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Report Scope & Overview:

Data Brokers Market is anticipated to develop at a CAGR of 4.41% from 2023 to 2030, from a value of USD 269.1 billion in 2022 to USD 382.10 billion in 2030.

A data broker is responsible for collecting information about individuals from both private sources and public records. This includes census and change of address records, driving records, user-contributed material on social networking sites, media and court reports, consumer purchase histories, voter registration lists, terrorist watch lists, Bank card transaction records, health care authorities, and web browsing histories are some of the key sources contributing to the expansion of this market. The growth of this market can be attributed to various factors. Firstly, there is an increasing demand for various data-based information regarding consumers, technical data related to weather and natural events, information about different organizations, drug studies, and real estate information, among others. This demand has led companies and organizations to seek out data brokerage firms to obtain necessary, relevant, and customized data-based information. This information is crucial for formulating marketing strategies in a more viable and effective manner. market for data brokerage services is expanding due to the need for accurate and comprehensive data. Companies and organizations recognize the importance of utilizing data to gain insights into their target audience, market trends, and industry developments. By partnering with data brokers, they can access a wide range of information that can help them make informed decisions and stay ahead of the competition.

Data Brokers Market Revenue Analysis

Market Dynamics

Drivers

  • There has been a noticeable rise in the need for effective data monetization and storage solutions.

  • Increasing demand for various data-based information regarding consumers and others.

  • New technologies and business models, such as social media and mobile applications, have revolutionized the accessibility, variety, and sheer volume of information available to us.

A data broker's operations lie in the storage of personal information and the collection of behavioral data from various online and offline sources, all without direct interaction with individuals. These data brokers not only possess highly informative and valuable data but also wield an immense amount of power. The ability to tap into such comprehensive data holds immense transformative potential for organizations, governments, the military, and even private individuals. In today's society, data serves as the bedrock of productivity, competition, and innovation. The advent of new technologies and business models, such as social media and mobile apps, has not only amplified the availability, diversity, and sheer quantity of data but has also given rise to a surge in data-driven enterprises. According to estimates by Gartner, there are approximately 4050 data brokers operating globally. Furthermore, government agencies and non-governmental organizations have made approximately 9.92 million datasets freely available to the public.

Restrains

  • Violation of privacy is a significant obstacle to market growth.

Data brokers acquire, process, and exchange data about individuals without their explicit consent or knowledge. This lack of awareness makes it challenging for consumers to fully understand the extent of their data-sharing agreements. Often, data-sharing consent is sneakily added, leaving users unaware of the implications. Unexpected data transfers can occur due to industry practices. For instance, a user may unknowingly consent to submit personal data to a company, only to find out years later that the data now belongs to a different company with entirely different practices. Data brokers often defend their actions by highlighting the anonymity of the data they collect and sell. However, numerous instances have proven that anonymous data can be easily de-anonymized by cross-referencing various data sets.

Opportunities

  • The increasing adoption of alternative data in the investment industry is expected to create significant opportunities for the data brokers market.

  • The increasing adoption of the Internet of Things (IoT) in various industries and the rising number of interconnected devices worldwide are notable trends.

Challenges

  • There are numerous stringent regulations in place, particularly in developed economies

Impact of the Russia-Ukraine

The conflict disrupts or damages data infrastructure in Ukraine or neighboring regions, it could affect the availability and quality of data that data brokers rely on. Data centers, servers, and communication networks may be vulnerable to disruption. Increased geopolitical tensions can lead to concerns about data privacy and security. Data brokers may face stricter regulations and scrutiny regarding how they handle and share data, particularly if there are concerns about data falling into the wrong hands or being exploited for political or malicious purposes. Geopolitical instability can create economic uncertainty. Businesses may become more cautious about their investments in data services, leading to a slowdown in the growth of the data broker’s market. Depending on the extent of international sanctions imposed on Russia, data brokers may face restrictions on doing business with Russian entities or using data sourced from Russia. This could disrupt their operations and sourcing strategies. the war may increase the demand for intelligence and geopolitical risk analysis services. Data brokers specializing in these areas may see increased business as organizations seek to navigate the uncertain geopolitical landscape. The conflict could also result in an escalation of cyberattacks and cyber threats. Data brokers, as holders of valuable data, may face an increased risk of cyberattacks, and they may need to invest more in cybersecurity measures.

