세계의 추천 엔진 시장 - 산업 규모, 점유율, 동향, 기회 및 예측(-2028년) : 유형별, 배포 모델별, 기업 규모별, 용도별, 최종 사용자별, 지역별, 경쟁업체별

Global recommendation engine market is anticipated to grow at a steady pace in the forecast period, 2024-2028. The increased desire to enhance the customer experience is fueling the need for recommendation engines. For instance, IBM Corporation expanded its IBM Watson Advertising Accelerator for OTT and video in May 2021. This tool was created to assist advertisers in moving beyond contextual relevance. Instead of relying on conventional advertising IDs, The amplifier uses artificial intelligence to constantly optimize OTT ad copy for better campaign outcomes at scale.

A recommendation engine is a system that recognizes employees and offers them relevant material. One example of how other technical developments continue to alter customer interest and utilize the available data is mobile applications. The advice engine is recognized as a key element of software and application products in the ICT sector. The two primary categories of recommendation engines are content-based filtering and collaborative filtering.

The recommendation system uses information analysis techniques to seek products that complement the user's preferences. For a variety of reasons, many advice engines are available. These include the picture recommendation engine, the product recommendation engine for online stores, the content recommendation engine, and the product suggestion engine. The increasing desire to enhance customer experience is satisfying the need for engines of recommendation.

Adoption of combine technology Fueling the Market Growth

Due to the increasing variety of industries and the subsequent growth in competition, many companies are attempting to combine technology, including computer science (AI), with their applications, businesses, analytics, and services. Around the world, quite a few firms are going through a digital transformation with an emphasis on using automation technologies to increase employee and customer knowledge. Due to the shift to digital, retailers can grow their client base, improve their customer connections, cut expenses, and raise employee morale. Increasing customer experience improvement methods and the growing scope of digital transformation are a few of the main factors driving the global recommendation engine market. For instance, in March 2021 SAP SE purchased Signavio. Signavio was a key player in the enterprise business process intelligence and process management arena. The solutions from Signavio were added to SAP's portfolio of business process intelligence and were designed to work with SAP's comprehensive process transformation portfolio. Owing to this the market is expected to grow in the forecast period.

Advantage To Record and Observe Customer Behavior Propelling the Market Growth

Due to the fact that customers usually make their purchasing decisions based on the position of the item in the shelf in brick and mortar businesses have a significant amount of ability to observe and shape customer behavior. The retail sector is adjusting to new and cutting-edge technologies as internet usage is increasing and new sales channels like e-commerce, mobile shopping, and smart technologies are emerging. With the help of latest technologies, such as self-checkout kiosks and smart point-of-sale systems, the market is growing rapidly. According to ZDNet, 70% of businesses have or are implementing a digital transformation plan. Since companies are moving towards digital transformation, the global recommendation engine market is expected to register a high CAGR in the forecast period.

Retailers may use digital transformation to increase customer acquisition, improve customer engagement, save operational costs, and boost staff morale. Along with other advantages, recommendation engine have a favorable effect on revenue and profits. Over the course of the predicted period, this positive influence will generate sizable prospects for the adoption of recommendation engines.

Moreover, the industry for recommendation engines is always concerned about the issue of inaccurate labeling brought by shifting user preferences. However, engineers are always trying to increase the precision and utility of suggestions. This fact is restraining the market growth in the forecast period.

The Market is Expanding as a Result of Rising Demand for Customized Digital Commerce Experiences Across Mobile and the Web

Companies are looking for strategies and tools to take advantage of. Millions of unique consumers can benefit from these experiences by using private data. Execution determines the outcome. When properly implemented, personalized customer experience may help businesses stand out from the competition, win over customers' loyalty, and achieve a durable competitive advantage-all of which are crucial in the current market.

Due to the increasing demand from consumers, many marketing professionals across organizations have shifted their attention to improving customer experience over time. A 10% boost in year-over-year growth, a 10% rise in average order value, and a 25% increase in closure rates, for instance, according to Adobe company, can be observed by businesses with the strongest omnichannel customer engagement strategy. In addition, companies with strong omnichannel customer interaction strategies and consumer service improvement programs retain 89% of their consumers on average, as opposed to 33% for those with weaker strategies. Technologies make sure that the brands provide a consistent message about their services across all channels in light of the expanding number of channels in operation. During the projected period, the market is anticipated to benefit from the rising need for enhanced customer service.

