
Recommendation Engine Market Report and Forecast 2025-2034
Description
The global recommendation engine market size reached nearly USD 3.76 Billion in 2024. The market is projected to grow at a CAGR of 15.50% between 2025 and 2034 to reach a value of around USD 15.89 Billion by 2034.
Key Trends in the Market
A recommendation engine refers to a technology which offers recommendations based on the behaviour patterns and preferences of consumers. This type of system uses statistical modelling and predictive analysis to provide a personalised experience to end users.
The EMR’s report titled “Recommendation Engine Market Report and Forecast 2025-2034” offers a detailed analysis of the market based on the following segments:
Market Breakup by Type
Personalised campaigns and customer discovery account for a significant portion of the recommendation engine market share. Personalised campaigns and customer discovery curate specific content and videos for the target audience, improving the user experience. This also leads to a higher subscription rate across websites and content delivery platforms. Furthermore, increasing investments by various end users towards personalising their product and service recommendations in order to enhance their scalability and profitability are fuelling the segment’s growth.
Market Share by End Use
According to the recommendation engine market analysis, the retail sector is likely to represent a substantial market share in the forecast period. There is a heightening adoption of recommendation engines by retailers to better analyse their customers’ interests and preferences and cultivate customer loyalty.
Rapid digitalisation in the retail sector, along with a swift transition from traditional to technologically advanced retailing strategies, is expected to further garner the segment’s growth in the forecast period.
Competitive Landscape
The comprehensive EMR report provides an in-depth assessment of the market based on the Porter's five forces model along with giving a SWOT analysis. The report gives a detailed analysis of the key players in the global recommendation engine market, covering their competitive landscape and latest developments like mergers, acquisitions, investments and expansion plans.
Netflix, Inc
Netflix, Inc is a company which offers high-quality streaming services. This company provides content of diverse genres, including anime, docu-dramas, and movies, among others. It was founded in 1997 and is headquartered in California, the United States.
Amazon Web Services, Inc.
Amazon Web Services, Inc. is a leading company which offers technological solutions, including cloud-based recommendation systems. The company also offers APIs to several end-use sectors as well as individuals. It was established in 2006 and is headquartered in Washington, the United States.
Tinder
Tinder is an online dating company which also offers geosocial networking applications. The services provided by this company are based on personalised user recommendations. The company was founded in 2012 and is headquartered in California, the United States.
Other players considered in the recommendation engine market report include Google LLC, SAP SE, Adobe Inc., Microsoft Corporation, Salesforce Inc., Oracle Corporation, Nosto Solutions Oy, and Dynamic Yield, among others.
Key Trends in the Market
A recommendation engine refers to a technology which offers recommendations based on the behaviour patterns and preferences of consumers. This type of system uses statistical modelling and predictive analysis to provide a personalised experience to end users.
- The increasing popularity of OTT platforms, the growing demand for high-quality content across entertainment websites, and the increasing availability of linguistically diverse content are propelling the recommendation engine market growth.
- Technological advancements in the BFSI sector are heightening the usage of recommendation algorithms and personalised banking systems to enhance customer satisfaction. Moreover, the rising demand for personalised services in various end-use sectors, including healthcare, BFSI, and retail, among others, is driving the market.
- One of the key recommendation engine market trends is the increasing adoption of consumer devices such as smartphones, tablets, and laptops, among others. Furthermore, in the forecast period, the expansion of the e-commerce sector is expected to drive the deployment of recommendation engines to track consumer behaviour and improve their experiences.
The EMR’s report titled “Recommendation Engine Market Report and Forecast 2025-2034” offers a detailed analysis of the market based on the following segments:
Market Breakup by Type
- Collaborative Filtering
- Content-Based Filtering
- Hybrid Recommendation Systems
- Others
- Cloud Based
- On-premises
- Context Aware
- Geospatial Aware
- Strategy and Operations Planning
- Product Planning and Proactive Asset Management
- Personalised Campaigns and Customer Discovery
- IT and Telecommunication
- BFSI
- Retail
- Media and Entertainment
- Healthcare
- Others
- North America
- Europe
- Asia Pacific
- Latin America
- Middle East and Africa
Personalised campaigns and customer discovery account for a significant portion of the recommendation engine market share. Personalised campaigns and customer discovery curate specific content and videos for the target audience, improving the user experience. This also leads to a higher subscription rate across websites and content delivery platforms. Furthermore, increasing investments by various end users towards personalising their product and service recommendations in order to enhance their scalability and profitability are fuelling the segment’s growth.
