Data Broker Business Overview
In the ever-expanding world of data, the data broker industry plays a crucial role in collecting, analyzing, and selling data from various sources. This industry has become a thriving and lucrative business, generating upwards of $200 billion in revenue per year (Privacy.com). Understanding the data broker industry and its major players is essential for anyone looking to venture into this field.
Understanding Data Broker Industry
The data broker industry is a multi-billion dollar business that assembles, analyzes, and sells data from various sources to create detailed dossiers on millions of individuals. These dossiers contain personal information like location data, health information, purchase history, and browsing history (Brennan Center). Data brokers gather information from public records, social media platforms, online surveys, and other sources to create comprehensive profiles on individuals. This information is then used by businesses, marketers, and organizations for various purposes, such as targeted advertising, fraud detection, risk mitigation, and more.
The global data broker market has witnessed substantial growth in recent years, with the industry projected to reach $545.431 billion by 2028, growing at a CAGR of 7.96% (Knowledge Sourcing). The industry’s vast potential has attracted numerous players, ranging from small startups to established corporations.
Revenue and Major Players
The data broker industry’s revenue is substantial, with estimates placing it at over $200 billion annually (Privacy.com). This impressive figure highlights the industry’s significant financial opportunities and its critical role in the data ecosystem. The revenue is driven by the demand for data by various industries, including marketing, advertising, financial services, healthcare, and more.
Several major players dominate the data broker industry. These companies have established themselves as leaders by leveraging their expertise, resources, and extensive data repositories. Some prominent data broker companies include:
Acxiom LLC
Acxiom LLC is a renowned data broker company that provides marketing and advertising solutions to businesses. They specialize in collecting and analyzing consumer data to create targeted marketing campaigns. Acxiom’s extensive data sets and advanced analytics capabilities make them a key player in the industry.
Epsilon Data Management LLC
Epsilon Data Management LLC is another prominent data broker company that focuses on customer relationship management and personalized marketing solutions. They offer data-driven marketing strategies, leveraging their vast reservoir of consumer data to help businesses enhance customer engagement and drive growth.
Oracle America Inc.
Oracle America Inc. is a global technology company that operates in various sectors, including data management. They provide data solutions and services, helping businesses effectively manage and utilize their data assets. Oracle’s comprehensive suite of data management tools positions them as a major player in the data broker industry.
Equifax Information Services, LLC
Equifax Information Services, LLC is a leading provider of consumer credit reporting and data analytics. They offer a wide range of solutions, including credit scoring, fraud detection, and identity verification. Equifax’s extensive data resources and expertise in risk assessment make them a significant player in the industry.
These companies, along with other players in the market, contribute to the growth and innovation within the data broker industry. As the industry continues to evolve, new companies and startups emerge, offering specialized data services to cater to specific industry needs.
Understanding the data broker industry landscape and its major players is crucial for those considering starting a data broker business. By gaining insights into the industry’s revenue potential and studying the established companies, aspiring data brokers can position themselves for success in this dynamic and growing field.
Starting a Data Broker Business
If you’re interested in entering the data broker industry and starting your own data broker business, there are several key steps to consider. Establishing a data broker business requires careful planning, legal considerations, and adherence to regulations in order to operate ethically and successfully.
Steps to Establish Your Business
- Define Your Niche: Determine the specific focus or niche for your data broker business. This could involve specializing in a particular industry, such as marketing or risk mitigation, or targeting a specific type of data.
- Develop a Business Plan: Create a comprehensive data broker business plan that outlines your goals, target market, marketing strategies, and financial projections. This plan will serve as a roadmap for your business and help guide your decision-making process.
- Secure Funding: Identify potential sources of funding for your data broker business. This could include personal savings, loans, or seeking investment from venture capitalists or angel investors. A solid business plan and clear value proposition will aid you in securing funding.