Market Segmentation

The global recommendation engine market is divided based on type, deployment model, enterprise size, application, end user and region. Based on type, the market is divided into collaborative filtering, content-based filtering, and hybrid recommendation. Based on deployment model, the market is divided into on-premises and cloud, Based on enterprise size, the market is divided into large enterprises, small & medium enterprises. Based on application, the market is divided into Personalized Campaigns & Customer Delivery, Strategy Operations & Planning, Product Planning, and Proactive Asset Management. Based on end user, the market is segmented into retail & consumer goods, IT & telecom, healthcare & life science, BFSI, media & entertainment, and others. Based on region, the market is divided into North America, Asia-Pacific, Europe, South America, and Middle East & Africa.

Market Players

Major market players in the global recommendation engine market are IBM Corporation, Hewlett Packard Enterprise Development LP, Intel Corporation, Amazon Web Services, Adobe, Salesforce, Inc, Microsoft Corporation, Oracle Corporation, Google LLC, and SAP SE.

Report Scope:

In this report, the global recommendation engine market has been segmented into following categories, in addition to the industry trends which have also been detailed below.

Recommendation Engine Market, By Type:

• Collaborative Filtering
• Content-based Filtering
• Hybrid recommendation

Recommendation Engine Market, By Deployment Model:

• On-Premises
• Cloud

Recommendation Engine Market, By Application:

• Personalized Campaigns & Customer Delivery
• Strategy Operations & Planning
• Product Planning
• Proactive Asset Management

Recommendation Engine Market, By Enterprise Size:

• Large Enterprises
• Small & Medium Enterprises

Recommendation Engine Market, By End User:

• Retail & Consumer Goods
• IT & Telecom
• Healthcare & Life Science
• BFSI
• Media
• Entertainment
• Others

Recommendation Engine Market, By Region:

• North America
• United States
• Canada
• Mexico
• Asia-Pacific
• China
• India
• Japan
• South Korea
• Indonesia
• Europe
• Germany
• United Kingdom
• France
• Russia
• Spain
• South America
• Brazil
• Argentina
• Middle East & Africa
• Saudi Arabia
• South Africa
• Egypt
• UAE
• Israel

Competitive Landscape

• Company Profiles: Detailed analysis of the major companies present in the Global Recommendation Engine Market.

Available Customizations:

• Global recommendation engine market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

• 1.1. Market Definition
• 1.2. Scope of the Market
• 1.3. Markets Covered
• 1.4. Years Considered for Study
• 1.5. Key Market Segmentations

2. Research Methodology

• 2.1. Objective of the Study
• 2.2. Baseline Methodology
• 2.3. Key Industry Partners
• 2.4. Major Association and Secondary Sources
• 2.5. Forecasting Methodology
• 2.6. Data Triangulation & Validation
• 2.7. Assumptions and Limitations

3. Executive Summary

4. Voice of Customers

5. Global Recommendation Engine Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Type (Collaborative Filtering, Content-based Filtering, Hybrid recommendation)
  • 5.2.2. By Deployment Model (On-Premises, Cloud)
  • 5.2.3. By Enterprise Size (Large Enterprises, Small and Medium Enterprises)
  • 5.2.4. By Application (Personalized Campaigns and Customer Delivery, Strategy Operations and Planning, Product Planning and Proactive Asset Management)
  • 5.2.5. By End User (Retail and Consumer Goods, IT and Telecom, Healthcare and Life Science, BFSI, Media and Entertainment, Others)
  • 5.2.6. By Region
• 5.3. By Company (2022)
• 5.4. Market Map

6. North America Recommendation Engine Market Outlook

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Type
  • 6.2.2. By Deployment Model
  • 6.2.3. By Enterprise Size
  • 6.2.4. By Application
  • 6.2.5. By End User
• 6.3. North America: Country Analysis
  • 6.3.1. United States Recommendation Engine Market Outlook
    • 6.3.1.1. Market Size & Forecast
      • 6.3.1.1.1. By Value
    • 6.3.1.2. Market Share & Forecast
      • 6.3.1.2.1. By Type
      • 6.3.1.2.2. By Deployment Model
      • 6.3.1.2.3. By Enterprise Size
      • 6.3.1.2.4. By Application
      • 6.3.1.2.5. By End User
  • 6.3.2. Canada Recommendation Engine Market Outlook
    • 6.3.2.1. Market Size & Forecast
      • 6.3.2.1.1. By Value
    • 6.3.2.2. Market Share & Forecast
      • 6.3.2.2.1. By Type
      • 6.3.2.2.2. By Deployment Model
      • 6.3.2.2.3. By Enterprise Size
      • 6.3.2.2.4. By Application
      • 6.3.2.2.5. By End User
  • 6.3.3. Mexico Recommendation Engine Market Outlook
    • 6.3.3.1. Market Size & Forecast
      • 6.3.3.1.1. By Value
    • 6.3.3.2. Market Share & Forecast
      • 6.3.3.2.1. By Type
      • 6.3.3.2.2. By Deployment Model
      • 6.3.3.2.3. By Enterprise Size
      • 6.3.3.2.4. By Application
      • 6.3.3.2.5. By End User

