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カスタマーインテリジェンスプラットフォームの世界市場：2023年～2030年

Global Customer Intelligence Platform Market - 2023-2030

出版日
ページ情報
英文 255 Pages
納期
即日から翌営業日
カスタマイズ可能
適宜更新あり
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=144.91円
カスタマーインテリジェンスプラットフォームの世界市場：2023年～2030年
出版日: 2023年12月29日
発行: DataM Intelligence
ページ情報: 英文 255 Pages
納期: 即日から翌営業日
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  • 概要
  • 目次
概要

概要

世界のカスタマーインテリジェンスプラットフォーム市場は、2022年に20億米ドルに達し、2023年から2030年の予測期間中にCAGR 29.1%で成長し、2030年には148億米ドルに達すると予測されています。

各業界の主要プレーヤーは、顧客中心のビジネス戦略を採用するようになっています。組織が顧客をよりよく理解し、喜ばせるためのツールや洞察を提供するカスタマーインテリジェンスプラットフォームは、この変化に不可欠です。パーソナライズされた顧客体験の需要は増加傾向にあります。カスタマーインテリジェンスプラットフォームは、企業が顧客データ、嗜好、行動を分析する力を与え、オーダーメイドの製品、サービス、コミュニケーションを提供することを可能にします。

AIとMLアルゴリズムによる高度な予測分析を導入することで、企業は顧客の行動をより正確に予測できるようになります。これには、将来の購買パターンの予測、潜在的な解約リスクの特定、特定の顧客行動の可能性の把握などが含まれます。センチメント分析や感情認識を含む高度なAI技術は、CIPに統合されています。これにより企業は、カスタマーレビューやソーシャルメディア、カスタマーサービスなど、様々なやり取りで表現される顧客の感情や意見、情動を理解することができます。

北米は、主要プレイヤーの利用可能性が高まっているため、世界のカスタマーインテリジェンスプラットフォーム市場を独占している地域です。米国のシリコンバレーをはじめ、北米全土に数多くのイノベーション・ハブが存在します。このハブは起業家精神とイノベーションを奨励し、その結果、カスタマーインテリジェンスプラットフォームのような最先端技術の創造と採用がもたらされます。北米の組織は、競争の激しいビジネス環境において競争力を高めるテクノロジーへの投資に躍起になっています。カスタマーインテリジェンスプラットフォームは、戦略的意思決定に活用される洞察力の獲得に貢献しています。

市場力学

ビッグデータと分析技術の進歩

ビッグデータ技術は、大量の顧客データの効率的な処理と保存を可能にします。カスタマーインテリジェンスプラットフォームは、様々なソースからの多様なデータセットを扱い、分析する必要があるため、この機能は極めて重要です。リアルタイム処理やインメモリ・コンピューティングなどの高度な分析テクノロジーにより、カスタマーインテリジェンスプラットフォームは顧客データをリアルタイムで分析できます。これは、タイムリーな意思決定を行い、パーソナライズされた顧客体験を提供するために即時の洞察を必要とするビジネスにとって不可欠です。

ビッグデータとアナリティクスは、カスタマーインテリジェンスプラットフォームに高度な予測モデリングと機械学習アルゴリズムを実装することを可能にします。この機能により、企業は顧客の行動を予測し、パターンを特定し、将来の動向を予測することができます。高度なアナリティクス技術は、CIPにおける顧客セグメンテーションとターゲティングの精度を高める。企業は機械学習アルゴリズムを活用し、行動、嗜好、人口統計に基づいて明確な顧客セグメントを特定することで、より効果的なマーケティング戦略を可能にします。

顧客の全体像を把握するニーズの高まり

カスタマーインテリジェンスプラットフォームは、企業が様々なタッチポイントからのデータを統合・分析し、個々の顧客に関する包括的で360度のビューを作成することを可能にします。全体像を把握することで、企業はチャネルを超えた顧客の行動、嗜好、相互作用を理解することができます。カスタマーインテリジェンスプラットフォームは、CRMシステム、マーケティング・データベース、ソーシャルメディア、取引記録などの異種ソースからの情報を統合し、顧客データの集中リポジトリの役割を果たします。統一されたデータリポジトリは、データのサイロを排除し、顧客情報の統一された真実のソースを提供します。

