Content Recommendation Engine Market Research Report Information By Component (Solution), By Filtering Approach (Collaborative Filtering, Content-Based Filtering), By Organization Size (Small & Medium Enterprises, Large Enterprises), And By Region (North America, Europe, Asia-Pacific, And Rest Of The World) –Market Forecast Till 2030.

Content Recommendation Engine Market Overview

Content Recommendation Engine Market Size was valued at USD 5.1 billion in 2022. The Content Recommendation Engine market industry is projected to grow from USD 6.55 Billion in 2023 to USD 29.50 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 28.50% during the forecast period (2023 – 2030). Accentuating the importance of enhancing customer experience, accelerating digitization, and expanding e-commerce are the key market drivers enhancing the Content Recommendation Engine market growth.

Source: Secondary Research, Primary Research, MRFR Database and Analyst Review

Content Recommendation Engine Market Trends

Focus on improving customer experience, acceleration of digitization, and growth of e-commerce will boost the market growth

Providing excellent customer care to customers is the largest difficulty for e-commerce enterprises. The widespread use of the Web as an e-commerce platform has resulted in a fundamental shift in how companies engage with their clients. By boosting cross-selling and fostering loyalty, the deployment of content recommender systems in an e-commerce environment may have an effect on both financial performance and the ferocity of consumer interactions. Aspect Software Inc. estimates that the churn rate for retail in the United States was 27% in 2018 and 22% for online retail.

E-commerce businesses focus more on customer purchase activity due to increased churn rate %. Based on that, they propose items to customers through their content recommendation platform. The content recommendation engine allows eCommerce businesses to scale the recommendation engine to more users, thereby boosting RO, suggesting new products by training the algorithms with specific keywords and demographic information of specific customers, and making precise and accurate recommendations based on a single customer's purchase history. In specialized eCommerce businesses, this form of recommender engine is frequently employed (Discogs and Artsy use this approach). Amazon Personalize also combines real-time user activity data with user profiles and product data to get the best product or content suggestions. In the second quarter of 2020, Amazon's net revenue from the online sales sector came to roughly USD 45.9 billion, with its content recommendation platform playing a significant role in this revenue. Amazon's recommendation system is responsible for 35% of its sales.

The market value has grown generally in recent years due to the rise in applications for the Content Recommendation Engine. The Content Recommendation Engine significantly impacts the verticals, including e-commerce, IT and telecoms, BFSI, educational sectors, etc. The market is being heavily utilized by new businesses concentrating on digital marketing to advertise their brands. Thus, driving the Content Recommendation Engine market revenue.

Content Recommendation Engine Market Segment Insights

Content Recommendation Engine Component Insights

Based on Components, the Content Recommendation Engine market segmentation includes Solutions. The Solution segment dominated the market, accounting for 35% of market revenue. solutions on the market for content recommendation engines provide customers with a variety of flexible options.

Content Recommendation Engine Filtering Approach Insights

The Content Recommendation Engine market segmentation, based on Filtering Approach, includes Collaborative Filtering, Content-Based Filtering. The collaborative filtering category generated the most income. Collaborative Filtering accounted for around 60-65% of overall income in 2021, and it is projected that it will hold the top spot throughout the forecast period. This is a result of the growing need among e-commerce businesses for reliable recommendation engines to enhance their customers' shopping experiences by providing product suggestions based on their preferences. For instance, Spotify suggests users listen to "Discover Weekly" and other playlists depending on their listening history.

Figure 1: Content Recommendation Engine Market, by Filtering Approach 2022 & 2030 (USD billion)

Source: Secondary Research, Primary Research, MRFR Database and Analyst Review

Content Recommendation Engine Organization Size Insights

Based on Organization Size, the content recommendation engine industry has been segmented into Small & Medium Enterprises, Large Enterprises. Large Enterprises held the largest segment share in 2022. This is due to major businesses' increased need for recommendation engines, which helps them make better decisions, manage their company portfolios more effectively, and gain a competitive edge in the worldwide market. Throughout the projection period, the SME category is anticipated to have the highest CAGR of 34.6%. This Content Recommendation, the Engine market sector, is driven by the growing requirement to provide a better user experience in the extremely competitive environment. The demand for recommendation engines among small and medium-sized businesses is also rising as a result of the growing necessity to identify alternative alternatives for reducing marketing and advertising expenditures because of restricted budgets.

Content Recommendation Engine Regional Insights

By Region, the study provides market insights into North America, Europe, Asia-Pacific and the Rest of the World. The North American Content Recommendation Engine market area will dominate this market. The major participants in the market are located in North America, and the development of cutting-edge technology has significantly influenced the growth of the content recommendation sector. The leading rivals are working very hard to enhance how visitors engage with their websites. The fast digitalization of the area and the Region's expanding internet and smartphone usage have played a vital role in the growth of the content recommendation industry in North America. North America is expected to maintain its dominant position worldwide during the next years. Technical developments and early adoption would fuel the rise of the market within the Region throughout the assessment period.

Further, the major countries studied in the market report are The U.S., Canada, German, France, the UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.

