Content Recommendation Engine Market Analysis
The global content recommendation engine market is predicted to grow at a healthy CAGR between 2020- 2027, states the recent Market Research Future (MRFR) analysis. A recommendation engine, simply put, is software which examines accessible, structured data for making recommendations for information that a website user is interested in, like a job posting, a video, a book, and others. The recommendation engines are extensively used in content-based websites, across social media platforms, and e-commerce.
Various factors are fuelling the global content recommendation engine market share. As per the recent MRFR market estimates, such factors include the increasing focus to enhance customer experience, need to analyze large volumes of customer data, and rapid digitalization.
On the contrary, the impact of the COVID-19 pandemic, lack of technical expertise, issues related to infrastructural and technological compatibilities, and protecting sensitive information of customers may limit the global content recommendation engine market growth over the forecast period.
Content Recommendation Engine Market Segmentation
The MRFR report throws light on an inclusive segmental analysis of the global content recommendation engine market based on component, organization size, filtering approach, and vertical.
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By component, the global content recommendation engine market is segmented into service and solution. Of these, the service segment will lead the market over the forecast period.
By organization size, the global content recommendation engine market is segmented into large enterprises and small and medium enterprises. Of these, the SMES will dominate the market over the forecast period.
By filtering approach, the global content recommendation engine market is segmented into hybrid filtering, content-based filtering, and collaborative filtering. Of these, the collaborative filtering will spearhead the market over the forecast period.
By vertical, the global content recommendation engine market is segmented into healthcare and pharmaceuticals, education and training, BFSI, IT and telecommunication, retailer and consumer goods, entertainment and gaming, e-commerce, and industrial. Of these, the e-commerce segment will have the lions share in the market over the forecast period.
Content Recommendation Engine Market Regional Analysis
By region, the global content recommendation engine market covers the recent trends and growth opportunity across North America, Europe, the Asia Pacific (APAC), and Rest of the World (RoW). Of these, North America will dominate the market over the forecast period. The presence of several major players, advances in technology, focus of the major players to enhance the user experience on a website, advances in technology, and high emphasis on technology innovation are adding to the global content recommendation engine market growth in the region.
In Europe, the global content recommendation engine market is predicted to hold the second-largest share over the forecast period for the rising demand for analyzing a large amount of user data.
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In the APAC region, the global content recommendation engine market is predicted to have promising growth over the forecast period. Rapid digitalization, increase in shopping through e-commerce platforms, rise in over the top players, increase in the number of mobile users, and high investments made by different companies for deploying content recommendation engine are adding to the global content recommendation engine market growth in the region. Korea, Indonesia, Australia, India, Japan, and China have the utmost market share.
Content Recommendation Engine Market Key Players
The leading players profiled in the global content recommendation engine market report include ThinkAnalytics (UK), Taboola (US), Revcontent (US), Outbrain (US), Kibo Commerce (US), IBM (US), Dynamic Yield (US), Cxense (Norway), Curata (US), Certona (US), Boomtrain (US), and Amazon Web Services (US), among others.
The global content recommendation engine market is fragmented and also competitive with the presence of many domestic as well as international industry players. They have incorporated assorted strategies to stay at the forefront and also cater to the surging needs of the customers, including collaborations, partnerships, contracts, geographic expansions, new product launches, joint ventures, and more. Additionally, these players are also making heavy investments in research and development activities for strengthening their portfolios and also creating a hold in the market.
TABLE OF CONTENTS
1 Executive Summary
2 Scope Of The Report
2.1 Market Definition
2.2 Scope Of The Study
2.2.1 Research Objectives
2.2.2 Assumptions & Limitations
2.3 Markets Structure
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3 Market Research Methodology
3.1 Research Process
3.2 Secondary Research
3.3 Primary Research
3.4 Forecast Model
Continued...
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Recommendation Search Engine Market report published by Value Market Research, which studies the future outlook of the market.
It includes the size, share, growth, trends, key players, segments and regional analysis in detail during the study year 2019-2027.The research report also covers the comprehensive profiles of the key players in the market and an in-depth view of the competitive landscape worldwide.
The major players in the Recommendation Search Engine Market include IBM, SAP, Salesforce, HPE, Oracle, Google, Microsoft, Intel, AWS, and Sentient Technologies..
This section includes a holistic view of the competitive landscape that includes various strategic developments such as key mergers & acquisitions, future capacities, partnerships, financial overviews, collaborations, new product developments, new product launches, and other developments.Get more information on "Global Recommendation Search Engine Market Research Report" by requesting FREE Sample Copy at https://www.valuemarketresearch.com/contact/recommendation-search-engine-market/download-sampleMarket SegmentationThe broad Recommendation Search Engine Market has been sub-grouped into the Type, Deployment Model, Application, End-user and Region.
The report studies these subsets with respect to the geographical segmentation.
The strategists can gain a detailed insight and devise appropriate strategies to target specific market.
VedaJunction provides Customized Learning Plans based on recommendation engine and analytical tools using individual performance indicators and content profiles.
Smart algorithms based on mastery and reinforcement learning govern the Personalized Learning plans for users.
Modifies the learning plan based on learner performance and content profile and improves its knowledge of recommendations.
According to a new market research report "Recommendation Engine Market by Type (Collaborative Filtering, Content-Based Filtering, and Hybrid Recommendation), Deployment Mode (Cloud and On-Premises), Technology, Application, End-User, and Region - Global Forecast to 2022" published by MarketsandMarkets™, the recommendation engine market size based on AI, is expected to grow from USD 801.1 Million in 2017 to USD 4414.8 Million by 2022, at a Compound Annual Growth Rate (CAGR) of 40.7% during the forecast period.Increase in focus toward enhancing consumer experience and growth in trend of digitalization are some of the major driving factors for the recommendation engine market.
Collaborative filtering type used in recommendation engines filter data based on the similarity of user interests.
The market for media and entertainment is expected to grow at a faster rate, owing to the increase in need for deployment of recommendation engine solution either on cloud or on-premises.North America is expected to account for the largest market share during the forecast periodNorth America is the most competitive and rapidly changing region in the recommendation engine market across the globe.
North America, among all the regions, has witnessed maximum adoption of recommendation engine, due to the rise in focus of the companies to enhance consumer experience, growth in technological advancement, and surge in government support.
The US and Canada are projected to extensively implement recommendation engine solutions.
Currently servicing 7500 customers worldwide including 80% of global Fortune 1000 companies as clients.
