Global Recommendation Engine Market: Global Industry Analysis and Forecast (2017-2026) – by Type, Technology, Application, End-user and by Geography

Global Recommendation Engine Market: Global Industry Analysis and Forecast (2017-2026) – by Type, Technology, Application, End-user and by Geography

Market Scenario

Global Recommendation Engine Market is expected to reach US$ XX Million by 2026 from US$ XX Million in 2016 at a CAGR of XX%. Global Recommendation Engine Market 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.

The Scope of the Global Recommendation Engine Market

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

• Proactive Asset Management • Personalized Campaigns & Customer Discovery • Strategy & Operation Planning • Product Planning

Global Recommendation Engine Market, by Deployment Mode

• 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 Trade Surveillance Systems Market

Table of Contents

Global Recommendation Engine Market

1. Preface 1.1. Report Scope and Market Segmentation 1.2. Research Highlights 1.3. Research Objectives 1.4. Key Questions Answered 2. Assumptions and Research Methodology 2.1. Report Assumptions 2.2. Abbreviations Used 2.3. Research Methodology 3. Executive Summary 3.1. Global Recommendation Engine Market Size, by Market Value (US$ Mn) and Market, by Region 4. Market Overview 4.1. Introduction 4.2. Market Indicator 4.3. Drivers and Restraints Snapshot Analysis 4.3.1. Drivers 4.3.2. Restraints 4.3.3. Opportunities 4.3.4. Porter’s Analysis 4.3.5. Value Chain Analysis 4.3.6. SWOT Analysis 5. Global Recommendation Engine Market Analysis and Forecast 5.1. Global Recommendation Engine Market Analysis and Forecast 5.2. Global Recommendation Engine Market Size & Y-o-Y Growth Analysis 5.2.1. North America 5.2.2. Europe 5.2.3. Asia Pacific 5.2.4. Middle East & Africa 5.2.5. Latin America 6. Global Recommendation Engine Market Analysis and Forecast, by Type 6.1. Introduction and Definition 6.2. Key Findings 6.3. Global Recommendation Engine Market Value Share Analysis, by Type 6.4. Market Size (US$ Mn) Forecast, by Type 6.5. Global Recommendation Engine Market Analysis, by Type 6.6. Global Recommendation Engine Market Attractiveness Analysis, by Type 7. Global Recommendation Engine Market Analysis and Forecast, by End user 7.1. Introduction and Definition 7.2. Global Recommendation Engine Market Value Share Analysis, by End user 7.3. Market Size (US$ Mn) Forecast, by End user 7.4. Global Recommendation Engine Market Analysis, by End user 7.5. Global Recommendation Engine Market Attractiveness Analysis, by End user 8. Global Recommendation Engine Market Analysis and Forecast, by Deployment Type 8.1. Introduction and Definition 8.2. Global Recommendation Engine Market Value Share Analysis, by Deployment Type 8.3. Market Size (US$ Mn) Forecast, by Deployment Type 8.4. Global Recommendation Engine Market Analysis, by Deployment Type 8.5. Global Recommendation Engine Market Attractiveness Analysis, by Deployment Type 9. Global Recommendation Engine Market Analysis and Forecast, by Technology 9.1. Introduction and Definition 9.2. Global Recommendation Engine Market Value Share Analysis, by Technology 9.3. Market Size (US$ Mn) Forecast, by Technology 9.4. Global Recommendation Engine Market Analysis, by Technology 9.5. Global Recommendation Engine Market Attractiveness Analysis, by Technology 10. Global Recommendation Engine Market Analysis and Forecast, by Application 10.1. Introduction and Definition 10.2. Global Recommendation Engine Market Value Share Analysis, by Application 10.3. Market Size (US$ Mn) Forecast, by