Maintaining The Balance of Customer Analytics and Data Privacy
Wed, April 14, 2021

Maintaining The Balance of Customer Analytics and Data Privacy

Companies from various industries are to become more data-driven by “expanding their customer data analytics initiatives" / Photo by: XArtProduction via Shutterstock

 

Companies from various industries are to become more data-driven by “expanding their customer data analytics initiatives," according to Aoife Sexton of CPO Magazine, a news platform on data protection and cybersecurity. Unfortunately, these initiatives conflict with and can be hindered by the ever-changing data privacy regulations if companies are unable to proactively deal with it. 

Sexton has spoken with firms across financial services, retail, telecommunications, and the automotive industry who are engaged in a tug-of-war with the data utility/data privacy tradeoff. This impacts key analytical areas such as personalization and predictive modeling, leaving businesses questions on how to use customer data to usher new business opportunities while safeguarding that data and complying with new, complex regulations. 

What Is Customer Analytics? 

Customer analytics is also known as customer data analytics, wrote Margaret Rouse of Search Business Analytics, a site dedicated to business intelligence and analytics professionals. Customer analytics is defined as the systematic explanation of an organization’s customer information and behavior to identify, attract, and retain their most profitable customers. 

Customers can access information anytime, anywhere. Therefore, it is important for companies to leverage predictive analytics and data to predict how customers will behave “when interacting with brands.” Creating a “single, accurate, view of a customer” to make informed decisions about how to attract and retain customers, identify high-value customers, and engaging with them is the goal of customer analytics. 

The more a company understands its customer’s buying habits and lifestyle preferences, “the more accurate predictive behaviors become and the better the customer journey becomes,” said Rouse. Without harnessing large volumes of data, any insight drawn from it could be inaccurate. 

Customer analytics is usually managed by an interdisciplinary group composed of business owners from various departments within the organization such as marketing, customer service, IT, sales, and business analysts. For the company to obtain the most meaningful insights from customer data, the team must first establish a middle ground on which business metrics they need to produce a single view of the customer experience. 

Poor customer data integration (CDI), multiple instances of customer relationship management (CRM) applications, as well as disparate enterprise resource planning (ERP) systems could leave the team with a fragmented view of the customer. 

Customer analytics is defined as the systematic explanation of an organization’s customer information and behavior to identify, attract, and retain their most profitable customers / Photo by: Viktoriia Hnatiuk via Shutterstock

 

Roadblocks In Customer Analytics 

There is demand for analytics projects but sadly, companies are struggling to make any progress. In a recent HBR survey, 69% of firms admitted that they still had to establish a data-driven organization, while 52% said they weren’t using data as a business asset, much less “fully dealing” with it as a potential liability, as reported by Randy Bean and Thomas H. Davenport.

For many organizations, the growing challenge of data privacy is a stumbling block for developing customer data analytics initiatives. Moreover, there is also an increased consumer awareness of their legal rights caused by the rise of privacy threats, creating challenges for brands. 

A firm can be fined for regulatory non-compliance or when a data breach occurs. If customers can’t trust firms to protect their data, then they can just switch to a competitor with a click of a button. 

Employing a Comprehensive Approach to Data Privacy Compliance 

According to community and online portal CGOC (Compliance, Governance and Oversight Council), it found that only 57% of companies train staff on data protection compliance, with only 25% conducting regular training and audit. These statistics reflect the narrow vision of companies with regard to data privacy compliance. For instance, many firms prepared for the General Data Protection Regulation (GDPR) by updating privacy notices on their websites, creating data inventories, doing minimal internal awareness training, and defining retention policies. 

These are useful steps but they do little to prepare companies “for the deeper operational changes required for GDPR compliance” such as tracking what data is aggregated for what purpose, adhering to specific retention rules for all data, and ensuring a legal basis for all data-driven activities. The solution? Balance has to be achieved between data privacy compliance and data utility, which requires an ongoing collaborative approach among legal, IT, marketing, and security departments, with an emphasis on setting up technology and human safeguards. 

Being Transparent With Customers

60% of consumers feel uncomfortable when companies use their data for analytics, as found by Truata, an expert provider of data anonymization and analysis. 74% of the respondents are uneasy about their personal data being sold to third parties, while 65% admit they are more likely to be loyal to an organization if they trust it to utilize their personal data appropriately. 

To build and maintain customer trust, firms must be proactive and transparent about how they use data. Companies must be prepared to demonstrate their competency in safeguarding sensitive information by acting responsibly and ethically.

It’s not a plausible idea to burden customers with the responsibility of reading privacy terms and notices just to see if an organization is acting ethically. In fact, this is an unrealistic and counterproductive approach. 

Data privacy should be a top priority when initiating analytics projects and formulating strategies. Companies must be competent enough to maintain the delicate balance between data utility and security. Now is the time to put the needs and concerns of customers first, enabling firms to gain a competitive advantage against other companies. 

To build and maintain customer trust, firms must be proactive and transparent about how they use data. Companies must be prepared to demonstrate their competency in safeguarding sensitive information by acting responsibly and ethically / Photo by: tsyhun via Shutterstock