Understanding PII and global privacy laws in Marketing

In today’s data-driven marketing environment, personal data has become both a valuable asset and a source of risk. The expansion of privacy regulations around the world, combined with the rise of AI and big data, means marketing and analytics teams must be more vigilant than ever about data protection and PII management.

Artificial intelligence has significantly raised the stakes: models can now scrape, cross-reference, and infer personally identifiable information (PII) at unprecedented scale and speed. From unstructured datasets like customer reviews or open web content. The same tools used to drive personalisation and campaign optimisation can just as easily be misused, making robust privacy protection and strict control over PII essential. It is not surprising, then, that as of early 2025, roughly 144 countries (covering over 80% of the world’s population – have enacted data protection laws). 

This article explores what PII is, how global privacy laws like GDPR and CCPA treat personal data, and best practices for managing PII in marketing analytics to ensure compliance and maintain customer trust.

What is PII and how does it differ from personal data?

Personally Identifiable Information (PII) usually refers to any data that can be used to identify a specific individual, either directly or in combination with other information. This can include direct identifiers (like a person’s name, email address or Social Security number) as well as indirect identifiers such as a combination of birth date and zip code that could pinpoint someone. PII is a widely used term, but there is no single universal legal definition for it: it varies by law and jurisdiction. Generally, if a piece of data refers to or can identify an individual, it’s considered PII. 

PII is often classified by sensitivity: 

• Sensitive PII: high-risk data if leaked, such as passport numbers, medical records, or financial information.
• Non-sensitive PII: lower-risk data like demographic details, which still requires protection.

In the European Union and many other jurisdictions, the term “personal data” is used instead of PII. Under the General Data Protection Regulation (GDPR), personal data is defined broadly as

any information relating to an identified or identifiable natural person

This means all PII is personal data, but not all personal data is necessarily PII. For example, IP addresses, cookies, device IDs, and online identifiers are explicitly counted as personal data under the GDPR, even if they don’t appear to be traditional identifiers. 

The California Consumer Privacy Act (CCPA) and its 2023 amendment California Privacy Rights Act (CPRA) use the term “personal information” in a similarly broad way, covering identifiers like device fingerprints, cookies, and household data as personal information subject to the law.

So, PII and personal data both cover information that could identify individuals, but GDPR’s personal data umbrella is more expansive. Organisations (especially those operating globally) must understand these definitions. If your organization collects user data, whether it’s an email address, a tracking cookie ID, or a device’s IP, privacy laws likely consider that personal data, and you have a duty to protect it.

Why anonymisation matters for privacy compliance

As data volumes grow, one of the most important strategies in privacy protection is anonymisation. Data anonymisation means transforming or removing personal identifiers from data so that individuals can no longer be identified. Under GDPR, truly anonymised data is not considered personal data because it cannot be traced back to a specific person. It’s important because if you can irreversibly anonymise the data you’ve collected (for example, by aggregating it or removing all identifiers), you can still extract useful insights without handling “personal” data in the legal sense.

It’s crucial to distinguish anonymisation from pseudonymization:

• Anonymisation: permanently removes all personal identifiers, making re-identification impossible.
• Pseudonymization: replaces identifiers with coded references (for example, replacing a name with a unique ID number). This makes it harder to identify someone directly, but it could be reversed or re-identified if you have the right key or additional information.

Under GDPR, pseudonymized data is still considered personal data (since re-identification is possible), although it’s subject to slightly relaxed requirements. 

Why does anonymisation matter, and governments create a whole bureaucratic machine around it? The reason is simple. It reduces data breach risk. If anonymised data leaks, it’s far less likely to harm anyone’s privacy.

Then, why is it important to obey those laws? 

First of all, there are ethical reasons. Companies want to build users' trust and contribute to a safer world.

Secondly, it can free up organisations to use data for analysis without breaching laws. For example, a marketing team might anonymise customer data to analyse trends across users without exposing anyone’s personal details. Many analytics tools provide features like IP address masking (replacing the last few digits of an IP) for GDPR compliance. Techniques like hashing or tokenising email addresses (turning them into random strings that can’t be traced back to the original email without a key) are another common method.

