章：市场动态

  • 司机
  • 挑战

第 14 章：市场趋势与发展

第 15 章：公司简介

  • 奥多比公司
    • 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
  • 亚马逊网路服务公司
    • 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
  • 微软公司
    • 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系统公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services Offered

第 16 章：策略建议

第 17 章：关于我们与免责声明

简介目录
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