Market Overview:

The global recommendation engine market reached a value of US$ 2.7 Billion in 2021. Looking forward, IMARC Group expects the market to reach US$ 16.3 Billion by 2027, exhibiting a CAGR of 35.61% during 2022-2027. Keeping in mind the uncertainties of COVID-19, we are continuously tracking and evaluating the direct as well as the indirect influence of the pandemic on different end use industries. These insights are included in the report as a major market contributor.

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, along with forecasts at the global, regional and country level from 2022-2027. 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.

Report Coverage:

Key Questions Answered in This Report:

• How has the global recommendation engine market performed so far and how will it perform in the coming years?
• What has been the impact of COVID-19 on the global recommendation engine market?
• What are the key regional markets?
• What is the breakup of the market based on the type?
• What is the breakup of the market based on the technology?
• What is the breakup of the market based on the deployment mode?
• What is the breakup of the market based on the application?
• What is the breakup of the market based on the end user?
• What are the various stages in the value chain of the industry?
• What are the key driving factors and challenges in the industry?
• What is the structure of the global recommendation engine market and who are the key players?
• What is the degree of competition in the industry?