Impact of Recession

Many organizations may face budget constraints during a recession, leading them to prioritize essential expenses over data purchases. This can result in reduced spending on data broker services. With businesses operating on tighter budgets, they may become more discerning about the quality of the data they purchase. Data brokers will need to ensure the accuracy and relevance of their data to maintain or grow their customer base. Economic downturns can sometimes lead to increased regulatory scrutiny and calls for greater data privacy and security regulations. Data brokers may face stricter compliance requirements, which could increase their operational costs. While some sectors may reduce their data purchases during a recession, others may increase them. For example, financial institutions might intensify their data analysis efforts to manage risk better. Data brokers can adapt to shifting market needs to remain relevant. Data breaches and cyber threats become more prevalent during economic downturns as criminals seek to exploit vulnerabilities. Data brokers will need to invest in robust cybersecurity measures to protect their data assets. Businesses looking to continue using data broker services may exert price pressure during a recession, seeking discounts or more favorable terms. Data brokers may need to be flexible with their pricing structures. Recessions can prompt data brokers to diversify their offerings and invest in long-term strategies. For example, they may focus on expanding their data analytics capabilities or exploring partnerships with other data-related companies.

Key Market Segmentation

By Data Type

  • Structured

  • Unstructured

  • Custom Structured

By Pricing Model    

  • Subscription Paid

  • Pay Per Use Paid

  • Hybrid Paid Models

By Customer Category

  • Consumers

  • Businesses

By End-User

  • Government

  • Manufacturing

  • BFSI

  • Healthcare

  • FMCG

Data Brokers Market Segmentation Analysis

Regional Analysis

The North American market dominated the Data Broker industry in 2022, holding the largest revenue share, and is projected to maintain its leadership position throughout the forecast period. This growth can be attributed to the presence of prominent data broker organizations and the prevalence of unregulated data broker solutions in the United States. These organizations are already capitalizing on the sale of vast amounts of data about US residents to a wide range of enterprises, including insurance companies, law enforcement agencies, and international groups. Surprisingly, despite the billion-dollar business revolving around customer data in the United States, most consumers remain oblivious to its existence. Data brokers, which are companies that collect and trade customer information, thrive on the valuable data provided by consumers. These data brokers employ various strategies, including marketing, to leverage the data they possess. Unfortunately, the United States lacks federal legislation governing the acquisition and utilization of these data-by-data brokers, leaving customers vulnerable and unprotected. This failure to regulate has resulted in a disservice to customers. However, there are a few states, such as Vermont and California, that have taken proactive measures to safeguard consumer data in the online realm.

REGIONAL COVERAGE:

North America

  • US

  • Canada

  • Mexico

Europe

  • Eastern Europe

    • Poland

    • Romania

    • Hungary

    • Turkey

    • Rest of Eastern Europe

  • Western Europe

    • Germany

    • France

    • UK

    • Italy

    • Spain

    • Netherlands

    • Switzerland

    • Austria

    • Rest of Western Europe

Asia Pacific

  • China

  • India

  • Japan

  • South Korea

  • Vietnam

  • Singapore

  • Australia

  • Rest of Asia Pacific

Middle East & Africa

  • Middle East

    • UAE

    • Egypt

    • Saudi Arabia

    • Qatar

    • Rest of Middle East

  • Africa

    • Nigeria

    • South Africa

    • Rest of Africa

Latin America

  • Brazil

  • Argentina

  • Colombia

  • Rest of Latin America

Key Players:

The major players in the market are Oracle, Thomson Reuters, Equifax, Inc., CoreLogic, TransUnion LLC, ID Analytics, LLC, Acxiom LLC, IBM, Ignite Technologies, Epsilon Data Management, LLC, Alibaba, TowerData Inc., Intelius, Inc., and others in the final report.

Oracle-Company Financial Analysis

Recent development

In June 2022, CoreLogic, a provider of property information analytics and data-enabled solutions, launched a cutting-edge cloud-based platform known as the Discovery Platform. This platform revolutionizes property analytics and data exchange, offering users a seamless and efficient experience.

In February 2022, Acxiom forged a strategic partnership with Treasure Data, a leading enterprise customer data platform (CDP). This collaboration aims to integrate Acxiom's Real Identity with Treasure Data CDP, enhancing Acxiom's data collection and identification capabilities. By leveraging this integration, brands can now easily identify and retain their valuable customers, empowering them to make informed business decisions.

