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Global Recommendation Engine Market to reach USD 13.03 Billion by 2027.

Global Recommendation Engine Market Size study, by Product Type (Collaborative Filtering, Content-based Filtering, Hybrid Recommendation), by Deployment (On-premise, cloud), by Application (Personalized Campaigns and Customer Delivery, Strategy Operations and Planning, Product Planning and Proactive Asset Management), by organization (SMEs, large enterprises) By end use (Information Technology, Healthcare, Retail, BFSI, Media & Entertainment, Others) and Regional Forecasts 2021-2027

Product Code: ICTICTS-68685882
Publish Date: 25-09-2021
Page: 200

Global Recommendation Engine Market is valued approximately at USD 1.77 Billion in 2020 and is anticipated to grow with a healthy growth rate of more than 33.0% over the forecast period 2021-2027. A recommendation engine is data filtering tool which uses machine learning algorithms for recommending the relevant items to user. The global Recommendation Engine market is being driven by growing adoption of digital technologies among organizations and increase in need to enhance the customer experience. Furthermore, rise in technological advancement in data analytics, and rise in sales from e-commerce platforms will provide new opportunities for the global Recommendation Engine industry. For instance, according to statista, there has been rise in spending on digital transformation technologies and services year on year as in year 2019, the spending reaches to USD 1.18 trillion which increases to USD 1.31 trillion in year 2020 and it is projected to increase to USD 2.3 by year 2030. As a result, rise in spending on digital transformation, which will serve as a catalyst for the Recommendation Engine industry in the future. However, increase in concerns over the customers personal information, may impede market growth over the forecast period of 2021-2027.

Asia Pacific, North America, Europe, Latin America, and Rest of the World are the key regions considered for the regional analysis of global recommendation engine market. The rapid adoption of advanced technologies and rise in government support for emerging technologies in makes the North America the leading region across the world in terms of market share. Whereas Asia Pacific is also anticipated to exhibit the highest growth rate over the forecast period 2021-2027, due to rising penetration of e-commerce, an upsurge in online shopping transactions, and an increase in the number of Over the Top (OTT) in the region.

Major market player included in this report are:
IBM
Google
AWS
Microsoft
Salesforce
Sentient Technologies
HPE
Oracle
Intel
SAP

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Product Type:
Collaborative Filtering
Content-based Filtering
Hybrid Recommendation
By Deployment :
On-premise
Cloud
By Application:
Personalized Campaigns and Customer Delivery
Strategy Operations and Planning
Product Planning and Proactive Asset Management
By organization:
SMEs
Large enterprises
By End Use:
Information Technology
Healthcare
Retail
BFSI
Media & Entertainment
Others
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019
Base year – 2020
Forecast period – 2021 to 2027.

