Recommendation Engine Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028

Recommendation Engine Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028


The global recommendation engine market size reached US$ 3.5 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 22.2 Billion by 2028, exhibiting a growth rate (CAGR) of 36.05% during 2022-2028.

Recommendation engine refers to a data filtering tool that enables marketers to offer relevant product recommendations to customers in real-time. It is leveraged with data analysis techniques and advanced algorithms, such as machine learning (ML) and artificial intelligence (AI), which can suggest relevant product catalogs to an individual. In addition, it can show products on websites, apps, and emails, based on customer preferences, past browser history, attributes, and situational context. At present, it is widely utilized in business-to-consumer (B2C) e-commerce fields, such as entertainment, mobile apps, and education, which require a personalization strategy.

Recommendation Engine Market Trends:
The coronavirus disease (COVID-19) pandemic and complete lockdowns imposed by governing agencies of numerous countries have encouraged enterprises to shift to online retail platforms. This represents one of the major factors catalyzing the demand for recommendation engines to increase sales and maintain a positive customer relationship. Apart from this, the thriving e-commerce industry on account of the increasing penetration of the Internet, the growing reliance on smartphones, and the emerging social media trend are contributing to the market growth. This can also be attributed to changing consumer spending habits and the rising need for convenience, immediacy, and simplicity during shopping. Moreover, the increasing adoption of the omnichannel approach to sales that focuses on providing a seamless customer experience is driving the market. Furthermore, due to the rapid expansion of businesses globally, there is a rise in the demand for recommendation engines to manage large volumes of data and engage users actively. They are also gaining traction in small and medium-sized enterprises (SMEs) worldwide to enable them to increase overall sales by cross-selling new products to existing customers and maximize average order value.

Key Market Segmentation:
IMARC Group provides an analysis of the key trends in each sub-segment of the global recommendation engine market report, along with forecasts at the global, regional and country level from 2023-2028. Our report has categorized the market based on type, technology, deployment mode, application and end user.

Breakup by Type:

Collaborative Filtering
Content-based Filtering
Hybrid Recommendation Systems
Others

Breakup by Technology:

Context Aware
Geospatial Aware

Breakup by Deployment Mode:

On-premises
Cloud-based

Breakup by Application:

Strategy and Operations Planning
Product Planning and Proactive Asset Management
Personalized Campaigns and Customer Discovery

Breakup by End User:

IT and Telecommunication
BFSI
Retail
Media and Entertainment
Healthcare
Others

Breakup by Region:

North America
United States
Canada
Asia-Pacific
China
Japan
India
South Korea
Australia
Indonesia
Others
Europe
Germany
France
United Kingdom
Italy
Spain
Russia
Others
Latin America
Brazil
Mexico
Others
Middle East and Africa

Competitive Landscape:
The competitive landscape of the industry has also been examined along with the profiles of the key players being Adobe Inc., Amazon.com Inc., Dynamic Yield (McDonald's), Google LLC (Alphabet Inc.), Hewlett Packard Enterprise Development LP, Intel Corporation, International Business Machines Corporation, Kibo Software Inc., Microsoft Corporation, Oracle Corporation, Recolize GmbH, Salesforce.com Inc. and SAP SE.

Key Questions Answered in This Report
1. How big is the global recommendation engine market?
2. What is the expected growth rate of the global recommendation engine market during 2023-2028?
3. What are the key factors driving the global recommendation engine market?
4. What has been the impact of COVID-19 on the global recommendation engine market?
5. What is the breakup of the global recommendation engine market based on the type?
6. What is the breakup of the global recommendation engine market based on the technology?
7. What is the breakup of the global recommendation engine market based on the deployment mode?
8. What is the breakup of the global recommendation engine market based on the application?
9. What is the breakup of the global recommendation engine market based on the end user?
10. What are the key regions in the global recommendation engine market?
11. Who are the key players/companies in the global recommendation engine market?