Anonymisation techniques

Common techniques include IP address masking, hashing, and tokenisation.

Emerging tools are making anonymisation easier and more powerful. For instance, AI is now being used to help scrub personal identifiers from datasets. A notable example is the A5 PII Anonymiser, an open-source tool that uses a built-in large language model (LLM) to automatically redact PII from documents offline. It can scan PDFs, Word, or Excel files and replace sensitive text (like names or locations) with placeholders, while keeping a hidden mapping so authorised users can re-identify if necessary. This kind of technology allows companies to leverage AI or big data analytics on customer datasets without exposing real personal information, a win-win for data-driven innovation and privacy compliance.

PII in the evolving privacy legislation landscape

Each of the global privacy laws has its own terminology and requirements for personal data/PII. They share a common goal: to give individuals more control over their information and to hold organisations accountable for protecting it. Two of the most influential frameworks are the EU’s GDPR and California’s CCPA (plus CPRA), which have inspired many similar laws worldwide.

​​GDPR (General Data Protection Regulation)

The GDPR, implemented in 2018 across the European Union, is often considered the gold standard of privacy laws. It defines personal data very broadly and requires a valid legal basis to process such data (e.g. user consent, contractual necessity, legitimate interest, etc.). GDPR gives EU residents strong rights over their data: 

• the right to access it, correct it, delete it (“right to be forgotten”),
• The right to restrict or object to certain processing, among others. 

GDPR can apply to companies anywhere in the world if they handle EU residents’ personal data. The penalties are severe. Regulators can impose fines up to €20 million or 4% of global annual turnover for serious infringements. This has led even marketing and analytics teams to be very cautious, as misuse of tracking data or a security lapse could trigger expensive fines and reputational damage.

CCPA/CPRA (California Consumer Privacy Act & California Privacy Rights Act)

CCPA/CPRA became effective in 2020 and strengthened via the CPRA in 2023, introducing GDPR-like rights for Californians. The CCPA/CPRA defines “personal information” broadly in a way very similar to GDPR’s personal data definition. It covers identifiers ranging from names and IDs to cookies, IP addresses, purchasing history, and even inferences about preferences. Under CCPA/CPRA, California residents have the right to:

• know what personal information a business has about them and how it’s used,
• delete that data, the right to correct inaccuracies, 
• opt out of the sale or sharing of their data for advertising purposes. 

The CPRA added a right to limit the use of sensitive personal information (like race, health, precise location) and created a dedicated agency (the CPPA) to enforce it. One key difference from GDPR is that laws like CCPA operate largely on an opt-out model. It means that businesses don’t always need upfront consent to collect personal data (except for sensitive categories or children’s data), but they must stop selling or sharing data if the consumer opts out. In practice, this means U.S. websites must include “Do Not Sell or Share My Info” links or honour browser signals like the Global Privacy Control to let users globally opt out. By contrast, GDPR typically requires opt-in consent for many data uses by e.g. accepting non-essential cookies. Penalties under CCPA/CPRA are lower per incident (e.g. up to ~$2,663 per unintentional violation or $7,988 for intentional violations).

Other U.S. State Laws

California was just the beginning. Since the CCPA, many other U.S. states like Colorado, Virginia, Utah, and Connecticut have passed their own privacy laws. More states are joining every year. While the exact rules differ from state to state, most of them give people similar rights: to access their data, delete it, or stop companies from selling or sharing it. These laws also require businesses to clearly explain how they collect data and to take steps to protect it. If your business operates across the U.S., it's now important to watch more than just California.

Global Developments

Around the world, privacy regulations are now the norm. Brazil’s LGPD, China’s PIPL, Canada’s updated PIPEDA and many others impose their own requirements. China’s Personal Information Protection Law (effective 2021), for example, requires consent for most personal data sharing and has strict rules about keeping data within China’s borders. Over 144 countries have adopted privacy or data protection regulations, covering everything from basic consumer privacy rights to specific sectors (health, finance) and emerging tech like AI. The GDPR has inspired many of these laws, meaning core principles like consent, data subject rights, breach notification duties, and heavy fines for non-compliance are becoming standard globally. For marketing and analytics professionals, this evolving landscape means one thing: privacy compliance is now a baseline requirement for operating anywhere. It’s not just about avoiding fines, it’s about meeting customer expectations of privacy and building trust in your brand.

