Description:Global Recommendation Engine Market is expected to reach US$ XX Million by 2026 from US$ XX Million in 2019 at a CAGR of XX%.
The report includes the analysis of impact of COVID-19 lock-down on the revenue of market leaders, followers, and disrupters. Since lock down was implemented differently in... moreGlobal Recommendation Engine Market is expected to reach US$ XX Million by 2026 from US$ XX Million in 2019 at a CAGR of XX%.
The report includes the analysis of impact of COVID-19 lock-down on the revenue of market leaders, followers, and disrupters. Since lock down was implemented differently in different regions and countries, impact of same is also different by regions and segments. The report has covered the current short term and long term impact on the market, same will help decision makers to prepare the outline for short term and long term strategies for companies by region.
Global Recommendation Engine Market
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Recommendation Engine Market is segmented by type, technology, application, deployment type, end user and geography. Based on Type market is classified into Hybrid Recommendation, Collaborative Filtering, Content-Based Filtering. Technology is divided into Geospatial Aware, Context aware. Application of the market are Proactive Asset Management, Personalized Campaigns & Customer Discovery, Strategy & Operation Planning, and Product Planning. Deployment mode is split into On-premises, Cloud. End user is divided into BFSI, Healthcare, Retail, Transportation, and Media & Entertainment. Region wise divided into North America, Europe, Asia Pacific, Middle East & Africa and Latin America.
Designing of targeted camping’s, as well as relevant product and content recommendations, could assist institutions engage more customers. So, review of customer data here plays a vital role to apprehend the customer behaviour and preferences. Furthermore, to analyse a important volume of data and automate the manual and tedious process of designing recommendations, companies need to design and lay out a plan of action. Could be accomplished by appropriate developing of AI recommendation engine solutions into their operations. Moreover, concerns associated to infrastructure compatibility is anticipated to be a main restraint for the rising of recommendation engine market. Technological similarity is linked to proper implementation of AI-based recommendation engines, improper implementation could lead to damages in the working mechanism of AI recommendation engine software and solutions.
Based on type, the hybrid recommendation type benefits different organizations combine 2 distinct data filtering types to accomplish larger accurate recommendations. On the basis of deployment model, cloud deployment mode segment is dominating larger market size and is expected to grow at a higher CAGR during the forecast period. Cloud-based solutions offer large and agile solutions to the end-users in the recommendation engine market.
On the basis of end user, retail is widely used. Retail end-user is expected to be the highest market during the forecast period, in terms of revenue, while the media and entertainment end-user is projected to increasing at the highest CAGR during the forecast period. Both end-users includes used recommendation engines powered by AI to achieve benefits, such as customer retention and increased revenue and Return on Investment (RoI), by deploying AI-powered recommendation engines.
In terms of geography, North American region is dominating largest market size during the forecast period. The major driving factors for the market are rising in need to understand the customer behaviour and preferences and the need to achieve business insights from a huge number of data to formulate various customer engagement strategies.
Key players operates on the market are, Salesforce, HPE, AWS, Oracle Corporation, Intel, Google, IBM, Microsoft, Sentient Technologies, SAP.
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Global Recommendation Engine Market, by Type
• Hybrid Recommendation
• Collaborative Filtering
• Content-Based Filtering
Global Recommendation Engine Market, by Technology
• Geospatial Aware
• Context Aware.
Global Recommendation Engine Market, by Application
• On-Premises
• Cloud
Global Recommendation Engine Market, by End-user
• BFSI
• Healthcare
• Retail
• Transportation
• Media & Entertainment
Global Recommendation Engine Market, by Geographies
• North America
• Europe
• Asia Pacific
• Middle East & Africa
• Latin America
The major key players that influence growth of Global Recommendation Engine Market includes:
• Salesforce
• HPE
• AWS
• Oracle Corporation
• Intel
• Google
• IBM
• Microsoft
• Sentient Technologies
• SAP
• Fuzzy.AI
• Infinite Analytics
• Adobe Inc.
• Amazon Web Services, Inc.
• Dynamic Yield, Inc.
• Evergage Inc.
• Google LLC
• International Business Machines Corp.
• Kibo Software Inc.
• Qubit... less
