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市場調查報告書

商品編碼

1401309

全球客戶智慧平台市場 - 2023-2030

Global Customer Intelligence Platform Market - 2023-2030

出版日期: 2023年12月29日 | 出版商:

DataM Intelligence | 英文 255 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

概述

全球客戶智慧平台市場將於 2022 年達到 20 億美元，預計到 2030 年將達到 148 億美元，2023-2030 年預測期間CAGR為 29.1%。

各行業的主要參與者擴大採用以客戶為中心的業務策略。客戶智慧平台提供工具和見解來幫助組織更好地了解和取悅客戶，對於這項變更至關重要。對個人化客戶體驗的需求正在不斷成長。客戶智慧平台使企業能夠分析客戶資料、偏好和行為，從而提供量身定做的產品、服務和通訊。

實施由人工智慧和機器學習演算法支援的高階預測分析可以讓企業更準確地預測客戶行為。其中包括預測未來的購買模式、識別潛在的客戶流失風險以及了解特定客戶行為的可能性。先進的人工智慧技術，包括情感分析和情緒識別，已整合到 CIP 中。它使企業能夠了解客戶在各種互動中表達的情緒、意見和情感，例如客戶評論、社交媒體和客戶服務互動。

由於主要參與者的可用性不斷增加，北美已成為全球客戶智慧平台市場的主導地區。北美各地都有許多創新中心，包括美國矽谷。這些中心鼓勵創業和創新，從而創造和採用客戶智慧平台等尖端技術。北美的組織被迫投資於能夠在高度競爭的商業環境中為他們提供競爭優勢的技術。客戶智慧平台有助於獲得可用於策略決策的見解。

動力學

巨量資料和分析技術的進步

巨量資料技術能夠有效率地處理和儲存大量客戶資料。該功能對於客戶智慧平台至關重要，因為它們需要處理和分析來自不同來源的不同資料集。先進的分析技術，包括即時處理和記憶體運算，使客戶智慧平台能夠即時分析客戶資料。這對於需要即時洞察以做出及時決策並提供個人化客戶體驗的企業至關重要。

巨量資料和分析支援在客戶智慧平台中實施複雜的預測建模和機器學習演算法。該功能使企業能夠預測客戶行為、識別模式並預測未來趨勢。先進的分析技術提高了 CIP 中客戶細分和定位的準確性。企業利用機器學習演算法根據行為、偏好和人口統計資料來識別不同的客戶群，從而實現更有效的行銷策略。

越來越需要全面了解客戶

客戶智慧平台使企業能夠整合和分析來自各個接觸點的資料，從而創建全面的 360 度個人客戶視圖。整體視圖有助於組織了解客戶行為、偏好和跨管道互動。客戶智慧平台充當客戶資料的集中儲存庫，匯集來自 CRM 系統、行銷資料庫、社群媒體和交易記錄等不同來源的資訊。統一的資料儲存庫消除了資料孤島，並為客戶資訊提供了統一的事實來源。

客戶智慧平台包含先進的分析工具，使組織能夠從客戶資料中提取可操作的見解。透過整合分析功能，企業可以發現資料中的模式、趨勢和相關性，從而做出明智的決策。客戶資料的整體視圖使企業能夠提供高度個人化的體驗。透過了解客戶偏好、購買歷史和參與模式，組織可以客製化產品、服務和行銷訊息，以滿足個人客戶的需求。

客戶智慧平台實施的複雜性

將客戶智慧平台與目前的企業系統（包括行銷自動化工具、客戶關係管理軟體和其他資料庫）整合是實施過程中的常見階段。實現無縫整合的複雜性源自於資料結構、格式和協定的變更。

組織通常從各種來源收集客戶資料，包括線上互動、社群媒體、CRM 系統等。這些資料來源的多樣性增加了實施過程的複雜性，因為整合和協調來自不同來源的資料需要仔細的規劃和執行。

全球企業在客戶智慧方面都有獨特的要求。客製化客戶智慧平台以適應特定的業務需求、行業細微差別和組織結構是一項複雜的工作。客製化平台通常涉及配置分析模型、儀表板和報告。客戶智慧平台的採用涉及培訓使用者如何有效利用該平台的功能。分析工具和功能的複雜性需要全面的培訓計劃，以確保使用者從平台中獲得有意義的見解。

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

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