PI vs PII: A Complete Guide to Personal Data Types

PI vs PII at a glance

• Though nuanced, the difference between personally identifiable information (PII) and personal information (PI), is something businesses under modern privacy laws must understand.
• At its core, PII is personal information that could be used to identify a specific individual, including a person’s name, Social Security number, home address, email address, and more.
• Personal information (PI), on the other hand, is more broad and can include details such as a favorite color or shopping habits, as long as they don’t identify a specific person.
• Laws like GDPR, CPRA, and HIPAA set strict rules for handling personal data, with special additional requirements for protecting sensitive PII.

PI vs. PII: What’s the difference?

When it comes to personal data, you’ll often come across two key terms: personal information (PI) and personally identifiable information (PII). While they may seem similar, and are – in that they both refer to data about individuals – they do have key differences that influence how organizations manage and protect them.

Personal information (PI) is a broad term that covers any data linked to an individual, whether directly or indirectly. This can include names, phone numbers, email addresses, or even online behaviors and purchasing patterns. However, by itself PI doesn't always identify a person. For example, a favorite color or a shopping habit may be classified as PI, but can’t reveal the individual's identity.

On the other hand, personally identifiable information (PII) is a specific subset of PI that can be used to identify a person, either on its own or in combination with other data. This could include sensitive information like a person's Social Security number, driver’s license details, passport number, or biometric data (e.g., fingerprints or facial recognition). Because PII can identify someone directly, it requires stricter protection measures to prevent misuse, such as identity theft or data breaches.

Why does the difference matter?

Understanding the distinction between PI and PII is crucial for organizations, as it impacts how they must handle personal data. While both types of information require protection, PII is generally subject to stricter regulations and guidelines due to its higher sensitivity and potential risks.

PI vs. PII: Defining personal information (PI)

Personal Information (PI) encompasses any data related to an individual or household. However, PI doesn’t always identify someone directly.

For instance, knowing someone’s favorite color or shopping preferences doesn’t necessarily reveal their identity. Many laws define PI as any information tied to an individual or household, even if it doesn’t provide a direct identification link.

While companies are required to protect PI, the legal obligations are typically less stringent compared to PII.

PI vs. PII: Defining personally identifiable information (PII)

Personally identifiable information (PII) is a more specific subset of PI—refering to any data that can be used, either alone or in combination with other information, to identify a specific person.

Examples of PII include:

• Social Security numbers
• Driver’s license numbers
• Passport details
• Biometric data (fingerprints, retina scans)
• Location data (addresses, GPS coordinates)
• Facial recognition data

Because of its ability to directly identify individuals, PII is a prime target for cybercriminals and identity thieves, which is why it’s subject to stronger data protection regulations.

Sensitivity levels of personal data

Not all personal data carries the same level of risk. Organizations often classify personal data into different categories based on its sensitivity.

Non-sensitive PII includes data that’s publicly available, such as information found in phone books or court records. While this still needs to be protected, its exposure poses less risk to individuals.

On the other hand, sensitive PII refers to data that, if exposed, could cause significant harm. Examples include:

• Financial account numbers
• Medical records
• Genetic information

Sensitive PII requires extra safeguards, such as encryption and limited access, to protect individuals from harm in the event of a data breach.

Some PI, while not classified as PII, can still be considered sensitive and requires careful handling. For example, information like religious beliefs, racial or ethnic origin, or sexual orientation can be personal and should be protected, even if it doesn’t directly identify someone.

By understanding these distinctions, organizations can better manage personal data, ensuring they apply the right level of protection based on its sensitivity and the risks involved.

PI vs PII: Examples across industries

Here's how different types of data are classified across various sectors, from clear-cut cases to more complex situations.

Healthcare

Clear PII

• Patient ID numbers
• Insurance policy numbers
• Social Security numbers
• Prescription numbers
• Medical record numbers

Example: A patient's prescription number links directly to their identity, medication history, and prescribing doctor—making it clear PII.

PI that becomes PII when combined

• Blood type + zip code + birth date (could identify a small group of people in a specific area)
• Height/weight + specific medical condition + gender (in rare disease cases, could identify individuals)
• Appointment times + clinic location + patient age (in smaller communities, could identify specific people)
• Workout data + heart rate + sleep patterns (when linked to specific medical conditions, could identify patients)

Could go either way

• Fitness app data: Raw step counts are PI, but when combined with GPS tracking and consistent routines like regular visits to a home address, it becomes PII
• Telehealth session data: General wait times are PI, but specific appointment slots with provider names could become PII
• Genetic testing results: Anonymized genetic markers are PI, but become PII when linked to family history or specific traits

E-commerce

Clear PII

• Shipping addresses
• Credit card numbers
• Account login credentials
• Order confirmation numbers
• Customer loyalty program IDs

Example: A loyalty program ID directly connects to a customer's purchase history, contact information, and payment methods.