カスタマーインテリジェンスプラットフォームは、企業が顧客データから実用的な洞察を引き出せるようにする高度な分析ツールを組み込んでいます。アナリティクス機能を統合することで、企業はデータ内のパターン、動向、相関関係を明らかにし、情報に基づいた意思決定につなげることができます。顧客データを全体的に把握することで、企業は高度にパーソナライズされた体験を提供できるようになります。顧客の嗜好、購買履歴、エンゲージメント・パターンを理解することで、企業は個々の顧客のニーズに合わせて製品、サービス、マーケティング・メッセージを調整することができます。

カスタマーインテリジェンスプラットフォーム導入の複雑さ

カスタマーインテリジェンスプラットフォームを、マーケティング・オートメーション・ツール、カスタマー・リレーションシップ・マネジメント・ソフトウェア、その他のデータベースなど、現在の企業システムと統合することは、導入手順における一般的な段階です。シームレスな統合を実現する複雑さは、データ構造、フォーマット、およびプロトコルのバリエーションから生じます。

組織は通常、オンライン・インタラクション、ソーシャルメディア、CRMシステムなど、さまざまなソースから顧客データを収集します。これらのデータソースが多様であるため、導入プロセスが複雑化します。

世界企業は、カスタマー・インテリジェンスに関して独自の要件を持っています。特定のビジネスニーズ、業界のニュアンス、組織構造に合わせてカスタマーインテリジェンス・プラットフォームをカスタマイズするのは複雑です。プラットフォームのカスタマイズには、多くの場合、分析モデル、ダッシュボード、レポートの構成が含まれます。カスタマーインテリジェンス・プラットフォームの採用には、プラットフォームの機能を効果的に活用する方法についてユーザーをトレーニングすることが必要です。アナリティクスツールや機能が複雑なため、ユーザーがプラットフォームから有意義な洞察を得られるようにするためには、包括的なトレーニングプログラムが必要です。

目次

第1章 調査手法と調査範囲

第2章 定義と概要

第3章 エグゼクティブサマリー

第4章 市場力学

  • 影響要因
    • 促進要因
      • ビッグデータと分析技術の進歩
      • 顧客の全体像を把握するニーズの高まり
    • 抑制要因
      • カスタマーインテリジェンスプラットフォームの導入の複雑さ
    • 機会
    • 影響分析

第5章 業界分析

  • ポーターのファイブフォース分析
  • サプライチェーン分析
  • 価格分析
  • 規制分析
  • ロシア・ウクライナ戦争の影響分析
  • DMIの見解

第6章 COVID-19分析

第7章 コンポーネント別

  • プラットフォーム
  • サービス別

第8章 展開モード別

  • オンプレミス
  • クラウド

第9章 企業規模別

  • 大企業
  • 中小企業

第10章 データチャネル別

  • ウェブと電子メール
  • ソーシャルメディア
  • モバイル
  • コールセンター
  • インストア
  • その他

第11章 用途別

  • 顧客データの収集と管理
  • 顧客セグメンテーションとターゲティング
  • 顧客経験管理
  • 顧客行動分析
  • オムニチャネル・マーケティング
  • パーソナライズドレコメンデーション
  • その他

第12章 エンドユーザー別

  • BFSI
  • IT・通信
  • 小売・eコマース
  • ヘルスケア
  • メディア・エンターテイメント
  • 旅行・観光
  • その他

第13章 地域別

  • 北米
    • 米国
    • カナダ
    • メキシコ
  • 欧州
    • ドイツ
    • 英国
    • フランス
    • イタリア
    • スペイン
    • その他欧州
  • 南米
    • ブラジル
    • アルゼンチン
    • その他南米
  • アジア太平洋
    • 中国
    • インド
    • 日本
    • オーストラリア
    • その他アジア太平洋地域
  • 中東・アフリカ

第14章 競合情勢

  • 競合シナリオ
  • 市況/シェア分析
  • M&A分析

第15章 企業プロファイル

  • SAS Institute Inc.
    • 会社概要
    • 製品ポートフォリオと説明
    • 財務概要
    • 主な発展
  • Oracle Corporation
  • International Business Machines Corporation
  • Accenture
  • Google LLC
  • SAP SE
  • Microsoft Corporation
  • Informatica Inc.
  • Salesforce, Inc.
  • Adobe Inc.