In February 2021, Equifax, Inc. successfully completed the acquisition of AccountScore Holdings Limited, a prominent company specializing in transaction data analytics. This acquisition marks a significant milestone for Equifax as it expands its product offerings by seamlessly integrating AccountScore's bank transaction data into its existing credit bureau information. This integration empowers Equifax to provide comprehensive and accurate insights to its clients, enabling them to make informed financial decisions.

Data Brokers Market Report Scope
Report Attributes Details
Market Size in 2022  US$ 269.1 Bn
Market Size by 2030  US$ 382.10 Bn
CAGR   CAGR of 4.41 % From 2023 to 2030
Base Year 2022
Forecast Period  2023-2030
Historical Data  2019-2021
Report Scope & Coverage Market Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments • By Data Type (Structured, Unstructured, Custom Structured)
• By Pricing Model (Subscription Paid, Pay Per Use Paid, Hybrid Paid Models)
• By Customer Category (Consumers, Businesses)
• By End-User (Government, Manufacturing, BFSI, Healthcare, FMCG)
Regional Analysis/Coverage North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia Rest of Latin America)
Company Profiles Oracle, Thomson Reuters, Equifax, Inc., CoreLogic, TransUnion LLC, ID Analytics, LLC, Acxiom LLC, IBM, Ignite Technologies, Epsilon Data Management, LLC, Alibaba, TowerData Inc., Intelius, Inc.
Key Drivers • There has been a noticeable rise in the need for effective data monetization and storage solutions.
• Increasing demand for various data-based information regarding consumers and others.
• New technologies and business models, such as social media and mobile applications, have revolutionized the accessibility, variety, and sheer volume of information available to us.
Market Restraints • Violation of privacy is a significant obstacle to market growth. 

 

Frequently Asked Questions

Ans. The CAGR of the Data Brokers Market for the forecast period 2022-2030 is 4.48%.

Ans: The market is expected to grow to USD 382.10 billion by the forecast period of 2030.

Ans: Yes, you can buy reports in bulk quantity as per your requirements. Check Here for more details.

Ans: North America region dominates the Data Brokers Market.

Ans:

  • There has been a noticeable rise in the need for effective data monetization and storage solutions.
  • Increasing demand for various data-based information regarding consumers and others.
  • New technologies and business models, such as social media and mobile applications, have revolutionized the accessibility, variety, and sheer volume of information available to us.

Table of Contents
1. Introduction

1.1 Market Definition
1.2 Scope
1.3 Research Assumptions

2. Research Methodology

3. Market Dynamics
3.1 Drivers
3.2 Restraints
3.3 Opportunities
3.4 Challenges

4. Impact Analysis
4.1 Impact of Russia-Ukraine War
4.2 Impact of Ongoing Recession
4.2.1 Introduction
4.2.2 Impact on major economies
4.2.2.1 US
4.2.2.2 Canada
4.2.2.3 Germany
4.2.2.4 France
4.2.2.5 United Kingdom
4.2.2.6 China
4.2.2.7 japan
4.2.2.8 South Korea
4.2.2.9 Rest of the World

5. Value Chain Analysis

6. Porter’s 5 forces model

7. PEST Analysis

8. Data Brokers Market Segmentation, By Data Type
8.1 Structured
8.2 Unstructured
8.3 Custom Structured

9. Data Brokers Market Segmentation, By Pricing Model
9.1 Subscription Paid
9.2 Pay Per Use Paid
9.3 Hybrid Paid Models

10. Data Brokers Market Segmentation, By Customer Category
10.1 Consumers
10.2 Businesses

11.  Data Brokers Market Segmentation, By End User
11.1 Government
11.2 Manufacturing
11.3 BFSI
11.4 Healthcare
11.5 FMCG

