As of Friday, March 1, Near transferred its operations to Azira, which you may access at
Please review Azira’s website for more information about its policies and practices.

Cate Zovod

VP Global Product & Industry Marketing

3 mins read

How To Ensure Your Consumer Behavior Data Is Privacy-Safe

In today’s data-driven landscape, the importance of data privacy cannot be overstated. Evolving regulations and heightened concerns about data privacy make it imperative for companies to prioritize the safeguarding of consumer data. This goes beyond conventional data security measures such as data clean rooms; it necessitates that data remain perpetually anonymized and never fully unpacked or de-anonymized.

This shift towards a privacy-safe ecosystem encompasses the stringent anonymization and consent of consumer data to comply with GDPR and CCPA, as well as ensuring that all operators used on data are privacy-safe and preserve the anonymity.

Maximizing Utility While Safeguarding Privacy

While most organizations will agree that protecting privacy is important, it usually comes at a cost. Data privacy and data utility often exhibit an inverse relationship. To illustrate this point, let’s examine two distinct platforms of third-party data providers.

The first third-party data platform entails sharing raw data feeds directly with their customers. In this scenario, data’s value can be exceptionally high, making it convenient for users to analyze and utilize. However, this approach typically sacrifices privacy and compliance, marking it as the “Red Zone” that most responsible companies should avoid.

On the other end of the spectrum, we have the second platform, which prioritizes compliance. While their commitment to compliance is unwavering, they aggregate data to such an extent that it becomes challenging for businesses to extract meaningful insights due to the lack of granularity. For example, if a retailer wants to understand the performance of a specific store, but the platform only allows them to see a geofenced area that includes a whole shopping center or neighborhood, that data is too aggregated to be helpful to the retailer.

To surmount the inherent trade-off between data privacy and utility, a paradigm shift is essential.

Embracing the Paradigm Shift

Achieving a privacy-safe consumer behavior data strategy necessitates a fundamental shift in data handling practices. To effectively navigate the complex landscape of data regulations and meet consumer privacy expectations, organizations must adopt forward-thinking approaches that prioritize data privacy while optimizing data utility.

The Key Pillars of Data Privacy

To ensure robust data privacy practices, organizations must adhere to the following principles:

Consented Data:
All consumer data should undergo consent processes at the source. This establishes privacy from the outset.
Privacy-Safe Operators:
Employ privacy-safe operators when working with anonymized data. These operators maximize utility while preserving anonymity, rendering the data useless to unauthorized users.
Fully Anonymization:
All consumer data should only be provided with complete anonymization. This ensures that consumers are not identifiable, not only via personally identifiable information, but also by location and temporal data. GDPR specifies that “data that has been de-identified or encrypted but can still be used to re-identify an individual in any combination is classified as Person Data.” Anonymization covers any data that could be used to re-identify an individual.

In a world where data is a prized resource, the responsibility to ensure data privacy is paramount. Consumers expect transparency and protection of their data. By embracing advanced technologies and a privacy-centric philosophy, businesses can excel in data management, ensuring the highest level of privacy while deriving valuable insights from consumer behavior data. This paradigm shift is not just a strategic (and regulatory) imperative; it’s a commitment to respecting consumer rights and securing a competitive edge in the evolving data landscape.

Want to learn more about how Near’s Consumer Behavior Data Intelligence platform ensures both data quality and privacy? Check out our eBook: Not All Data Is Created Equal or request a demo.
This site is registered on as a development site. Switch to a production site key to remove this banner.