Application 10.4. Global Recommendation Engine Market Analysis, by Application 10.5. Global Recommendation Engine Market Attractiveness Analysis, by Application 11. Global Recommendation Engine Market Analysis, by Region 11.1. Global Recommendation Engine Market Value Share Analysis, by Region 11.2. Market Size (US$ Mn) Forecast, by Region 11.3. Global Recommendation Engine Market Attractiveness Analysis, by Region 12. North America Recommendation Engine Market Analysis 12.1. Key Findings 12.2. North America Recommendation Engine Market Overview 12.3. North America Recommendation Engine Market Value Share Analysis, by Type 12.4. North America Recommendation Engine Market Forecast, by Type 12.4.1. Hybrid Recommendation 12.4.2. Collaborative Filtering 12.4.3. Content-Based Filtering 12.5. North America Recommendation Engine Market Value Share Analysis, by End user 12.6. North America Recommendation Engine Market Forecast, by End user 12.6.1. BFSI 12.6.2. Healthcare 12.6.3. Retail 12.6.4. Transportation 12.6.5. Media & Entertainment 12.7. North America Recommendation Engine Market Value Share Analysis, by Deployment Type 12.8. North America Recommendation Engine Market Forecast, by Deployment Type 12.8.1. Cloud 12.8.2. On-Premises 12.9. North America Recommendation Engine Market Value Share Analysis, by Technology 12.10. North America Recommendation Engine Market Forecast, by Technology 12.10.1. Geospatial Aware 12.10.2. Context Aware. 12.11. North America Recommendation Engine Market Value Share Analysis, by Application 12.12. North America Recommendation Engine Market Forecast, by Application 12.12.1. Proactive Asset Management 12.12.2. Personalized Campaigns & Customer Discovery 12.12.3. Strategy & Operation Planning 12.12.4. Product Planning 12.13. North America Recommendation Engine Market Value Share Analysis, by Country 12.14. North America Recommendation Engine Market Forecast, by Country 12.14.1.1. U.S., 12.14.1.2. Canada, 12.15. North America Recommendation Engine Market Analysis, by Country 12.16. U.S. Recommendation Engine Market Forecast, by Type 12.16.1. Hybrid Recommendation 12.16.2. Collaborative Filtering 12.16.3. Content-Based Filtering 12.17. U.S. Recommendation Engine Market Forecast, by End user 12.17.1. BFSI 12.17.2. Healthcare 12.17.3. Retail 12.17.4. Transportation 12.17.5. Media & Entertainment 12.18. U.S. Recommendation Engine Market Forecast, by Deployment Type 12.18.1. Cloud 12.18.2. On-Premises 12.19. U.S. Recommendation Engine Market Forecast, by Technology 12.19.1. Geospatial Aware 12.19.2. Context Aware. 12.20. U.S. Recommendation Engine Market Forecast, by Application 12.20.1. Proactive Asset Management 12.20.2. Personalized Campaigns & Customer Discovery 12.20.3. Strategy & Operation Planning 12.20.4. Product Planning 12.21. Canada Recommendation Engine Market Forecast, by Type 12.21.1. Hybrid Recommendation 12.21.2. Collaborative Filtering 12.21.3. Content-Based Filtering 12.22. Canada Recommendation Engine Market Forecast, by End user 12.22.1. BFSI 12.22.2. Healthcare 12.22.3. Retail 12.22.4. Transportation 12.22.5. Media & Entertainment 12.23. Canada Recommendation Engine Market Forecast, by Deployment Type 12.23.1. Cloud 12.23.2. On-Premises 12.24. Canada Recommendation Engine Market Forecast, by Technology 12.24.1. Geospatial Aware 12.24.2. Context Aware. 