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Recommendation Engine Trends and Forecast
The future of the recommendation engine market looks promising with opportunities in the information technology, healthcare, retail, BFSI, and media & entertainment markets. The recommendation engine market is expected to reach an estimated $14.3 billion by 2030 with a CAGR of 22.3% from 2024 to 2030. The major drivers for this market are increasing emphasis on improving the customer experience, rising trend of digitalization, and growing demand for large volumes of data analysis.
A more than 150-page report is developed to help in your business decisions. Sample figures with some insights are shown below.
Recommendation Engine by Segment
The study includes a forecast for the global recommendation engine by type, organization, application, end use, and region.
Recommendation Engine Market by Type [Shipment Analysis by Value from 2018 to 2030]:
• Collaborative Filtering
• Content-Based Filtering
• Hybrid Recommendation
Recommendation Engine Market by Organization [Shipment Analysis by Value from 2018 to 2030]:
• SMEs
• Large Enterprise
Recommendation Engine Market by Application [Shipment Analysis by Value from 2018 to 2030]:
• Personalized Campaigns And Customer Delivery
• Strategy Operations And Planning
• Product Planning And Proactive Asset Management
Recommendation Engine Market by End Use [Shipment Analysis by Value from 2018 to 2030]:
• Information Technology
• Healthcare
• Retail
• BFSI
• Media & Entertainment
• Others
Recommendation Engine Market by Region [Shipment Analysis by Value from 2018 to 2030]:
• North America
• Europe
• Asia Pacific
• The Rest of the World
List of Recommendation Engine Companies
Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. With these strategies recommendation engine companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the recommendation engine companies profiled in this report include-
• Adobe
• Amazon Web Services
• Google
• Hewlett Packard Enterprise Development
• International Business Machines
• Intel
• Microsoft
• Oracle
• Salesforce.com
• SAP
Recommendation Engine Market Insights
Lucintel forecasts that personalized campaigns and customer delivery will remain the largest segment over the forecast period due to an increase in the need for improved customer service and experiences.
North America will remain the largest region over the forecast period due to the regionÄX%$%Xs expanding acceptance of innovative technology and increased government backing for new technologies.
Features of the Recommendation Engine Market
Market Size Estimates: Recommendation engine market size estimation in terms of value ($B).
Trend and Forecast Analysis: Market trends (2018 to 2023) and forecast (2024 to 2030) by various segments and regions.
Segmentation Analysis: Recommendation engine market size by type, organization, application, end use, and region in terms of value ($B).
Regional Analysis: Recommendation engine market breakdown by North America, Europe, Asia Pacific, and Rest of the World.
Growth Opportunities: Analysis of growth opportunities in different type, organization, application, end use, and regions for the recommendation engine market.
Strategic Analysis: This includes M&A, new product development, and competitive landscape of the recommendation engine market.
Analysis of competitive intensity of the industry based on Porter’s Five Forces model.
FAQ
Q1. What is the recommendation engine market size?
Answer: The global recommendation engine market is expected to reach an estimated $14.3 billion by 2030.
Q2. What is the growth forecast for recommendation engine market?
Answer: The global recommendation engine market is expected to grow with a CAGR of 22.3% from 2024 to 2030.
Q3. What are the major drivers influencing the growth of the recommendation engine market?
Answer: The major drivers for this market are increasing emphasis on improving the customer experience, rising trend of digitalization, and growing demand for large volumes of data analysis.
Q4. What are the major segments for recommendation engine market?
Answer: The future of the recommendation engine market looks promising with opportunities in the information technology, healthcare, retail, BFSI, and media & entertainment markets.
Q5. Who are the key recommendation engine market companies?
Answer: Some of the key recommendation engine companies are as follows:
• Adobe
• Amazon Web Services
• Google
• Hewlett Packard Enterprise Development
• International Business Machines
• Intel
• Microsoft
• Oracle
• Salesforce.com
• SAP
Q6. Which recommendation engine market segment will be the largest in future?
Answer: Lucintel forecasts that personalized campaigns and customer delivery will remain the largest segment over the forecast period due to an increase in the need for improved customer service and experiences.
Q7. In recommendation engine market, which region is expected to be the largest in next 5 years?
Answer: North America will remain the largest region over the forecast period due to the regionÄX%$%Xs expanding acceptance of innovative technology and increased government backing for new technologies.
Q.8 Do we receive customization in this report?
Answer: Yes, Lucintel provides 10% customization without any additional cost.
This report answers following 11 key questions:
Q.1. What are some of the most promising, high-growth opportunities for the recommendation engine market by type (collaborative filtering, content-based filtering, and hybrid recommendation), organization (SMEs and large enterprise), application (personalized campaigns and customer delivery, strategy operations and planning, and product planning and proactive asset management), end use (information technology, healthcare, retail, BFSI, media & entertainment, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
Q.2. Which segments will grow at a faster pace and why?
Q.3. Which region will grow at a faster pace and why?
Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
Q.5. What are the business risks and competitive threats in this market?
Q.6. What are the emerging trends in this market and the reasons behind them?
Q.7. What are some of the changing demands of customers in the market?
Q.8. What are the new developments in the market? Which companies are leading these developments?
Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?
