Key takeaways
- Anonymous data refers to website visitors or users whose personally identifiable information is unknown or not yet collected.
- Data anonymization is the deliberate removal of identifying information from customer data, often to comply with privacy regulations.
- An anonymous user can become identifiable when they submit personal information, such as completing a form or logging into an account.
- Data anonymization supports compliance with regulations like GDPR and CCPA, including the right to be forgotten.
- Anonymous data is typically used for aggregated audience insights, while identifiable data enables deterministic customer profiles and personalization.
- A customer data platform can manage both identifiable data and anonymization requests, helping marketers maintain privacy compliance while preserving data utility.
Data anonymization and anonymous data do not mean the same thing. The two concepts may not seem similar at first glance, but it's important to know the difference.
Why? Because, as a marketer, you control the former — and in the age of GDPR and consumer privacy laws, it's vital to meet the stringent mandates from these regulations.
Why is it important to understand anonymous data vs. data anonymization in marketing?
I recently had a call with a prospective customer who has been leading a task force at his company for a fairly massive marketing technology project.
The goal of the call was to provide this prospect with clarity around the differences between CDPs and DMPs (of which there are many — I'll get to those later).
Ultimately, "data anonymization vs. anonymous data" was a talking point that came up.
It dawned on me after hanging up that this is something many marketing pros like this particular prospect may still be a bit fuzzy. Thus, I thought it’d be worth zooming in on it.
What is anonymous data?
This difference between the two terms is at the very root of what distinguishes a customer data platform and a data management platform.
Anonymous data is essentially defined as data having no name acknowledged or an unknown name for someone who engages with your brand. In other words, their name and personally identifiable information (PII) are completely withheld.
You know nothing about these individuals: not their name, location, email address — nada. All you know is they landed on your site and didn't allow you to collect their info.
At any given time, though, a specific individual’s anonymous status can change to known — meaning they become a legitimate contact (if not an ideal lead just yet).
What is data anonymization?
Data anonymization, on the other hand, refers to the transformation of customers' data on the part of marketers such as yourself. And the reasons for this can vary widely.
The process here is almost a reversal of sorts to the previous concept: Remove all website data and data from other sources (ads, emails, apps) per the consumer's request.
In this instance an acknowledged name or other identifier is deliberately removed from a database, per this petition. The identity of this person is scrubbed away.
All information that is linked to a given individual in your database is deleted. There's no longer a way to distinguish or trace the person beyond this point.
Now, why would you or any other business technology user want or have to do this?
Well, with GDPR compliance crucial for all brands today (more on that shortly) and similar federal laws and international measures only around the corner, companies like yours need to take consumers' privacy concerns to heart.
Protecting consumers has become an important task for lawmakers around the globe, but especially here in the United States and in the European Union.
How anonymous users become known contacts
A person can do a number of things to change their status from anonymous to known.
For example, someone browsing a website without having logged in or providing a piece of personally identifiable information is browsing anonymously.
Their behavior is still theirs, and the personal info may still be associated with that person. But their site data doesn't provide enough insights to build a known-customer profile.
However, once they, say, fill out a lead capture form on your website — like those for your newsletter signups or to get discounts on certain products or services — their info is known.
Just like that, the individual's identity is know. You have additional information about them and maybe their buying behavior, and they're now a known commodity in your database.
GDPR and CCPA requirements for data anonymization
Here's the cold, hard truth: Failing to take existing and upcoming data protection regulations seriously can lead to hefty fines and a loss of any trust you had with your customer base and prospects.
The General Data Protection Regulation, the California Consumer Privacy Act, and all other existing and prospective consumer privacy measures that could affect your business need to be dealt with accordingly.
By "dealt with," we mean handling a few important tasks:
- Complying with all data rules and regulations that apply to you. For instance, if you do conduct business in the EU (or simply market to leads there), satisfying all GDPR requirements is a must. (You don't want to be one of the companies to face sizable GDPR fines from the EU.)
- Using a consent management solution to automatically label and adjust contacts' profiles to see if they will allow you to collect and use their data. If you have BlueConic, it's easy to ensure you provide consent options to users who engage with you and track consent given.
- Stay up-to-date on consumer data privacy measures to make sure you and your organization are caught up on laws that do or will directly affect you. It never hurts to regularly read up on potential and imminent regulations that will greatly impact your team and brand.
All of these measures have one commonality: Data anonymization upon consumers' request needs to be handled quickly and efficiently to avoid the wrath of legislators behind these data-handling mandates.
You can't accomplish this with a DMP. But a CDP like ours can sure help.
How a customer data platform enables data anonymization
A developer who works on a leading DMP explained that their tool "can't augment a profile that's addressable (i.e., identifiable) with data that is collected anonymously" or vice versa.
The key differentiator between how a DMP and CDP handle first-party data collection and merging with third-party data: This may only occur when the data doesn’t have an identifier or when that identifier has been removed.
While this has highly useful applications, it’s also a considerable hole if you’re trying to build up a central database filled with leads' and customers' first-party data.
Marketers need addressable, identifiable people who actually interact with their brand. In order to make use of this customer data across the marketing technology stack, these details are critical if not required.
Anonymized data is good enough for the kind of probabilistic groupings that are the basis of reach; it’s decidedly not when you aspire to create an accurate, deterministic dataset about your customers.
My point, you ask? Customer data platforms deal intentionally in first-party, identifiable (or potentially identifiable) data collection. Data management platforms deal in audience creation based on scrubbed, aggregated and/or non-identifiable data.
Discover if your company is ready to onboard a pure-play customer data platform like BlueConic. Take our quick CDP Readiness Assessment today.
Frequently asked questions
What is the meant by data anonymization?
Data anonymization is the process of permanently removing or altering personally identifiable information so an individual can no longer be identified. Once data is fully anonymized, it cannot be traced back to a specific person.
What is an example of anonymized data?
An example of anonymized data is a customer dataset where names, email addresses, phone numbers, IP addresses, and other identifiers have been removed or irreversibly transformed. The remaining information, such as purchase totals or behavioral trends, cannot be linked to a specific individual.
What is the difference between data masking and data anonymization?
Data masking hides sensitive information but keeps the original data intact and recoverable. Data anonymization permanently removes identifying information so it cannot be restored. Masked data can often be reversed under certain conditions, while anonymized data cannot.
How do you anonymize your data?
You anonymize data by removing or irreversibly altering identifiers such as names, emails, device IDs, and account numbers. Common techniques include deleting direct identifiers, aggregating records, generalizing data fields, or applying irreversible hashing methods. The goal is to ensure the individual cannot be reidentified.
