Businesses and marketing leaders find themselves at an interesting crossroads in history. They are constantly struggling to balance the competing interests of respecting customer privacy and data while simultaneously using that data for marketing personalization.
Over the last decade, consumers have developed a complicated relationship with technology and privacy. Data and technology have made it increasingly easier to provide personalized online experiences. But, consumers are becoming more and more apprehensive about their data privacy.
Businesses and marketers often find themselves walking the fine line to give consumers the personalization and privacy they want. Businesses have a difficult balancing act to negotiate between transparency, security, and a personalized experience. It is something that companies across all verticals have to get right or risk losing valuable customers.
Striking the Right Balance
Consumers expect personalization and want brands to accurately anticipate their needs based on data insights related to their preferences and buying habits. Meanwhile, consumer mistrust continues to grow, especially after several high-profile data leaks.
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A global effort to reform how businesses collect and use data about consumers has resulted in increasing limitations, especially those concerning the use of third-party data.
Businesses often operate under the misconception that privacy and personalization are conflicting concepts and not symbiotic opportunities. This privacy paradox sets up a potential conflict between data and marketing leaders, customer experience (CX) leaders, analytics leaders, security and risk leaders, and other stakeholders. It undermines CX initiatives, limits the new business value, and frustrates customers.
Companies are losing out on the opportunity to create great customer experiences because of needlessly risk-averse privacy ideas that limit the use of customer data. The key is to keep data use in context and bring value to customers.
Customization is Key
The goal of customization is to enrich the experience of the individual, but few brands deliver on that. With the rise in internet-enabled product availability and price visibility and customer experience has become the crucial differentiator among organizations.
Data privacy concerns often lead businesses to use only non-personal data, such as aggregate behavior data and anonymized information, which may be helpful but is not always compelling to customers. Consumers want to be recognized and like their experiences personalized, and if they don’t get it, they may go elsewhere. Hence, organizations that combine identity data with behavioral data will surpass those that don’t.
Personal Choice and Transparency
Enterprises worldwide are now forced to pull back the curtain. The days of blind trust are now being replaced with the demand for complete transparency. Organizations will need to endow services and products with the capability to easily and openly select the level of personalization based on the appetite of the consumers in handing over their personal data.
Thereby, the prevailing desire for choice will drive the need to provide a sliding scale of privacy and personalization. This will impact everything from app design to marketing campaigns.
Organizations are already pushing enhanced data privacy policies content to their user base. With time, the consumers will demand policies that are easier to access, read and understand, and choose.
Data Governance
Businesses will also need to enhance their data governance policies and reassess how they collect and store their customer data.
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Progressive businesses are already moving beyond the legal and regulatory requirements and addressing data privacy as a matter of customer perception and trust. Some have even created platforms to review company policies about their use of personal data, so they don’t push away their customers.
While many companies are busy trying to avoid GDPR penalties, marketing leaders believe businesses need to start reassessing their digital strategies and their implications on data.
