Quick answer
Public data is information anyone can access without logging in, paying, or bypassing a restriction. Personally identifiable information (PII) is any information that can identify a specific individual, either on its own or when combined with other data.
Key takeaways
- Public data is information anyone can access without authentication.
- PII is information that identifies an individual, whether or not it’s publicly available.
- Publicly accessible information can still be PII.
- Privacy laws primarily regulate personal information, not anonymous facts.
- Designing data collection workflows around only necessary, non-personal data reduces legal, operational, and security risk.
If you’re collecting data from the web, one of the most important distinctions to understand is the difference between public data and personally identifiable information (PII). These two categories are often confused because information can be both publicly accessible and personally identifiable at the same time.
Understanding the difference is essential for building compliant data collection workflows, reducing legal risk, and designing web scraping projects that respect privacy regulations.
The key point: public availability does not change whether data counts as PII. A person’s work email listed on a company website is still personal information, even though anyone can view it.
This distinction determines what you can collect, how you should store it, and what legal obligations apply.
What is public data?
Public data is information that’s openly accessible, with no login, payment, or workaround required. It typically doesn’t involve:
- Logging into an account
- Purchasing access
- Bypassing technical restrictions
- Circumventing authentication systems
Common examples:
- Product prices
- Product descriptions
- Stock availability
- Public company filings
- Government datasets
- Public business listings
- News articles
- Weather information
For example, if an online retailer shows a product’s price and availability to every visitor, that’s public data.
But public doesn’t mean unrestricted. Even publicly accessible information can still be subject to:
- Copyright law
- Database rights (varies by jurisdiction)
- Website Terms of Service
- Privacy regulations, if personal information is involved
That’s why organizations should check both accessibility and legal restrictions before collecting data at scale.
What is personally identifiable information (PII)?
PII is any information that identifies, or can reasonably identify, a specific person. Some identifiers work on their own. Others only become identifying when combined with additional information.
Examples of PII:
- Full name
- Personal email address
- Phone number
- Home address
- Passport or national ID number
- Social Security number
- Device identifiers linked to a person
- IP addresses (under many privacy regulations)
- User account IDs
Some data looks harmless alone but becomes PII in combination. For example, date of birth, employer, job title, and city of residence together can uniquely identify someone.
Can information be both public and PII?
Yes, and this is where most confusion starts.
Take a company’s “Meet Our Team” page. It might publicly display:
- Employee names
- Job titles
- Corporate email addresses
- Professional biographies
Everything on that page is publicly accessible. But the employee names and email addresses are still personal information, because they identify specific individuals.
Privacy laws generally regulate personal information regardless of whether it’s publicly visible. That overlap is the whole reason this distinction matters.
Why does the distinction matter?
It affects every stage of a data collection project: compliance obligations, what you collect, and how you store it.
1. Privacy compliance
Most privacy regulations, including GDPR and CCPA/CPRA, focus on personal information, not ordinary public facts. If your dataset contains PII, you may need to:
- Establish a lawful basis for processing
- Limit collection to necessary information
- Protect stored data
- Honor deletion requests
- Document retention policies
If you’re collecting only product prices, inventory levels, or public business information, privacy obligations are generally much lower.
2. Data collection design
Organizations often collect more information than they need. Say an e-commerce company wants competitor pricing intelligence. The data required is usually just:
- Product ID
- Product title
- Brand
- Price
- Availability
- Seller name
There’s rarely a business need to collect reviewer names, customer profiles, or personal contact information. Following data minimization cuts both compliance risk and operational complexity.
3. Data storage requirements
Datasets containing PII need stronger safeguards than datasets containing anonymous market data. Common measures include:
- Encryption
- Role-based access controls
- Audit logging
- Data retention schedules
- Secure deletion processes
These reduce the impact of unauthorized access and support compliance with privacy regulations.
Why does this matter for web scraping?
Businesses commonly use web scraping for competitive pricing, product catalog monitoring, market research, digital shelf analytics, and inventory tracking. These use cases mostly involve factual, non-personal information.
Collecting product prices, stock status, ratings, shipping estimates, and brand information generally carries far fewer privacy concerns than collecting customer accounts, user profiles, personal email addresses, or individual browsing behavior.
Before scraping, it’s worth asking:
- Is the information publicly accessible?
- Does it identify a person?
- Do we actually need the personal information?
- Can we anonymize or exclude it?
These questions cut unnecessary compliance obligations before collection even starts.
Public data and PII are different, but they can overlap
Public data describes how information can be accessed. PII describes what the information represents. A publicly listed business email is visible to everyone, but it’s still personal information because it identifies a specific person.
Recognizing this distinction helps organizations build better governance policies instead of treating all publicly accessible data the same way.
Where the risk usually creeps in
Most compliance problems don’t come from bad intent. They come from teams building scrapers in-house without a clear process for separating public facts from personal data, then collecting more than they need because nobody flagged it early.
A managed web scraping service like ScrapeHero builds this separation into the collection process itself, extracting only the fields a project actually requires (price, stock, SKU, ratings) and excluding personal identifiers by default rather than filtering them out after the fact.
For teams that don’t want to own the ongoing legal review of what a scraper touches, that’s often a simpler path than maintaining an in-house pipeline and re-auditing it every time a target site changes.
FAQ
Is publicly available data automatically exempt from privacy law?
No. Public availability affects accessibility, not legal classification. If the data identifies a person, it can still count as PII regardless of how easy it is to access.
Can a single data point be both public and PII at the same time?
Yes. A work email on a company website is a common example: it’s publicly visible and personally identifiable at the same time.
What’s the safest approach for a web scraping project?
Collect only the data you actually need, avoid personal identifiers where possible, and check both the accessibility and legal status (copyright, ToS, privacy law) of the data before scraping at scale.
Does scraping public product data (price, stock, SKU) carry the same compliance risk as scraping personal data?
No. Product-level facts like price and availability generally carry far lower privacy risk than data tied to individuals, such as customer profiles or personal emails.