- Formulate Data Collection Strategies: Determine how you will collect data for your business. Explore different methods such as partnering with data providers, utilizing web scraping techniques, or leveraging data from public sources. Ensure that your data collection methods comply with applicable laws and regulations.
- Build Data Infrastructure: Establish the necessary infrastructure to store and manage the data you collect. Invest in robust data management systems, security measures, and data storage solutions to ensure the integrity and confidentiality of the data you handle.
- Curate Data Quality: Ensure the accuracy and quality of the data you collect. Implement data cleansing processes, validation techniques, and data verification procedures to maintain reliable and up-to-date data sets.
- Establish Data Privacy Policies: Develop clear and transparent data privacy policies that outline how you collect, use, store, and share data. Prioritize data security and privacy to build trust with your clients and protect the personal information of individuals.
- Create Data Monetization Strategies: Explore different data monetization strategies to generate revenue from the data you collect. This could include selling data sets to interested parties, offering data analytics services, or providing data-driven insights to clients.
Legal Considerations and Regulations
When starting a data broker business, it’s crucial to understand and comply with relevant legal considerations and regulations.
- Data Protection Laws: Familiarize yourself with data protection laws and regulations that govern the collection, storage, and use of personal data. Depending on your jurisdiction, this may include regulations such as the General Data Protection Regulation (GDPR) in the European Union or the California Consumer Privacy Act (CCPA) in the United States.
- Consumer Consent and Opt-Out: Respect consumer rights by obtaining proper consent for data collection and providing clear opt-out mechanisms for individuals who wish to have their data removed or not shared.
- Transparency and Disclosure: Be transparent about your data collection practices, including the types of data collected, purposes for which it is used, and any third-party sharing. Provide individuals with clear information about their rights and options regarding their data.
- Data Security Measures: Implement robust data security measures to protect the confidentiality, integrity, and availability of the data you handle. This may involve encryption, access controls, regular security audits, and training your employees on data protection best practices.
- Industry-Specific Regulations: Depending on the nature of your data broker business, there may be industry-specific regulations to consider. For example, if you handle financial data, you may need to comply with regulations such as the Gramm-Leach-Bliley Act (GLBA) in the United States.
By following these steps and adhering to legal considerations and regulations, you can establish a solid foundation for your data broker business and work towards building a reputable and successful venture in the data broker industry.
Types of Data Brokers
Within the data broker industry, there are various types of brokers that specialize in different areas of data collection and analysis. These include marketing and advertising brokers, fraud detection brokers, risk mitigation brokers, and people search sites. Let’s explore each type in more detail.
Marketing and Advertising Brokers
Marketing and advertising brokers are focused on collecting and analyzing consumer data to facilitate targeted advertising campaigns. They compile comprehensive profiles of individuals, including personal preferences, online behavior, and purchasing history. This data allows marketers to deliver personalized advertisements to specific target audiences. By leveraging the insights derived from consumer data, marketing and advertising brokers help businesses optimize their marketing strategies and increase their chances of reaching potential customers.
Fraud Detection Brokers
Fraud detection brokers play a crucial role in identifying and preventing fraudulent activities. They utilize sophisticated algorithms and data analysis techniques to detect patterns and anomalies in large datasets. By analyzing various data points such as transaction history, IP addresses, and biometric data, fraud detection brokers can flag potentially fraudulent activities in real-time. This helps businesses and financial institutions protect themselves and their customers from potential fraud, ensuring secure transactions and maintaining trust in the digital marketplace.
Risk Mitigation Brokers
Risk mitigation brokers focus on assessing and managing potential risks for businesses and organizations. They gather data from various sources to evaluate risks associated with different aspects of business operations, such as cybersecurity, compliance, and financial stability. By analyzing this data, risk mitigation brokers provide insights and recommendations to help businesses make informed decisions and minimize potential risks. These brokers are instrumental in helping organizations navigate complex risk landscapes and ensure the longevity and security of their operations.