12.25. Canada Recommendation Engine Market Forecast, by Application 12.25.1. Proactive Asset Management 12.25.2. Personalized Campaigns & Customer Discovery 12.25.3. Strategy & Operation Planning 12.25.4. Product Planning 12.26. North America Recommendation Engine Market Attractiveness Analysis 12.26.1. By Type 12.26.2. By End user 12.26.3. By Deployment Type 12.26.4. By Technology 12.26.5. By Application 12.27. PEST Analysis 13. Europe Recommendation Engine Market Analysis 13.1. Key Findings 13.2. Europe Recommendation Engine Market Overview 13.3. Europe Recommendation Engine Market Value Share Analysis, by Type 13.4. Europe Recommendation Engine Market Forecast, by Type 13.4.1. Hybrid Recommendation 13.4.2. Collaborative Filtering 13.4.3. Content-Based Filtering 13.5. Europe Recommendation Engine Market Value Share Analysis, by End user 13.6. Europe Recommendation Engine Market Forecast, by End user 13.6.1. BFSI 13.6.2. Healthcare 13.6.3. Retail 13.6.4. Transportation 13.6.5. Media & Entertainment 13.7. Europe Recommendation Engine Market Value Share Analysis, by Deployment Type 13.8. Europe Recommendation Engine Market Forecast, by Deployment Type 13.8.1. Cloud 13.8.2. On-Premises 13.9. Europe Recommendation Engine Market Value Share Analysis, by Technology 13.10. Europe Recommendation Engine Market Forecast, by Technology 13.10.1. Geospatial Aware 13.10.2. Context Aware. 13.11. Europe Recommendation Engine Market Value Share Analysis, by Application 13.12. Europe Recommendation Engine Market Forecast, by Application 13.12.1. Proactive Asset Management 13.12.2. Personalized Campaigns & Customer Discovery 13.12.3. Strategy & Operation Planning 13.12.4. Product Planning 13.13. Europe Recommendation Engine Market Value Share Analysis, by Country 13.14. Europe Recommendation Engine Market Forecast, by Country 13.14.1.1. Germany 13.14.1.2. U.K. 13.14.1.3. France 13.14.1.4. Italy 13.14.1.5. Spain 13.14.1.6. Rest of Europe 13.15. Europe Recommendation Engine Market Analysis, by Country/ Sub-region 13.16. Germany Recommendation Engine Market Forecast, by Type 13.16.1. Hybrid Recommendation 13.16.2. Collaborative Filtering 13.16.3. Content-Based Filtering 13.17. Germany Recommendation Engine Market Forecast, by End user 13.17.1. BFSI 13.17.2. Healthcare 13.17.3. Retail 13.17.4. Transportation 13.17.5. Media & Entertainment 13.18. Germany Recommendation Engine Market Forecast, by Deployment Type 13.18.1. Cloud 13.18.2. On-Premises 13.19. Germany Recommendation Engine Market Forecast, by Technology 13.19.1. Geospatial Aware 13.19.2. Context Aware. 13.20. Germany Recommendation Engine Market Forecast, by Application 13.20.1. Proactive Asset Management 13.20.2. Personalized Campaigns & Customer Discovery 13.20.3. Strategy & Operation Planning 13.20.4. Product Planning 13.21. U.K. Recommendation Engine Market Forecast, by Type 13.21.1. Hybrid Recommendation 13.21.2. Collaborative Filtering 13.21.3. Content-Based Filtering 13.22. U.K. Recommendation Engine Market Forecast, by End user 13.22.1. BFSI 13.22.2. Healthcare 13.22.3. Retail 13.22.4. Transportation 13.22.5. Media & Entertainment 13.23. U.K. Recommendation Engine Market Forecast, by Deployment Type 13.23.1. Cloud 13.23.2. On-Premises 13.24. U.K. Recommendation Engine Market Forecast, by Technology 13.24.1. Geospatial Aware 13.24.2. Context Aware. 13.25. U.K. Recommendation Engine Market Forecast, by Application 13.25.1. Proactive Asset Management 13.25.2. Personalized Campaigns & Customer Discovery 13.25.3. Strategy & Operation Planning 13.25.4. Product Planning 13.26. France Recommendation Engine Market Forecast, by Type 13.26.1. Hybrid Recommendation 13.26.2. Collaborative Filtering 13.26.3. Content-Based Filtering 13.27. France Recommendation Engine Market Forecast, by End user 13.27.1. BFSI 13.27.2. Healthcare 13.27.3. Retail 13.27.4. Transportation 13.27.5. Media & Entertainment 13.28. France Recommendation Engine Market Forecast, by Deployment Type 13.28.1. Cloud 13.28.2. On-Premises 13.29. France Recommendation Engine Market Forecast, by Technology 13.29.1. Geospatial Aware 13.29.2. Context Aware. 