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Privacy: Forget the Bare Minimum and Think Much Bigger

cuebiq logoEU and U.S regulators have cast their watchful eyes on data privacy. Perhaps the biggest show of might against those not adequately safeguarding consumers’ data are the recent spates of penalties spanning US$22.5 million, €50 million, and even the record multi-billion dollar fine being negotiated right now by a social media giant.

Needless to say, beyond the clear moral and ethical implications of not safeguarding consumers’ data, privacy compliance has become a business issue that is much too expensive to ignore. It’s in brands, agencies and publishers’ best interests to future-proof their approaches today. And, if you aim to just meet the laws and regulations where they are at today, you are already on the back foot. It’s time to think like a law-maker (or even someone who simply wants to safeguard their own grandmother’s or elderly neighbor’s data), and plan for a future that 100% protects consumers and the data they hold and share access to.

How? And where do we start?

Plan for a Much Stricter Future

Firstly, we have to admit that we as an industry have been painfully slow to respond to the privacy issues, and have often, only worked fast – and somewhat last minute – to meet the mere demands mandated by regulation in lieu of more future-proof solutions.

Rather than anticipate what future privacy laws may unveil or restrict, or worse, react to regulation as it comes into effect, state by state, nationally and internationally, consider a future-proof privacy approach that enables you to relax and rest easy as newer, stricter, more powerfully enforced privacy laws are rolled out in the coming years.

Bye-Bye Self-Reporting

Secondly, turn your back on the idea of self-reported compliance. Self regulation is not an acceptable solution, and it’s not going to last as law-makers poke around current practices and approaches.

Use an Auditable Data Provenance Framework

Safeguarding consumer privacy is paramount, but, if I’m honest, we didn’t intend to become the leader in privacy controls and frameworks. We became so as a result of our desire to put the consumer first and give them a choice that they could easily understand. With that goal in mind, we launched as the first solution that independently verifies data provenance, user consent and fully ensure privacy compliance. Our solution leverages Blockchain technology to create an immutable, verifiable and auditable data provenance and consent management framework, which certifies opt-in and opt-out. We also ensured that our solution is transparent and easy in that it enables all of our users, partners, and customers to perform or request a third-party audit of any of our products, as well as validate consent, while preserving user anonymity.

As a result, our publisher partners are also enabled to offer advertisers CCPA-compliant audiences for targeting. This innovation shifts the paradigm for data providers moving from a model based on self-reported compliance to an auditable, immutable, and verifiable data provenance and consent management framework.

Decide How You Want to Roll as the Cookie Crumbles

In this evolving landscape, a number of players in the space will find their business models and approaches under fire and difficult to maintain in their current form. There are likely many more multi million and billion-dollar fines for privacy lapse boo-boo’s in the future. But, if you think bigger, broader and farther than regulators, and see the current landscape as an opportunity to lead the industry as it forges its way forward, then new privacy laws will no longer be something that you need to read, panic or lament about as others race to shift to a legally compliant privacy position.

Read more: The Logistical Nightmare Looming on Data Privacy: Time to Get Your Head Out of the Sand

Antonio Tomarchio
Antonio Tomarchio
Antonio Tomarchio is the CEO and Founder of Cubeiq. He is an industry veteran in mobile marketing, mobile big data, location intelligence, business intelligence, offline analytics, attribution analysis with a deep understanding of SaaS and DaaS (Data as a Service) Business model.

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