第16章 付録

目次
Product Code: ICT7650

Overview

Global Customer Intelligence Platform Market reached US$ 2.0 Billion in 2022 and is expected to reach US$ 14.8 Billion by 2030, growing with a CAGR of 29.1% during the forecast period 2023-2030.

Major key players across industries are increasingly adopting customer-centric business strategies. Customer intelligence platforms, which offer tools and insights to help organisations better understand and please their customers, are crucial to this change. The demand for personalized customer experiences is on the rise. Customer intelligence platforms empower businesses to analyze customer data, preferences and behaviors, allowing them to deliver tailored products, services and communications.

Implementing advanced predictive analytics powered by AI and ML algorithms allows businesses to forecast customer behaviors more accurately. The includes predicting future purchasing patterns, identifying potential churn risks and understanding the likelihood of specific customer actions. Advanced AI techniques, including sentiment analysis and emotion recognition, are integrated into CIPs. The enables businesses to understand customer sentiments, opinions and emotions expressed in various interactions, such as customer reviews, social media and customer service interactions.

North America is a dominating region in the global customer intelligence platform market due to the growing availability of the major key players. Numerous innovation hubs are found all over North America, including Silicon Valley in U.S. The hubs encourage entrepreneurship and innovation, which results in the creation and adoption of cutting-edge technology like customer intelligence platforms. Organizations in North America are driven to invest in technologies that provide them a competitive edge in the highly competitive business environment. Customer intelligence platforms contribute to gaining insights that are leveraged for strategic decision-making.

Dynamics

Advancements in Big Data and Analytics Technologies

Big Data technologies enable the efficient processing and storage of large volumes of customer data. The capability is crucial for Customer Intelligence Platforms, as they need to handle and analyze diverse datasets from various sources. Advanced analytics technologies, including real-time processing and in-memory computing, allow customer intelligence platforms to analyze customer data in real-time. The is essential for businesses that require immediate insights to make timely decisions and provide personalized customer experiences.

Big Data and Analytics enable the implementation of sophisticated predictive modeling and machine learning algorithms within customer intelligence platforms. The capability allows businesses to forecast customer behaviors, identify patterns and anticipate future trends. Advanced analytics techniques enhance the accuracy of customer segmentation and targeting within CIPs. Businesses leverage machine learning algorithms to identify distinct customer segments based on behavior, preferences and demographics, enabling more effective marketing strategies.

Growing Need to Gain a Holistic View of Customer

Customer Intelligence Platforms enable businesses to consolidate and analyze data from various touchpoints, creating a comprehensive and 360-degree view of individual customers. The holistic view helps organizations understand customer behaviors, preferences and interactions across channels. Customer intelligence platforms serve as centralized repositories for customer data, bringing together information from disparate sources such as CRM systems, marketing databases, social media and transactional records. The unified data repository eliminates data silos and provides a unified source of truth for customer information.

Customer Intelligence Platforms incorporate advanced analytics tools that allow organizations to extract actionable insights from customer data. By integrating analytics capabilities, businesses uncover patterns, trends and correlations within the data, leading to informed decision-making. A holistic view of customer data empowers businesses to deliver highly personalized experiences. By understanding customer preferences, purchase history and engagement patterns organizations tailor products, services and marketing messages to meet individual customer needs.

Complexity of Implementation of Customer Intelligence Platform

Integrating a customer intelligence platform with current corporate systems, including marketing automation tools, customer relationship management software and other databases, is a common phase in the implementation procedure. The complexity of achieving seamless integration arises from variations in data structures, formats and protocols.

Organizations typically gather customer data from various sources, including online interactions, social media, CRM systems and more. The diverse nature of these data sources adds complexity to the implementation process, as consolidating and harmonizing data from disparate origins requires careful planning and execution.

Globally Businesses have unique requirements when it comes to customer intelligence. Customizing the customer intelligence platform to align with specific business needs, industry nuances and organizational structures is intricate. Tailoring the platform often involves configuring analytics models, dashboards and reports. The adoption of Customer Intelligence Platforms involves training users on how to effectively leverage the platform's capabilities. The complexity of the analytics tools and features require comprehensive training programs to ensure that users derive meaningful insights from the platform.

