The Death of Identity: KYC in the Age of Data Privacy

The Evolution of Customer Understanding in the Digital Landscape

The principle of “know your customer” remains central to successful business strategy. Historically, organizations in the digital realm have built detailed customer profiles utilizing data from various sources, including third-party cookies, social media activity, and purchased demographic information.

The Shift Towards First-Party Data

However, increasing concerns regarding data privacy are prompting a re-evaluation of this approach. Businesses now have a chance to redefine their connection with customer data, concentrating exclusively on first-party data and observed behavioral patterns.

Digital analytics, advertising platforms, and marketing tools have long been utilized to monitor customer actions across multiple interaction points. This tracking facilitated the development of comprehensive data profiles.

Growing Privacy Concerns and Regulatory Changes

These profiles were then used to deliver personalized experiences, enhancing engagement through relevance and contextual understanding. Currently, this practice of customer profiling is facing increased examination.

New data privacy laws are being enacted by regulatory bodies, exemplified by the recent Colorado Privacy Act. Furthermore, Apple’s privacy features, introduced in iOS 14.8 and iOS 15, have seen widespread adoption – approximately 96% of users have chosen to disable app tracking for advertising purposes.

Google has also announced the phasing out of third-party cookies and a cessation of individual-level tracking within its Chrome browser.

The Future of Customer Insights: Behavioral Intelligence

Although these changes may disrupt current digital marketing practices, they represent a crucial and beneficial evolution in how brands will gain customer understanding. Focusing on individual identification is neither the most efficient nor the most effective method for discerning customer intentions, needs, and challenges.

Instead of knowing who the customer is, brands should prioritize understanding what they do and why.

The advancements in artificial intelligence (AI) and machine learning (ML) are enabling companies to analyze and interpret first-party data in real-time.

This capability allows for the development of actionable behavioral intelligence, offering a more robust and privacy-conscious approach to customer understanding.

Advancing Security Through Pattern Recognition

Having spent 35 years within the security sector, a clear parallel emerges regarding the future direction of threat mitigation. Traditionally, security efforts centered on identifying individual signatures to detect and address malicious actors. However, recent years have witnessed the emergence of innovative companies and methodologies that utilize patterns of signals to preemptively identify and neutralize threats.

This approach translates directly to the realm of digital business. Companies can harness digital experience intelligence (DXI), derived from behavioral patterns and contextual data within extensive datasets, to uncover threats and opportunities.

These DXI platforms employ machine learning and artificial intelligence to analyze comprehensive, historical behavioral and session data, yielding immediate and valuable insights.

Real-time analysis empowers organizations to discern patterns in customer behavior, understanding not only *how* they interact, but also *why* – all while upholding user privacy standards.

These insights facilitate the delivery of enhanced products, services, and experiences through:

Uncovering New Opportunities and Insights

Behavioral analysis allows for the grouping of users exhibiting similar actions, enabling more targeted marketing efforts. Furthermore, it can reveal previously unseen patterns that unlock new revenue streams.

As an example, a major home improvement retailer leveraged DXI data from FullStory to observe a surge in garage mat sales during the COVID-19 pandemic. Further investigation of behavioral patterns indicated concurrent purchases of materials and equipment commonly used in home gym construction. This led to adjustments in merchandising and marketing to capitalize on the emerging trend.

Enhancing Customer Satisfaction

Providing exceptional digital experiences and identifying areas for improvement no longer necessitates extensive personally identifiable information. Businesses can proactively detect and address user frustration, signaled by actions like “rage clicks” or repetitive page reloads when expected changes don’t occur, rather than relying on delayed feedback from call centers or surveys.

Analyzing user actions like pinching and zooming can reveal the need for improved mobile optimization. Conversely, content highlighting and extensive scrolling provide valuable insights into crucial user interactions.

Strengthening Security Posture

DXI platforms can identify anomalous behavioral patterns and flag outliers in real-time, allowing companies to respond to threats more swiftly. Utilizing aggregate behavioral data as a guide, organizations can proactively identify potential vulnerabilities and implement preventative measures against breaches and fraudulent activities.

The Growing Importance of First-Party Data

For a considerable period, businesses have depended on digital profiling techniques to gain deeper insights into customer behavior and inform strategic choices. However, recent changes aimed at limiting third-party cookies and tracking methods have presented obstacles.

Fortunately, organizations can leverage the capabilities of AI to analyze extensive volumes of first-party data concerning behaviors – not individual identities – to enhance customer understanding and service while simultaneously safeguarding user privacy.

Navigating the Shift in Data Strategies

The decline of third-party data necessitates a renewed focus on information collected directly from customers.

This shift requires companies to prioritize the collection and analysis of first-party data.

• This data is gathered directly from interactions with a company’s own properties.
• Examples include website activity, purchase history, and customer support interactions.

By utilizing AI, businesses can unlock valuable patterns and trends within this data.

This allows for more personalized and effective customer experiences.

Note: The author holds an investment in DXI technology firm FullStory.