PI that becomes PII when combined

• Purchase history + delivery preferences + postal code (reveals specific household shopping patterns)
• Regular subscription orders + delivery instructions + payment methods (identifies specific customers)
• Browser behavior + saved addresses + order frequency (creates unique customer profiles)
• Return patterns + payment details + product reviews (can identify specific customers)

Could go either way

• Product reviews: A review about "great running shoes" is PI, but mentioning "perfect for my daily Central Park morning runs" could become PII
• Gift registries: Public wish lists are PI, but combined with event dates and location details could become PII
• Shopping cart abandonment data: General product interest is PI, but paired with stored payment methods and browser fingerprinting could become PII

Education

Clear PII

• Student ID numbers
• Transcripts
• Financial aid records
• Parent/guardian contact information
• Student email addresses

Example: A student transcript contains grades, courses, attendance records, and disciplinary actions—all directly tied to their identity.

PI that becomes PII when combined

• Course schedule + sports team membership + graduation year (could identify specific students)
• Meal plan preferences + dormitory assignment + club memberships (creates unique student profiles)
• Library checkout history + computer lab usage + study room bookings (reveals individual patterns)
• Academic accommodations + class attendance + extracurricular activities (could identify specific students)

Could go either way

• Club membership lists: General participation numbers are PI, but officer roles with meeting times and locations could become PII
• Academic competition results: Overall scores are PI, but specific achievement categories with grade levels could identify students
• Campus event attendance: General head count is PI, but combination of multiple event check-ins could create identifiable patterns

Legal frameworks and compliance standards protecting PI and PII

Data privacy laws set rules for handling personal information. These laws protect people's personal data and give them rights over how it's used.

General Data Protection Regulation

The GDPR is the European Union's flagship data protection law, applying to any organization handling personal data of EU residents. It aims to give individuals greater control over their personal information (PI) and personally identifiable information (PII) by allowing them to access, update, or delete their data.

Companies under GDPR must obtain clear consent from individuals before processing their PI and PII and must explain exactly how this data will be used. If a data breach occurs, businesses are required to report it quickly, protecting individuals from potential misuse of their PI and PII. Non-compliance can lead to severe fines.

How Transcend help protect PI and PII for GDPR compliance

• DSR Automation simplifies data subject request (DSRs) fulfillment, enabling businesses to quickly locate, modify, delete, or return PII as users exercise their rights under GDPR.
• Consent Management ensures clear tracking of user opt-in preferences, safeguarding the handling of PII across all systems, while ensuring transparency about data use.
• Data mapping tools like Data Inventory and Silo Discovery automatically discover and categorize PI and PII across systems, helping businesses maintain comprehensive and accurate Records of Processing Activities (ROPA)—a requirement of GDPR Article 30.

California Consumer Privacy Act (CCPA)

The CCPA focuses on the protection of personal information (PI) for California residents, covering data that can be "reasonably linked" to individuals or households. This includes direct identifiers like Social Security numbers as well as indirect data, such as browsing history or shopping habits.

The CCPA gives individuals the right to know what data is being collected, and the ability to access, delete, or opt out of having their PI and PII sold. Violating these rights can result in hefty fines of up to $7,500 per intentional violation.

How Transcend helps protect PI and PII for CCPA Compliance

• DSR Automation allows businesses to quickly and easily process Data Subject Requests, helping California residents access, delete, or opt-out of the sale of their PI and PII through a user-friendly Privacy Center.
• Tools like Data Inventory, Silo Discovery, and Structured Discovery automatically locate and categorize PI and PII within your systems, ensuring you have a comprehensive understanding of the personal data you handle for CCPA compliance.
• Consent Management helps businesses track and enforce consumer opt-out preferences across all data flows, ensuring the protection of PI and PII while maintaining CCPA compliance.