13.30. France Recommendation Engine Market Forecast, by Application 13.30.1. Proactive Asset Management 13.30.2. Personalized Campaigns & Customer Discovery 13.30.3. Strategy & Operation Planning 13.30.4. Product Planning 13.31. Italy Recommendation Engine Market Forecast, by Type 13.31.1. Hybrid Recommendation 13.31.2. Collaborative Filtering 13.31.3. Content-Based Filtering 13.32. Italy Recommendation Engine Market Forecast, by End user 13.32.1. BFSI 13.32.2. Healthcare 13.32.3. Retail 13.32.4. Transportation 13.32.5. Media & Entertainment 13.33. Italy Recommendation Engine Market Forecast, by Deployment Type 13.33.1. Cloud 13.33.2. On-Premises 13.34. Italy Recommendation Engine Market Forecast, by Technology 13.34.1. Geospatial Aware 13.34.2. Context Aware. 13.35. Italy Recommendation Engine Market Forecast, by Application 13.35.1. Proactive Asset Management 13.35.2. Personalized Campaigns & Customer Discovery 13.35.3. Strategy & Operation Planning 13.35.4. Product Planning 13.36. Spain Recommendation Engine Market Forecast, by Type 13.36.1. Hybrid Recommendation 13.36.2. Collaborative Filtering 13.36.3. Content-Based Filtering 13.37. Spain Recommendation Engine Market Forecast, by End user 13.37.1. BFSI 13.37.2. Healthcare 13.37.3. Retail 13.37.4. Transportation 13.37.5. Media & Entertainment 13.38. Spain Recommendation Engine Market Forecast, by Deployment Type 13.38.1. Cloud 13.38.2. On-Premises 13.39. Spain Recommendation Engine Market Forecast, by Technology 13.39.1. Geospatial Aware 13.39.2. Context Aware. 13.40. Spain Recommendation Engine Market Forecast, by Application 13.40.1. Proactive Asset Management 13.40.2. Personalized Campaigns & Customer Discovery 13.40.3. Strategy & Operation Planning 13.40.4. Product Planning 13.41. Rest of Europe Recommendation Engine Market Forecast, by Type 13.41.1. Hybrid Recommendation 13.41.2. Collaborative Filtering 13.41.3. Content-Based Filtering 13.42. Rest of Europe Recommendation Engine Market Forecast, by End user 13.42.1. BFSI 13.42.2. Healthcare 13.42.3. Retail 13.42.4. Transportation 13.42.5. Media & Entertainment 13.43. Rest of Europe Recommendation Engine Market Forecast, by Deployment Type 13.43.1. Cloud 13.43.2. On-Premises 13.44. Rest Of Europe Recommendation Engine Market Forecast, by Technology 13.44.1. Geospatial Aware 13.44.2. Context Aware. 13.45. Rest Of Europe Recommendation Engine Market Forecast, by Application 13.45.1. Proactive Asset Management 13.45.2. Personalized Campaigns & Customer Discovery 13.45.3. Strategy & Operation Planning 13.45.4. Product Planning 13.46. Europe Recommendation Engine Market Attractiveness Analysis 13.46.1. By Type 13.46.2. By End user 13.46.3. By Deployment Type 13.46.4. By Technology 13.46.5. By Application 13.47. PEST Analysis 14. Asia Pacific Recommendation Engine Market Analysis 14.1. Key Findings 14.2. Asia Pacific Recommendation Engine Market Overview 14.3. Asia Pacific Recommendation Engine Market Value Share Analysis, by Type 14.4. Asia Pacific Recommendation Engine Market Forecast, by Type 14.4.1. Hybrid Recommendation 14.4.2. Collaborative Filtering 14.4.3. Content-Based Filtering 14.5. Asia Pacific Recommendation Engine Market Value Share Analysis, by End user 14.6. Asia Pacific Recommendation Engine Market Forecast, by End user 14.6.1. BFSI 14.6.2. Healthcare 14.6.3. Retail 14.6.4. Transportation 14.6.5. Media & Entertainment 14.7. Asia Pacific Recommendation Engine Market Value Share Analysis, by Deployment Type 14.8. Asia Pacific Recommendation Engine Market Forecast, by Deployment Type 14.8.1. Cloud 14.8.2. On-Premises 14.9. Asia Pacific Recommendation Engine Market Value Share Analysis, by Technology 14.10. Asia Pacific Recommendation Engine Market Forecast, by Technology 14.10.1. Geospatial Aware 14.10.2. Context Aware. 