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レコメンデーションエンジン市場レポート：2030年までの動向、予測、競合分析

Recommendation Engine Market Report: Trends, Forecast and Competitive Analysis to 2030
出版日: | 発行: Lucintel | ページ情報: 英文 150 - page report | 納期: 3営業日

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レコメンデーションエンジン市場レポート：2030年までの動向、予測、競合分析
出版日: 2024年01月29日
発行: Lucintel
ページ情報: 英文 150 - page report
納期: 3営業日
ご注意事項 :
本レポートは最新情報反映のため適宜更新し、内容構成変更を行う場合があります。ご検討の際はお問い合わせください。
  • 全表示
  • 概要
  • 目次
概要

レコメンデーションエンジンの動向と予測

レコメンデーションエンジン市場の将来は、IT、ヘルスケア、リテール、BFSI、メディアとエンターテインメント市場における機会で有望視されています。レコメンデーションエンジン市場は、2024年から2030年までのCAGRが22.3%で、2030年までに推定143億米ドルに達すると予想されます。この市場の主な促進要因は、顧客体験の向上を重視する傾向が強まっていること、デジタル化のトレンドが高まっていること、大量のデータ分析に対する需要が高まっていることです。

レコメンデーションエンジン市場の洞察

Lucintel社は、顧客サービスや顧客体験の向上に対するニーズの高まりから、パーソナライズされたキャンペーンや顧客デリバリーが予測期間中最大のセグメントであり続けると予測しています。

北米は、革新的な技術の受容が拡大し、新技術に対する政府の支援が増加しているため、予測期間中も最大地域であり続けるでしょう。

よくある質問

Q1.市場規模は？

A1.世界のレコメンデーションエンジン市場は、2030年までに推定143億米ドルに達すると予想されています。

Q2.市場の成長予測は？

A2.世界のレコメンデーションエンジン市場は、2024年から2030年にかけてCAGR 22.3%で成長する見込みです。

Q3.市場の成長に影響を与える主な促進要因は？

A3.この市場の主な促進要因は、顧客体験の向上を重視する傾向の高まり、デジタル化の傾向の高まり、大量のデータ分析に対する需要の高まりです。

Q4.市場の主要セグメントは？

A4.レコメンデーションエンジン市場の将来は、IT、ヘルスケア、小売、BFSI、メディア＆エンターテインメント市場において有望です。

Q5.市場の主要企業は？

A5.レコメンデーションエンジンの主要企業は以下の通りです。

  • Adobe
  • Amazon Web Services
  • Google
  • Hewlett Packard Enterprise Development
  • International Business Machines
  • Intel
  • Microsoft
  • Oracle
  • Salesforce.com
  • SAP

Q6.今後、最大となる市場セグメントは？

A6.Lucintel社は、顧客サービスや顧客体験の向上に対するニーズの高まりから、パーソナライズされたキャンペーンや顧客提供が予測期間中最大のセグメントであり続けると予測しています。

Q7.市場において、今後5年間に最大になると予想される地域は？

A7.北米は、革新的技術の受容が拡大し、新技術に対する政府の支援も増加しているため、予測期間中も最大地域であり続ける。

Q8.レポートのカスタマイズは可能？

A8.はい、Lucintelは追加費用なしで10%のカスタマイズを提供します。

目次

第1章 エグゼクティブサマリー

第2章 世界のレコメンデーションエンジン市場：市場力学

  • イントロダクション、背景、分類
  • サプライチェーン
  • 業界の促進要因と課題

第3章 2018年から2030年までの市場動向と予測分析

  • マクロ経済動向（2018～2023年）と予測（2024～2030年）
  • 世界のレコメンデーションエンジン市場動向（2018～2023年）と予測（2024～2030年）
  • タイプ別の世界のレコメンデーションエンジン市場
    • 協調フィルタリング
    • コンテンツベースのフィルタリング
    • ハイブリッドの推奨
  • 組織別の世界のレコメンデーションエンジン市場
    • 中小企業
    • 大企業
  • アプリケーション別の世界のレコメンデーションエンジン市場
    • パーソナライズされたキャンペーンと顧客への配信
    • 戦略運営と企画立案
    • 商品企画とプロアクティブな資産管理
  • 最終用途別の世界のレコメンデーションエンジン市場
    • 情報技術
    • ヘルスケア
    • 小売り
    • BFSI
    • メディアとエンターテイメント
    • その他

第4章 2018年から2030年までの地域別の市場動向と予測分析

  • 地域別の世界のレコメンデーションエンジン市場
  • 北米のレコメンデーションエンジン市場
  • 欧州のレコメンデーションエンジン市場
  • アジア太平洋のレコメンデーションエンジン市場
  • その他地域のレコメンデーションエンジン市場