Managing PII in Marketing Analytics and Server-Side Tracking

For marketing and analytics teams, working with user data is a day-to-day reality. From tracking website visits and campaign conversions to personalising customer experiences. However, much of that data qualifies as PII/personal data, meaning it must be handled with care. This is where modern techniques like Server-side Tracking come into play as a way to balance data-driven marketing with privacy compliance.

Traditional digital marketing has relied heavily on third-party cookies and client-side scripts. These methods can unintentionally leak PII or violate privacy preferences. For example, if a marketer isn’t careful, a user’s email address might end up being captured in a URL or sent to an analytics tool, or tracking scripts might drop cookies without proper consent.

In Server-side Tracking, the data collection logic is moved from the user’s browser to your own server (or a cloud server under your control). Instead of the browser directly pinging dozens of third-party services with user data, the browser communicates only with your server, and then your server acts as a gateway that forwards data to various tools after sanitising it. This approach offers several advantages for privacy and data quality:

• Greater data control: When you collect analytics data on your own server, you have complete control over what information is collected, stored, and passed on. You can centrally enforce policies like stripping out PII before it leaves your server. For instance, if a user’s name or email is part of an event payload, your server-side setup can hash or drop that field before forwarding the event to Google Analytics or a Facebook Pixel. This way, you ensure no raw PII is shared with third parties. With Server-side Tracking, you manage data on your server, enabling you to collect first-party data while staying GDPR compliant. 
• Improved privacy and security: By keeping data collection first-party, server-side setups naturally align with privacy requirements. Cookies are set on your own domain, so they aren’t automatically blocked by browsers in the way third-party cookies are. Using server-side infrastructure, you can choose to host data in a region of your choice (for example, EU companies can ensure all tracking data stays on EU-based servers). Privacy-conscious companies often select providers that offer regional or self-hosted Server-side Tracking. For example, TAGGRS provides distributed servers independent of major US cloud providers, so businesses can keep EU data within Europe.
• Accuracy and performance benefits: Aside from compliance, Server-side Tracking can significantly improve data quality for marketers. Because it’s less subject to browser quirks and ad-blockers (from the user’s perspective, they are just sending data to your site, not any external domain), you often capture more events and more reliably. According to our latest case studies, our clients using TAGGRS Server-side Tracking often capture 10-20% more conversions. Additionally, page load speeds improve, and heavy JavaScript tags are reduced in the client, since the server is doing the heavy lifting. Faster pages mean better user experience and potentially better SEO. It also means users are less likely to bounce before your tracking fires. So you end up with “cleaner” data that truly reflects user behaviour. Many organisations report that by implementing server-side tagging, they increase conversion measurement accuracy. From a compliance perspective, data accuracy combined with privacy means you aren’t forced into a trade-off between insight and ethics. You can have both “data you can trust” and respect for user privacy.
• Consent integration: Importantly, Server-side Tracking doesn’t eliminate the need for user consent. You still must comply with laws like GDPR that require consent for tracking. However, it can simplify consent management. You can configure your server to only process data from users who have given consent, since the server acts as a gatekeeper. Modern Consent Management Platforms (CMPs) can be integrated such that a user’s consent preferences are communicated to the server, which then decides which tags to fire or which data to strip.

In summary, PII management in marketing analytics is about knowing what data you’re collecting, ensuring you have user permission, and leveraging technology to protect that data. Server-side Tracking is a modern technique that supports these goals by centralising data collection and allowing built-in privacy safeguards. However, it’s not a silver bullet. Organisations still must configure their systems correctly and obtain valid consent or anonymise data. As privacy laws tighten, the industry is clearly moving toward solutions like this.