Segment Analysis

The global customer intelligence platform market is segmented based on component, deployment mode, enterprise size, data channel, application, end-user and region.

Growing Adoption of Customer Intelligence Platform Services in Customer Intelligence Platform Market

Based on the component, the customer intelligence platform market is segmented into platforms and services. Implementing a customer intelligence platform is a complex process that involves integrating with existing systems, configuring analytics tools and ensuring data accuracy. CIP Services help businesses navigate this complexity by offering expertise in implementation and customization, ensuring a smooth deployment.

Businesses have unique needs when it comes to customer intelligence. CIP Services provide customization options, allowing organizations to tailor the platform to their specific requirements. The includes configuring analytics dashboards, setting up data integrations and aligning the platform with business goals. CIP Services often include consulting and advisory services where experts work with businesses to identify key objectives, strategies and KPIs. The advisory role helps organizations make informed decisions on how to leverage customer intelligence effectively.

Major key players in the market launched innovative products in the market. For instance, on March 07, 2023, Microsoft launched Dynamics 365 Copilot for applications that handle tasks such as sales, marketing and customer service. The program creates email and contextual chat responses to customer support inquiries using technology from OpenAI. It assists marketers in creating product listings for e-commerce and identifying client segments to target.

Geographical Penetration

North America is a Dominating Region in the Customer Intelligence Platform Market Due to the Availability of Tech-Savvy Consumers

North America accounted for the largest market share in the global customer intelligence platform market due to the high adoption of technology. North America has a robust and technologically advanced economy. The robust economy of the area gives companies the means and inclination to invest in cutting-edge technologies, such as platforms for customer information. North American consumers frequently adopt technological advances. The tech-savvy consumer base encourages businesses to invest in customer intelligence platforms to better understand and cater to consumer preferences.

Major key players in North America launched innovative products in the region which helps to boost regional market growth over the forecast period. For instance, on October 17, 2023, FunnelStory, a provider of product analytics for Go-to-Market (GTM) teams launched an AI-powered product funnel intelligence platform for revenue teams. It allows sales teams to order proofs of concept, trials and renewals that are important and adds consistency to sales projections.

Competitive Landscape

The major global players in the market include SAS Institute Inc. oracle Corporation, International Business Machines Corporation, Accenture, Google LLC, SAP SE, Microsoft Corporation, Informatica Inc., Salesforce, Inc. and Adobe Inc.

COVID-19 Impact Analysis

The pandemic accelerated the pace of digital transformation across industries. Businesses, including those using customer intelligence platforms, increasingly prioritized online channels and digital engagement to meet the changing preferences of consumers. The pandemic led to significant shifts in consumer behavior. There was an increased reliance on online shopping, digital services and remote interactions. Customer intelligence platforms played a crucial role in helping businesses understand and adapt to these evolving consumer preferences.

E-commerce and retail sectors faced both challenges and opportunities. While physical retail was impacted, businesses with strong online platforms leveraged customer intelligence platforms to gain insights into changing customer needs, personalize online experiences and optimize digital marketing strategies. The uncertainty during the pandemic increased the demand for real-time customer insights. Customer intelligence platforms that could provide actionable data to support decision-making became more valuable, helping businesses navigate rapidly changing market conditions.

Russia-Ukraine War Impact Analysis

Geopolitical tensions and conflicts lead to economic uncertainty, affecting businesses' confidence and investment decisions. Companies become more cautious, potentially impacting spending on technologies, including customer intelligence platforms. The Russia-Ukraine war leads to disruptions in global supply chains, affecting the availability of components and technologies. The customer intelligence platforms market relies on suppliers or manufacturing processes in the affected regions, so there are challenges in maintaining a seamless supply chain.

Economic and geopolitical uncertainties lead to shifts in demand patterns. Companies in regions directly impacted by the conflict prioritize different aspects of their operations, potentially affecting the adoption and investment in customer intelligence platforms. Geopolitical events lead to currency fluctuations, impacting the cost of technologies and services. Currency devaluations or fluctuations in exchange rates influence the affordability and adoption of customer intelligence platforms.