Related post: Achieving CCPA Cookie Consent Compliance—A 2024 Guide

Health Insurance Portability and Accountability Act (HIPAA)

HIPAA governs the protection of Protected Health Information (PHI), a specific category of PII that includes health-related data, such as medical records, lab results, and insurance details. Healthcare providers, insurers, and their partners must safeguard PHI, ensuring that it’s stored securely, shared only with proper authorization, and accessible to patients for review and correction.

How Transcend helps protect PHI and PII for HIPAA compliance

• DSR Automation provides secure access management and automates privacy request fulfillment for healthcare organizations, ensuring the protection of PHI in compliance with HIPAA.
• Security controls like role-based access, audit trails, deterministic queries, and encryption protect PHI and other sensitive PII, helping organizations stay compliant with HIPAA’s Security Rule.
• Privacy Center allows healthcare organizations to clearly communicate privacy practices to patients and securely manage PHI and other sensitive PII requests beyond basic email systems.

Security measures for protecting data

If you collect any sort of personal or sensitive information from your consumers or your customers, data security should always be top of mind. There are many best practices for protecting customer data, but the two most important are strong encryption and strict access controls.

Here's how they work to save you and your customers from breaches (as well as a lot of headaches).

Encryption technologies

Encryption converts data into an unreadable format that can only be decoded with the right key. Some common encryption methods include:

• AES (Advanced Encryption Standard)
• RSA (Rivest-Shamir-Adleman)
• TLS/SSL for data in transit

Organizations should use strong encryption (https://transcend.io/blog/privacy-playbook-safeguard-against-a-data-breach-start-with-privacy) for both stored data and data being transferred. End-to-end encryption adds an extra layer of protection for communications.

Proper key management is also essential. Keys must be stored securely and rotated regularly. Multi-factor authentication should be required to access encryption keys.

Transcend provides end-to-end encryption for user data across your tech stack, backed by industry-leading security controls and deterministic queries to keep personal information secure wherever it's stored.

Access controls and regular audits

Limiting data access helps prevent breaches. Organizations should follow the principle of least privilege, which means giving users only the minimum access needed to do their jobs.

Role-based access control (or RBAC) assigns permissions based on job roles. It helps manage access for many users. Other important access controls include:

• Strong password policies
• Multi-factor authentication
• Session timeouts
• Access logging

Regular security audits are needed to find weaknesses. Audits should check:

• Who has access to what data
• If access rights are still needed
• For any unusual access patterns

Automated tools can help monitor for suspicious activity. Manual reviews by security experts are also important.

Consequences of data breaches

In 2023, data breaches hit an all-time high, with incidents increasing by 72%. This surge in breaches is a growing concern for both individuals and organizations, as the consequences often extend far beyond the initial event.

For businesses, the financial fallout is significant. Companies can face hefty fines, legal costs, and expenses related to fixing security vulnerabilities. On top of that, they may lose customers who, in search of greater security, turn to competitors.

For individuals, the stakes are even higher. When sensitive data is exposed, it can lead to identity theft, fraud, and a lengthy, costly process of recovery. The damage is not just financial—it can also cause significant emotional distress for victims.

Reputation is another critical aspect. Companies that suffer a data breach often lose customer trust, which can have a lasting impact on their brand and future growth. Beyond that, the effects can ripple through the organization in unexpected ways, including:

• Operational disruptions
• Loss of intellectual property
• Strained business relationships
• Higher cybersecurity insurance premiums

The severity of the impact largely depends on the type of data exposed. Breaches involving sensitive information, such as financial or health data, tend to cause more damage.

To protect themselves, companies need to be proactive. This means implementing strong security measures, educating employees on best practices, and having a clear plan in place for quickly responding to breaches when they occur.

Techniques for data discovery and classification

To effectively protect your users' data, it’s essential to keep it organized, secure, and properly mapped. You wouldn’t want to leave sensitive information scattered across systems or duplicated. Here’s how to stay on top of your data and protect it properly.

Data classification methods

Data classification is the process of organizing information based on its sensitivity and importance. It helps ensure that data is handled appropriately and securely. You can classify data manually or automate the process using tools that categorize it quickly and efficiently.

Common classification levels include:

• Public: Non-sensitive data, accessible to everyone
• Internal: Information meant for internal use only, not for public sharing
• Confidential: Sensitive data that requires protection but isn’t classified as highly sensitive
• Restricted: Highly sensitive data with strict access controls to prevent unauthorized access

Proper classification informs decisions on access controls, encryption, and retention policies, making it a key piece of effectively protecting PI and PII.