People Search Sites
People search sites specialize in collecting and aggregating personal information about individuals from various sources. They provide users with the ability to search for and access publicly available information such as contact details, social media profiles, and professional histories. People search sites can be used for a variety of purposes, including reconnecting with old friends or colleagues, conducting background checks, or locating individuals for legal or professional reasons. It’s important to note that while this information is publicly available, it can still raise concerns about privacy and data security.
These different types of data brokers play a significant role in the data broker industry, providing valuable insights and services to businesses, organizations, and individuals. However, it’s essential to be aware of the ethical and privacy concerns associated with data collection and usage. The extensive collection and retention of personal information by data brokers have raised questions about data security, privacy practices, and the need for regulatory oversight.
Prominent Data Broker Companies
In the data broker industry, several companies have established themselves as major players, offering a wide range of data services to various industries. Here are some prominent data broker companies:
Acxiom LLC
Acxiom LLC is recognized as one of the leading data selling companies in the industry. They collect data on hundreds of millions of people from various sources such as public records, consumer surveys, and online tracking (Avast). Acxiom has extensive profiles on 700 million consumers, with up to 1,500 specific traits on each individual. These profiles are sold to different industries, including credit card issuers, banks, telecom companies, and insurers. The comprehensive data provided by Acxiom enables businesses to gain valuable insights and make informed decisions.
Epsilon Data Management LLC
Epsilon Data Management LLC is another prominent company in the data broker industry. Their flagship product, PeopleCloud, utilizes consumer behavior data to develop insights for potential purchases (Built In). By combining demographic information, offline purchases, and online actions, Epsilon creates a profile for each lead. They further enhance these profiles by incorporating partner data, forming a “connected identity” for marketing purposes. Epsilon’s data-driven approach helps businesses optimize their marketing strategies and effectively target their desired audience.
Oracle America Inc.
Oracle America Inc. is a well-established data broker company that offers a wide range of data services and solutions. They provide comprehensive data management and analytics tools to help businesses extract valuable insights from their data. Oracle’s data services cover various industries, including finance, healthcare, retail, and more. With their advanced data processing capabilities, Oracle empowers businesses to make data-driven decisions and enhance their operations.
Equifax Information Services, LLC
Equifax Information Services, LLC is one of the three largest credit bureaus, along with Experian and TransUnion. These credit bureaus collect and provide credit history information to creditors and lenders. While Equifax primarily focuses on credit-related data, they also offer additional data services to businesses. However, it’s worth noting that Equifax, along with other credit bureaus, has experienced significant data breaches in the past, which exposed sensitive personal information of millions of individuals (Avast). Despite these incidents, Equifax remains a prominent player in the data broker industry.
These are just a few examples of the prominent data broker companies that operate in the industry. Other notable companies include CoreLogic, which offers consumer information, business intelligence, financial and property data, and analytics to clients in various sectors. With their extensive data resources and expertise, these companies play a significant role in facilitating data-driven decision-making for businesses across multiple industries.
For those considering entering the data broker industry, studying these prominent companies can provide valuable insights into the data broker business model and potential opportunities for growth.
Data Collection Methods
Data brokers rely on various methods to collect the vast amount of data they accumulate. Understanding the sources of data and the role of machine learning applications is crucial for comprehending the data broker industry.
Sources of Data
Data brokers gather information from a multitude of sources, both online and offline. These sources include:
- Social media sites: Data brokers collect data from platforms like Facebook, Twitter, and Instagram, where individuals voluntarily share personal information.
- Public records: Information from public records such as property records, court records, and government databases is often accessed by data brokers.
- Loyalty programs: Data brokers obtain data from loyalty programs offered by retailers, airlines, and other businesses.
- Mobile apps: Data brokers may partner with app developers to collect data through software development kits (SDKs) integrated into mobile applications.
- Banks and insurance agencies: Financial institutions and insurance companies provide data on individuals’ financial activities and policies.
- Other data brokers: Data brokers also exchange and purchase data from one another to enhance their databases.
