Global recommendation engine industry expected to reach $16.3 billion by 2027 –


the “Recommendation Engines Market: Global Industry Trends, Share, Size, Growth, Opportunities and Forecast 2022-2027” report has been added to from offer.

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, growing at a CAGR of 35.61 % in 2022-2027.

Companies cited

  • 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

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.

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 trend of social media 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 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 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?

Main topics covered:

1 Preface

2 Scope and methodology

3 Executive summary

4 Presentation

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 Breakdown by Type

7 Market Breakdown by Technology

8 Market Breakdown by Deployment Mode

9 Market Breakdown by Application

10 Market Breakdown by End User

11 Market Breakdown by Region

12 SWOT Analysis

13 Value chain analysis

14 Analysis of the five forces of carriers

15 Price Analysis

16 Competitive Landscape

16.1 Market structure

16.2 Key Players

16.3 Profiles of Key Players

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