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

  • ID: 4481359
  • Report
  • Region: Global
  • 145 pages
  • Markets and Markets
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Market for Recommendation Engine Based on AI Expected to Grow to USD 4414.8 Million by 2022, at a CAGR of 40.7%

FEATURED COMPANIES

  • AWS
  • Google
  • IBM
  • Intel
  • Oracle
  • SAP
  • MORE

"The recommendation engine market based on AI, is projected to grow at a CAGR of 40.7% during the forecast period"

The market for recommendation engine 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 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). However, designing of targeted campings, 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.

Further, concerns related to infrastructure compatibility is expected to be a major restraint for the growth of recommendation engine market. As technological compatibility 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.

"The hybrid recommendation type is expected to grow at the fastest rate during the forecast period"

Based on type, the recommendation engine market, include collaborative filtering, content-based filtering, and hybrid recommendation. 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 APAC region is expected to witness the highest growth rate during the forecast period"

Asia Pacific (APAC) 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 have 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.

In the process to determine and verify the market size for several segments and subsegments 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%

The major vendors in the global recommendation engine market based on AI, are IBM (US), SAP (Germany), Salesforce (US), HPE (US), Oracle (US), Google (US), Microsoft (US), Intel (US), AWS (US), and Sentient Technologies (US).

  • 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)
  • Value-added Resellers (VARs)

Research Coverage

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. Applications are segmented into personalized campaigns and customer discovery, product planning, strategy and operations planning, and proactive asset management. The technologies involved in the recommendation engine market are context aware and geospatial aware. The end-users segment includes BFSI, retail, healthcare, media and entertainment, transportation, and others (telecom, energy and utilities, manufacturing, and education). On the basis of regions, recommendation engine is segmented into North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and Latin America.

The report is expected to help the market leaders and new entrants in the recommendation engine market based on AI, in the following ways:

1. The report segments the market into various subsegments, hence it covers the market comprehensively. The report provides the closest approximations of the revenue numbers for the overall market and subsegments. The market numbers are further split into different application areas and regions.

2. The report helps to understand the overall growth of the market. It provides information on the key market drivers, restraints, challenges, and opportunities.

3. The report helps to better understand competitors and gain more insights to strengthen organizations position in the market. In addition, the study presents the positioning of the key players based on their product offerings and business strategies.

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FEATURED COMPANIES

  • AWS
  • Google
  • IBM
  • Intel
  • Oracle
  • SAP
  • MORE

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
     11.1 Introduction
     11.2 North America
             11.2.1 United States
             11.2.2 Canada
     11.3 Europe
             11.3.1 United Kingdom
             11.3.2 Germany
             11.3.3 Switzerland
             11.3.4 Rest of Europe
     11.4 Asia Pacific
             11.4.1 China
             11.4.2 Japan
             11.4.3 Rest of Asia Pacific
     11.5 Middle East and Africa
             11.5.1 Middle East
             11.5.2 Africa
     11.6 Latin America
             11.6.1 Brazil
             11.6.2 Rest of Latin America

12 Competitive Landscape
     12.1 Overview
     12.2 Top Players Operating in the AI Recommendation Engine Market
     12.3 Competitive Scenario
             12.3.1 New Product Launches/Product Enhancements
             12.3.2 Partnerships, Agreements, and Collaborations
             12.3.3 Mergers and Acquisitions
             12.3.4 Business Expansions

13 Company Profiles
     13.1 Introduction
(Business Overview, Products/Solutions and Services Offered, Recent Developments, SWOT Analysis, View)*
     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
*Details on Business Overview, Products/Solutions and Services Offered, Recent Developments, SWOT Analysis, View Might Not Be Captured in Case of Unlisted Companies.
     13.12 Key Innovators
             13.12.1 Fuzzy.AI
             13.12.2 Infinite Analytics