Figure 2: CONTENT RECOMMENDATION ENGINE MARKET SHARE BY REGION 2022 (%)

The Asia Pacific Content Recommendation Engine market's fastest-growing market. APAC is also anticipated to be a very promising market, given the expansion of the eCommerce sector and the massive surge in data across all end users. The need for recommendation engines in the area is fueled by factors including the increasing e-commerce penetration, an increase in online shopping transactions, and growth in the number of Over the Top (OTT) service providers. Moreover, China’s Content Recommendation Engine market held the largest market share, and the Indian Content Recommendation Engine market was the fastest-growing market in the Asia-Pacific region.

The increased desire to enhance the customer experience fuels the need for recommendation engines. Businesses' growing use of digital technologies is driving up the need for recommendation engine solutions. A few main factors influencing the Europe market are the expansion of approaches to enhance customer experience and the expanding breadth of digital transformation. Further, the German Content Recommendation Engine market held the largest market share, and the UK Content Recommendation Engine market was the fastest-growing market in the European Region.

Content Recommendation Engine Key Market Players & Competitive Insights

Leading market companies are making significant investments in R&D to broaden their product offerings, which will spur further expansion of the market for Content Recommendation Engine. Important market developments include new product releases, contractual agreements, mergers and acquisitions, greater investments, and collaboration with other organizations. Market participants also engage in several strategic actions to increase their worldwide presence. The content recommendation engine industry must offer products at reasonable prices to grow and thrive in a more cutthroat and competitive environment.

One of the primary business strategies manufacturers employs worldwide for the Content Recommendation Engine industry to benefit customers and expand the market sector is local manufacturing to reduce operating costs. Some of the biggest benefits to medicine in recent years have come from the Content Recommendation Engine industry. The Content Recommendation Engine industry has offered some of the most significant medical advantages in recent years. Major players in the Content Recommendation Engine market, including Amazon Web Services (US), Boomtrain (US), Certona (US), Curata (US), Cxense (Norway), Dynamic Yield (US), IBM (US), Kibo Commerce (US), Outbrain (US), Revcontent (US), Taboola (US), ThinkAnalytics (UK)., and others, are attempting to increase market demand by investing in research and development operations.

With its headquarters in Armonk, New York, and operations in more than 175 nations, the International Business Machines Corporation (IBM), sometimes known as Big Blue, is an American technology company. It offers host and consulting services in various fields, including mainframe computers and nanotechnology and is an expert in computer hardware, middleware, and software. The IBM Watson Advertising Accelerator for OTT and video was expanded in May 2021, according to an announcement from IBM. This program is intended to assist advertisers in going beyond contextual relevance alone. The Accelerator's goal is to use artificial intelligence to dynamically optimize OTT ad creative for better campaign results at scale, independent of conventional advertising identifiers. Although Accelerator is compatible with most streaming systems, IBM is working closely with Xandr, a pioneer in programmable and convergent video solutions, to broaden its use.

Adobe Inc., formerly Adobe Systems Incorporated, is a worldwide American software corporation headquartered in San Jose, California, and a Delaware company registered. The same page improved personalization with Adobe Target, and Adobe introduced a real-time consumer data platform in January 2022. A cohesive profile derived from all online and offline interactions is made available to Adobe Target thanks to this recent connection with the Adobe Real-time Customer Data Platform (CDP).

Key Companies in the Content Recommendation Engine market include

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  Amazon Web Services (US)

  
  


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  Boomtrain (US)

  
  


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  Certona (US)

  
  


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  Curata (US)

  
  


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  Cxense (Norway)

  
  


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  Dynamic Yield (US)

  
  


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  IBM (US)

  
  


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  Kibo Commerce (US)

  
  


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  Outbrain (US)

  
  


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  Revcontent (US)

  
  


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  Taboola (US)

  
  


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  ThinkAnalytics (UK)

  
  

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  March 2021: A key player in the enterprise business process intelligence and process management arena, Signavio, was acquired by SAP SE. The products from Signavio are incorporated into SAP's business process intelligence portfolio and work in conjunction with SAP's comprehensive process transformation portfolio.

  
  


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  February 2021: UNBXD Inc. and Google Cloud worked together to provide retail establishments with AI-powered commerce search on Google Cloud. Unbxd intended to use Google Cloud's cutting-edge search, recommendation, and AI capabilities as part of the partnership to enhance product discovery for retail consumers. Also, the business intended to offer its Google Cloud-hosted commerce search service to retail clients.

  
  

Content Recommendation Engine Market Segmentation

Content Recommendation Engine Component Outlook

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  Solution

  
  

Content Recommendation Engine Filtering Approach Outlook

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  Collaborative Filtering

  
  


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  Content-Based Filtering

  
  

Content Recommendation Engine Organization Size Outlook

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  Small & Medium Enterprises

  
  


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  Large Enterprises

  
  

Content Recommendation Engine Regional Outlook

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  North America

  
  

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  US

  
  


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  Canada

  
  

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  Europe

  
  

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  Germany

  
  


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  France

  
  


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  UK

  
  


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  Italy

  
  


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  Spain

  
  


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  Rest of Europe

  
  

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  Asia-Pacific

  
  
  
  
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    China

    
    
  
  
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    Japan

    
    
  
  
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    India

    
    
  
  
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    Australia

    
    
  
  
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    South Korea

    
    
  
  
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    Australia

    
    
  
  
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    Rest of Asia-Pacific

    
    
  
  
  
  


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  Rest of the World

  
  
  
  
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    Middle East

    
    
  
  
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    Africa

    
    
  
  
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    Latin America