PUNE, India, March 19, 2018 /PRNewswire/ --
ReportsnReports.com adds Recommendation Engine Market is forecast to reach $4414.8 million by 2022 from $801.1 million in 2017 at a CAGR of 40.7% during (2017-2022) driven by increase in focus toward enhancing consumer experience and growth in trend of digitalization, surge in demand to analyze large volumes of data and increase in use of deep learning technology in recommendation solution.
Browse 76 Market Data Tables and 49 Figures spread through 143 Pages and in-depth TOC on "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" http://www.reportsnreports.com/reports/1399076-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-for-st-to-2022.html .
The major vendors in the global recommendation engine market based on AI, include IBM (US), SAP (Germany), Salesforce (US), HPE (US), Oracle (US), Google (US), Microsoft (US), Intel (US), AWS (US), and Sentient Technologies (US).
Asia-Pacific is expected to grow at the highest CAGR in the global recommendation engine market during the forecast period. Moreover, several factors, such as rapid expansion of local enterprises, increase in infrastructure developments, and growth in need to analyze customer data has driven the adoption of recommendation engines across different end-users. The North American region is expected to account for the largest market size during the forecast period. The major driving factors for the market are increase in need to understand the customer behavior and preferences and the need to achieve business insights from a large number of data to formulate various customer engagement strategies.
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The target audience for recommendation engine market includes AI recommendation engine software and platform providers, Venture capitalists and angel investors, Information Technology (IT) management directors/managers, Government organizations, Research organizations, Consultants/advisory firms, IT governance directors/managers, AI system integrators, Managed Service Providers (MSPs) and Value-added Resellers (VARs). The growth in focus toward enhancing the customer experience is a major factor driving the growth of the recommendation engine market. Moreover, enhancing customer experience is important to achieve customer engagement and retention, thereby achieving higher sales and Return on Investment (RoI).
Based on type, the Recommendation Engine Market includes collaborative filtering, content-based filtering, and hybrid recommendation. The hybrid recommendation type is expected to grow at the fastest rate during the forecast period. The hybrid recommendation type helps various organizations combine 2 different data filtering types to achieve more accurate recommendations. Hence, this contributes to the adoption of hybrid recommendation type in the AI-powered recommendation systems.
The collaborative filtering type segment is expected to be the largest contributor in the recommendation engine market during the forecast period. However, designing of targeted camping's, as well as relevant product and content recommendations, could help organizations engage more customers. Hence, analysis of customer data here plays a vital role to understand the customer behavior and preferences. Furthermore, to analyze a large volume of data and automate the manual and tedious process of designing recommendations, enterprises need to design and lay out a plan of action. This could be accomplished by appropriate implementation of AI recommendation engine solutions into their operations.
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The recommendation engine market powered by AI has been segmented on the basis of types (collaborative filtering, content-based filtering, and hybrid recommendation), deployment modes, technologies, applications, end-users, and regions. The recommendation solutions help AI recommendation software and platform providers; venture capitalists/angel investors; IT management directors/managers; and BFSI, healthcare, retail, media and entertainment, and government organizations to improve business operations, enhance decision-making, and reduce costs. The deployment modes in the recommendation engine market are cloud and on-premises.
In the process to determine and verify the recommendation engine market size for several segments and sub segments gathered through secondary research, extensive primary interviews were conducted with key people.
- By Company Type: Tier 1 - 18%, Tier 2 - 47%, and Tier 3 - 35%
- By Designation: C-level - 22%, Director level - 42%, and Others - 36%
- By Region: North America - 24%, Europe - 48%, APAC - 16%, and MEA - 12%
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