Data discovery tools

Data discovery tools help locate and map PI and PII across your systems. These tools scan databases, networks, and files to identify where sensitive information is stored—helping your business comply with privacy regulations and reduce data breach risks.

Key features of data discovery tools include:

• Pattern matching to identify PII
• File type recognition for finding sensitive data
• Database scanning to locate PII across systems
• Network mapping to understand where data resides
• Reporting and analytics to track data across your organization

These tools help businesses uncover hidden or forgotten data, prevent unauthorized access, and keep data inventories up-to-date with regular scans. With Transcend’s next-generation data discovery tools, you can detect both obvious and hard-to-find personal information, while our smart content classification quickly organizes data for compliance purposes.

With continuous monitoring and automatic updates to your data inventory, Transcend ensures you always have a real-time, accurate view of PI and PII across your organization.

PII in the healthcare sector

The healthcare industry has some of the strictest rules when it comes to protecting PII, especially when it involves medical records and health insurance data.

Protected medical records

Medical records contain Protected Health Information (PHI), which includes details about an individual’s health, care, and payment history. This can also include personal identifiers like names, addresses, and birthdates. Healthcare providers must maintain the privacy of PHI using secure systems and only allow authorized staff to access or edit these records.

Patients have the right to access their medical records, request copies, and ask for corrections if they find errors in the data.

Health insurance information

Health insurance data, including policy numbers and claims histories, is highly sensitive. Not only does this data contain financial information, but it can also reveal sensitive details about an individual’s health and treatments.

Insurance providers must implement strong data protection measures, including secure claims processing systems and staff privacy training. Even routine documents, like Explanation of Benefits statements, contain sensitive information that requires careful handling.

The impact of a breach in health insurance data goes beyond privacy concerns—it can affect coverage decisions, pricing, and access to care. Protecting this information is vital for both individual privacy and healthcare outcomes.

The risk of PII exposure to cyber threats

With the explosion of data collection, cybercriminals have more opportunities to target PI and PII. As more personal data is stored online, the value of breaching these data stores continues to rise.

Over 500,000 new malware variants are detected daily, and cybercriminals are constantly developing more sophisticated ways to access and exploit PII.

Common cyber threats targeting PII include:

• Advanced phishing campaigns that impersonate trusted services
• Ransomware attacks that encrypt sensitive data
• SQL injection attacks that target customer databases
• Social engineering tactics exploiting insider access
• Zero-day vulnerabilities that exploit unpatched security flaws
• Man-in-the-middle attacks that intercept data in transit

The consequences of PII exposure go beyond immediate financial losses. Stolen personal data can lead to identity theft, fraudulent accounts, and unauthorized transactions, which can harm individuals' credit scores and damage businesses' reputations. When breaches occur, companies face not only financial penalties but also loss of customer trust and long-term damage to their brand.

Protecting PII: A multi-layered approach

To effectively protect PII, organizations need a robust, multi-layered security strategy:

• Implement strong access controls and authentication protocols
• Conduct regular security awareness training for employees
• Use end-to-end encryption to secure sensitive data
• Maintain continuous network monitoring for potential threats
• Perform regular security assessments to identify vulnerabilities
• Follow data minimization principles to limit data collection and storage

Individuals can also take steps to protect their own personal data, such as using strong passwords, limiting the amount of personal information shared, and monitoring their credit regularly.

Together, these layered defenses help create multiple barriers against the growing threat of cyberattacks targeting PII.

Empower your customers to protect sensitive information

Data protection is a shared responsibility between businesses and their customers. With Transcend’s autonomous privacy operations, you can minimize risk and ensure your business remains secure.

Our Privacy Center makes it easy for your customers to manage their personal data. Instead of dealing with confusing contracts or outdated forms, they can easily opt-out or exercise their data rights in a transparent, user-friendly way.

Our suite of privacy compliance tools, along with end-to-end encryption, ensures that you stay legally compliant and protected. Trust in data protection solutions that work—and give your customers the confidence that their data is in safe hands.

Contact us today to strengthen your privacy practices and protect your business year-round.

About Transcend

Transcend is a next-generation platform for privacy and data governance. Encoding privacy at the code layer, we provide solutions for any privacy challenge your teams may be facing—including classifying, protecting, and managing personal information across your tech stack.

From automated data mapping tools that discover and classify PI and PII, to DSR Automation for handling privacy requests, to Consent Management for controlling data collection and sharing, Transcend has you covered as your company grows and evolves in a swiftly changing regulatory environment.