Market Share by End Use
According to the recommendation engine market analysis, the retail sector is likely to represent a substantial market share in the forecast period. There is a heightening adoption of recommendation engines by retailers to better analyse their customers’ interests and preferences and cultivate customer loyalty.
Rapid digitalisation in the retail sector, along with a swift transition from traditional to technologically advanced retailing strategies, is expected to further garner the segment’s growth in the forecast period.
Competitive Landscape
The comprehensive EMR report provides an in-depth assessment of the market based on the Porter's five forces model along with giving a SWOT analysis. The report gives a detailed analysis of the key players in the global recommendation engine market, covering their competitive landscape and latest developments like mergers, acquisitions, investments and expansion plans.
Netflix, Inc
Netflix, Inc is a company which offers high-quality streaming services. This company provides content of diverse genres, including anime, docu-dramas, and movies, among others. It was founded in 1997 and is headquartered in California, the United States.
Amazon Web Services, Inc.
Amazon Web Services, Inc. is a leading company which offers technological solutions, including cloud-based recommendation systems. The company also offers APIs to several end-use sectors as well as individuals. It was established in 2006 and is headquartered in Washington, the United States.
Tinder
Tinder is an online dating company which also offers geosocial networking applications. The services provided by this company are based on personalised user recommendations. The company was founded in 2012 and is headquartered in California, the United States.
Other players considered in the recommendation engine market report include Google LLC, SAP SE, Adobe Inc., Microsoft Corporation, Salesforce Inc., Oracle Corporation, Nosto Solutions Oy, and Dynamic Yield, among others.
Table of Contents
178 Pages
- 1 Executive Summary
- 1.1 Market Size 2024-2025
- 1.2 Market Growth 2025(F)-2034(F)
- 1.3 Key Demand Drivers
- 1.4 Key Players and Competitive Structure
- 1.5 Industry Best Practices
- 1.6 Recent Trends and Developments
- 1.7 Industry Outlook
- 2 Market Overview and Stakeholder Insights
- 2.1 Market Trends
- 2.2 Key Verticals
- 2.3 Key Regions
- 2.4 Supplier Power
- 2.5 Buyer Power
- 2.6 Key Market Opportunities and Risks
- 2.7 Key Initiatives by Stakeholders
- 3 Economic Summary
- 3.1 GDP Outlook
- 3.2 GDP Per Capita Growth
- 3.3 Inflation Trends
- 3.4 Democracy Index
- 3.5 Gross Public Debt Ratios
- 3.6 Balance of Payment (BoP) Position
- 3.7 Population Outlook
- 3.8 Urbanisation Trends
- 4 Country Risk Profiles
- 4.1 Country Risk
- 4.2 Business Climate
- 5 Global Recommendation Engine Market Analysis
- 5.1 Key Industry Highlights
- 5.2 Global Recommendation Engine Historical Market (2018-2024)
- 5.3 Global Recommendation Engine Market Forecast (2025-2034)
- 5.4 Global Recommendation Engine Market by Type
- 5.4.1 Collaborative Filtering
- 5.4.1.1 Historical Trend (2018-2024)
- 5.4.1.2 Forecast Trend (2025-2034)
- 5.4.2 Content-Based Filtering
