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Recommendation Engine Market Estimated to Cross US$ 20.3 Bn by 2030

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The worldwide Recommendation Engine market measurement is anticipated to achieve USD 20.3 billion by 2030 and is anticipated to increase at a CAGR of 35.2% from 2021 to 2030.

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Growth Factors

 The growing adoption of digital technologies among organizations is one of the key factors driving the market. In addition, the rising competition among organizations and the need to provide a better customer experience are increasing the demand for recommendation systems.

The increasing need to enhance customer experience is fueling the demand for recommendation engines. The growing adoption of digital technologies among organizations is also resulting in the increased demand for recommendation engine solutions.

Report Coverage

Report Scope Details
Market Size USD 20.3 billion by 2030
Growth Rate CAGR of 35.2% From 2021 to 2030
Base Year 2020
Historic Data 2017 to 2020
Forecast Period 2021 to 2030
Segments Covered Type, Deployment, Application, Organization, End-use
Regional Scope North America, Europe, Asia Pacific, Latin America, Middle East & Africa
Companies Mentioned Adobe; Amazon Web Services, Inc.; Google LLC;  Hewlett Packard Enterprise Development LP; International Business Machines Corporation; Intel Corporation; Microsoft Corporation; Oracle; Salesforce.com, Inc.; SAP SE

Report Highlights

The collaborative filtering segment accounted for the largest revenue share of over 44.0% in 2020 and is projected to retain its lead over the forecast period. This can be attributed to the rising demand for reliable recommendation engines from e-commerce platforms to enhance their customers’ shopping experience by suggesting products based on their tastes and preferences.

The hybrid recommendation segment is projected to expand at the highest CAGR of 36.4% over the forecast period. The growth of this segment can be attributed to the increase in demand from organizations that need features of both collaborative filtering and content-based filtering.

The cloud segment accounted for the largest revenue share of over 88.0% in 2020 and is projected to register the highest CAGR over the forecast period. This can be attributed to the increase in demand from players adopting cloud technologies to integrate recommendation engines onto their web-based applications, including businesses across industries such as media and entertainment and retail.

The on-premise segment accounted for the second-largest revenue share in 2020. The growth of this segment can be attributed to the demand for on-premise recommendation systems from large enterprises owing to their higher spending capacity for on-premise infrastructure and data security solutions.

The personalized campaigns and customer delivery segment accounted for the largest revenue share of more than 42.0% in 2020. The dominance of this segment can be accredited to the increase in the need to provide better customer experience and services to customers.

The product planning and proactive asset management segment is anticipated to account for the second-largest revenue share by the end of the forecast period. Additionally, this segment is projected to expand at the highest CAGR of 36.1% during the forecast period.

The retail segment accounted for the largest revenue share of nearly 28.0% in 2020 and is expected to retain its lead over the forecast period. This can be attributed to the growing adoption of recommendation systems by and retail organizations to provide better and quick services to their customers owing to the increasing competition in the industry.

The large enterprise segment accounted for the largest revenue share of more than 56.0% in 2020. This can be attributed to the higher demand for recommendation engines from large enterprises to make better decisions, efficiently manage their business portfolio, and gain a competitive edge in the global market.

The SMEs segment is projected to exhibit the highest CAGR of 34.6% during the forecast period. The rising need to offer a better user experience in the highly competitive market is driving this segment.

The North American regional market accounted for the largest revenue share of over 36.0% in 2020 and is expected to retain its lead over the forecast period. This can be attributed to the growing adoption of advanced technologies and increase in government support for emerging technologies in the region.

The Asia Pacific market is anticipated to expand at the highest CAGR of 38.5% over the forecast period. Factors such as the rising penetration of e-commerce, an upsurge in online shopping transactions, and an increase in the number of Over the Top (OTT) service providers are fueling the demand for recommendation engines in the region.

