What is PII, and How Can You Make It An Asset for Your Product Analytics Strategy?

This article outlines what PII (Personally Identifiable Information) constitutes and the implications of collecting it according to GDPR. You will learn how to securely process PII for your analytics needs, and how customer analytics tools enable you to make data privacy compliance easier.
Personally Identifiable Information
PII or Personally Identifiable Information is any data that allows identifying a person, either by using the data itself or when used in combination with other collected data. Examples of PII include full names, locations, social security numbers, emails, bank accounts, license plate numbers, etc.
Ever since the GDPR came into effect in 2018, there has been a higher focus on ensuring personal data privacy around the world, which compels organizations to maintain their credibility and compliance by finding efficient ways to make PII secure for mobile and web analytics. According to the GDPR framework, if an organization collects information related to people in the European Union, their personal information or PII processing should be GDPR compliant.
The GDPR is only one of the many data privacy guidelines that apply to businesses. Many more such regulatory bodies and their guidelines pertain to regions (e.g., PIPEDA) or the type of business you run (e.g., HIPAA). But we will look further into GDPR since it affects some of the largest consumer markets in the world. It has since become the ‘gold standard’ for more regulations that followed, thus making them one of the foremost data privacy regulations out there today.

What Does PII Compliance Mean for Businesses Based on GDPR Guidelines?

PII Examples
GDPR compliance is not easy to navigate as some of its mandates are highly demanding and sometimes nuanced. For example, the categorization of PII in itself can entail many things of which even ‘pseudo identifiers’ may qualify.
Psuedo identifiers are any information or combination of information that has been pseudonymized but can be retraced to easily recognize someone’s personal identity. Pseudonyms are usually a better way to store personal information in databases by assigning a pseudo name or ID to a person’s name, email, etc. But if this information is contained in a format that is retraceable, it can compromise the user’s identity.
Moreover, violations of these guidelines can lead to hefty fines, which makes it even more urgent for businesses to comply with GDPR. However, customer analytics tools can make it easier for businesses to collect and use PII data if they have pre-defined data privacy checks embedded into their data logic..
Web and mobile analytics tools that are GDPR compliant deal with how organizations handle PII data, which mainly entails the following:
Lawfulness and transparency: PII should be collected by companies with the lawful consent of individuals and with the utmost transparency. Therefore, if you are collecting data from websites or apps that can identify users, it must with the consent of the users.
Limiting and minimalizing data collection: Any data that organizations collect from persons should be with the necessary intent of being used within their products or services. This means that you shouldn’t collect personal data that is unnecessary to the purpose of using your product or service.
Storage and confidentiality: Information storage is a sensitive issue, especially with data misuse becoming more and more prevalent in today’s digital and remote environment. One of the main points of securely processing PII has to do with how it is stored in company databases and who has access to it.
For example, are users informed ahead about the confidentiality of the data they provide? Who can read and access the data, and how is it hosted and maintained? All of these questions should be answered before you use PII in product analytics.
Accountability: Companies are responsible for safeguarding user data. This could include having all the information regarding the usage of PII transparently documented for users to read and understand, conducting employee trainings, and having agreements in place regarding third-party data use.
This simply means that you are in control of the personal data that you collect from users. Therefore, you are to ensure the best-in-class security compliance for customer data processing, including your analytics strategies.
Is there any information that does not fall into the PII category? The answer is ‘yes’. Some information can be collected by organizations without violating any guidelines, which we will discuss below.

What is Not PII?

Information that is typically entered by users or collected by the servers and browsers from which they operate does not fall under PII.
If the information is non-linkable, i.e., it cannot be used in combination to identify a person, it will not be considered PII. In such cases, information that is linkable needs to be stored in different locations of your database so that it cannot be combined. The information may include a person’s gender, race, country of origin, zip code, age range, job title, or workplace.
If a person’s device information includes IP addresses or other host-specific, unique identifiers that can be linked to a specific person, it is also considered PII. But masked IP addresses, device type, browser info, plugins, time zones, preferred languages, and other device-specific data that are non-linkable are not PII.

Can GDPR-Compliant PII for Analytics Lead to Business Growth and Stability?

The GDPR is meant to protect individuals’ information from being misused, shared, or compromised in any way. This gives users a right to their privacy, as well as inherently enables businesses to utilize customer data more meaningfully. Ideally, you can ensure that you are GDPR compliant by using product analytics solutions that make it easy for businesses to work with PII in the following ways:

Maintaining Data Quality and Value

Organizations can use first-party data gathered through user consent and approval to improve their digital experience and make it more rewarding. As customers grow to trust businesses with more data due to the security compliance and the assurance of information privacy, data processing and analysis becomes a long-term business strategy.
More data means more analytics power. Sifting through loads of unusable and unstructured data from third-party and second-party data integration can pressure businesses to maintain their data processing and analytics prowess.
Customer analytics tools and features, in turn, can maintain the value and quality of the data you collect through features that can track the customer journey, send out push notifications, collect ratings, report crashes, and more. The incoming data is then managed and processed through dashboards and reports giving your organization a clear vision of the user data that you’ll need, and the ones you won’t.
Therefore, when you focus on first-party data collection, you enable more efficient tools for analysis that simplifies data collection and helps you comply with PII-related regulations.

Ensuring Compliant Data Storage and Maintenance

Data privacy compliant analytics tools help in maintaining the integrity of data, accurately preserving it wherever it gets stored. They do this by first ensuring that only the necessary data is collected and second, by encrypting and masking sensitive information wherever necessary.
Furthermore, these analytics tools take data protection into account at all times by maintaining strict protocols that make data collected automatically privacy-compliant. They also implement systems that track sensitive PII to prevent breaches. Regular, up-to-date compliance and audits are also part of the data protection process. But the data still stays within the control of your organization when you operate with a privacy-first analytics tool.

Expanding Business Scope and Scalability

Securing PII data can limit the organizational resources as they are not always equipped with a cost-efficient, well-maintained infrastructure for their data storage. So, even as customers are willing to share more of their personal data for business use, privacy and security compliance issues can come in the way of enterprise scalability.
If, for example, you want to expand your business to other countries or regions, your own infrastructure might not allow you to process the data without spending hours building new data management features. Instead, product analytics tools have inbuilt or add-on capabilities and provide the flexibility and adaptability needed across more regions. You can also equip yourself with these tools to handle information influx through real-time dashboards and highly accurate metrics.
Having an analytics platform that ensures the storage and processing of PII in compliance with the GDPR, gives you more control over the way that you access, analyze, and act upon this information to form insights, all the while being the most cost-efficient solution.
As data security becomes more and more complex, protecting customers’ PII has proven to be a task that can lead businesses to abandon unsecure methods of data analysis. While convenient at first, it has proven to be a problem in the long term.
Choosing the right platforms to trust your customer and product information can ease this journey toward achieving greater freedom with how you manage your organizational assets.
Protecting customer rights is, at present, one of the factors that make you stand out from the competition while also making you an advocate for information security and rights.
Interested to learn more about how your business can make data privacy a priority? Check out more Countly articles from our blog and academy!
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