14.11. Asia Pacific Recommendation Engine Market Value Share Analysis, by Application 14.12. Asia Pacific Recommendation Engine Market Forecast, by Application 14.12.1. Proactive Asset Management 14.12.2. Personalized Campaigns & Customer Discovery 14.12.3. Strategy & Operation Planning 14.12.4. Product Planning 14.13. Asia Pacific Recommendation Engine Market Value Share Analysis, by Country 14.14. Asia Pacific Recommendation Engine Market Forecast, by Country 14.14.1. China, 14.14.2. India, 14.14.3. Japan, 14.14.4. ASEAN, 14.14.5. Rest of Asia Pacific, 14.15. Asia Pacific Recommendation Engine Market Analysis, by Country/ Sub-region 14.16. China Recommendation Engine Market Forecast, by Type 14.16.1. Hybrid Recommendation 14.16.2. Collaborative Filtering 14.16.3. Content-Based Filtering 14.17. China Recommendation Engine Market Forecast, by End user 14.17.1. BFSI 14.17.2. Healthcare 14.17.3. Retail 14.17.4. Transportation 14.17.5. Media & Entertainment 14.18. China Recommendation Engine Market Forecast, by Deployment Type 14.18.1. Cloud 14.18.2. On-Premises 14.19. China Recommendation Engine Market Forecast, by Technology 14.19.1. Geospatial Aware 14.19.2. Context Aware. 14.20. China Recommendation Engine Market Forecast, by Application 14.20.1. Proactive Asset Management 14.20.2. Personalized Campaigns & Customer Discovery 14.20.3. Strategy & Operation Planning 14.20.4. Product Planning 14.21. India Recommendation Engine Market Forecast, by Type 14.21.1. Hybrid Recommendation 14.21.2. Collaborative Filtering 14.21.3. Content-Based Filtering 14.22. India Recommendation Engine Market Forecast, by End user 14.22.1. BFSI 14.22.2. Healthcare 14.22.3. Retail 14.22.4. Transportation 14.22.5. Media & Entertainment 14.23. India Recommendation Engine Market Forecast, by Deployment Type 14.23.1. Cloud 14.23.2. On-Premises 14.24. India Recommendation Engine Market Forecast, by Technology 14.24.1. Geospatial Aware 14.24.2. Context Aware. 14.25. India Recommendation Engine Market Forecast, by Application 14.25.1. Proactive Asset Management 14.25.2. Personalized Campaigns & Customer Discovery 14.25.3. Strategy & Operation Planning 14.25.4. Product Planning 14.26. Japan Recommendation Engine Market Forecast, by Type 14.26.1. Hybrid Recommendation 14.26.2. Collaborative Filtering 14.26.3. Content-Based Filtering 14.26.4. Alternative Fuel 14.27. Japan Recommendation Engine Market Forecast, by End user 14.27.1. BFSI 14.27.2. Healthcare 14.27.3. Retail 14.27.4. Transportation 14.27.5. Media & Entertainment 14.28. Japan Recommendation Engine Market Forecast, by Deployment Type 14.28.1. Cloud 14.28.2. On-Premises 14.29. Japan Recommendation Engine Market Forecast, by Technology 14.29.1. Geospatial Aware 14.29.2. Context Aware. 14.30. Japan Recommendation Engine Market Forecast, by Application 14.30.1. Proactive Asset Management 14.30.2. Personalized Campaigns & Customer Discovery 14.30.3. Strategy & Operation Planning 14.30.4. Product Planning 14.31. ASEAN Recommendation Engine Market Forecast, by Type 14.31.1. Hybrid Recommendation 14.31.2. Collaborative Filtering 14.31.3. Content-Based Filtering 14.32. ASEAN Recommendation Engine Market Forecast, by End user 14.32.1. BFSI 14.32.2. Healthcare 14.32.3. Retail 14.32.4. Transportation 14.32.5. Media & Entertainment 14.33. ASEAN Recommendation Engine Market Forecast, by Deployment Type 14.33.1. Cloud 14.33.2. On-Premises 14.34. ASEAN Recommendation Engine Market Forecast, by Technology 14.34.1. Geospatial Aware 14.34.2. Context Aware. 