7. Asia-Pacific Recommendation Engine Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Type
  • 7.2.2. By Deployment Model
  • 7.2.3. By Enterprise Size
  • 7.2.4. By Application
  • 7.2.5. By End User
• 7.3. Asia-Pacific: Country Analysis
  • 7.3.1. China Recommendation Engine Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Type
      • 7.3.1.2.2. By Deployment Model
      • 7.3.1.2.3. By Enterprise Size
      • 7.3.1.2.4. By Application
      • 7.3.1.2.5. By End User
  • 7.3.2. India Recommendation Engine Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Type
      • 7.3.2.2.2. By Deployment Model
      • 7.3.2.2.3. By Enterprise Size
      • 7.3.2.2.4. By Application
      • 7.3.2.2.5. By End User
  • 7.3.3. Japan Recommendation Engine Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Type
      • 7.3.3.2.2. By Deployment Model
      • 7.3.3.2.3. By Enterprise Size
      • 7.3.3.2.4. By Application
      • 7.3.3.2.5. By End User
  • 7.3.4. South Korea Recommendation Engine Market Outlook
    • 7.3.4.1. Market Size & Forecast
      • 7.3.4.1.1. By Value
    • 7.3.4.2. Market Share & Forecast
      • 7.3.4.2.1. By Type
      • 7.3.4.2.2. By Deployment Model
      • 7.3.4.2.3. By Enterprise Size
      • 7.3.4.2.4. By Application
      • 7.3.4.2.5. By End User
  • 7.3.5. Indonesia Recommendation Engine Market Outlook
    • 7.3.5.1. Market Size & Forecast
      • 7.3.5.1.1. By Value
    • 7.3.5.2. Market Share & Forecast
      • 7.3.5.2.1. By Type
      • 7.3.5.2.2. By Deployment Model
      • 7.3.5.2.3. By Enterprise Size
      • 7.3.5.2.4. By Application
      • 7.3.5.2.5. By End User

8. Europe Recommendation Engine Market Outlook

• 8.1. Market Size & Forecast
  • 8.1.1. By Value
• 8.2. Market Share & Forecast
  • 8.2.1. By Type
  • 8.2.2. By Deployment Model
  • 8.2.3. By Enterprise Size
  • 8.2.4. By Application
  • 8.2.5. By End User
• 8.3. Europe: Country Analysis
  • 8.3.1. Germany Recommendation Engine Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1. By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1. By Type
      • 8.3.1.2.2. By Deployment Model
      • 8.3.1.2.3. By Enterprise Size
      • 8.3.1.2.4. By Application
      • 8.3.1.2.5. By End User
  • 8.3.2. United Kingdom Recommendation Engine Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1. By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1. By Type
      • 8.3.2.2.2. By Deployment Model
      • 8.3.2.2.3. By Enterprise Size
      • 8.3.2.2.4. By Application
      • 8.3.2.2.5. By End User
  • 8.3.3. France Recommendation Engine Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1. By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1. By Type
      • 8.3.3.2.2. By Deployment Model
      • 8.3.3.2.3. By Enterprise Size
      • 8.3.3.2.4. By Application
      • 8.3.3.2.5. By End User
  • 8.3.4. Russia Recommendation Engine Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Type
      • 8.3.4.2.2. By Deployment Model
      • 8.3.4.2.3. By Enterprise Size
      • 8.3.4.2.4. By Application
      • 8.3.4.2.5. By End User
  • 8.3.5. Spain Recommendation Engine Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Type
      • 8.3.5.2.2. By Deployment Model
      • 8.3.5.2.3. By Enterprise Size
      • 8.3.5.2.4. By Application
      • 8.3.5.2.5. By End User

9. South America Recommendation Engine Market Outlook

• 9.1. Market Size & Forecast
  • 9.1.1. By Value
• 9.2. Market Share & Forecast
  • 9.2.1. By Type
  • 9.2.2. By Deployment Model
  • 9.2.3. By Enterprise Size
  • 9.2.4. By Application
  • 9.2.5. By End User
• 9.3. South America: Country Analysis
  • 9.3.1. Brazil Recommendation Engine Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1. By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1. By Type
      • 9.3.1.2.2. By Deployment Model
      • 9.3.1.2.3. By Enterprise Size
      • 9.3.1.2.4. By Application
      • 9.3.1.2.5. By End User
  • 9.3.2. Argentina Recommendation Engine Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1. By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1. By Type
      • 9.3.2.2.2. By Deployment Model
      • 9.3.2.2.3. By Enterprise Size
      • 9.3.2.2.4. By Application
      • 9.3.2.2.5. By End User