10 best practices for PII compliance and data protection

Staying compliant with privacy laws and protecting PII is an ongoing effort. It involves technology, processes, and people. Below are some best practices that marketing and analytics professionals should implement to manage PII responsibly and beyond:

1. Conduct regular data audits and classification: You can’t protect what you don’t know you have. Regularly inventory the personal data your organisation collects, and classify it (e.g., identify what is sensitive PII vs. non-sensitive, where it’s stored, and who has access). This helps in understanding your risk areas and ensuring proper safeguards are in place for each type of data.
2. Minimise data collection: Collect only the data that is necessary for your business purpose. If you don’t need a piece of personal information, don’t collect it. For example, if a birth date or phone number isn’t required for a marketing campaign, don’t include it in your form. Fewer data collected means fewer liabilities. This principle of data minimisation is enshrined in laws like GDPR and is just good practice.
3. Implement strong security controls: Protect the PII you do have through technical measures. Use encryption for data at rest and in transit, especially for sensitive fields. Limit access to personal data to only those employees or systems that truly need it. Implement access control and authentication to databases or data warehouses holding customer info. If data is pseudonymized, keep the key secure and limit who can re-link identities.
4. Use anonymisation and pseudonymization tools: Where possible, anonymise data so it’s no longer personal. For analytics, consider using aggregated reports or privacy-preserving techniques like the GDPR Tool from TAGGRS. If full anonymisation isn’t feasible, pseudonymize or mask personal identifiers. 
5. Integrate a Consent Management Platform (CMP): Consent management is vital in the age of GDPR and CCPA. Implement a reputable CMP on your websites and apps to collect and store user consent for various data processing purposes. The CMP should present clear opt-in/opt-out choices and list what each user has agreed to. Make sure your analytics and marketing tags are configured to respect these choices.
6. Be transparent and update policies: Maintain an up-to-date privacy policy that clearly explains what personal data you collect, how you use it, and the rights users have. For marketing contexts, also be clear about any third-party tools or data sharing that occurs. Transparency builds trust and is required by law. Whenever your data practices change or new laws kick in, update your policies and communicate significant changes to users.
7. Review your Third-Party partners and tools: Marketers often use many third-party services, analytics providers, email marketing platforms, advertising networks, etc. Each of these might touch personal data. It’s critical to do due diligence on your vendors. Ensure they have strong privacy and security measures. If you’re transferring personal data from the EU to a service provider in another country, check that legal transfer mechanisms are in place. Remember that under laws like GDPR, you are responsible for what your processors do with the data. So work only with partners who commit to compliance.
8. Train employees on privacy best practices: Human error is a leading cause of data incidents. Conduct regular training for your team on topics like phishing awareness, proper data handling, and the importance of consent and preferences. Ensure they understand internal policies, e.g., not to download customer data to unsecured devices, or not to use personal accounts for work data. When everyone in the organisation treats personal data with care, the risk of accidental exposure drops.
9. Prepare for data breaches: Despite best efforts, breaches can happen. Have a clear incident response plan specifically for data breaches. This should outline how to quickly contain a breach, who to notify, and how to fix it. Being prepared can significantly reduce the impact of a breach and ensure you meet any legal notification deadlines (GDPR requires reporting certain breaches within 72 hours to regulators).
10. Stay updated on legal changes: Privacy regulations continue to evolve. Assign someone (or a team) the responsibility of monitoring privacy law developments and ensuring the organisation adapts. Having a privacy officer or at least a point person to track this and update compliance practices is crucial. In many cases, appointing a Data Protection Officer (DPO) can help keep your privacy program on track.

Following these best practices will not only keep you on the right side of the law but also foster customer trust. Consumers are increasingly aware of privacy issues. Showing that your company respects its data can be a competitive advantage.

Conclusion

Understanding and safeguarding PII is an essential part of any marketing and analytics strategy. Privacy is no longer a niche concern. It’s a frontline issue that affects brand reputation, legal standing, and the quality of your data-driven insights.

By embracing best practices, from conducting data audits and securing consent to deploying privacy-focused tech and training your team, you can navigate this complex landscape. The payoff is worth the effort. You reduce the risk of breaches and penalties, and you strengthen your relationship with customers through transparency and respect. After all, in the long run, data you can trust is built on customers being able to trust you with their data.