Global Recommendation Engine Market 2018-2022 - Key innovators Include Fuzzy.AI & Infinite Analytics
DUBLIN, April 4, 2018 /PRNewswire/ --
The "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" report has been added to ResearchAndMarkets.com's offering.
The global recommendation engine market 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.
The major driving factors for the market are growth in focus toward enhancing the customer experience and upsurge in rate of digitalization.
The collaborative filtering segment is expected to account for the largest market size during the forecast period. The collaborative filtering technique uses a large volume of information, such as users' behavior, preferences, and activities from the past records to segment users based on similarity of likings.
Several industry verticals, such as retail, media and entertainment, transportation, Banking, Financial Services, and Insurance (BFSI), healthcare, energy and utilities, manufacturing, and education have deployed recommendation engines powered by AI for various applications, including personalized campaigns and customer discovery, product planning, strategy and operations planning, and proactive asset management.
The cloud deployment mode segment is expected to account for the larger market size and is expected to grow at a higher CAGR during the forecast period. The cloud-based solutions offer wide and agile solutions to the end-users in the recommendation engine market.
The context aware segment is expected to account for the larger market size during the forecast period. On contrary, the geospatial aware segment is expected to be the faster growing technology type during the forecast period due to the need to understand users' behavior and preferences based on the past location records.
The personalized campaigns and customer discovery application is expected to account for the largest market size during the forecast period, while the strategy and operations planning application is expected to have the highest CAGR during the forecast period. Various end-users have included recommendation engines based on AI for product planning, proactive asset management, intelligent data collection, and cross-layer network-wide correlation of monitoring data.
The retail end-user is expected to be the highest contributor during the forecast period, in terms of revenue, while the media and entertainment end-user is projected to grow at the highest CAGR during the forecast period. Both end-users have 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 addition, growth in government support toward enhancing digitalization across various countries coupled with increase in the eCommerce market has driven the demand for recommendation engines. The other end-users, such as transportation, BFSI, healthcare, energy and utilities, manufacturing, and education have contributed significantly to the growth of the recommendation engine market based on AI, due to an increased focus of the companies to enhance customer experience on the basis of their purchasing and searching pattern.
The major vendors offering recommendation engine based on AI, across the globe include IBM (US), SAP (Germany), Salesforce (US), HPE (US), Oracle (US), Google (US), Microsoft (US), Intel (US), AWS (US), and Sentient Technologies (US).
Key Topics Covered:
1 Introduction
1.1 Objectives of the Study
1.2 Market Definition
1.3 Years Considered for the Study
1.4 Currency
1.5 Stakeholders
2 Research Methodology
2.1 Research Data
2.1.1 Secondary Data
2.1.2 Primary Data
2.1.2.1 Breakdown of Primaries
2.1.2.2 Key Industry Insights
2.2 Market Size Estimation
2.3 Research Assumptions
2.3.1 AI Recommendation Engine Market: Assumptions
2.4 Limitations
3 Executive Summary
4 Premium Insights
4.1 Attractive Market Opportunities in the AI Recommendation Engine Market
4.2 AI Market By End-User
4.3 AI Market By Region
4.4 Market Investment Scenario
5 Market Overview and Industry Trends
5.1 Introduction
5.2 AI Recommendation Engine and Data Filtering Models
5.3 AI Recommendation Engine Market: Use Cases
5.3.1 Use Case #1: AI-Powered Recommendation Solution to Increase Revenue in the Ecommerce Sector
5.3.2 Use Case #2: AI-Powered Customer Relationship Management (CRM) Solution to Drive Customer Engagement in the Hospitality Sector
5.3.3 Use Case: AI-Powered Recommendation Solution to Increase Customer Engagement in the Ecommerce Sector
5.3.4 Use Case: AI-Powered Recommendation Solution to Generate More Orders and Increase Revenue in the Retail Sector
5.4 Market Dynamics
5.4.1 Drivers
5.4.1.1 Increasing Focus on Enhancing the Customer Experience
5.4.1.2 Growing Trend of Digitalization
5.4.2 Restraints
5.4.2.1 Concerns Over Infrastructure Compatibility
5.4.3 Opportunities
5.4.3.1 Growing Use of the Deep Learning Technology in AI Recommendation Engine Solutions
5.4.3.2 Increasing Demand to Analyze Large Volumes of Data
5.4.4 Challenges
5.4.4.1 Concerns Over Accessing Customers' Personal Data
5.4.4.2 Lack of Skills and Expertise
6 AI Recommendation Engine Market, By Type
6.1 Introduction
6.2 Collaborative Filtering
6.3 Content-Based Filtering
6.4 Hybrid Recommendation
7 Market, By Technology
7.1 Introduction
7.2 Context Aware
7.2.1 Machine Learning and Deep Learning
7.2.2 Natural Language Processing
7.3 Geospatial Aware
8 AI Recommendation Engine Market, By Application
8.1 Introduction
8.2 Personalized Campaigns and Customer Discovery
8.3 Product Planning
8.4 Strategy and Operations Planning
8.5 Proactive Asset Management
8.6 Others
9 AI Recommendation Engine Market, By Deployment Mode
9.1 Introduction
9.2 Cloud
9.3 On-Premises
10 AI Recommendation Engine Market, By End-User
10.1 Introduction
10.2 Retail
10.3 Media and Entertainment
10.4 Transportation
10.5 Banking, Financial Services, and Insurance
10.6 Healthcare
10.7 Others
11 AI Recommendation Engine Market, By Region
12 Competitive Landscape
12.1 Overview
12.2 Top Players Operating in the AI Recommendation Engine Market
12.3 Competitive Scenario
13 Company Profiles
13.1 Introduction
13.2 IBM
13.3 Google
13.4 AWS
13.5 Microsoft
13.6 Salesforce
13.7 Sentient Technologies
13.8 HPE
13.9 Oracle
13.10 Intel
13.11 SAP
13.12 Key Innovators
13.12.1 Fuzzy.AI
13.12.2 Infinite Analytics
For more information about this report visit https://www.researchandmarkets.com/research/vvvw5l/global?w=5
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