14.35. ASEAN Recommendation Engine Market Forecast, by Application 14.35.1. Proactive Asset Management 14.35.2. Personalized Campaigns & Customer Discovery 14.35.3. Strategy & Operation Planning 14.35.4. Product Planning 14.36. Rest of Asia Pacific Recommendation Engine Market Forecast, by Type 14.36.1. Hybrid Recommendation 14.36.2. Collaborative Filtering 14.36.3. Content-Based Filtering 14.37. Rest of Asia Pacific Recommendation Engine Market Forecast, by End user 14.37.1. BFSI 14.37.2. Healthcare 14.37.3. Retail 14.37.4. Transportation 14.37.5. Media & Entertainment 14.38. Rest of Asia Pacific Recommendation Engine Market Forecast, by Deployment Type 14.38.1. Cloud 14.38.2. On-Premises 14.39. Rest of Asia Pacific Recommendation Engine Market Forecast, by Technology 14.39.1. Geospatial Aware 14.39.2. Context Aware. 14.40. Rest of Asia Pacific Recommendation Engine Market Forecast, by Application 14.40.1. Proactive Asset Management 14.40.2. Personalized Campaigns & Customer Discovery 14.40.3. Strategy & Operation Planning 14.40.4. Product Planning 14.41. Asia Pacific Recommendation Engine Market Attractiveness Analysis 14.41.1. By Type 14.41.2. By End user 14.41.3. By Deployment Type 14.41.4. By Technology 14.41.5. By Application 14.42. PEST Analysis 15. Middle East & Africa Recommendation Engine Market Analysis 15.1. Key Findings 15.2. Middle East & Africa Recommendation Engine Market Overview 15.3. Middle East & Africa Recommendation Engine Market Value Share Analysis, by Type 15.4. Middle East & Africa Recommendation Engine Market Forecast, by Type 15.4.1. Hybrid Recommendation 15.4.2. Collaborative Filtering 15.4.3. Content-Based Filtering 15.5. Middle East & Africa Recommendation Engine Market Value Share Analysis, by End user 15.6. Middle East & Africa Recommendation Engine Market Forecast, by End user 15.6.1. BFSI 15.6.2. Healthcare 15.6.3. Retail 15.6.4. Transportation 15.6.5. Media & Entertainment 15.7. Middle East & Africa Recommendation Engine Market Value Share Analysis, by Deployment Type 15.8. Middle East & Africa Recommendation Engine Market Forecast, by Deployment Type 15.8.1. Cloud 15.8.2. On-Premises 15.9. Middle East & Africa Recommendation Engine Market Value Share Analysis, by Technology 15.10. Middle East & Africa Recommendation Engine Market Forecast, by Technology 15.10.1. Geospatial Aware 15.10.2. Context Aware. 15.11. Middle East & Africa Recommendation Engine Market Value Share Analysis, by Application 15.12. Middle East & Africa Recommendation Engine Market Forecast, by Application 15.12.1. Proactive Asset Management 15.12.2. Personalized Campaigns & Customer Discovery 15.12.3. Strategy & Operation Planning 15.12.4. Product Planning 15.13. Middle East & Africa Recommendation Engine Market Value Share Analysis, by Country 15.14. Middle East & Africa Recommendation Engine Market Forecast, by Country 15.14.1. GCC, 15.14.2. South Africa, 15.14.3. Rest of Middle East & Africa, 15.15. Middle East & Africa Recommendation Engine Market Analysis, by Country/ Sub-region 15.16. GCC Recommendation Engine Market Forecast, by Type 15.16.1. Hybrid Recommendation 15.16.2. Collaborative Filtering 15.16.3. Content-Based Filtering 15.17. GCC Recommendation Engine Market Forecast, by End user 15.17.1. BFSI 15.17.2. Healthcare 15.17.3. Retail 15.17.4. Transportation 15.17.5. Media & Entertainment 15.18. GCC Recommendation Engine Market Forecast, by Deployment Type 15.18.1. Cloud 15.18.2. On-Premises 15.19. GCC Recommendation Engine Market Forecast, by Technology 15.19.1. Geospatial Aware 15.19.2. Context Aware. 