How data privacy readiness builds and maintains customer trust

Before the digital revolution of the early 2000’s, customer trust was primarily based on product quality. As our lives have moved online—socially, financially, medically, and more—this trust has shifted to focus on how companies handle data. In a study earlier this year, 451 Research found that 89% of consumers are concerned with protecting their personal data. In 2020 and beyond, data readiness, or the state of having a master data management strategy and infrastructure in place, is essential for building and maintaining customer trust.

Why data readiness is required for customer trust

With the enforcement of data privacy laws like GDPR and CCPA over the past few years, data has become a key factor in customer decision making. Regardless of the transaction type—from social media logins to online product orders to using fitness apps—individuals are more aware of their data than ever before. Gone are the days of corporations owning the data they collected; now, customers want to know what data is collected, what it’s used for, who has access, and how to delete it. In short, the power has shifted: customers are now in charge of their data.

As part of this data ownership, customers can initiate Data Subject Requests (DSRs) to learn about how their personal data is used. Companies must be able to respond to these requests efficiently and completely, but this is only possible when data processes are lean and organized. A data ready culture requires transparent data journeys, secure storage, and restricted access, all under constant governance and maintenance. Many organizations have moved quickly to implement the necessary changes, but customer trust hasn’t moved quite as fast. In a study conducted by the Pew Research Center in June 2019, 79% of American consumers stated that they were “not confident” that companies would publicly admit to and take responsibility for misusing customer data. This lack of confidence makes one thing clear: being proactive and transparent about data is the fastest way for companies to increase customer trust and gain larger market share. Subscription-based services have made brand loyalty and customer retention even more lucrative, encouraging today’s companies to prioritize customer trust for 2020 and beyond.

Customer expectations in a post-COVID world

The economic and social uncertainties caused by the COVID pandemic have made data privacy readiness even more of a key differentiator. Customers want stability, reassurance, and trust. When enjoying normal activities in the physical world is risky, the last thing people want is to feel at risk in their online activities.

As the world adapts and industries fluctuate, customer expectations are also focused on how businesses use customer data with each other. The disorganization of one company can easily increase the risk and liability of its partner. So, whether it’s to preserve their reputation, adhere to data privacy regulations, or stay prepared for a sudden merger or acquisition, companies have many reasons to maintain data readiness. Any company not prioritizing data privacy readiness is putting its customers —and itself—at risk.

Companies lagging on data privacy readiness risk significant consequences due to lost customer trust. These include damage to brand reputation, limited traffic and growth, and falling behind their competitors. In addition, companies face direct financial risk due to data privacy laws. In fact, the average expected cost of non-compliance is $14.82 million, which is 2.7 times the cost of implementing data privacy readiness.

2020 has brought significant change to businesses and industries around the world. Data privacy is a constant that continues to affect customers and businesses alike. Maintaining positive customer relationships and expectations of long-term stability will require every organization to stay data ready.

Evan Alkhas is a Strategy Manager at Logic20/20 with extensive knowledge in robotic process automation, virtual assistants, business process optimization, and technical product management.