Key Players

  • Adobe
  • Amazon Web Services, Inc.
  • Google LLC
  • Hewlett Packard Enterprise Development LP
  • International Business Machines Corporation
  • Intel Corporation
  • Microsoft Corporation
  • Oracle
  • Salesforce.com, Inc.
  • SAP SE

Market Segmentation

  • Type
    • Collaborative Filtering
    • Content-based Filtering
    • Hybrid Recommendation
  • Deployment
    • On-premise
    • Cloud
  • Application
    • Personalized Campaigns and Customer Delivery
    • Strategy Operations and Planning
    • Product Planning and Proactive Asset Management
  • Organization
    • SMEs
    • Large Enterprise
  • End-use
    • Information Technology
    • Healthcare
    • Retail
    • BFSI
    • Media & Entertainment
    • Others
  • Regional
    • North America
      • U.S.
      • Canada
    • Europe
      • U.K.
      • Germany
      • France
      • Italy
    • Asia Pacific
      • China
      • India
      • Japan
    • Latin America
      • Brazil
      • Mexico
    • Middle East & Africa

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Reasons to Purchase this Report:

– Market segmentation analysis including qualitative and quantitative research incorporating the impact of economic and policy aspects
– Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
– Market value USD Million and volume Units Million data for each segment and sub-segment
– Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
– Comprehensive company profiles covering the product offerings, key financial information, recent developments, SWOT analysis, and strategies employed by the major market players

Table of Contents

Chapter 1.  Introduction

1.1.  Research Objective

1.2.  Scope of the Study

1.3.  Definition

Chapter 2.  Research Methodology

2.1.  Research Approach

2.2.  Data Sources

2.3.  Assumptions & Limitations

Chapter 3.  Executive Summary

3.1.  Market Snapshot

Chapter 4.  Market Variables and Scope

4.1.  Introduction

4.2.  Market Classification and Scope

4.3.  Industry Value Chain Analysis

4.3.1.    Raw Material Procurement Analysis

4.3.2.    Sales and Distribution Channel Analysis

4.3.3.    Downstream Buyer Analysis

Chapter 5.  Market Dynamics Analysis and Trends

5.1.  Market Dynamics

5.1.1.    Market Drivers

5.1.2.    Market Restraints

5.1.3.    Market Opportunities

5.2.  Porter’s Five Forces Analysis

5.2.1.    Bargaining power of suppliers

5.2.2.    Bargaining power of buyers

5.2.3.    Threat of substitute

5.2.4.    Threat of new entrants

5.2.5.    Degree of competition

Chapter 6.  Competitive Landscape

6.1.1.    Company Market Share/Positioning Analysis

6.1.2.    Key Strategies Adopted by Players

6.1.3.    Vendor Landscape

6.1.3.1.        List of Suppliers

6.1.3.2.        List of Buyers

Chapter 7.  Global Recommendation Engine Market, By Type

7.1.  Recommendation Engine Market, by Type, 2021-2030

7.1.1.    Collaborative Filtering

7.1.1.1.        Market Revenue and Forecast (2017-2030)

7.1.2.    Content-based Filtering

7.1.2.1.        Market Revenue and Forecast (2017-2030)

7.1.3.    Hybrid Recommendation

7.1.3.1.        Market Revenue and Forecast (2017-2030)

Chapter 8.  Global Recommendation Engine Market, By Deployment

8.1.  Recommendation Engine Market, by Deployment, 2021-2030

8.1.1.    On-premise

8.1.1.1.        Market Revenue and Forecast (2017-2030)

8.1.2.    Cloud

8.1.2.1.        Market Revenue and Forecast (2017-2030)

Chapter 9.  Global Recommendation Engine Market, By Application

9.1.  Recommendation Engine Market, by Application, 2021-2030

9.1.1.    Personalized Campaigns and Customer Delivery

9.1.1.1.        Market Revenue and Forecast (2017-2030)

9.1.2.    Strategy Operations and Planning

9.1.2.1.        Market Revenue and Forecast (2017-2030)

9.1.3.    Product Planning and Proactive Asset Management

9.1.3.1.        Market Revenue and Forecast (2017-2030)

Chapter 10.      Global Recommendation Engine Market, By Organization

10.1.        Recommendation Engine Market, by Organization, 2021-2030

10.1.1.  SMEs

10.1.1.1.      Market Revenue and Forecast (2017-2030)

10.1.2.  Large Enterprise

10.1.2.1.      Market Revenue and Forecast (2017-2030)

Chapter 11.      Global Recommendation Engine Market, By End-use

11.1.        Recommendation Engine Market, by End-use, 2021-2030

11.1.1.  Information Technology

11.1.1.1.      Market Revenue and Forecast (2017-2030)

11.1.2.  Healthcare

11.1.2.1.      Market Revenue and Forecast (2017-2030)

11.1.3.  Retail

11.1.3.1.      Market Revenue and Forecast (2017-2030)

11.1.4.  BFSI

11.1.4.1.      Market Revenue and Forecast (2017-2030)

11.1.5.  Media & Entertainment

11.1.5.1.      Market Revenue and Forecast (2017-2030)

11.1.6.  Others

11.1.6.1.      Market Revenue and Forecast (2017-2030)

Chapter 12.      Global Recommendation Engine  Market, Regional Estimates and Trend Forecast

