Table of Content

1 INTRODUCTION
1.1 Study Assumptions
1.2 Scope of the Study


2 RESEARCH METHODOLOGY


3 EXECUTIVE SUMMARY


4 MARKET DYNAMICS
4.1 Market Overview
4.2 Market Drivers
4.2.1 Adoption of AI Based Recommendation Engine Solutions
4.2.2 Growing Demand for Enhancing the Customer Experience
4.3 Market Restraints
4.3.1 Lack of Skills and Expertise Across Emerging Verticles
4.4 Industry Attractiveness - Porter’s Five Force Analysis
4.4.1 Threat of New Entrants
4.4.2 Bargaining Power of Buyers/Consumers
4.4.3 Bargaining Power of Suppliers
4.4.4 Threat of Substitute Products
4.4.5 Intensity of Competitive Rivalry
4.5 Technology Snapshot
4.5.1 Big Data + Machine Learning
4.5.2 Collective Intelligence Algorithms
4.5.3 Contextual Algorithms
4.5.4 Personalization Algorithms


5 MARKET SEGMENTATION
5.1 By Size of the Organization
5.1.1 Large Enterprise
5.1.2 Small and Medium Enterprise
5.2 By Types
5.2.1 Collaborative Filtering
5.2.2 Content-Based Filtering
5.2.3 Hybrid Recommendation Systems
5.2.4 Other Types
5.3 By End-user Industry
5.3.1 IT & Telecommunication
5.3.2 BFSI
5.3.3 Retail
5.3.4 Industrial
5.3.5 Media &?Entertainment
5.3.6 Healthcare
5.3.7 Other End-user Industries
5.4 Geography
5.4.1 North America
5.4.2 Europe
5.4.3 Asia-Pacific
5.4.4 Rest of the World


6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 IBM Corp.
6.1.2 Amazon Web Services Inc.
6.1.3 Cloudera Inc.
6.1.4 Revcontent LLC
6.1.5 Recombee
6.1.6 Recolize GmbH
6.1.7 Microsoft Corp.
6.1.8 SAP SE
6.1.9 Salesforce.com inc.
6.1.10 Kibo Software Inc
6.1.11 Certona Corporation


7 INVESTMENT ANALYSIS


8 MARKET OPPORTUNITIES AND FUTURE TRENDS