By Component

  • Platform
  • Services

By Deployment Mode

  • On-premise
  • Cloud

By Enterprise Size

  • Large Enterprise
  • Small and Medium-sized Enterprise

By Data Channel

  • Web and Email
  • Social Media
  • Mobile
  • Call Centers
  • In Store
  • Others

By Application

  • Customer Data Collection and Management
  • Customer Segmentation and Targeting
  • Customer Experience Management
  • Customer Behavior Analytics
  • Omnichannel Marketing
  • Personalized Recommendation
  • Others

By End-User

  • BFSI
  • IT and Telecom
  • Retail and E-commerce
  • Healthcare
  • Media and Entertainment
  • Travel and Tourism
  • Others

By Region

  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • France
    • Italy
    • Spain
    • Rest of Europe
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia-Pacific
    • China
    • India
    • Japan
    • Australia
    • Rest of Asia-Pacific
  • Middle East and Africa

Key Developments

  • On December 13, 2023, Proxima, a data intelligence software company launched an AI-powered consumer intelligence platform to better evaluate business health and performance. The consumer data intelligence platform from Proxima makes use of over 60 million distinct buyer personas and a huge data pool of first-party data from prominent media channels.
  • On November 18, 2022, ProfitWheel launched the integrated consumer intelligence platform Engine Consumr.ai which enables advertisers and their agencies to discern more effectively who comprises their consumers.
  • On June 29, 2023, Twilio launched Frame AI's customer intelligence platform which provides AI insights and recommendations to enhance contact center operations and customer experiences. The Twilio Customer AI product, which incorporates generative AI into its Customer Engagement Platform enhanced by the new cooperation with Frame AI.

Why Purchase the Report?

  • To visualize the global customer intelligence platform market segmentation based on component, deployment mode, enterprise size, data channel, application, end-user and region, as well as understand key commercial assets and players.
  • Identify commercial opportunities by analyzing trends and co-development.
  • Excel data sheet with numerous data points of customer intelligence platform market-level with all segments.
  • PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
  • Product mapping available as excel consisting of key products of all the major players.

The global customer intelligence platform market report would provide approximately 85 tables, 95 figures and 255 Pages.

Target Audience 2023

  • Manufacturers/ Buyers
  • Industry Investors/Investment Bankers
  • Research Professionals
  • Emerging Companies

Table of Contents

1. Methodology and Scope

  • 1.1. Research Methodology
  • 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

  • 3.1. Snippet by Component
  • 3.2. Snippet by Deployment Mode
  • 3.3. Snippet by Enterprise Size
  • 3.4. Snippet by Data Channel
  • 3.5. Snippet by Application
  • 3.6. Snippet by End-User
  • 3.7. Snippet by Region

4. Dynamics

  • 4.1. Impacting Factors
    • 4.1.1. Drivers
      • 4.1.1.1. Advancements in Big Data and Analytics Technologies
      • 4.1.1.2. Growing Need to Gain a Holistic View of Customer
    • 4.1.2. Restraints
      • 4.1.2.1. Complexity of Implementation of Customer Intelligence Platform
    • 4.1.3. Opportunity
    • 4.1.4. Impact Analysis

5. Industry Analysis

  • 5.1. Porter's Five Force Analysis
  • 5.2. Supply Chain Analysis
  • 5.3. Pricing Analysis
  • 5.4. Regulatory Analysis
  • 5.5. Russia-Ukraine War Impact Analysis
  • 5.6. DMI Opinion

6. COVID-19 Analysis

  • 6.1. Analysis of COVID-19
    • 6.1.1. Scenario Before COVID
    • 6.1.2. Scenario During COVID
    • 6.1.3. Scenario Post COVID
  • 6.2. Pricing Dynamics Amid COVID-19
  • 6.3. Demand-Supply Spectrum
  • 6.4. Government Initiatives Related to the Market During Pandemic
  • 6.5. Manufacturers Strategic Initiatives
  • 6.6. Conclusion

7. By Component

  • 7.1. Introduction
    • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 7.1.2. Market Attractiveness Index, By Component
  • 7.2. Platform*
    • 7.2.1. Introduction
    • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 7.3. Services

8. By Deployment Mode

  • 8.1. Introduction
    • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 8.1.2. Market Attractiveness Index, By Deployment Mode
  • 8.2. On-premise*
    • 8.2.1. Introduction
    • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 8.3. Cloud

