Note: This article was written by Ted Schlein of Kleiner Perkins, an investor of FullStory. It originally appeared in TechCrunch.
“Know your customer” is one of the foundational concepts of business. In the digital age, companies have learned much about their customers by forming individual profiles from third-party cookies, social content, purchased demographics and more. But in the face of growing demands for privacy, businesses have the opportunity to overhaul their relationship with customer data to focus solely on first-party data and patterns of behavior.
Companies have employed digital analytics, advertising and marketing solutions to track customers and connect their behaviors across touch points. This enabled the creation of data profiles, which have been leveraged to deliver personalized experiences that resonate through relevance and context.
Expect more scrutiny around privacy
Now, however, this practice of profiling and identifying customers is increasingly coming under scrutiny. Regulators are adopting new data and consumer privacy legislation, most recently seen with the Colorado Privacy Act. Moreover, Apple’s privacy implementations in iOS 14.8 and iOS 15 have been adopted by an estimated 96% of users, who have opted to stop apps from tracking their activity for ad targeting. And Google has announced it will no longer support third-party cookies and will stop tracking on an individual basis altogether through its Chrome browser.
While these developments threaten to upend how digital marketing is performed today, they signal a necessary, and effective, shift in the ways brands will understand their customers in the future. Prioritizing individual profiles is far from the fastest or most effective way to understand and address customers’ intentions, needs and struggles. Brands don’t need to know who; they need to know what and why.
Thanks to rapid advances in artificial intelligence (AI) and machine learning (ML), companies can process and interpret first-party data in real time and develop actionable behavioral intelligence.
Pattern analysis as a way forward
The security industry, which I’ve been involved in for 35 years, provides a template for the path forward. Historically, security professionals have sought to pinpoint individuals’ signatures in order to identify, thwart or at least prosecute bad actors. However, the last few years have marked the rise of some incredibly promising companies and approaches that leverage patterns of signals to proactively surface and stop threats before they happen.
Similarly, when it comes to surfacing threats and opportunities for digital business, companies can leverage Digital Experience Intelligence (DXI) gleaned from behavioral patterns and context across massive behavioral datasets. These DXI platforms can layer ML and AI onto complete, retroactive behavioral and session data to generate immediate, rich insights.
Real-time analysis can help companies identify patterns of behavior to understand how customers engage, and why—all while protecting their privacy. Based on these insights, businesses can provide better products, services and experiences through:
New insights and opportunities
Behavioral analysis can be used to cluster users who take similar types of actions and target them more intelligently, while also discovering patterns that can lead to new revenue opportunities.
For instance, a large home improvement retailer used data surfaced through FullStory’s DXI platform to identify a spike in the sale of garage mats during the COVID-19 quarantine. Deeper analysis of behavioral patterns revealed that customers were also buying other materials and equipment consistent with building home gyms. Based on this insight, the company updated its merchandising and marketing strategies to capitalize on the trend.
Improved customer satisfaction
Companies no longer need a trove of personally identifiable information to offer great digital experiences, or to detect flaws in subpar ones. Rather than waiting for a call center complaint or negative survey feedback, businesses can proactively detect and take fast action on frustration signals such as “rage clicks” or repeated page reloads that occur when visitors don’t see an expected change.
Pinching and zooming behavior can indicate that user experiences need to be better tailored for mobile screen sizes, whereas content highlighting or deep scrolling lends new insights into key interactions.
By detecting patterns in anomalous behavior, DXI platforms can flag outliers as they occur, enabling companies to counter threats sooner. With aggregate behavioral data as a guide, businesses can pinpoint risks in advance and take preventive action against potential breaches or fraud attempts.
First-party data for the future
Companies that have long relied on digital profiling to better understand customers and drive business decisions have been stymied by recent developments to curb third-party cookies and tracking. But by harnessing the power of AI to process vast amounts of first-party data about behavior—not individuals—companies can know and serve their customers better than ever while protecting user privacy.