10. Middle East & Africa Recommendation Engine Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Type
  • 10.2.2. By Deployment Model
  • 10.2.3. By Enterprise Size
  • 10.2.4. By Application
  • 10.2.5. By End User
• 10.3. Middle East & Africa: Country Analysis
  • 10.3.1. Saudi Arabia Recommendation Engine Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Type
      • 10.3.1.2.2. By Deployment Model
      • 10.3.1.2.3. By Enterprise Size
      • 10.3.1.2.4. By Application
      • 10.3.1.2.5. By End User
  • 10.3.2. South Africa Recommendation Engine Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Type
      • 10.3.2.2.2. By Deployment Model
      • 10.3.2.2.3. By Enterprise Size
      • 10.3.2.2.4. By Application
      • 10.3.2.2.5. By End User
  • 10.3.3. UAE Recommendation Engine Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Type
      • 10.3.3.2.2. By Deployment Model
      • 10.3.3.2.3. By Enterprise Size
      • 10.3.3.2.4. By Application
      • 10.3.3.2.5. By End User
  • 10.3.4. Israel Recommendation Engine Market Outlook
    • 10.3.4.1. Market Size & Forecast
      • 10.3.4.1.1. By Value
    • 10.3.4.2. Market Share & Forecast
      • 10.3.4.2.1. By Type
      • 10.3.4.2.2. By Deployment Model
      • 10.3.4.2.3. By Enterprise Size
      • 10.3.4.2.4. By Application
      • 10.3.4.2.5. By End User
  • 10.3.5. Egypt Recommendation Engine Market Outlook
    • 10.3.5.1. Market Size & Forecast
      • 10.3.5.1.1. By Value
    • 10.3.5.2. Market Share & Forecast
      • 10.3.5.2.1. By Type
      • 10.3.5.2.2. By Deployment Model
      • 10.3.5.2.3. By Enterprise Size
      • 10.3.5.2.4. By Application
      • 10.3.5.2.5. By End User

11. Market Dynamics

• 11.1. Drivers
• 11.2. Challenges

12. Market Trends & Developments

13. Company Profiles

• 13.1. IBM Corporation
  • 13.1.1. Business Overview
  • 13.1.2. Key Revenue and Financials (If Available)
  • 13.1.3. Recent Developments
  • 13.1.4. Key Personnel
  • 13.1.5. Key Product/Services
• 13.2. Hewlett Packard Enterprise Development LP
  • 13.2.1. Business Overview
  • 13.2.2. Key Revenue and Financials
  • 13.2.3. Recent Developments
  • 13.2.4. Key Personnel
  • 13.2.5. Key Product/Services
• 13.3. Intel Corporation
  • 13.3.1. Business Overview
  • 13.3.2. Key Revenue and Financials (If Available)
  • 13.3.3. Recent Developments
  • 13.3.4. Key Personnel
  • 13.3.5. Key Product/Services
• 13.4. Amazon Web Services
  • 13.4.1. Business Overview
  • 13.4.2. Key Revenue and Financials (If Available)
  • 13.4.3. Recent Developments
  • 13.4.4. Key Personnel
  • 13.4.5. Key Product/Services
• 13.5. Adobe
  • 13.5.1. Business Overview
  • 13.5.2. Key Revenue and Financials (If Available)
  • 13.5.3. Recent Developments
  • 13.5.4. Key Personnel
  • 13.5.5. Key Product/Services
• 13.6. Salesforce, Inc.
  • 13.6.1. Business Overview
  • 13.6.2. Key Revenue and Financials (If Available)
  • 13.6.3. Recent Developments
  • 13.6.4. Key Personnel
  • 13.6.5. Key Product/Services
• 13.7. Microsoft Corporation.
  • 13.7.1. Business Overview
  • 13.7.2. Key Revenue and Financials
  • 13.7.3. Recent Developments
  • 13.7.4. Key Personnel
  • 13.7.5. Key Product/Services
• 13.8. Oracle Corporation,
  • 13.8.1. Business Overview
  • 13.8.2. Key Revenue and Financials (If Available)
  • 13.8.3. Recent Developments
  • 13.8.4. Key Personnel
  • 13.8.5. Key Product/Services
• 13.9. Google LLC
  • 13.9.1. Business Overview
  • 13.9.2. Key Revenue and Financials (If Available)
  • 13.9.3. Recent Developments
  • 13.9.4. Key Personnel
  • 13.9.5. Key Product/Services
• 13.10. SAP SE
  • 13.10.1. Business Overview
  • 13.10.2. Key Revenue and Financials (If Available)
  • 13.10.3. Recent Developments
  • 13.10.4. Key Personnel
  • 13.10.5. Key Product/Services

14. Strategic Recommendations

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