12. Regional Analysis
12.1 Introduction
12.2 North America
12.2.1 North America Data Brokers Market By Country
12.2.2 North America Data Brokers Market By Data Type
12.2.3 North America Data Brokers Market By Pricing Model
12.2.4 North America Data Brokers Market By Customer Category
12.2.5 North America Data Brokers Market By End User
12.2.6 USA
12.2.6.1 USA Data Brokers Market By Data Type
12.2.6.2 USA Data Brokers Market By Pricing Model
12.2.6.3 USA Data Brokers Market By Customer Category
12.2.6.4 USA Data Brokers Market By End User
12.2.7 Canada
12.2.7.1 Canada Data Brokers Market By Data Type
12.2.7.2 Canada Data Brokers Market By Pricing Model
12.2.7.3 Canada Data Brokers Market By Customer Category
12.2.7.4 Canada Data Brokers Market By End User
12.2.8 Mexico
12.2.8.1 Mexico Data Brokers Market By Data Type
12.2.8.2 Mexico Data Brokers Market By Pricing Model
12.2.8.3 Mexico Data Brokers Market By Customer Category
12.2.8.4 Mexico Data Brokers Market By End User
12.3 Europe
12.3.1 Eastern Europe
12.3.1.1 Eastern Europe Data Brokers Market By Country
12.3.1.2 Eastern Europe Data Brokers Market By Data Type
12.3.1.3 Eastern Europe Data Brokers Market By Pricing Model
12.3.1.4 Eastern Europe Data Brokers Market By Customer Category
12.3.1.5 Eastern Europe Data Brokers Market By End User
12.3.1.6 Poland
12.3.1.6.1 Poland Data Brokers Market By Data Type
12.3.1.6.2 Poland Data Brokers Market By Pricing Model
12.3.1.6.3 Poland Data Brokers Market By Customer Category
12.3.1.6.4 Poland Data Brokers Market By End User
12.3.1.7 Romania
12.3.1.7.1 Romania Data Brokers Market By Data Type
12.3.1.7.2 Romania Data Brokers Market By Pricing Model
12.3.1.7.3 Romania Data Brokers Market By Customer Category
12.3.1.7.4 Romania Data Brokers Market By End User
12.3.1.8 Hungary
12.3.1.8.1 Hungary Data Brokers Market By Data Type
12.3.1.8.2 Hungary Data Brokers Market By Pricing Model
12.3.1.8.3 Hungary Data Brokers Market By Customer Category
12.3.1.8.4 Hungary Data Brokers Market By End User
12.3.1.9 Turkey
12.3.1.9.1 Turkey Data Brokers Market By Data Type
12.3.1.9.2 Turkey Data Brokers Market By Pricing Model
12.3.1.9.3 Turkey Data Brokers Market By Customer Category
12.3.1.9.4 Turkey Data Brokers Market By End User
12.3.1.10 Rest of Eastern Europe
12.3.1.10.1 Rest of Eastern Europe Data Brokers Market By Data Type
12.3.1.10.2 Rest of Eastern Europe Data Brokers Market By Pricing Model
12.3.1.10.3 Rest of Eastern Europe Data Brokers Market By Customer Category
12.3.1.10.4 Rest of Eastern Europe Data Brokers Market By End User
12.3.2 Western Europe
12.3.2.1 Western Europe Data Brokers Market By Country
12.3.2.2 Western Europe Data Brokers Market By Data Type
12.3.2.3 Western Europe Data Brokers Market By Pricing Model
12.3.2.4 Western Europe Data Brokers Market By Customer Category
12.3.2.5 Western Europe Data Brokers Market By End User
12.3.2.6 Germany
12.3.2.6.1 Germany Data Brokers Market By Data Type
12.3.2.6.2 Germany Data Brokers Market By Pricing Model
12.3.2.6.3 Germany Data Brokers Market By Customer Category
12.3.2.6.4 Germany Data Brokers Market By End User
12.3.2.7 France
12.3.2.7.1 France Data Brokers Market By Data Type
12.3.2.7.2 France Data Brokers Market By Pricing Model
12.3.2.7.3 France Data Brokers Market By Customer Category
12.3.2.7.4 France Data Brokers Market By End User
12.3.2.8 UK
12.3.2.8.1 UK Data Brokers Market By Data Type
12.3.2.8.2 UK Data Brokers Market By Pricing Model
12.3.2.8.3 UK Data Brokers Market By Customer Category
12.3.2.8.4 UK Data Brokers Market By End User
12.3.2.9 Italy
12.3.2.9.1 Italy Data Brokers Market By Data Type
12.3.2.9.2 Italy Data Brokers Market By Pricing Model
12.3.2.9.3 Italy Data Brokers Market By Customer Category
12.3.2.9.4 Italy Data Brokers Market By End User
12.3.2.10 Spain
12.3.2.10.1 Spain Data Brokers Market By Data Type
12.3.2.10.2 Spain Data Brokers Market By Pricing Model
12.3.2.10.3 Spain Data Brokers Market By Customer Category
12.3.2.10.4 Spain Data Brokers Market By End User
12.3.2.11 Netherlands
12.3.2.11.1 Netherlands Data Brokers Market By Data Type
12.3.2.11.2 Netherlands Data Brokers Market By Pricing Model
12.3.2.11.3 Netherlands Data Brokers Market By Customer Category
12.3.2.11.4 Netherlands Data Brokers Market By End User
12.3.2.12 Switzerland
12.3.2.12.1 Switzerland Data Brokers Market By Data Type
12.3.2.12.2 Switzerland Data Brokers Market By Pricing Model
12.3.2.12.3 Switzerland Data Brokers Market By Customer Category
12.3.2.12.4 Switzerland Data Brokers Market By End User
12.3.2.13 Austria
12.3.2.13.1 Austria Data Brokers Market By Data Type
12.3.2.13.2 Austria Data Brokers Market By Pricing Model
12.3.2.13.3 Austria Data Brokers Market By Customer Category
12.3.2.13.4 Austria Data Brokers Market By End User
12.3.2.14 Rest of Western Europe
12.3.2.14.1 Rest of Western Europe Data Brokers Market By Data Type
12.3.2.14.2 Rest of Western Europe Data Brokers Market By Pricing Model
12.3.2.14.3 Rest of Western Europe Data Brokers Market By Customer Category
12.3.2.14.4 Rest of Western Europe Data Brokers Market By End User
12.4 Asia-Pacific
12.4.1 Asia Pacific Data Brokers Market By Country
12.4.2 Asia Pacific Data Brokers Market By Data Type
12.4.3 Asia Pacific Data Brokers Market By Pricing Model
12.4.4 Asia Pacific Data Brokers Market By Customer Category
12.4.5 Asia Pacific Data Brokers Market By End User
12.4.6 China
12.4.6.1 China Data Brokers Market By Data Type
12.4.6.2 China Data Brokers Market By Pricing Model
12.4.6.3 China Data Brokers Market By Customer Category
12.4.6.4 China Data Brokers Market By End User