List of Tables
Table 1 Global AI Recommendation Engine Market Size and Growth Rate, 2015-2022 (USD Million, Y-O-Y %)
Table 2 AI Recommendation Engine Market Size, By Type, 2015-2022 (USD Million)
Table 3 Collaborative Filtering: Market Size, By Region, 2015-2022 (USD Million)
Table 4 Content-Based Filtering: Market Size, By Region, 2015-2022 (USD Million)
Table 5 Hybrid Recommendation: Market Size, By Region, 2015-2022 (USD Million)
Table 6 AI Recommendation Engine Market Size, By Technology, 2015-2022 (USD Million)
Table 7 Context Aware: Market Size, By Type, 2015-2022 (USD Million)
Table 8 Context Aware: Market Size, By Region, 2015-2022 (USD Million)
Table 9 Machine Learning and Deep Learning Market Size, By Region, 2015-2022 (USD Million)
Table 10 Natural Language Processing Market Size, By Region, 2015-2022 (USD Million)
Table 11 Geospatial Aware: Market Size, By Region, 2015-2022 (USD Million)
Table 12 AI Recommendation Engine Market Size, By Application, 2015-2022 (USD Million)
Table 13 Personalized Campaigns and Customer Discovery: Market Size, By Region, 2015-2022 (USD Million)
Table 14 Product Planning: Market Size, By Region, 2015-2022 (USD Million)
Table 15 Strategy and Operations Planning: Market Size, By Region, 2015-2022 (USD Million)
Table 16 Proactive Asset Management: Market Size, By Region, 2015-2022 (USD Million)
Table 17 Others: Market Size, By Region, 2015-2022 (USD Million)
Table 18 AI Recommendation Engine Market Size, By Deployment Mode, 2015-2022 (USD Million)
Table 19 Cloud: Market Size, By Region, 2015-2022 (USD Million)
Table 20 On-Premises: Market Size, By Region, 2015-2022 (USD Million)
Table 21 AI Recommendation Engine Market Size, By End-User, 2015-2022 (USD Million)
Table 22 Retail: Market Size, By Region, 2015-2022 (USD Million)
Table 23 Media and Entertainment: Market Size, By Region, 2015-2022 (USD Million)
Table 24 Transportation: Market Size, By Region, 2015-2022 (USD Million)
Table 25 Banking, Financial Services, and Insurance: Market Size, By Region, 2015-2022 (USD Million)
Table 26 Healthcare: Market Size, By Region, 2015-2022 (USD Million)
Table 27 Others: Market Size, By Region, 2015-2022 (USD Million)
Table 28 AI Recommendation Engine Market Size, By Region, 2015-2022 (USD Million)
Table 29 Data Traffic in North America, 2016-2022 (Petabytes/Month)
Table 30 Major Eretailers in North America
Table 31 North America: Market Size, By Country, 2015-2022 (USD Million)
Table 32 North America: Market Size, By Type, 2015-2022 (USD Million)
Table 33 North America: Market Size, By Technology, 2015-2022 (USD Million)
Table 34 North America: Context Aware Market Size, By Type, 2015-2022 (USD Million)
Table 35 North America: Market Size, By Application, 2015-2022 (USD Million)
Table 36 North America: Market Size, By Deployment Mode, 2015-2022 (USD Million)
Table 37 North America: Market Size, By End-User, 2015-2022 (USD Million)
Table 38 Data Traffic in Europe, 2016-2022 (Petabytes/Month)
Table 39 Major Eretailers in Europe
Table 40 Europe: Market Size, By Country, 2015-2022 (USD Million)
Table 41 Europe: Market Size, By Type, 2015-2022 (USD Million)
Table 42 Europe: Market Size, By Technology, 2015-2022 (USD Million)
Table 43 Europe: Context Aware AI Recommendation Engine Market Size, By Type, 2015-2022 (USD Million)
Table 44 Europe: Market Size, By Application, 2015-2022 (USD Million)
Table 45 Europe: Market Size, By Deployment Mode, 2015-2022 (USD Million)
Table 46 Europe: Market Size, By End-User, 2015-2022 (USD Million)
Table 47 Data Traffic in Asia Pacific, 2016-2022 (Petabytes/Month)
Table 48 Major Eretailers in Asia Pacific
Table 49 Asia Pacific: Market Size, By Country, 2015-2022 (USD Million)
Table 50 Asia Pacific: Market Size, By Type, 2015-2022 (USD Million)
Table 51 Asia Pacific: Market Size, By Technology, 2015-2022 (USD Million)
Table 52 Asia Pacific: Context Aware AI Recommendation Engine Market Size, By Type, 2015-2022 (USD Million)
Table 53 Asia Pacific: Market Size, By Application, 2015-2022 (USD Million)
Table 54 Asia Pacific: Market Size, By Deployment Mode, 2015-2022 (USD Million)
Table 55 Asia Pacific: Market Size, By End-User, 2015-2022 (USD Million)
Table 56 Data Traffic in Middle East and Africa, 2016-2022 (Petabytes/Month)
Table 57 Middle East and Africa: Market Size, By Region, 2015-2022 (USD Million)
Table 58 Middle East and Africa: Market Size, By Type, 2015-2022 (USD Million)
Table 59 Middle East and Africa: Market Size, By Technology, 2015-2022 (USD Million)
Table 60 Middle East and Africa: Context Aware AI Recommendation Engine Market Size, By Type, 2015-2022 (USD Million)
Table 61 Middle East and Africa: Market Size, By Application, 2015-2022 (USD Million)
Table 62 Middle East and Africa: Market Size, By Deployment Mode, 2015-2022 (USD Million)
Table 63 Middle East and Africa: Market Size, By End-User, 2015-2022 (USD Million)
Table 64 Data Traffic in Latin America, 2016-2022 (Petabytes/Month)
Table 65 Major Eretailers in Latin America
Table 66 Latin America: Market Size, By Country, 2015-2022 (USD Million)
Table 67 Latin America: Market Size, By Type, 2015-2022 (USD Million)
Table 68 Latin America: Market Size, By Technology, 2015-2022 (USD Million)
Table 69 Latin America: Context Aware AI Recommendation Engine Market Size, By Type, 2015-2022 (USD Million)
Table 70 Latin America: Market Size, By Application, 2015-2022 (USD Million)
Table 71 Latin America: Market Size, By Deployment Mode, 2015-2022 (USD Million)
Table 72 Latin America: Market Size, By End-User, 2015-2022 (USD Million)
Table 73 New Product Launches/Product Enhancements, 2016-2017
Table 74 Partnerships, Agreements, and Collaborations, 2015-2017
Table 75 Mergers and Acquisitions, 2016-2017
Table 76 Business Expansions, 2017

