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Global Recommendation Engine Market (2022 to 2027) - Industry Trends, Share, Size, Growth, Opportunity and Forecasts

·8-min read
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Global Recommendation Engine Market

Global Recommendation Engine Market
Global Recommendation Engine Market

Dublin, May 03, 2022 (GLOBE NEWSWIRE) -- The "Recommendation Engine Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2022-2027" report has been added to ResearchAndMarkets.com's offering.

The global recommendation engine market reached a value of US$ 2.7 billion in 2021. Looking forward, the market is projected 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, the analyst is 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

This report 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. 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

  • 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

  • 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?

Key Topics Covered:

1 Preface

2 Scope and 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

12 SWOT Analysis

13 Value Chain Analysis

14 Porters Five Forces Analysis

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

For more information about this report visit https://www.researchandmarkets.com/r/ua7kw5

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