12.4.7 India
12.4.7.1 India Data Brokers Market By Data Type
12.4.7.2 India Data Brokers Market By Pricing Model
12.4.7.3 India Data Brokers Market By Customer Category
12.4.7.4 India Data Brokers Market By End User
12.4.8 Japan
12.4.8.1 Japan Data Brokers Market By Data Type
12.4.8.2 Japan Data Brokers Market By Pricing Model
12.4.8.3 Japan Data Brokers Market By Customer Category
12.4.8.4 Japan Data Brokers Market By End User
12.4.9 South Korea
12.4.9.1 South Korea Data Brokers Market By Data Type
12.4.9.2 South Korea Data Brokers Market By Pricing Model
12.4.9.3 South Korea Data Brokers Market By Customer Category
12.4.9.4 South Korea Data Brokers Market By End User
12.4.10 Vietnam
12.4.10.1 Vietnam Data Brokers Market By Data Type
12.4.10.2 Vietnam Data Brokers Market By Pricing Model
12.4.10.3 Vietnam Data Brokers Market By Customer Category
12.4.10.4 Vietnam Data Brokers Market By End User
12.4.11 Singapore
12.4.11.1 Singapore Data Brokers Market By Data Type
12.4.11.2 Singapore Data Brokers Market By Pricing Model
12.4.11.3 Singapore Data Brokers Market By Customer Category
12.4.11.4 Singapore Data Brokers Market By End User
12.4.12 Australia
12.4.12.1 Australia Data Brokers Market By Data Type
12.4.12.2 Australia Data Brokers Market By Pricing Model
12.4.12.3 Australia Data Brokers Market By Customer Category
12.4.12.4 Australia Data Brokers Market By End User
12.4.13 Rest of Asia-Pacific
12.4.13.1 Rest of Asia-Pacific Data Brokers Market By Data Type
12.4.13.2 Rest of Asia-Pacific Data Brokers Market By Pricing Model
12.4.13.3 Rest of Asia-Pacific Data Brokers Market By Customer Category
12.4.13.4 Rest of Asia-Pacific Data Brokers Market By End User
12.5 Middle East & Africa
12.5.1 Middle East
12.5.1.1 Middle East Data Brokers Market By Country
12.5.1.2 Middle East Data Brokers Market By Data Type
12.5.1.3 Middle East Data Brokers Market By Pricing Model
12.5.1.4 Middle East Data Brokers Market By Customer Category
12.5.1.5 Middle East Data Brokers Market By End User
12.5.1.6 UAE
12.5.1.6.1 UAE Data Brokers Market By Data Type
12.5.1.6.2 UAE Data Brokers Market By Pricing Model
12.5.1.6.3 UAE Data Brokers Market By Customer Category
12.5.1.6.4 UAE Data Brokers Market By End User
12.5.1.7 Egypt
12.5.1.7.1 Egypt Data Brokers Market By Data Type
12.5.1.7.2 Egypt Data Brokers Market By Pricing Model
12.5.1.7.3 Egypt Data Brokers Market By Customer Category
12.5.1.7.4 Egypt Data Brokers Market By End User
12.5.1.8 Saudi Arabia
12.5.1.8.1 Saudi Arabia Data Brokers Market By Data Type
12.5.1.8.2 Saudi Arabia Data Brokers Market By Pricing Model
12.5.1.8.3 Saudi Arabia Data Brokers Market By Customer Category
12.5.1.8.4 Saudi Arabia Data Brokers Market By End User
12.5.1.9 Qatar
12.5.1.9.1 Qatar Data Brokers Market By Data Type
12.5.1.9.2 Qatar Data Brokers Market By Pricing Model
12.5.1.9.3 Qatar Data Brokers Market By Customer Category
12.5.1.9.4 Qatar Data Brokers Market By End User
12.5.1.10 Rest of Middle East
12.5.1.10.1 Rest of Middle East Data Brokers Market By Data Type
12.5.1.10.2 Rest of Middle East Data Brokers Market By Pricing Model
12.5.1.10.3 Rest of Middle East Data Brokers Market By Customer Category
12.5.1.10.4 Rest of Middle East Data Brokers Market By End User
12.5.2. Africa
12.5.2.1 Africa Data Brokers Market By Country
12.5.2.2 Africa Data Brokers Market By Data Type
12.5.2.3 Africa Data Brokers Market By Pricing Model
12.5.2.4 Africa Data Brokers Market By Customer Category
12.5.2.5 Africa Data Brokers Market By End User
12.5.2.6 Nigeria
12.5.2.6.1 Nigeria Data Brokers Market By Data Type
12.5.2.6.2 Nigeria Data Brokers Market By Pricing Model
12.5.2.6.3 Nigeria Data Brokers Market By Customer Category
12.5.2.6.4 Nigeria Data Brokers Market By End User
12.5.2.7 South Africa
12.5.2.7.1 South Africa Data Brokers Market By Data Type
12.5.2.7.2 South Africa Data Brokers Market By Pricing Model
12.5.2.7.3 South Africa Data Brokers Market By Customer Category
12.5.2.7.4 South Africa Data Brokers Market By End User
12.5.2.8 Rest of Africa
12.5.2.8.1 Rest of Africa Data Brokers Market By Data Type
12.5.2.8.2 Rest of Africa Data Brokers Market By Pricing Model
12.5.2.8.3 Rest of Africa Data Brokers Market By Customer Category
12.5.2.8.4 Rest of Africa Data Brokers Market By End User
12.6. Latin America
12.6.1 Latin America Data Brokers Market By Country
12.6.2 Latin America Data Brokers Market By Data Type
12.6.3 Latin America Data Brokers Market By Pricing Model
12.6.4 Latin America Data Brokers Market By Customer Category
12.6.5 Latin America Data Brokers Market By End User
12.6.6 Brazil
12.6.6.1 Brazil Data Brokers Market By Data Type
12.6.6.2 Brazil Data Brokers Market By Pricing Model
12.6.6.3 Brazil Data Brokers Market By Customer Category
12.6.6.4 Brazil Data Brokers Market By End User
12.6.7 Argentina
12.6.7.1 Argentina Data Brokers Market By Data Type
12.6.7.2 Argentina Data Brokers Market By Pricing Model
12.6.7.3 Argentina Data Brokers Market By Customer Category
12.6.7.4 Argentina Data Brokers Market By End User
12.6.8 Colombia
12.6.8.1 Colombia Data Brokers Market By Data Type
12.6.8.2 Colombia Data Brokers Market By Pricing Model
12.6.8.3 Colombia Data Brokers Market By Customer Category
12.6.8.4 Colombia Data Brokers Market By End User
12.6.9 Rest of Latin America
12.6.9.1 Rest of Latin America Data Brokers Market By Data Type
12.6.9.2 Rest of Latin America Data Brokers Market By Pricing Model
12.6.9.3 Rest of Latin America Data Brokers Market By Customer Category
12.6.9.4 Rest of Latin America Data Brokers Market By End User

