| 出版社 | IMARC Group |
| 出版年月 | 2025年10月 |
Recommendation Engine Market Size, Share, Trends and Forecast
レコメンデーションエンジン市場規模、シェア、トレンド、予測 : タイプ、テクノロジー、導入モード、用途、エンドユーザー、地域別、2025-2033年
世界のレコメンデーションエンジン市場規模は、2024年に63億2,000万米ドルと評価されました。IMARCグループは、今後、市場規模は2033年までに726億2,000万米ドルに達し、2025年から2033年にかけて29.62%のCAGR（年平均成長率）で成長すると予測しています。北米は現在、市場を支配しており、2024年には40.0%の市場シェアを占めると予想されています。AIと機械学習の進歩により、企業はeコマース、エンターテイメント、デジタルマーケティングなど、あらゆる分野でパーソナライズされた体験を提供できるようになり、市場は大幅な成長を遂げています。リアルタイムでコンテキストを認識し、パーソナライズされたレコメンデーションへの需要の高まりが市場の成長を後押ししています。クラウドベースのソリューションとビッグデータの台頭は、レコメンデーションエンジンの機能をさらに強化し、レコメンデーションエンジン市場シェアの拡大に大きく貢献しています。
レコメンデーションエンジン市場の成長を牽引する主な要因は、eコマース、エンターテインメント、ヘルスケアなどの分野におけるパーソナライズされたユーザーエクスペリエンスの需要の高まりです。例えば、アーサーは2024年1月に、オンラインビジネス向けのAI駆動型レコメンデーションエンジンを強化するレコメンデーションシステムサポートをリリースしました。このテクノロジーは、パフォーマンスの問題とデータドリフトに対処し、正確で関連性の高いレコメンデーションを保証します。これらのシステムを監視することで、アーサーは顧客満足度と収益成長を促進し、デジタル経済におけるeコマースおよびコンテンツプラットフォームがレコメンデーションシステムを活用する方法に革命をもたらしています。ビッグデータとAIテクノロジーの台頭により、企業は消費者の行動を分析し、カスタマイズされたレコメンデーションを提供できるようになりました。さらに、機械学習アルゴリズムの採用拡大とクラウドコンピューティングインフラストラクチャの拡張により、レコメンデーションシステムのスケーラビリティと効率性が向上しています。これらの要因が相まって市場の成長を促し、顧客エンゲージメントを向上させ、企業の収益創出を促進しています。
米国のレコメンデーションエンジン市場を牽引する主な要因として、eコマース、ストリーミングサービス、デジタルマーケティングなどの分野におけるパーソナライズされた顧客体験へのニーズの高まりが挙げられます。例えば、2024年4月、ブルームリーチはディスカバリープラットフォーム向けにAIを活用した新機能を発表し、eコマースの商品レコメンデーションを強化しました。主なアップデートには、ビジュアルレコメンデーション、パーソナライズされた提案のための高度なアルゴリズム、分析ダッシュボードの改善などが含まれます。これらのイノベーションは、コンバージョン率の向上と、顧客と企業の両方のショッピング体験の向上を目指しています。データの可用性の向上とAI、機械学習、ディープラーニングの進歩が相まって、企業はより正確で関連性の高い商品やコンテンツの提案を行うことができます。さらに、クラウドベースのソリューションの利用増加とオムニチャネル戦略への移行により、レコメンデーションエンジンの導入が加速し、顧客エンゲージメントが強化され、市場の成長が促進されています。
Report Overview
The global recommendation engine market size was valued at USD 6.32 Billion in 2024. Looking forward, IMARC Group estimates the market to reach USD 72.62 Billion by 2033, exhibiting a CAGR of 29.62% from 2025-2033. North America currently dominates the market, holding a market share of 40.0% in 2024. The market is witnessing significant growth driven by advancements in AI and machine learning, enabling businesses to deliver personalized experiences across e-commerce, entertainment, and digital marketing. Increasing demand for real-time, context-aware, and personalized recommendations is boosting market growth. Cloud-based solutions and the rise of big data are further enhancing the capabilities of recommendation engines contributing positively to the recommendation engine market share.
recommendation engine market
The main factors driving the growth of the recommendation engine market are the rising need for personalized user experiences in sectors such as e-commerce, entertainment, and healthcare. For instance, in January 2024, Arthur launched Recommender System Support enhancing AI-driven recommendation engines for online businesses. This technology addresses performance issues and data drift, ensuring accurate, relevant recommendations. By monitoring these systems Arthur boosts customer satisfaction and revenue growth revolutionizing how e-commerce and content platforms utilize recommender systems in the digital economy. The rise of big data and AI technologies enables businesses to analyze consumer behavior and offer tailored recommendations. Additionally, the growing adoption of machine learning algorithms and the expansion of cloud computing infrastructure are enhancing the scalability and efficiency of recommendation systems. These factors collectively fuel the market’s growth improving customer engagement and boosting revenue generation for businesses.