第5章 競合の分析

  • 製品ポートフォリオ分析
  • 運用上の統合
  • ポーターのファイブフォース分析

第6章 成長機会と戦略的分析

  • 成長機会分析
    • タイプ別の世界のレコメンデーションエンジン市場の成長機会
    • 組織別の世界のレコメンデーションエンジン市場の成長機会
    • アプリケーション別の世界のレコメンデーションエンジン市場の成長機会
    • 最終用途別の世界のレコメンデーションエンジン市場の成長機会
    • 地域別の世界のレコメンデーションエンジン市場の成長機会
  • 世界のレコメンデーションエンジン市場における新たな動向
  • 戦略的分析
    • 新製品の開発
    • 世界のレコメンデーションエンジン市場の能力拡大
    • 世界のレコメンデーションエンジン市場における合併、買収、合弁事業
    • 認証とライセンシング

第7章 有力企業の企業プロファイル

  • Adobe
  • Amazon Web Services
  • Google
  • Hewlett Packard Enterprise Development
  • International Business Machines
  • Intel
  • Microsoft
  • Oracle
  • Salesforce.com
  • SAP
目次

Recommendation Engine Trends and Forecast

The future of the recommendation engine market looks promising with opportunities in the information technology, healthcare, retail, BFSI, and media & entertainment markets. The recommendation engine market is expected to reach an estimated $14.3 billion by 2030 with a CAGR of 22.3% from 2024 to 2030. The major drivers for this market are increasing emphasis on improving the customer experience, rising trend of digitalization, and growing demand for large volumes of data analysis.

A more than 150-page report is developed to help in your business decisions.

Recommendation Engine by Segment

The study includes a forecast for the global recommendation engine by type, organization, application, end use, and region.

Recommendation Engine Market by Type [Shipment Analysis by Value from 2018 to 2030]:

  • Collaborative Filtering
  • Content-Based Filtering
  • Hybrid Recommendation

Recommendation Engine Market by Organization [Shipment Analysis by Value from 2018 to 2030]:

  • SMEs
  • Large Enterprise

Recommendation Engine Market by Application [Shipment Analysis by Value from 2018 to 2030]:

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

Recommendation Engine Market by End Use [Shipment Analysis by Value from 2018 to 2030]:

  • Information Technology
  • Healthcare
  • Retail
  • BFSI
  • Media & Entertainment
  • Others

Recommendation Engine Market by Region [Shipment Analysis by Value from 2018 to 2030]:

  • North America
  • Europe
  • Asia Pacific
  • The Rest of the World

List of Recommendation Engine Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. With these strategies recommendation engine companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the recommendation engine companies profiled in this report include-

  • Adobe
  • Amazon Web Services
  • Google
  • Hewlett Packard Enterprise Development
  • International Business Machines
  • Intel
  • Microsoft
  • Oracle
  • Salesforce.com
  • SAP

Recommendation Engine Market Insights

Lucintel forecasts that personalized campaigns and customer delivery will remain the largest segment over the forecast period due to an increase in the need for improved customer service and experiences.

North America will remain the largest region over the forecast period due to the region's expanding acceptance of innovative technology and increased government backing for new technologies.

Features of the Recommendation Engine Market

Market Size Estimates: Recommendation engine market size estimation in terms of value ($B).

Trend and Forecast Analysis: Market trends (2018 to 2023) and forecast (2024 to 2030) by various segments and regions.

Segmentation Analysis: Recommendation engine market size by type, organization, application, end use, and region in terms of value ($B).

Regional Analysis: Recommendation engine market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different type, organization, application, end use, and regions for the recommendation engine market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the recommendation engine market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

FAQ

Q1. What is the recommendation engine market size?

Answer: The global recommendation engine market is expected to reach an estimated $14.3 billion by 2030.

Q2. What is the growth forecast for recommendation engine market?

Answer: The global recommendation engine market is expected to grow with a CAGR of 22.3% from 2024 to 2030.

Q3. What are the major drivers influencing the growth of the recommendation engine market?

Answer: The major drivers for this market are increasing emphasis on improving the customer experience, rising trend of digitalization, and growing demand for large volumes of data analysis.

Q4. What are the major segments for recommendation engine market?

Answer: The future of the recommendation engine market looks promising with opportunities in the information technology, healthcare, retail, BFSI, and media & entertainment markets.

Q5. Who are the key recommendation engine market companies?

Answer: Some of the key recommendation engine companies are as follows.

  • Adobe
  • Amazon Web Services
  • Google
  • Hewlett Packard Enterprise Development
  • International Business Machines
  • Intel
  • Microsoft
  • Oracle
  • Salesforce.com
  • SAP

Q6. Which recommendation engine market segment will be the largest in future?

Answer: Lucintel forecasts that personalized campaigns and customer delivery will remain the largest segment over the forecast period due to an increase in the need for improved customer service and experiences.

Q7. In recommendation engine market, which region is expected to be the largest in next 5 years?

Answer: North America will remain the largest region over the forecast period due to the region's expanding acceptance of innovative technology and increased government backing for new technologies.

Q.8 Do we receive customization in this report?

Answer: Yes, Lucintel provides 10% customization without any additional cost.