List of Figures
Figure 1 AI Recommendation Engine Market Segmentation
Figure 2 Global Market: Research Design
Figure 3 Breakdown of Primary Interviews: By Company, Designation, and Region
Figure 4 Data Triangulation
Figure 5 Market Size Estimation Methodology: Bottom-Up Approach
Figure 6 Market Size Estimation Methodology: Top-Down Approach
Figure 7 Market Snapshot By Type (2017 vs 2022)
Figure 8 Market Snapshot By Deployment Mode
Figure 9 Market Snapshot By Technology
Figure 10 Market Snapshot By Application (2017 vs 2022)
Figure 11 Market Snapshot By End-User
Figure 12 Market Regional Snapshot
Figure 13 Increasing Focus on Enhancing the Customer Experience is Expected to Drive the Growth of the AI Recommendation Engine Market During the Forecast Period
Figure 14 Media and Entertainment End-User is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 15 Asia Pacific is Expected to Have the Fastest Growth Rate During the Forecast Period
Figure 16 Asia Pacific is Expected to Be the Best Market to Investment In, in the Next 5 Years
Figure 17 AI Recommendation Engine: Data Filtering Models
Figure 18 AI Recommendation Engine Market: Drivers, Restraints, Opportunities, and Challenges
Figure 19 Hybrid Recommendation Segment is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 20 Geospatial Aware Segment is Expected to Exhibit A Higher CAGR During the Forecast Period
Figure 21 Natural Language Processing Segment is Expected to Exhibit A Higher CAGR During the Forecast Period
Figure 22 Strategy and Operations Planning Application is Expected to Exhibit the Highest CAGR During the Forecast Period
Figure 23 Cloud Deployment Mode is Expected to Exhibit A Higher CAGR During the Forecast Period
Figure 24 Media and Entertainment End-User is Expected to Exhibit the Highest CAGR During the Forecast Period
Figure 25 Asia Pacific is Expected to Have the Highest CAGR in the AI Recommendation Engine Market During the Forecast Period
Figure 26 Asia Pacific is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 27 North America: Market Snapshot
Figure 28 Media and Entertainment End-User is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 29 Media and Entertainment End-User is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 30 Asia Pacific: Market Snapshot
Figure 31 Media and Entertainment End-User is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 32 Media and Entertainment End-User is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 33 Media and Entertainment End-User is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 34 Key Developments By the Leading Players in the AI Recommendation Engine Market
Figure 35 Geographic Revenue Mix of Market Players
Figure 36 IBM: Company Snapshot
Figure 37 IBM: SWOT Analysis
Figure 38 Google: Company Snapshot
Figure 39 Google: SWOT Analysis
Figure 40 AWS: Company Snapshot
Figure 41 AWS: SWOT Analysis
Figure 42 Microsoft: Company Snapshot
Figure 43 Microsoft: SWOT Analysis
Figure 44 Salesforce: Company Snapshot
Figure 45 Salesforce: SWOT Analysis
Figure 46 HPE: Company Snapshot
Figure 47 Oracle: Company Snapshot
Figure 48 Intel: Company Snapshot
Figure 49 SAP: Company Snapshot

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  • AWS
  • Fuzzy.AI
  • Google
  • HPE
  • IBM
  • Infinite Analytics
  • Intel
  • Microsoft
  • Oracle
  • SAP
  • Salesforce
  • Sentient Technologies
Note: Product cover images may vary from those shown
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