Key drivers in the United States recommendation engine market include the growing need for personalized customer experiences in sectors such as e-commerce, streaming services, and digital marketing. For instance, in April 2024, Bloomreach launched new AI-powered features for its Discovery platform, enhancing ecommerce product recommendations. Key updates include visual recommendations, advanced algorithms for personalized suggestions, and an improved analytics dashboard. These innovations aim to boost conversions and improve the shopping experience for both customers and businesses. The rise in data availability, combined with advancements in AI, machine learning, and deep learning, enables businesses to deliver more accurate and relevant product or content suggestions. Additionally, the increasing use of cloud-based solutions and the shift toward omnichannel strategies are accelerating the adoption of recommendation engines, enhancing customer engagement and driving market growth.
Recommendation Engine Market Trends:
Rising Adoption of AI and Machine Learning
The adoption of AI, machine learning, and deep learning algorithms is transforming the recommendation engine market, driving more accurate and personalized suggestions for users. By analyzing large datasets and identifying patterns in user behavior, these advanced technologies enable businesses to offer highly relevant recommendations in real time. As a result, companies in sectors like e-commerce, streaming, and digital marketing are experiencing enhanced customer engagement. For instance, in March 2025, Union Minister of India announced the launch of AIKosha, an AI datasets platform, and the AI Compute Portal, providing subsidized GPU access. Additional initiatives include an AI-powered recommendation system for public officials and programs to enhance AI research and skill development, positioning India as a global AI leader. This trend is expected to continue, with the recommendation engine market forecast predicting substantial growth as AI-powered solutions become more widespread.
Real-time Recommendations
Real-time recommendations are becoming a significant trend in the recommendation engine market, driven by the need for context-aware suggestions based on immediate user behavior, location, and time. By analyzing data on the fly, recommendation engines can provide personalized suggestions that are highly relevant to the user’s current situation, whether in e-commerce, media, or travel. For instance, in March 2025, Globant, in collaboration with Google Cloud, launched the AI Retail Search and Recommendations platform, enhancing online shopping through personalized searches and intelligent recommendations. Leveraging generative AI boosts customer engagement and sales. The solution was showcased at the NRF, highlighting Globant’s commitment to redefining retail experiences through innovative technology. This enhances customer satisfaction and engagement. As technology advances, the recommendation engine market outlook indicates a strong growth trajectory, with real-time, personalized recommendations becoming a standard expectation across industries.
Personalization for Enhanced User Experience
Personalization is a key trend in the recommendation engine market, with businesses increasingly focusing on hyper-personalized recommendations to improve user satisfaction and engagement. By analyzing individual preferences, past behaviors, and even social media activity, companies in e-commerce and entertainment are tailoring their suggestions to create a more engaging, unique experience for each user. This not only enhances the overall user journey but also boosts conversion rates and customer loyalty. As consumer expectations for personalization continue to rise, the recommendation engine market growth is expected to accelerate, driven by advancements in AI and machine learning technologies.
Recommendation Engine Market Report Scope:
| Report Features | Details |
|---|---|
| Base Year of the Analysis | 2024 |
| Historical Period | 2019-2024 |
| Forecast Period | 2025-2033 |
| Units | Billion USD |
| Scope of the Report | Exploration of Historical Trends and Market Outlook, Industry Catalysts and Challenges, Segment-Wise Historical and Future Market Assessment:
|
| Types Covered | Collaborative Filtering, Content-based Filtering, Hybrid Recommendation Systems, Others |
| Technologies Covered | Context Aware, Geospatial Aware |
| Deployment Modes Covered | On-premises, Cloud-based |
| Applications Covered | Strategy and Operations Planning, Product Planning and Proactive Asset Management, Personalized Campaigns and Customer Discovery |
| End Users Covered | IT and Telecommunication, BFSI, Retail, Media and Entertainment, Healthcare, Others |
| Region Covered | Asia Pacific, Europe, North America, Latin America, Middle East and Africa |
| Countries Covered | United States, Canada, Germany, France, United Kingdom, Italy, Spain, Russia, China, Japan, India, South Korea, Australia, Indonesia, Brazil, Mexico |
| Companies Covered | Adobe Inc., Amazon.com Inc., Dynamic Yield (McDonald’s), Google LLC (Alphabet Inc.), Hewlett Packard Enterprise Development LP, Intel Corporation, International Business Machines Corporation, Kibo Software Inc., Microsoft Corporation, Oracle Corporation, Recolize GmbH, Salesforce.com Inc., SAP SE |
| Customization Scope | 10% Free Customization |
| Post-Sale Analyst Support | 10-12 Weeks |
| Delivery Format | PDF and Excel through Email (We can also provide the editable version of the report in PPT/Word format on special request) |