15.20. GCC Recommendation Engine Market Forecast, by Application 15.20.1. Proactive Asset Management 15.20.2. Personalized Campaigns & Customer Discovery 15.20.3. Strategy & Operation Planning 15.20.4. Product Planning 15.21. South Africa Recommendation Engine Market Forecast, by Type 15.21.1. Hybrid Recommendation 15.21.2. Collaborative Filtering 15.21.3. Content-Based Filtering 15.22. South Africa Recommendation Engine Market Forecast, by End user 15.22.1. BFSI 15.22.2. Healthcare 15.22.3. Retail 15.22.4. Transportation 15.22.5. Media & Entertainment 15.23. South Africa Recommendation Engine Market Forecast, by Deployment Type 15.23.1. Cloud 15.23.2. On-Premises 15.24. South Africa Recommendation Engine Market Forecast, by Technology 15.24.1. Geospatial Aware 15.24.2. Context Aware. 15.25. South Africa Recommendation Engine Market Forecast, by Application 15.25.1. Proactive Asset Management 15.25.2. Personalized Campaigns & Customer Discovery 15.25.3. Strategy & Operation Planning 15.25.4. Product Planning 15.26. Rest of Middle East & Africa Recommendation Engine Market Forecast, by Type 15.26.1. Hybrid Recommendation 15.26.2. Collaborative Filtering 15.26.3. Content-Based Filtering 15.27. Rest of Middle East & Africa Recommendation Engine Market Forecast, by End user 15.27.1. BFSI 15.27.2. Healthcare 15.27.3. Retail 15.27.4. Transportation 15.27.5. Media & Entertainment 15.28. Rest of Middle East & Africa Recommendation Engine Market Forecast, by Deployment Type 15.28.1. Cloud 15.28.2. On-Premises 15.29. Rest of Middle East & Africa Recommendation Engine Market Forecast, by Technology 15.29.1. Geospatial Aware 15.29.2. Context Aware. 15.30. Rest of Middle East & Africa Recommendation Engine Market Forecast, by Application 15.30.1. Proactive Asset Management 15.30.2. Personalized Campaigns & Customer Discovery 15.30.3. Strategy & Operation Planning 15.30.4. Product Planning 15.31. Middle East & Africa Recommendation Engine Market Attractiveness Analysis 15.31.1. By Type 15.31.2. By End user 15.31.3. By Deployment Type 15.31.4. By Technology 15.31.5. By Application 15.32. PEST Analysis 16. Latin America Recommendation Engine Market Analysis 16.1. Key Findings 16.2. Latin America Recommendation Engine Market Overview 16.3. Latin America Recommendation Engine Market Value Share Analysis, by Type 16.4. Latin America Recommendation Engine Market Forecast, by Type 16.4.1. Hybrid Recommendation 16.4.2. Collaborative Filtering 16.4.3. Content-Based Filtering 16.5. Latin America Recommendation Engine Market Value Share Analysis, by End user 16.6. Latin America Recommendation Engine Market Forecast, by End user 16.6.1. BFSI 16.6.2. Healthcare 16.6.3. Retail 16.6.4. Transportation 16.6.5. Media & Entertainment 16.7. Latin America Recommendation Engine Market Value Share Analysis, by Deployment Type 16.8. Latin America Recommendation Engine Market Forecast, by Deployment Type 16.8.1. Cloud 16.8.2. On-Premises 16.9. Latin America Recommendation Engine Market Value Share Analysis, by Technology 16.10. Latin America Recommendation Engine Market Forecast, by Technology 16.10.1. Geospatial Aware 16.10.2. Context Aware. 