- 5.4.2.1 Historical Trend (2018-2024)
- 5.4.2.2 Forecast Trend (2025-2034)
- 5.4.3 Hybrid Recommendation Systems
- 5.4.3.1 Historical Trend (2018-2024)
- 5.4.3.2 Forecast Trend (2025-2034)
- 5.4.4 Others
- 5.5 Global Recommendation Engine Market by Deployment Type
- 5.5.1 Cloud Based
- 5.5.1.1 Historical Trend (2018-2024)
- 5.5.1.2 Forecast Trend (2025-2034)
- 5.5.2 On-premises
- 5.5.2.1 Historical Trend (2018-2024)
- 5.5.2.2 Forecast Trend (2025-2034)
- 5.6 Global Recommendation Engine Market by Technology
- 5.6.1 Context Aware
- 5.6.1.1 Historical Trend (2018-2024)
- 5.6.1.2 Forecast Trend (2025-2034)
- 5.6.2 Geospatial Aware
- 5.6.2.1 Historical Trend (2018-2024)
- 5.6.2.2 Forecast Trend (2025-2034)
- 5.7 Global Recommendation Engine Market by Application
- 5.7.1 Strategy and Operations Planning
- 5.7.1.1 Historical Trend (2018-2024)
- 5.7.1.2 Forecast Trend (2025-2034)
- 5.7.2 Product Planning and Proactive Asset Management
- 5.7.2.1 Historical Trend (2018-2024)
- 5.7.2.2 Forecast Trend (2025-2034)
- 5.7.3 Personalised Campaigns and Customer Discovery
- 5.7.3.1 Historical Trend (2018-2024)
- 5.7.3.2 Forecast Trend (2025-2034)
- 5.8 Global Recommendation Engine Market by End Use
- 5.8.1 IT and Telecommunication
- 5.8.1.1 Historical Trend (2018-2024)
- 5.8.1.2 Forecast Trend (2025-2034)
- 5.8.2 BFSI
- 5.8.2.1 Historical Trend (2018-2024)
- 5.8.2.2 Forecast Trend (2025-2034)
- 5.8.3 Retail
- 5.8.3.1 Historical Trend (2018-2024)
- 5.8.3.2 Forecast Trend (2025-2034)
- 5.8.4 Media and Entertainment
- 5.8.4.1 Historical Trend (2018-2024)
- 5.8.4.2 Forecast Trend (2025-2034)
- 5.8.5 Healthcare
- 5.8.5.1 Historical Trend (2018-2024)
- 5.8.5.2 Forecast Trend (2025-2034)
- 5.8.6 Others
- 5.9 Global Recommendation Engine Market by Region
- 5.9.1 North America
- 5.9.1.1 Historical Trend (2018-2024)
- 5.9.1.2 Forecast Trend (2025-2034)
- 5.9.2 Europe
- 5.9.2.1 Historical Trend (2018-2024)
- 5.9.2.2 Forecast Trend (2025-2034)
- 5.9.3 Asia Pacific
- 5.9.3.1 Historical Trend (2018-2024)
- 5.9.3.2 Forecast Trend (2025-2034)
- 5.9.4 Latin America
- 5.9.4.1 Historical Trend (2018-2024)
- 5.9.4.2 Forecast Trend (2025-2034)
- 5.9.5 Middle East and Africa
- 5.9.5.1 Historical Trend (2018-2024)
- 5.9.5.2 Forecast Trend (2025-2034)
- 6 North America Recommendation Engine Market Analysis
- 6.1 United States of America
- 6.1.1 Historical Trend (2018-2024)
- 6.1.2 Forecast Trend (2025-2034)
- 6.2 Canada
- 6.2.1 Historical Trend (2018-2024)
- 6.2.2 Forecast Trend (2025-2034)
- 7 Europe Recommendation Engine Market Analysis
- 7.1 United Kingdom
- 7.1.1 Historical Trend (2018-2024)
- 7.1.2 Forecast Trend (2025-2034)
- 7.2 Germany
- 7.2.1 Historical Trend (2018-2024)
- 7.2.2 Forecast Trend (2025-2034)
- 7.3 France
- 7.3.1 Historical Trend (2018-2024)
- 7.3.2 Forecast Trend (2025-2034)
- 7.4 Italy
- 7.4.1 Historical Trend (2018-2024)
- 7.4.2 Forecast Trend (2025-2034)
- 7.5 Others
- 8 Asia Pacific Recommendation Engine Market Analysis
- 8.1 China
- 8.1.1 Historical Trend (2018-2024)
- 8.1.2 Forecast Trend (2025-2034)
- 8.2 Japan
- 8.2.1 Historical Trend (2018-2024)
- 8.2.2 Forecast Trend (2025-2034)
- 8.3 India
- 8.3.1 Historical Trend (2018-2024)
- 8.3.2 Forecast Trend (2025-2034)
- 8.4 ASEAN