9. By Enterprise Size

  • 9.1. Introduction
    • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
    • 9.1.2. Market Attractiveness Index, By Enterprise Size
  • 9.2. Large Enterprise*
    • 9.2.1. Introduction
    • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 9.3. Small and Medium-sized Enterprise

10. By Data Channel

  • 10.1. Introduction
    • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Data Channel
    • 10.1.2. Market Attractiveness Index, By Data Channel
  • 10.2. Web and Email*
    • 10.2.1. Introduction
    • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 10.3. Social Media
  • 10.4. Mobile
  • 10.5. Call Centers
  • 10.6. In Store
  • 10.7. Others

11. By Application

  • 11.1. Introduction
    • 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.1.2. Market Attractiveness Index, By Application
  • 11.2. Customer Data Collection and Management*
    • 11.2.1. Introduction
    • 11.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 11.3. Customer Segmentation and Targeting
  • 11.4. Customer Experience Management
  • 11.5. Customer Behavior Analytics
  • 11.6. Omnichannel Marketing
  • 11.7. Personalized Recommendation
  • 11.8. Others

12. By End-User

  • 12.1. Introduction
    • 12.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 12.1.2. Market Attractiveness Index, By End-User
  • 12.2. BFSI*
    • 12.2.1. Introduction
    • 12.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 12.3. IT and Telecom
  • 12.4. Retail and E-commerce
  • 12.5. Healthcare
  • 12.6. Media and Entertainment
  • 12.7. Travel and Tourism
  • 12.8. Others

13. By Region

  • 13.1. Introduction
    • 13.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
    • 13.1.2. Market Attractiveness Index, By Region
  • 13.2. North America
    • 13.2.1. Introduction
    • 13.2.2. Key Region-Specific Dynamics
    • 13.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 13.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 13.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
    • 13.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Data Channel
    • 13.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 13.2.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 13.2.9. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 13.2.9.1. U.S.
      • 13.2.9.2. Canada
      • 13.2.9.3. Mexico
  • 13.3. Europe
    • 13.3.1. Introduction
    • 13.3.2. Key Region-Specific Dynamics
    • 13.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 13.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 13.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
    • 13.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Data Channel
    • 13.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 13.3.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 13.3.9. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 13.3.9.1. Germany
      • 13.3.9.2. UK
      • 13.3.9.3. France
      • 13.3.9.4. Italy
      • 13.3.9.5. Spain
      • 13.3.9.6. Rest of Europe
  • 13.4. South America
    • 13.4.1. Introduction
    • 13.4.2. Key Region-Specific Dynamics
    • 13.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 13.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 13.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
    • 13.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Data Channel
    • 13.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 13.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 13.4.9. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 13.4.9.1. Brazil
      • 13.4.9.2. Argentina
      • 13.4.9.3. Rest of South America
  • 13.5. Asia-Pacific
    • 13.5.1. Introduction
    • 13.5.2. Key Region-Specific Dynamics
    • 13.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 13.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 13.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
    • 13.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Data Channel
    • 13.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 13.5.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 13.5.9. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 13.5.9.1. China
      • 13.5.9.2. India
      • 13.5.9.3. Japan
      • 13.5.9.4. Australia
      • 13.5.9.5. Rest of Asia-Pacific
  • 13.6. Middle East and Africa
    • 13.6.1. Introduction
    • 13.6.2. Key Region-Specific Dynamics
    • 13.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 13.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 13.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
    • 13.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Data Channel
    • 13.6.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 13.6.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

14. Competitive Landscape

  • 14.1. Competitive Scenario
  • 14.2. Market Positioning/Share Analysis
  • 14.3. Mergers and Acquisitions Analysis

15. Company Profiles

  • 15.1. SAS Institute Inc.*
    • 15.1.1. Company Overview
    • 15.1.2. Product Portfolio and Description
    • 15.1.3. Financial Overview
    • 15.1.4. Key Developments
  • 15.2. Oracle Corporation
  • 15.3. International Business Machines Corporation
  • 15.4. Accenture
  • 15.5. Google LLC
  • 15.6. SAP SE
  • 15.7. Microsoft Corporation
  • 15.8. Informatica Inc.
  • 15.9. Salesforce, Inc.
  • 15.10. Adobe Inc.

LIST NOT EXHAUSTIVE

16. Appendix

  • 16.1. About Us and Services
  • 16.2. Contact Us