Recommendation engine markets: collaborative filtering, content-based filtering and hybrid recommender systems



DUBLIN, October 19, 2022 /PRNewswire/ — The “Recommendation Engines Market: Global Industry Trends, Share, Size, Growth, Opportunities and Forecast 2022-2027” report has been added to from offer.

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The global recommendation engine market reached a value of US$2.7 billion in 2021. Going forward, the market is expected to reach US$16.3 billion by 2027, posting a CAGR of 35.61% over the period 2022-2027.

Keeping in mind the uncertainties of COVID-19, the analyst continuously monitors and assesses the direct and indirect influence of the pandemic on the various end-use industries. This information is included in the report as a major market contributor.

Recommendation engine refers to a data filtering tool that allows marketers to offer relevant product recommendations to customers in real time. It relies on advanced data analysis techniques and algorithms, such as machine learning (ML) and artificial intelligence (AI), which can suggest relevant product catalogs to an individual.

Additionally, it may display products on websites, apps, and emails, based on customer preferences, browser history, attributes, and situational context. At present, it is widely used in business-to-consumer (B2C) e-commerce areas such as entertainment, mobile apps, and education, which require a personalization strategy.

Recommendation Engine Market Trends

The coronavirus disease (COVID-19) pandemic and complete shutdowns imposed by government agencies in many countries have encouraged businesses to shift to online retail platforms. This represents one of the major factors driving the demand for recommendation engines to increase sales and maintain a positive customer relationship.

Apart from this, the thriving e-commerce industry due to growing internet penetration, growing addiction to smartphones, and emerging social media trend is helping the market grow. It can also be attributed to changing consumer consumption habits and the growing need for convenience, immediacy and simplicity when shopping.

Additionally, the growing adoption of the omnichannel approach to sales focused on providing a seamless customer experience is driving the market. Additionally, due to the rapid expansion of businesses globally, there is an increase in the demand for recommendation engines to handle large volumes of data and actively engage users.

They are also gaining traction in small and medium-sized enterprises (SMBs) around the world to enable them to increase their overall sales by selling new products to existing customers and maximizing average order value.

Key questions answered by this report

  • How has the global recommendation engine market behaved so far and how will it behave in the coming years?

  • What has been the impact of COVID-19 on the global recommendation engine market?

  • What are the main regional markets?

  • What is the market breakdown by type?

  • What is the shattering of the technology-based market?

  • What is the market breakdown by deployment mode?

  • What is the market breakdown by application?

  • What is the market breakdown by end user?

  • What are the different stages of the industry value chain?

  • What are the key drivers and challenges in the industry?

  • What is the structure of the global recommendation engine market and who are the key players?

  • How competitive is the industry?

Competitive landscape

The competitive landscape of the industry has also been examined along with the profiles of key players

  • Adobe Inc.

  • Inc.

  • Dynamic Yield (McDonald’s)

  • Google LLC (Alphabet Inc.)

  • Hewlett Packard Enterprise Development LP

  • intel company

  • International Commercial Machinery Society

  • Kibo Software Inc.

  • Microsoft Corporation

  • Oracle Corporation

  • Recolize GmbH

  • Inc.

  • SAP SE

Key market segmentation

Breakdown by type:

Breakdown by technology:

  • Aware of the context

  • geospatial aware

Breakdown by deployment mode:

Breakdown by application:

  • Operations strategy and planning

  • Product planning and proactive asset management

  • Personalized campaigns and customer discovery

Breakdown by end user:

  • IT and Telecommunications

  • BFSI

  • Detail

  • Media and Entertainment

  • Health care

  • Others

Breakdown by region:

  • North America

  • United States

  • Canada

  • Asia Pacific

  • China

  • Japan

  • India

  • South Korea

  • Australia

  • Indonesia

  • Others

  • Europe

  • Germany

  • France

  • UK

  • Italy

  • Spain

  • Russia

  • Others

  • Latin America

  • Brazil

  • Mexico

  • Others

  • Middle East and Africa

For more information on this report, visit

Media Contact:

Research and Markets
Laura Woodsenior
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