- 8.4.1 Historical Trend (2018-2024)
- 8.4.2 Forecast Trend (2025-2034)
- 8.5 Australia
- 8.5.1 Historical Trend (2018-2024)
- 8.5.2 Forecast Trend (2025-2034)
- 8.6 Others
- 9 Latin America Recommendation Engine Market Analysis
- 9.1 Brazil
- 9.1.1 Historical Trend (2018-2024)
- 9.1.2 Forecast Trend (2025-2034)
- 9.2 Argentina
- 9.2.1 Historical Trend (2018-2024)
- 9.2.2 Forecast Trend (2025-2034)
- 9.3 Mexico
- 9.3.1 Historical Trend (2018-2024)
- 9.3.2 Forecast Trend (2025-2034)
- 9.4 Others
- 10 Middle East and Africa Recommendation Engine Market Analysis
- 10.1 Saudi Arabia
- 10.1.1 Historical Trend (2018-2024)
- 10.1.2 Forecast Trend (2025-2034)
- 10.2 United Arab Emirates
- 10.2.1 Historical Trend (2018-2024)
- 10.2.2 Forecast Trend (2025-2034)
- 10.3 Nigeria
- 10.3.1 Historical Trend (2018-2024)
- 10.3.2 Forecast Trend (2025-2034)
- 10.4 South Africa
- 10.4.1 Historical Trend (2018-2024)
- 10.4.2 Forecast Trend (2025-2034)
- 10.5 Others
- 11 Market Dynamics
- 11.1 SWOT Analysis
- 11.1.1 Strengths
- 11.1.2 Weaknesses
- 11.1.3 Opportunities
- 11.1.4 Threats
- 11.2 Porter’s Five Forces Analysis
- 11.2.1 Supplier’s Power
- 11.2.2 Buyer’s Power
- 11.2.3 Threat of New Entrants
- 11.2.4 Degree of Rivalry
- 11.2.5 Threat of Substitutes
- 11.3 Key Indicators for Demand
- 11.4 Key Indicators for Price
- 12 Competitive Landscape
- 12.1 Supplier Selection
- 12.2 Key Global Players
- 12.3 Key Regional Players
- 12.4 Key Player Strategies
- 12.5 Company Profiles
- 12.5.1 Netflix, Inc
- 12.5.1.1 Company Overview
- 12.5.1.2 Product Portfolio
- 12.5.1.3 Demographic Reach and Achievements
- 12.5.1.4 Certifications
- 12.5.2 Amazon Web Services, Inc.
- 12.5.2.1 Company Overview
- 12.5.2.2 Product Portfolio
- 12.5.2.3 Demographic Reach and Achievements
- 12.5.2.4 Certifications
- 12.5.3 Tinder
- 12.5.3.1 Company Overview
- 12.5.3.2 Product Portfolio
- 12.5.3.3 Demographic Reach and Achievements
- 12.5.3.4 Certifications
- 12.5.4 Google LLC
- 12.5.4.1 Company Overview
- 12.5.4.2 Product Portfolio
- 12.5.4.3 Demographic Reach and Achievements
- 12.5.4.4 Certifications
- 12.5.5 SAP SE
- 12.5.5.1 Company Overview
- 12.5.5.2 Product Portfolio
- 12.5.5.3 Demographic Reach and Achievements
- 12.5.5.4 Certifications
- 12.5.6 Adobe Inc.
- 12.5.6.1 Company Overview
- 12.5.6.2 Product Portfolio
- 12.5.6.3 Demographic Reach and Achievements
- 12.5.6.4 Certifications
- 12.5.7 Microsoft Corporation
- 12.5.7.1 Company Overview
- 12.5.7.2 Product Portfolio
- 12.5.7.3 Demographic Reach and Achievements
- 12.5.7.4 Certifications
- 12.5.8 Salesforce Inc.
- 12.5.8.1 Company Overview
- 12.5.8.2 Product Portfolio
- 12.5.8.3 Demographic Reach and Achievements
- 12.5.8.4 Certifications
- 12.5.9 Oracle Corporation
- 12.5.9.1 Company Overview
- 12.5.9.2 Product Portfolio
- 12.5.9.3 Demographic Reach and Achievements
- 12.5.9.4 Certifications
- 12.5.10 Nosto Solutions Oy
- 12.5.10.1 Company Overview
- 12.5.10.2 Product Portfolio
- 12.5.10.3 Demographic Reach and Achievements
- 12.5.10.4 Certifications
- 12.5.11 Dynamic Yield
- 12.5.11.1 Company Overview
- 12.5.11.2 Product Portfolio
- 12.5.11.3 Demographic Reach and Achievements
- 12.5.11.4 Certifications
- 12.5.12 Others
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