The death of identity knowing your customer in the age of data privacy

The death of identity knowing your customer in the age of data privacy

One of the core ideas of business is “now your customer.” Companies have learnt a lot about their clients in the digital era by developing personalized profiles based on third-party cookies, social material, demographics purchased, and more. 

However, in the face of rising privacy concerns, organizations have the option to restructure their consumer data relationships to focus primarily on first-party data and patterns of behavior.

To track customers and correlate their activities across contact points, businesses have used digital analytics, advertising, and marketing technologies. This allowed for the establishment of data profiles, which have been used to create tailored experiences that are relevant and contextually relevant.

However, this method of profiling and identifying clients is now being questioned more and more. Regulators are adopting new data and consumer privacy laws, the most recent example being the Colorado Privacy Act. Furthermore, Apple’s privacy features in iOS 14.8 and iOS 15 have been accepted by 96 percent of customers, who have chosen to prevent applications from tracking their activities for ad targeting. Furthermore, Google has declared that it would no longer support third-party cookies and will stop monitoring individuals using its Chrome browser entirely.

While these advances have the potential to disrupt current digital marketing practices, they also herald a necessary and effective shift in how organizations will understand their customers in the future. Individual profiles are far from the quickest or most successful approach to comprehend and solve consumers’ intents, wants, and challenges. 

Brands do not care who they are; they care about what they are doing and why they are doing it. Companies can collect and understand first-party data in real-time and produce actionable behavioral intelligence thanks to significant breakthroughs in artificial intelligence (AI) and machine learning (ML).

The security sector, which I have worked in for 35 years, serves as a model for the future. Historically, security experts have attempted to identify, stop, or at the very least prosecute malicious actors by tracing their signatures. 

However, in recent years, some extremely promising firms and methodologies have emerged that use signal patterns to proactively identify and stop risks before they occur.