13 Company Profile
13.1 Oracle
13.1.1 Company Overview
13.1.2 Financials
13.1.3 Product/Services/Offerings
13.1.4 SWOT Analysis
13.1.5 The SNS View
13.2 Thomson Reuters.
13.2.1 Company Overview
13.2.2 Financials
13.2.3 Product/Services/Offerings
13.2.4 SWOT Analysis
13.2.5 The SNS View
13.3 Equifax, Inc.
13.3.1 Company Overview
13.3.2 Financials
13.3.3 Product/Services/Offerings
13.3.4 SWOT Analysis
13.3.5 The SNS View
13.4 CoreLogic.
13.4.1 Company Overview
13.4.2 Financials
13.4.3 Product/Services/Offerings
13.4.4 SWOT Analysis
13.4.5 The SNS View
13.5 TransUnion LLC.
13.5.1 Company Overview
13.5.2 Financials
13.5.3 Product/Services/Offerings
13.5.4 SWOT Analysis
13.5.5 The SNS View
13.6 ID Analytics, LLC.
13.6.1 Company Overview
13.6.2 Financials
13.6.3 Product/Services/Offerings
13.6.4 SWOT Analysis
13.6.5 The SNS View
13.7 Acxiom LLC.
13.7.1 Company Overview
13.7.2 Financials
13.7.3 Product/Services/Offerings
13.7.4 SWOT Analysis
13.7.5 The SNS View
13.8 IBM.
13.8.1 Company Overview
13.8.2 Financials
13.8.3 Product/Services/Offerings
13.8.4 SWOT Analysis
13.8.5 The SNS View
13.9 Ignite Technologies.
13.9.1 Company Overview
13.9.2 Financials
13.9.3 Product/Services/Offerings
13.9.4 SWOT Analysis
13.9.5 The SNS View
13.10 Epsilon Data Management, LLC.
13.10.1 Company Overview
13.10.2 Financials
13.10.3 Product/Services/Offerings
13.10.4 SWOT Analysis
13.10.5 The SNS View

