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May 10, 2024

Make data privacy a competitive differentiator

Customers value their data privacy. Businesses should embrace it too. Here’s how to start.


For consumers, it was love at first sight for Apple’s App Tracking Transparency (ATT) feature. Within weeks of the privacy control’s 2021 release, fully 96% of iPhone users had opted to disable app tracking. The message was clear: Consumers value their privacy, and want to control the use of their data. 

Fast forward three years and despite those astonishing numbers, many companies are still somewhat defensive about data privacy. They know the customer wants it, and dutifully they honor that desire by seeking consent, or by letting users “opt out” of data gathering and sharing—perhaps by checking or unchecking a box buried deep in a “Preference” pane.

What these companies fail to understand is that embracing customers’ data privacy, as opposed to merely allowing it, can be very good for business. In an increasingly data-centric marketplace, privacy can be a powerful differentiator, and a gleaming jewel in a business’s brand identity.

Want to succeed in business? Build trust. 

Trust is a core ingredient of successful brand identities. Topping the list of the most beloved brands in America are Patagonia and Costco, two businesses that make a priority of cultivating close, trusting relationships with their customers. (Apple and Amazon just missed the list.)  

As with any relationship, there is no single factor that makes a customer trust a business, but data privacy looms increasingly large. In a recent survey, 26% of consumers said they’ve left a brand in the past 12 months over concerns about how their personal data was being used. Another 73% said they’re attracted to brands that provide a greater sense of safety and security—a 9% jump year over year—while 88% say will buy from a trusted brand more often. The upshot? A strong focus on data privacy not only strengthens brands, but can open revenue opportunities through marketing and sales.

CX is just the start

If the goal is building a maintaining a customer’s trust (and it is!), a business’s commitment to data privacy must be manifest in every aspect of customer experience (CX). But savvy consumers know “window dressing” when they see it, which is why it’s essential that businesses also “walk the talk,” making privacy a priority throughout the value chain, and within their own processes and culture. In practice this can involve such measures as:

  • Integrating a privacy-by-design workstream into the governance of MarTech (Marketing Technology) programs.

  • Integrating anonymization of consumer data into design culture. 

  • Going beyond regulatory compliance (GDPR, CPRA) and emphasizing privacy for data and AI assets across the value chain, including data lineage, model / prompt lineage, data reliability input, and responsible AI output.

  • Building trust through open, public communication about privacy. 

Prioritize data anonymization  

When a customer says she wants to keep “my data” private, the emphasis is implicitly on the “my.” Consumers are in general unperturbed by the thought of a business retaining the fact that somebody purchased Item X for Price Y on Date Z, as long as that information is scrubbed of names or other identifiers that could tie the purchase to a particular customer. So-called “anonymization” protocols can provide this comfort, but these efforts are often fragmented across an organization. By creating a unified approach—from MarTech and AdTech to CRM and generative AI models that train on customer data—companies must ensure that anonymization stays front and center for every business function.

It can be a delicate balancing act. Overly aggressive anonymization renders data less useful, but inadequate protection puts individuals’ privacy at risk. Only by taking a comprehensive approach to data and AI governance can businesses find the right balance of techniques for privacy, compliance, lineage, and anonymization—and nowhere is governance more important, by the way, than in cross-border data flows of customer analytics.  

Beyond data privacy: data ethics

Data privacy is now integral to a positive CX, and to the perception of trust that is a growing factor in customer acquisition and retention. But some companies are taking it further, to great effect. In the UK, cosmetics retailer Lush was dissatisfied with the handling of its customer data by third parties, and revamped its approach to authentication. Now, two years later, the company’s technology arm promotes digital ethics—a comprehensive framework of which data privacy is just one principle.

With the rapid uptake of generative AI, which promises to further deepen the relationship between businesses and their customers, and to make customer data more precious than ever, it’s imperative to balance innovation with responsibility. There has never been a better time for businesses to start seeing their ethical obligations to consumers not as a box to be checked or a bar to be cleared, but as a competitive advantage and an opportunity to be seized with both hands.

To learn more about data privacy, read our blog, What could put the brakes on gen AI? Data privacy. 
 



Diptesh Singh

Global Leader, Data & AI Management

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Diptesh is a leader with 20+ years of experience in helping clients find value from their Data & AI assets, safely and responsibly. He is an industry speaker and a thought leader in the field of Data & AI management (AI governance, MDM, PIM, CDP, observability, privacy, MarTech & responsible AI).

Diptesh.Singh@cognizant.com



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