Content Recommendation Engine Market Overview:
The global report on the Content Recommendation Engine Market predicts a 30% CAGR during the forecast period of 2018 to 2023, where the market valuation would touch a mark of around USD 6 billion. Market Research Future (MRFR) identifies the growing demand for personalized content as one of the major traction providers. Among others, rising competition in the market, demand from major companies who wish to bolster their online presence, rapidly developing e-commerce sites, and demand for search engine optimization are expected to provide substantial support to the market.
Content Recommendation Engine Market Segmentation:
The global market report on the content recommendation engine market depends on a segmentation that includes a proper study of component, organization size, filtering approach, and vertical.
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By component, the content recommendation engine market includes segments like solution and service.
By organization size, the study of the content recommendation engine market covers small & medium enterprises and large enterprises. The large enterprises are investing much to support their business deals, which is bolstering the content recommendation engine market growth.
By filtering approach, the report on the content recommendation engine market includes content-based filtering, collaborative filtering, and hybrid filtering.
By vertical, the understanding of the content recommendation engine market includes e-commerce, media, industrial, education & training, retailer and consumer goods, entertainment & gaming, BFSI, IT & telecommunication, and healthcare & pharmaceuticals.
Content Recommendation Engine Market Regional Analysis:
Major players are from North America, which would go in favor of the North American market and help it retain its market presence during the forecast period. A growing need to analyze user data is expected to take the European market forward.
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Content Recommendation Engine Market Key Players:
- 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)
These companies mainly focus on improving their market stand using measures like a merger, acquisition, innovation, launching of product, research, and others. But these also improve the global market results. MRFR analyzed the latest moves made by these companies to understand how the market is getting backed by various trends.
Industry News:
Recently, Bolo Indya, a Gurugram-based user-generated content platform, announced its success in raising $300,000 Pre-Series A1 round of funding that was getting helmed by India Accelerator, Eagle10 Ventures, and HNIs. The company is planning to invest the fund in enhancing the development of language evangelists, personalization and recommendation engine and improve the team to expand the portfolio and quicken the pace of product development.
In April 2020, CNN announced the acquisition of Canopy, an all-purpose content personalization structure that relies on on-device machine learning, human curation, and differential privacy to assist its readers discover things they prefer all the while putting a lid on their private information. This new acquisition is in sync with the news agency’s endeavors to stay abreast in a market that is primarily governed by Facebook and Apple. Experts believe that the startup will emerge as an anchoring part of CNN’s new projects.
The COVID-19 crisis has impacted several industries and the content management system is not any exception. A huge amount of data on the disease is getting churned out each minute and companies are trying to filter out the fake and hook the best to get more audience. This might help the market register better growth.
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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
3 Market Research Methodology
3.1 Research Process
3.2 Secondary Research
3.3 Primary Research
3.4 Forecast Model
4 Market Landscape
Continued…
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