33.72% CAGR Growth of Content Recommendation Engine Market Growth Statistics to Make Multi-Billion Dollar Market during 2019 – 2026 | AWS, IBM, Taboola, Outbrain, Dynamic Yield

BusinessIndustryReports has recently broadcasted a new study to its broad research portfolio, which is titled as “Global Content Recommendation Engine Market” Research Report 2019 provides an in-depth analysis of the Content Recommendation Engine with the forecast of market size and growth. The analysis includes addressable market, market by volume, market share by business type and by segment (external and in-house).The research study examines the Content Recommendation Engine on the basis of a number of criteria, such as the product type, application, and its geographical presence.

Global Content Recommendation Engine Market Overview:

The report spread across 200 pages is an overview of the Global Content Recommendation Engine Market Report 2019. The Global Content Recommendation Engine Market is projected to grow at a healthy growth rate from 2019 to 2026 according to new research. The study focuses on market trends, leading players, supply chain trends, technological innovations, key developments, and future strategies.

The Global Content Recommendation Engine Market valued approximately USD 1.58 Billion in 2018 is anticipated to grow with a CAGR of 33.72% over the forecasted period of 2019-2026. The content recommendation engine is software that analyzes available data to make suggestions for something that a website user might be interested in, such as a book, a video or a job, among other possibilities.

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The Global Content Recommendation Engine Market is segmented on the basis of Component, Filtering Approach, Vertical and Region. Content Recommendation Engine market is cover distinctive segment market estimate, both volume and value, also cover diverse businesses customers' data, which is imperative for the makers.

Based on the Component, the Global Content Recommendation Engine Market is sub-segmented into Solution, Service and others. On the basis of Filtering Approach, the Global Content Recommendation Engine Market is classified into Collaborative, Content-Based, Hybrid and others. Based on the Vertical, the Global Content Recommendation Engine Market is sub-segmented into E-commerce, Media, Entertainment & Gaming, Retail, Hospitality, IT & Telecommunication, BFSI, Education & training, Healthcare & Pharmaceutical and others.

In terms of the geographic analysis, The Content Recommendation Engine Market in North America is expected to grow at the highest CAGR during the forecast period. Moreover, the presence of major players in the Content Recommendation Engine Market ecosystem results in the increasing adoption of these systems in North America.

Latest Industry News:

Amazon Web Services (AWS) (September 20, 2019) – Amazon Web Services, Inc. (AWS), an Amazon.com company, announced the general availability of G4 instances, a new GPU-powered Amazon Elastic Compute Cloud (Amazon EC2) instance designed to help accelerate machine learning inference and graphics-intensive workloads, both of which are computationally demanding tasks that benefit from additional GPU acceleration. G4 instances provide the industry’s most cost-effective machine learning inference for applications, like adding metadata to an image, object detection, recommender systems, automated speech recognition, and language translation. G4 instances also provide a very cost-effective platform for building and running graphics-intensive applications, such as remote graphics workstations, video transcoding, photo-realistic design, and game streaming in the cloud.

“We focus on solving the toughest challenges that hold our customers back from taking advantage of compute intensive applications,” said Matt Garman, Vice President, Compute Services, AWS. “AWS offers the most comprehensive portfolio to build, train, and deploy machine learning models powered by Amazon EC2’s broad selection of instance types optimized for different machine learning use cases. With new G4 instances, we’re making it more affordable to put machine learning in the hands of every developer. And with support for the latest video decode protocols, customers running graphics applications on G4 instances get superior graphics performance over G3 instances at the same cost.”

Purchase this report online with 200 Pages, List of Tables & Figures and in-depth Table of Contents on “Global Content Recommendation Engine Market Report 2019” @ https://www.businessindustryreports.com/buy-now/167835/single

Top Leading Key in Players Global Content Recommendation Engine Market: IBM, Amazon Web Services (AWS), Revcontent, Taboola, Outbrain, Cxense, Dynamic Yield, Curata and others.  .

With the presence of a large pool of participants, the Global Content Recommendation Engine Market is displaying a highly competitive business landscape, finds a new research report by Business Industry Reports (BIR). IBM, Amazon Web Services (AWS), Revcontent, Taboola, Outbrain, Cxense, Dynamic Yield, Curata are some of the key vendors of Content Recommendation Engine across the world. These players across Content Recommendation Engine Market are focusing aggressively on innovation, as well as on including advanced technologies in their existing products.

Region segment: Content Recommendation Engine Market report is segmented into several key regions, with sales, revenue, market share (%) and growth Rate (%) of Content Recommendation Engine in these regions, from 2013 to 2026 (forecast), covering: North America, Europe, Asia Pacific, Middle East & Africa and South America

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Major Points in Table of Contents:

Global Content Recommendation Engine Market Report 2019

1 Executive Summary

2 Global Content Recommendation Engine Market Definition and Scope

3 Global Content Recommendation Engine Market Dynamics

4 Global Content Recommendation Engine Market Industry Analysis

5 Global Content Recommendation Engine Market, by Component

6 Global Content Recommendation Engine Market, by Filtering Approach

7 Global Content Recommendation Engine Market, by Vertical

8 Global Content Recommendation Engine Market, by Regional Analysis

9 Competitive Intelligence

10 Research Process

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