- Surveys and sweepstakes: Data brokers may collect data through surveys, sweepstakes, and other marketing initiatives.
The data collected from these sources can range from basic personal details to highly sensitive information, including health issues, arrest records, income levels, and physical addresses (Privacy.com, Avast, R Street Institute, OfficeFinder, Market Growth Reports).
Machine Learning Applications
Machine learning plays a significant role in the data broker industry. By utilizing advanced algorithms and statistical models, data brokers can process and analyze the vast amounts of data they collect. Machine learning applications enable data brokers to:
- Identify patterns and correlations: Machine learning algorithms can identify patterns and correlations within the data, allowing data brokers to make inferences and predictions about individuals.
- Segment and categorize data: Machine learning enables data brokers to categorize data into different segments based on various criteria such as demographics, behaviors, and preferences.
- Personalize marketing and advertising efforts: By leveraging machine learning, data brokers can create personalized marketing and advertising campaigns tailored to specific individuals or target audiences.
- Improve data quality: Machine learning algorithms can help data brokers clean and verify data, ensuring its accuracy and reliability.
Machine learning applications empower data brokers to derive insights and extract value from the vast amount of data they collect, enabling them to offer targeted marketing, fraud detection, risk mitigation, and other services to their clients.
Understanding the data collection methods and the role of machine learning applications gives insight into how data brokers operate within the data broker industry. By gathering data from various sources and leveraging advanced technologies, data brokers compile extensive databases that fuel their business models and provide valuable insights to their clients.
Data Monetization and Ethical Concerns
As the data broker industry continues to expand, the practice of data monetization has become a significant aspect of this business. Data monetization involves converting data into a revenue-generating asset, whether by selling data products and services or leveraging data for marketing and advertising purposes. This process has gained substantial traction and is expected to grow exponentially in the coming years, making it a valuable tool for organizations of all sizes (LinkedIn).
Data Monetization Strategies
Data brokers play a crucial role in enabling data monetization. They provide platforms and services that allow organizations to buy and sell data. Some common data broker platforms include Datafindr, DataStreamX, Infochimps, Datasift, Data Market, and Factual. These platforms facilitate the transactional process, making it easier for organizations to monetize their data (LinkedIn).
Artificial intelligence (AI) has also played a significant role in enhancing data monetization strategies. With the power of AI, organizations can analyze large data sets to uncover valuable insights that can be used to generate revenue. This advancement in technology has further increased the value of data monetization for organizations (LinkedIn).
However, it is crucial for organizations to approach data monetization ethically and responsibly. Concerns about consumer privacy are growing as data monetization strategies become more prevalent. Data brokers collect personal data about consumers, which can be used for targeted marketing campaigns and other revenue-generating activities. To maintain trust and avoid damaging their reputation or facing regulatory action, organizations must prioritize consumer privacy. This includes collecting data with consent, being transparent about its use, and implementing robust data protection measures (LinkedIn).
Privacy and Regulatory Challenges
The rapid growth of data monetization has raised privacy and regulatory challenges. Organizations need to be mindful of privacy laws and regulations in the jurisdictions they operate in. This includes complying with data protection regulations such as the General Data Protection Regulation (GDPR) in the European Union or the California Consumer Privacy Act (CCPA) in the United States.
Consumer concerns about the collection and use of personal data are increasing, emphasizing the need for responsible data handling practices. Organizations should prioritize transparency in their data monetization strategies, clearly communicating to consumers how their data is being collected, used, and protected.
By taking privacy and regulatory challenges into account, organizations can navigate the data monetization landscape while maintaining trust and compliance. Implementing robust data governance practices, obtaining necessary consents, and adopting privacy-by-design principles are essential steps in addressing these concerns.
In summary, data monetization offers valuable opportunities for organizations to generate revenue. However, it is crucial to approach data monetization ethically and responsibly, prioritizing consumer privacy and complying with relevant regulations. By doing so, organizations can unlock the potential of data while managing the associated ethical concerns.