Target Audience of the Global Recommendation Engine Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2027 (USD Billion)
1.2.1. Recommendation Engine Market , by Region, 2019-2027 (USD Billion)
1.2.2. Recommendation Engine Market , by Product Type, 2019-2027 (USD Billion)
1.2.3. Recommendation Engine Market , by Deployment , 2019-2027 (USD Billion)
1.2.4. Recommendation Engine Market , by Application, 2019-2027 (USD Billion)
1.2.5. Recommendation Engine Market, by Organization, 2019-2027 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Recommendation Engine Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Recommendation Engine Market Dynamics
3.1. Recommendation Engine Market Impact Analysis (2019-2027)
3.1.1. Market Drivers
3.1.1.1. Growing adoption of digital technologies among organizations
3.1.1.2. Increase in need to enhance customer experience
3.1.2. Market Restraint
3.1.2.1. Increase in concerns over the customers’ personal information
3.1.3. Market Opportunities
3.1.3.1. Advancements in data analytics
Chapter 4. Global Recommendation Engine Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2027)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
Chapter 5. Global Recommendation Engine Market , by Product Type
5.1. Market Snapshot
5.2. Global Recommendation Engine Market by Product Type, Performance – Potential Analysis
5.3. Global Recommendation Engine Market Estimates & Forecasts by Product Type 2018-2027 (USD Billion)
5.4. Recommendation Engine Market , Sub Segment Analysis
5.4.1. Collaborative Filtering
5.4.2. Content-based Filtering
5.4.3. Hybrid Recommendation
Chapter 6. Global Recommendation Engine Market , by Deployment
a. Market Snapshot
6.1. Global Recommendation Engine Market by Deployment , Performance – Potential Analysis
6.2. Global Recommendation Engine Market Estimates & Forecasts by Deployment 2018-2027 (USD Billion)
6.3. Recommendation Engine Market , Sub Segment Analysis
6.3.1. On-premise
6.3.2. Cloud
Chapter 7. Global Recommendation Engine Market , by Application
b. Market Snapshot
7.1. Global Recommendation Engine Market by Application, Performance – Potential Analysis
7.2. Global Recommendation Engine Market Estimates & Forecasts by Application 2018-2027 (USD Billion)
7.3. Recommendation Engine Market , Sub Segment Analysis
7.3.1. Personalized Campaigns and Customer Delivery
7.3.2. Strategy Operations and Planning
7.3.3. Product Planning and Proactive Asset Management
Chapter 8. Global Recommendation Engine Market , by Organization
c. Market Snapshot
8.1. Global Recommendation Engine Market by Deployment , Performance – Potential Analysis
8.2. Global Recommendation Engine Market Estimates & Forecasts by Deployment 2018-2027 (USD Billion)
8.3. Recommendation Engine Market , Sub Segment Analysis
8.3.1. SMEs
8.3.2. Large Enterprises
Chapter 9. Global Recommendation Engine Market , by End-use
d. Market Snapshot
9.1. Global Recommendation Engine Market by Deployment , Performance – Potential Analysis
9.2. Global Recommendation Engine Market Estimates & Forecasts by Deployment 2018-2027 (USD Billion)
9.3. Recommendation Engine Market , Sub Segment Analysis
9.3.1. Information Technology
9.3.2. Healthcare
9.3.3. Retail
9.3.4. BFSI
9.3.5. Media & Entertainment
9.3.6. Others
Chapter 10. Global Recommendation Engine Market , Regional Analysis
10.1. Recommendation Engine Market , Regional Market Snapshot
10.2. North America Recommendation Engine Market
10.2.1. U.S. Recommendation Engine Market
10.2.1.1. Product Type breakdown estimates & forecasts, 2018-2027
10.2.1.2. Deployment breakdown estimates & forecasts, 2018-2027
10.2.1.3. Application breakdown estimates & forecasts, 2018-2027
10.2.1.4. Organization breakdown estimates & forecasts, 2018-2027
10.2.1.5. End Use breakdown estimates & forecasts, 2018-2027
10.2.2. Canada Recommendation Engine Market
10.3. Europe Recommendation Engine Market Snapshot
10.3.1. U.K. Recommendation Engine Market
10.3.2. Germany Recommendation Engine Market
10.3.3. France Recommendation Engine Market
10.3.4. Spain Recommendation Engine Market
10.3.5. Italy Recommendation Engine Market
10.3.6. Rest of Europe Recommendation Engine Market
10.4. Asia-Pacific Recommendation Engine Market Snapshot
10.4.1. China Recommendation Engine Market
10.4.2. India Recommendation Engine Market
10.4.3. Japan Recommendation Engine Market
10.4.4. Australia Recommendation Engine Market
10.4.5. South Korea Recommendation Engine Market
10.4.6. Rest of Asia Pacific Recommendation Engine Market
10.5. Latin America Recommendation Engine Market Snapshot
10.5.1. Brazil Recommendation Engine Market
10.5.2. Mexico Recommendation Engine Market
10.6. Rest of The World Recommendation Engine Market
Chapter 11. Competitive Intelligence
11.1. Top Market Strategies
11.2. Company Profiles
11.2.1. IBM
11.2.1.1. Key Information
11.2.1.2. Overview
11.2.1.3. Financial (Subject to Data Availability)
11.2.1.4. Product Summary
11.2.1.5. Recent Developments
11.2.2. Google
11.2.3. AWS
11.2.4. Microsoft
11.2.5. Salesforce
11.2.6. Sentient Technologies
11.2.7. HPE
11.2.8. Oracle
11.2.9. Intel
11.2.10. SAP
Chapter 12. Research Process
12.1. Research Process
12.1.1. Data Mining
12.1.2. Analysis
12.1.3. Market Estimation
12.1.4. Validation
12.1.5. Publishing
12.2. Research Attributes
12.3. Research Assumption

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Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
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Regulatory landscape and expected changes or developments.
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