12.1.        North America

12.1.1.  Market Revenue and Forecast, by Type (2017-2030)

12.1.2.  Market Revenue and Forecast, by Deployment (2017-2030)

12.1.3.  Market Revenue and Forecast, by Application (2017-2030)

12.1.4.  Market Revenue and Forecast, by Organization (2017-2030)

12.1.5.  Market Revenue and Forecast, by End-use (2017-2030)

12.1.6.  U.S.

12.1.6.1.      Market Revenue and Forecast, by Type (2017-2030)

12.1.6.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.1.6.3.      Market Revenue and Forecast, by Application (2017-2030)

12.1.6.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.1.6.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.1.7.  Rest of North America

12.1.7.1.      Market Revenue and Forecast, by Type (2017-2030)

12.1.7.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.1.7.3.      Market Revenue and Forecast, by Application (2017-2030)

12.1.7.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.1.7.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.2.        Europe

12.2.1.  Market Revenue and Forecast, by Type (2017-2030)

12.2.2.  Market Revenue and Forecast, by Deployment (2017-2030)

12.2.3.  Market Revenue and Forecast, by Application (2017-2030)

12.2.4.  Market Revenue and Forecast, by Organization (2017-2030)

12.2.5.  Market Revenue and Forecast, by End-use (2017-2030)

12.2.6.  UK

12.2.6.1.      Market Revenue and Forecast, by Type (2017-2030)

12.2.6.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.2.6.3.      Market Revenue and Forecast, by Application (2017-2030)

12.2.6.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.2.6.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.2.7.  Germany

12.2.7.1.      Market Revenue and Forecast, by Type (2017-2030)

12.2.7.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.2.7.3.      Market Revenue and Forecast, by Application (2017-2030)

12.2.7.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.2.7.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.2.8.  France

12.2.8.1.      Market Revenue and Forecast, by Type (2017-2030)

12.2.8.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.2.8.3.      Market Revenue and Forecast, by Application (2017-2030)

12.2.8.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.2.8.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.2.9.  Rest of Europe

12.2.9.1.      Market Revenue and Forecast, by Type (2017-2030)

12.2.9.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.2.9.3.      Market Revenue and Forecast, by Application (2017-2030)

12.2.9.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.2.9.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.3.        APAC

12.3.1.  Market Revenue and Forecast, by Type (2017-2030)

12.3.2.  Market Revenue and Forecast, by Deployment (2017-2030)

12.3.3.  Market Revenue and Forecast, by Application (2017-2030)

12.3.4.  Market Revenue and Forecast, by Organization (2017-2030)

12.3.5.  Market Revenue and Forecast, by End-use (2017-2030)

12.3.6.  India

12.3.6.1.      Market Revenue and Forecast, by Type (2017-2030)

12.3.6.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.3.6.3.      Market Revenue and Forecast, by Application (2017-2030)

12.3.6.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.3.6.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.3.7.  China

12.3.7.1.      Market Revenue and Forecast, by Type (2017-2030)

12.3.7.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.3.7.3.      Market Revenue and Forecast, by Application (2017-2030)

12.3.7.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.3.7.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.3.8.  Japan

12.3.8.1.      Market Revenue and Forecast, by Type (2017-2030)

12.3.8.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.3.8.3.      Market Revenue and Forecast, by Application (2017-2030)

12.3.8.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.3.8.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.3.9.  Rest of APAC

12.3.9.1.      Market Revenue and Forecast, by Type (2017-2030)

12.3.9.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.3.9.3.      Market Revenue and Forecast, by Application (2017-2030)

12.3.9.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.3.9.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.4.        MEA

