Global Recommendation Engine Market: 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, the market is expected 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

This research 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. The 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

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

Breakup by Region:

• North America
• United States
• Canada
• Asia-Pacific
• China
• Japan
• India
• South Korea
• Australia
• Indonesia
• Europe
• Germany
• France
• United Kingdom
• Italy
• Spain
• Russia
• Latin America
• Brazil
• Mexico
• 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?