For any questions related to Recommendation Engine Market, Recommendation Engine Market Size, Recommendation Engine Market Growth, Recommendation Engine Market Analysis, Recommendation Engine Market Report, Recommendation Engine Market Share, Recommendation Engine Market Trends, Recommendation Engine Market Forecast, Recommendation Engine Companies, write Lucintel analyst at email: helpdesk@lucintel.com. We will be glad to get back to you soon.
Table of Contents
1. Executive Summary
2. Global Recommendation Engine Market : Market Dynamics
2.1: Introduction, Background, and Classifications
2.2: Supply Chain
2.3: Industry Drivers and Challenges
3. Market Trends and Forecast Analysis from 2018 to 2030
3.1. Macroeconomic Trends (2018-2023) and Forecast (2024-2030)
3.2. Global Recommendation Engine Market Trends (2018-2023) and Forecast (2024-2030)
3.3: Global Recommendation Engine Market by Type
3.3.1: Collaborative Filtering
3.3.2: Content-based Filtering
3.3.3: Hybrid Recommendation
3.4: Global Recommendation Engine Market by Organization
3.4.1: SMEs
3.4.2: Large Enterprise
3.5: Global Recommendation Engine Market by Application
3.5.1: Personalized Campaigns and Customer Delivery
3.5.2: Strategy Operations and Planning
3.5.3: Product Planning and Proactive Asset Management
3.6: Global Recommendation Engine Market by End Use
3.6.1: Information Technology
3.6.2: Healthcare
3.6.3: Retail
3.6.4: BFSI
3.6.5: Media & Entertainment
3.6.6: Others
4. Market Trends and Forecast Analysis by Region from 2018 to 2030
4.1: Global Recommendation Engine Market by Region
4.2: North American Recommendation Engine Market
4.2.1: North American Recommendation Engine Market by Application: Personalized Campaigns and Customer Delivery, Strategy Operations and Planning, and Product Planning and Proactive Asset Management
4.2.2: North American Recommendation Engine Market by End Use: Information Technology, Healthcare, Retail, BFSI, Media & Entertainment, and Others
4.3: European Recommendation Engine Market
4.3.1: European Recommendation Engine Market by Application: Personalized Campaigns and Customer Delivery, Strategy Operations and Planning, and Product Planning and Proactive Asset Management
4.3.2: European Recommendation Engine Market by End Use: Information Technology, Healthcare, Retail, BFSI, Media & Entertainment, and Others
4.4: APAC Recommendation Engine Market
4.4.1: APAC Recommendation Engine Market by Application: Personalized Campaigns and Customer Delivery, Strategy Operations and Planning, and Product Planning and Proactive Asset Management
4.4.2: APAC Recommendation Engine Market by End Use: Information Technology, Healthcare, Retail, BFSI, Media & Entertainment, and Others
4.5: ROW Recommendation Engine Market
4.5.1: ROW Recommendation Engine Market by Application: Personalized Campaigns and Customer Delivery, Strategy Operations and Planning, and Product Planning and Proactive Asset Management
4.5.2: ROW Recommendation Engine Market by End Use: Information Technology, Healthcare, Retail, BFSI, Media & Entertainment, and Others
5. Competitor Analysis
5.1: Product Portfolio Analysis
5.2: Operational Integration
5.3: Porter’s Five Forces Analysis
6. Growth Opportunities and Strategic Analysis
6.1: Growth Opportunity Analysis
6.1.1: Growth Opportunities for the Global Recommendation Engine Market by Type
6.1.2: Growth Opportunities for the Global Recommendation Engine Market by Organization
6.1.3: Growth Opportunities for the Global Recommendation Engine Market by Application
6.1.4: Growth Opportunities for the Global Recommendation Engine Market by End Use
6.1.5: Growth Opportunities for the Global Recommendation Engine Market by Region
6.2: Emerging Trends in the Global Recommendation Engine Market
6.3: Strategic Analysis
6.3.1: New Product Development
6.3.2: Capacity Expansion of the Global Recommendation Engine Market
6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global Recommendation Engine Market
6.3.4: Certification and Licensing
7. Company Profiles of Leading Players
7.1: Adobe
7.2: Amazon Web Services
7.3: Google
7.4: Hewlett Packard Enterprise Development
7.5: International Business Machines
7.6: Intel
7.7: Microsoft
7.8: Oracle
7.9: Salesforce.com
7.10: SAP
.
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Lucintel has been in the business of market research and management consulting since 2000 and has published over 1000 market intelligence reports in various markets / applications and served over 1,000 clients worldwide. This study is a culmination of four months of full-time effort performed by Lucintel's analyst team. The analysts used the following sources for the creation and completion of this valuable report:
In-depth interviews of the major players in this market
Detailed secondary research from competitors’ financial statements and published data
Extensive searches of published works, market, and database information pertaining to industry news, company press releases, and customer intentions
A compilation of the experiences, judgments, and insights of Lucintel’s professionals, who have analyzed and tracked this market over the years.
Extensive research and interviews are conducted across the supply chain of this market to estimate market share, market size, trends, drivers, challenges, and forecasts. Below is a brief summary of the primary interviews that were conducted by job function for this report.
Thus, Lucintel compiles vast amounts of data from numerous sources, validates the integrity of that data, and performs a comprehensive analysis. Lucintel then organizes the data, its findings, and insights into a concise report designed to support the strategic decision-making process. The figure below is a graphical representation of Lucintel’s research process.
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