12.4.1.  Market Revenue and Forecast, by Type (2017-2030)

12.4.2.  Market Revenue and Forecast, by Deployment (2017-2030)

12.4.3.  Market Revenue and Forecast, by Application (2017-2030)

12.4.4.  Market Revenue and Forecast, by Organization (2017-2030)

12.4.5.  Market Revenue and Forecast, by End-use (2017-2030)

12.4.6.  GCC

12.4.6.1.      Market Revenue and Forecast, by Type (2017-2030)

12.4.6.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.4.6.3.      Market Revenue and Forecast, by Application (2017-2030)

12.4.6.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.4.6.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.4.7.  North Africa

12.4.7.1.      Market Revenue and Forecast, by Type (2017-2030)

12.4.7.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.4.7.3.      Market Revenue and Forecast, by Application (2017-2030)

12.4.7.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.4.7.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.4.8.  South Africa

12.4.8.1.      Market Revenue and Forecast, by Type (2017-2030)

12.4.8.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.4.8.3.      Market Revenue and Forecast, by Application (2017-2030)

12.4.8.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.4.8.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.4.9.  Rest of MEA

12.4.9.1.      Market Revenue and Forecast, by Type (2017-2030)

12.4.9.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.4.9.3.      Market Revenue and Forecast, by Application (2017-2030)

12.4.9.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.4.9.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.5.        Latin America

12.5.1.  Market Revenue and Forecast, by Type (2017-2030)

12.5.2.  Market Revenue and Forecast, by Deployment (2017-2030)

12.5.3.  Market Revenue and Forecast, by Application (2017-2030)

12.5.4.  Market Revenue and Forecast, by Organization (2017-2030)

12.5.5.  Market Revenue and Forecast, by End-use (2017-2030)

12.5.6.  Brazil

12.5.6.1.      Market Revenue and Forecast, by Type (2017-2030)

12.5.6.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.5.6.3.      Market Revenue and Forecast, by Application (2017-2030)

12.5.6.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.5.6.5.      Market Revenue and Forecast, by End-use (2017-2030)

12.5.7.  Rest of LATAM

12.5.7.1.      Market Revenue and Forecast, by Type (2017-2030)

12.5.7.2.      Market Revenue and Forecast, by Deployment (2017-2030)

12.5.7.3.      Market Revenue and Forecast, by Application (2017-2030)

12.5.7.4.      Market Revenue and Forecast, by Organization (2017-2030)

12.5.7.5.      Market Revenue and Forecast, by End-use (2017-2030)

Chapter 13.  Company Profiles

13.1.              Adobe

13.1.1.  Company Overview

13.1.2.  Product Offerings

13.1.3.  Financial Performance

13.1.4.  Recent Initiatives

13.2.              Amazon Web Services, Inc.

13.2.1.  Company Overview

13.2.2.  Product Offerings

13.2.3.  Financial Performance

13.2.4.  Recent Initiatives

13.3.              Google LLC

13.3.1.  Company Overview

13.3.2.  Product Offerings

13.3.3.  Financial Performance

13.3.4.  Recent Initiatives

13.4.              Hewlett Packard Enterprise Development LP

13.4.1.  Company Overview

13.4.2.  Product Offerings

13.4.3.  Financial Performance

13.4.4.  Recent Initiatives

13.5.              International Business Machines Corporation

13.5.1.  Company Overview

13.5.2.  Product Offerings

13.5.3.  Financial Performance

13.5.4.  Recent Initiatives

13.6.              Intel Corporation

13.6.1.  Company Overview

13.6.2.  Product Offerings

13.6.3.  Financial Performance

13.6.4.  Recent Initiatives

13.7.              Microsoft Corporation

13.7.1.  Company Overview

13.7.2.  Product Offerings

13.7.3.  Financial Performance

13.7.4.  Recent Initiatives

13.8.              Oracle

13.8.1.  Company Overview

13.8.2.  Product Offerings

13.8.3.  Financial Performance

13.8.4.  Recent Initiatives

13.9.              Salesforce.com, Inc.

13.9.1.  Company Overview

13.9.2.  Product Offerings

13.9.3.  Financial Performance

13.9.4.  Recent Initiatives

13.10.           SAP SE

13.10.1.               Company Overview

13.10.2.               Product Offerings

13.10.3.               Financial Performance

13.10.4.               Recent Initiatives

Chapter 14.  Research Methodology

14.1.              Primary Research

14.2.              Secondary Research

14.3.              Assumptions

Chapter 15.  Appendix

15.1.              About Us

15.2.              Glossary of Terms

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