This report answers following 11 key questions:

  • Q.1. What are some of the most promising, high-growth opportunities for the recommendation engine market by type (collaborative filtering, content-based filtering, and hybrid recommendation), organization (SMEs and large enterprise), application (personalized campaigns and customer delivery, strategy operations and planning, and product planning and proactive asset management), end use (information technology, healthcare, retail, BFSI, media & entertainment, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
  • Q.2. Which segments will grow at a faster pace and why?
  • Q.3. Which region will grow at a faster pace and why?
  • Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
  • Q.5. What are the business risks and competitive threats in this market?
  • Q.6. What are the emerging trends in this market and the reasons behind them?
  • Q.7. What are some of the changing demands of customers in the market?
  • Q.8. What are the new developments in the market? Which companies are leading these developments?
  • Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
  • Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
  • Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Global Recommendation Engine Market : Market Dynamics

  • 2.1: Introduction, Background, and Classifications
  • 2.2: Supply Chain
  • 2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2018 to 2030

  • 3.1. Macroeconomic Trends (2018-2023) and Forecast (2024-2030)
  • 3.2. Global Recommendation Engine Market Trends (2018-2023) and Forecast (2024-2030)
  • 3.3: Global Recommendation Engine Market by Type
    • 3.3.1: Collaborative Filtering
    • 3.3.2: Content-based Filtering
    • 3.3.3: Hybrid Recommendation
  • 3.4: Global Recommendation Engine Market by Organization
    • 3.4.1: SMEs
    • 3.4.2: Large Enterprise
  • 3.5: Global Recommendation Engine Market by Application
    • 3.5.1: Personalized Campaigns and Customer Delivery
    • 3.5.2: Strategy Operations and Planning
    • 3.5.3: Product Planning and Proactive Asset Management
  • 3.6: Global Recommendation Engine Market by End Use
    • 3.6.1: Information Technology
    • 3.6.2: Healthcare
    • 3.6.3: Retail
    • 3.6.4: BFSI
    • 3.6.5: Media & Entertainment
    • 3.6.6: Others

4. Market Trends and Forecast Analysis by Region from 2018 to 2030

  • 4.1: Global Recommendation Engine Market by Region
  • 4.2: North American Recommendation Engine Market
    • 4.2.1: North American Recommendation Engine Market by Application: Personalized Campaigns and Customer Delivery, Strategy Operations and Planning, and Product Planning and Proactive Asset Management
    • 4.2.2: North American Recommendation Engine Market by End Use: Information Technology, Healthcare, Retail, BFSI, Media & Entertainment, and Others
  • 4.3: European Recommendation Engine Market
    • 4.3.1: European Recommendation Engine Market by Application: Personalized Campaigns and Customer Delivery, Strategy Operations and Planning, and Product Planning and Proactive Asset Management
    • 4.3.2: European Recommendation Engine Market by End Use: Information Technology, Healthcare, Retail, BFSI, Media & Entertainment, and Others
  • 4.4: APAC Recommendation Engine Market
    • 4.4.1: APAC Recommendation Engine Market by Application: Personalized Campaigns and Customer Delivery, Strategy Operations and Planning, and Product Planning and Proactive Asset Management
    • 4.4.2: APAC Recommendation Engine Market by End Use: Information Technology, Healthcare, Retail, BFSI, Media & Entertainment, and Others
  • 4.5: ROW Recommendation Engine Market
    • 4.5.1: ROW Recommendation Engine Market by Application: Personalized Campaigns and Customer Delivery, Strategy Operations and Planning, and Product Planning and Proactive Asset Management
    • 4.5.2: ROW Recommendation Engine Market by End Use: Information Technology, Healthcare, Retail, BFSI, Media & Entertainment, and Others

5. Competitor Analysis

  • 5.1: Product Portfolio Analysis
  • 5.2: Operational Integration
  • 5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

  • 6.1: Growth Opportunity Analysis
    • 6.1.1: Growth Opportunities for the Global Recommendation Engine Market by Type
    • 6.1.2: Growth Opportunities for the Global Recommendation Engine Market by Organization
    • 6.1.3: Growth Opportunities for the Global Recommendation Engine Market by Application
    • 6.1.4: Growth Opportunities for the Global Recommendation Engine Market by End Use
    • 6.1.5: Growth Opportunities for the Global Recommendation Engine Market by Region
  • 6.2: Emerging Trends in the Global Recommendation Engine Market
  • 6.3: Strategic Analysis
    • 6.3.1: New Product Development
    • 6.3.2: Capacity Expansion of the Global Recommendation Engine Market
    • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global Recommendation Engine Market
    • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

  • 7.1: Adobe
  • 7.2: Amazon Web Services
  • 7.3: Google
  • 7.4: Hewlett Packard Enterprise Development
  • 7.5: International Business Machines
  • 7.6: Intel
  • 7.7: Microsoft
  • 7.8: Oracle
  • 7.9: Salesforce.com
  • 7.10: SAP