14. Competitive Landscape
14.1 Competitive Benchmarking
14.2 Market Share Analysis
14.3 Recent Developments
14.3.1 Industry News
14.3.2 Company News
14.3 Mergers & Acquisitions

15. USE Cases and Best Practices
 

16. Conclusion

An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.

Each report that we prepare takes a timeframe of 350-400 business hours for production. Starting from the selection of titles through a couple of in-depth brain storming session to the final QC process before uploading our titles on our website we dedicate around 350 working hours. The titles are selected based on their current market cap and the foreseen CAGR and growth.

 

The 5 steps process:

Step 1: Secondary Research:

Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.

Secondary Research

Step 2: Primary Research

When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data.  This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.

We at SNS Insider have divided Primary Research into 2 parts.

Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.

This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.

Primary Research

Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.

Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.

Step 3: Data Bank Validation

Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.

Data Bank Validation

Step 4: QA/QC Process

After all the data collection and validation our team does a final level of quality check and quality assurance to get rid of any unwanted or undesired mistakes. This might include but not limited to getting rid of the any typos, duplication of numbers or missing of any important information. The people involved in this process include technical content writers, research heads and graphics people. Once this process is completed the title gets uploader on our platform for our clients to read it.

Step 5: Final QC/QA Process:

This is the last process and comes when the client has ordered the study. In this process a final QA/QC is done before the study is emailed to the client. Since we believe in giving our clients a good experience of our research studies, therefore, to make sure that we do not lack at our end in any way humanly possible we do a final round of quality check and then dispatch the study to the client.

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