Seven Peaks Insights

Keys to Data Security and Privacy: PII Masking and PII Tokenization

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Is your organization grappling with the constant threat of data breaches, endangering your customers and your brand? Prepare to navigate a course toward secure and hyper-personalized MarTech success with Personally Identifiable Information (PII) using PII Masking and PII Tokenization techniques in this 3-part series of articles focused on methods and tools you can use to properly safeguard your customer data.

Part 1 (this article), Part 2, and Part 3

Let's embark on this critical exploration, as we empower you to keep your customers engaged while their sensitive data remains impenetrably protected and fully compliant with European regulations (GDPR) and more (PDPA).


What is PII?

Personal Identifiable Information (PII) is defined as any representation of information that permits the identity of an individual to whom the information applies to be reasonably inferred by either direct or indirect means.

As data professionals at the C-level know all too well, PII encompasses details as fundamental as a person's full name, home address, email, and more. These are the keys that can unlock the doors to an individual's identity, making PII the most coveted and vulnerable aspect of our data.


Understanding PII Masking

Before we examine the intricacies of Personally Identifiable Information (PII) Masking, it's essential to establish a strong foundation of knowledge surrounding the topic. In this section, we'll take a comprehensive look at PII Masking, from its fundamental definition to its benefits. 

Understanding the essence of PII Masking is crucial for marketers, data professionals, and business leaders, as it forms the bedrock of secure and privacy-conscious customer engagement strategies.

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Defining PII Masking

PII Masking is a powerful data protection technique, designed to secure sensitive customer information while allowing businesses to harness the full potential of data-driven marketing.

The primary purpose of PII masking is to safeguard individual privacy and security, while still enabling data sharing, collaboration, and analysis in a responsible and compliant manner. It's a vital tool for organizations and individuals who handle sensitive data in today's data-driven world.

Sensitive PII

Sensitive PII refers to a subset of PII that carries a higher risk of harm if compromised or disclosed without authorization. This means that exposing sensitive PII could lead to significant financial, reputational, emotional, or physical harm to an individual. These include:

Unique ID Numbers

These are uniquely assigned to individuals and are highly vulnerable to misuse. Their importance in masking is critical.

Medical Records

Extremely sensitive and private, containing intimate details about a person's health. Masking is often mandated by law.

Passport Numbers

While not used as frequently as other identifiers, they grant access to travel and are valuable for identity theft. Their importance is high.

Financial Information

Highly sensitive, allowing access to financial resources and vulnerability to fraud. Masking is critical.

Full Names

While not unique (especially common names), combined with other information, they can identify individuals. Their importance is high.

Home Address

Can give insight into personal life and movements. Its importance depends on context.


Widely used and often readily available online. Masking can be helpful to prevent spam and phishing but isn't as crucial as other unique identifiers.



PII Masking employs advanced technology and methodologies. Here, we can explore the underlying technology behind PII Masking solutions, including encryption, tokenization, and data anonymization.

1. Identifying PII

The first step is to identify all PII within the data you're working with. This includes directly identifiable information like names, addresses, and ID numbers, as well as indirectly identifying information like IP addresses and medical records

2. Choosing a Method

Once you've identified the PII, you need to decide which masking method to use. Three common approaches are:


This involves converting the PII into an human-unreadable format using a key (such as a hash, using a secure encryption algorithm such as SHA-256, for example). Only authorized individuals with the key can decrypt and access the original data. Encryption is suitable for situations where data needs to be stored or transmitted securely.


This replaces PII with randomly generated, non-sensitive tokens that hold no intrinsic meaning. A separate system stores the mapping between tokens and the original PII. This allows authorized users to access the data via the tokens while keeping the original PII hidden.

Data Anonymization

This transforms the PII into a statistically equivalent but non-identifiable form. Techniques like data aggregation, differential privacy, and k-anonymization can be used. This is useful for data analysis where preserving data utility is important while minimizing privacy risks.

3. Implementing the Chosen Method

Different methods require different tools and techniques for implementation.


Encryption libraries and APIs are readily available for different programming languages and platforms. Examples include AES, RSA, Blowfish and Twofish etc.


Tokenization platforms and services can be used to manage the tokenization process and store the token-PII mapping securely. MoEngage is an engagement platform example that provides this, as well as certain CDPs such as mParticle.

Data Anonymization

Statistical software packages and data science libraries can be used to implement various anonymization techniques. CDP platform mParticle can also provide this service.

4. Validation and Monitoring

After masking the PII, it's important to validate the effectiveness of the chosen method. This involves testing whether the masking process has successfully obscured the original data while maintaining data quality and usability. It's also crucial to monitor the masked data for potential security vulnerabilities and ensure ongoing compliance with data privacy regulations.


The Benefits

In today's data-driven world, protecting sensitive customer information is paramount. PII masking acts as a vital protective shield, safeguarding data from unauthorized access and fostering trust in your brand. Let's explore some of the benefits it offers:

Transparency and Privacy

Implementing PII masking showcases a proactive commitment to data protection, demonstrating transparency to customers about how their information is handled and secured. This builds trust and strengthens customer relationships.

Reduced Privacy Concerns

Customers value organizations that respect their privacy. PII masking directly addresses concerns about data collection and usage, ensuring customers feel safe sharing their information and fostering trust.

Mitigating Reputational Damage

Data breaches and privacy scandals can significantly damage a brand's reputation. PII masking minimizes these risks by acting as a preventative measure, protecting the brand's image and customer confidence.

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Balancing Personalization with Privacy

In the highly dynamic landscape of marketing, where data is both the lifeblood and the treasure trove, there exists a paradox. On one hand, we, as marketers, have access to a wealth of information about our customers, allowing us to craft hyper-personalized campaigns and foster deep connections. 

Yet, this wealth of data poses a significant challenge: how can we harness it without compromising the privacy and security of our customers' most sensitive information? 

This paradox brings us to the forefront of a critical discussion in the marketing industry, one that concerns every marketer: the protection of Personally Identifiable Information (PII).


Reshaping Customer Relationships

In the broader context of the marketing industry, PII Masking and PII Tokenization play pivotal roles in reshaping customer relationships, ensuring compliance with data privacy regulations, and fostering trust. By adhering to data compliance standards and staying ahead of evolving regulations, businesses can position themselves as stewards of customer data, building strong, lasting relationships inherently based on trust.


This article is part 1/3 of the thought leadership article series: PII Masking and PII Tokenization in Marketing. See the full list below:

Part 1: PII Masking and PII Tokenization: Keys to Data Security and Privacy (This article)
Part 2: PII Masking and PII Tokenization: The Power of PII-Tokenized Sending
Part 3: PII Masking and PII Tokenization: Industry Insights and the Future of Data Protection

Bo Profile Cropped

Bo Lund Pedersen
MarTech Lead

Bo is a digital marketing innovator with IT expertise & leadership. Bo has a decade of experience working across Europe and Asia, and is adept at scaling teams. He has a proven track record of driving growth and pioneering strategies for global brands such as Google, Microsoft and Apple, conceiving and executing high-impact MarTech solutions, enriching customer experiences, and propelling revenue expansion. 



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