1 Preface
2 Scope and Methodology
2.1 Objectives of the Study
2.2 Stakeholders
2.3 Data Sources
2.3.1 Primary Sources
2.3.2 Secondary Sources
2.4 Market Estimation
2.4.1 Bottom-Up Approach
2.4.2 Top-Down Approach
2.5 Forecasting Methodology
3 Executive Summary
4 Introduction
4.1 Overview
4.2 Key Industry Trends
5 Global Recommendation Engine Market
5.1 Market Overview
5.2 Market Performance
5.3 Impact of COVID-19
5.4 Market Forecast
6 Market Breakup by Type
6.1 Collaborative Filtering
6.1.1 Market Trends
6.1.2 Market Forecast
6.2 Content-based Filtering
6.2.1 Market Trends
6.2.2 Market Forecast
6.3 Hybrid Recommendation Systems
6.3.1 Market Trends
6.3.2 Market Forecast
6.4 Others
6.4.1 Market Trends
6.4.2 Market Forecast
7 Market Breakup by Technology
7.1 Context Aware
7.1.1 Market Trends
7.1.2 Market Forecast
7.2 Geospatial Aware
7.2.1 Market Trends
7.2.2 Market Forecast
8 Market Breakup by Deployment Mode
8.1 On-premises
8.1.1 Market Trends
8.1.2 Market Forecast
8.2 Cloud-based
8.2.1 Market Trends
8.2.2 Market Forecast
9 Market Breakup by Application
9.1 Strategy and Operations Planning
9.1.1 Market Trends
9.1.2 Market Forecast
9.2 Product Planning and Proactive Asset Management
9.2.1 Market Trends
9.2.2 Market Forecast
9.3 Personalized Campaigns and Customer Discovery
9.3.1 Market Trends
9.3.2 Market Forecast
10 Market Breakup by End User
10.1 IT and Telecommunication
10.1.1 Market Trends
10.1.2 Market Forecast
10.2 BFSI
10.2.1 Market Trends
10.2.2 Market Forecast
10.3 Retail
10.3.1 Market Trends
10.3.2 Market Forecast
10.4 Media and Entertainment
10.4.1 Market Trends
10.4.2 Market Forecast
10.5 Healthcare
10.5.1 Market Trends
10.5.2 Market Forecast
10.6 Others
10.6.1 Market Trends
10.6.2 Market Forecast
11 Market Breakup by Region
11.1 North America
11.1.1 United States
11.1.1.1 Market Trends
11.1.1.2 Market Forecast
11.1.2 Canada
11.1.2.1 Market Trends
11.1.2.2 Market Forecast
11.2 Asia-Pacific
11.2.1 China
11.2.1.1 Market Trends
11.2.1.2 Market Forecast
11.2.2 Japan
11.2.2.1 Market Trends
11.2.2.2 Market Forecast
11.2.3 India
11.2.3.1 Market Trends
11.2.3.2 Market Forecast
11.2.4 South Korea
11.2.4.1 Market Trends
11.2.4.2 Market Forecast
11.2.5 Australia
11.2.5.1 Market Trends
11.2.5.2 Market Forecast
11.2.6 Indonesia
11.2.6.1 Market Trends
11.2.6.2 Market Forecast
11.2.7 Others
11.2.7.1 Market Trends
11.2.7.2 Market Forecast
11.3 Europe
11.3.1 Germany
11.3.1.1 Market Trends
11.3.1.2 Market Forecast
11.3.2 France
11.3.2.1 Market Trends
11.3.2.2 Market Forecast
11.3.3 United Kingdom
11.3.3.1 Market Trends
11.3.3.2 Market Forecast
11.3.4 Italy
11.3.4.1 Market Trends
11.3.4.2 Market Forecast
11.3.5 Spain
11.3.5.1 Market Trends
11.3.5.2 Market Forecast
11.3.6 Russia
11.3.6.1 Market Trends
11.3.6.2 Market Forecast
11.3.7 Others
11.3.7.1 Market Trends
11.3.7.2 Market Forecast
11.4 Latin America
11.4.1 Brazil
11.4.1.1 Market Trends
11.4.1.2 Market Forecast
11.4.2 Mexico
11.4.2.1 Market Trends
11.4.2.2 Market Forecast
11.4.3 Others
11.4.3.1 Market Trends
11.4.3.2 Market Forecast
11.5 Middle East and Africa
11.5.1 Market Trends
11.5.2 Market Breakup by Country
11.5.3 Market Forecast
12 SWOT Analysis
12.1 Overview
12.2 Strengths
12.3 Weaknesses
12.4 Opportunities
12.5 Threats
13 Value Chain Analysis
14 Porters Five Forces Analysis
14.1 Overview
14.2 Bargaining Power of Buyers
14.3 Bargaining Power of Suppliers
14.4 Degree of Competition
14.5 Threat of New Entrants
14.6 Threat of Substitutes
15 Price Analysis
16 Competitive Landscape
16.1 Market Structure
16.2 Key Players
16.3 Profiles of Key Players
16.3.1 Adobe Inc.
16.3.1.1 Company Overview
16.3.1.2 Product Portfolio
16.3.1.3 Financials
16.3.1.4 SWOT Analysis
16.3.2 Amazon.com Inc.
16.3.2.1 Company Overview
16.3.2.2 Product Portfolio
16.3.2.3 Financials
16.3.2.4 SWOT Analysis
16.3.3 Dynamic Yield (McDonald's)
16.3.3.1 Company Overview
16.3.3.2 Product Portfolio
16.3.4 Google LLC (Alphabet Inc.)
16.3.4.1 Company Overview
16.3.4.2 Product Portfolio
16.3.4.3 SWOT Analysis
16.3.5 Hewlett Packard Enterprise Development LP
16.3.5.1 Company Overview
16.3.5.2 Product Portfolio
16.3.5.3 Financials
16.3.5.4 SWOT Analysis
16.3.6 Intel Corporation
16.3.6.1 Company Overview
16.3.6.2 Product Portfolio
16.3.6.3 Financials
16.3.6.4 SWOT Analysis
16.3.7 International Business Machines Corporation
16.3.7.1 Company Overview
16.3.7.2 Product Portfolio
16.3.7.3 Financials
16.3.7.4 SWOT Analysis
16.3.8 Kibo Software Inc.
16.3.8.1 Company Overview
16.3.8.2 Product Portfolio
16.3.9 Microsoft Corporation
16.3.9.1 Company Overview
16.3.9.2 Product Portfolio
16.3.9.3 Financials
16.3.9.4 SWOT Analysis
16.3.10 Oracle Corporation
16.3.10.1 Company Overview
16.3.10.2 Product Portfolio
16.3.10.3 Financials
16.3.10.4 SWOT Analysis
16.3.11 Recolize GmbH
16.3.11.1 Company Overview
16.3.11.2 Product Portfolio
16.3.12 Salesforce.com Inc.
16.3.12.1 Company Overview
16.3.12.2 Product Portfolio
16.3.12.3 Financials
16.3.12.4 SWOT Analysis
16.3.13 SAP SE
16.3.13.1 Company Overview
16.3.13.2 Product Portfolio
16.3.13.3 Financials
16.3.13.4 SWOT Analysis

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