16.11. Latin America Recommendation Engine Market Value Share Analysis, by Application 16.12. Latin America Recommendation Engine Market Forecast, by Application 16.12.1. Proactive Asset Management 16.12.2. Personalized Campaigns & Customer Discovery 16.12.3. Strategy & Operation Planning 16.12.4. Product Planning 16.13. Latin America Recommendation Engine Market Value Share Analysis, by Country 16.14. Latin America Recommendation Engine Market Forecast, by Country 16.14.1.1. Brazil, 16.14.1.2. Mexico 16.14.1.3. Rest of Latin America, 16.15. Latin America Recommendation Engine Market Analysis, by Country/ Sub-region 16.16. Brazil Recommendation Engine Market Forecast, by Type 16.16.1. Hybrid Recommendation 16.16.2. Collaborative Filtering 16.16.3. Content-Based Filtering 16.17. Brazil Recommendation Engine Market Forecast, by End user 16.17.1. BFSI 16.17.2. Healthcare 16.17.3. Retail 16.17.4. Transportation 16.17.5. Media & Entertainment 16.18. Brazil Recommendation Engine Market Forecast, by Deployment Type 16.18.1. Cloud 16.18.2. On-Premises 16.19. Brazil Recommendation Engine Market Forecast, by Technology 16.19.1. Geospatial Aware 16.19.2. Context Aware. 16.20. Brazil Recommendation Engine Market Forecast, by Application 16.20.1. Proactive Asset Management 16.20.2. Personalized Campaigns & Customer Discovery 16.20.3. Strategy & Operation Planning 16.20.4. Product Planning 16.21. Mexico Recommendation Engine Market Forecast, by Type 16.21.1. Hybrid Recommendation 16.21.2. Collaborative Filtering 16.21.3. Content-Based Filtering 16.22. Mexico Recommendation Engine Market Forecast, by End user 16.22.1. BFSI 16.22.2. Healthcare 16.22.3. Retail 16.22.4. Transportation 16.22.5. Media & Entertainment 16.23. Mexico Recommendation Engine Market Forecast, by Deployment Type 16.23.1. Cloud 16.23.2. On-Premises 16.24. Mexico Recommendation Engine Market Forecast, by Technology 16.24.1. Geospatial Aware 16.24.2. Context Aware. 16.25. Mexico Recommendation Engine Market Forecast, by Application 16.25.1. Proactive Asset Management 16.25.2. Personalized Campaigns & Customer Discovery 16.25.3. Strategy & Operation Planning 16.25.4. Product Planning 16.26. Rest of Latin America Recommendation Engine Market Forecast, by Type 16.26.1. Hybrid Recommendation 16.26.2. Collaborative Filtering 16.26.3. Content-Based Filtering 16.27. Rest of Latin America Recommendation Engine Market Forecast, by End user 16.27.1. BFSI 16.27.2. Healthcare 16.27.3. Retail 16.27.4. Transportation 16.27.5. Media & Entertainment 16.28. Rest of Latin America Recommendation Engine Market Forecast, by Deployment Type 16.28.1. Cloud 16.28.2. On-Premises 16.29. Rest of Latin America Recommendation Engine Market Forecast, by Technology 16.29.1. Geospatial Aware 16.29.2. Context Aware. 16.30. Rest of Latin America Recommendation Engine Market Forecast, by Application 16.30.1. Proactive Asset Management 16.30.2. Personalized Campaigns & Customer Discovery 16.30.3. Strategy & Operation Planning 16.30.4. Product Planning 16.31. Latin America Recommendation Engine Market Attractiveness Analysis 16.31.1. By Type 16.31.2. By End user 16.31.3. By Deployment Type 16.31.4. By Technology 16.31.5. By Application 16.32. PEST Analysis 17. Company Profiles 17.1. Market Share Analysis, by Company 17.2. Competition Matrix 17.3. Company Profiles: Key Players 17.3.1. HPE 17.3.1.1. Company Overview 17.3.1.2. Financial Overview 17.3.1.3. Business Strategy 17.3.1.4. Recent Developments 17.3.1.5. Healthcare Footprint 17.3.2. Salesforce 17.3.3. AWS 17.3.4. Oracle Corporation 17.3.5. Intel 17.3.6. Google 17.3.7. IBM 17.3.8. Microsoft 17.3.9. Sentient Technologies 17.3.10. SAP 18. Primary Key Insights

About This Report

Report ID2852
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