As the world grows increasingly inclined toward data, there are more concerns about data privacy. Every time customers are required to provide their personal data, the first concern that arises is their safety and, more importantly, their privacy.
Research by Tableau shows that 48% of internet users have stopped shopping online due to privacy concerns. This shows the extent to which a lack of privacy can offend customers and lead to a decline in the customer base. Therefore, one of the ways to build trust with customers for long-term loyalty is to prioritize data privacy. That is, companies must learn to strike a balance between extracting meaningful insights from data for decision-making and respecting the privacy of individuals whose data has been used for such purposes.
While leveraging customer data for business intelligence, ethical considerations that meet data privacy standards must be incorporated to build trust and boost customer loyalty. Before going into how this can be achieved, let’s first consider the concept of data privacy.
Data privacy refers to the responsible use of data in a way that protects individuals’ privacy. It refers to all the measures taken between the collection and processing of data that ensure that data is used only with authorized consent. It allows people to determine to what extent their personal information, such as name, contact information, and location, is shared or used.
Data privacy is of two kinds:
Ethical consideration is equivalent to giving your customers a voice and placing priority on their interests. It shows that you’re not just about providing the best product and service; you’re also about giving them a shield that provides them with a sense of safety, building trust, and setting the stage for long-term commitment with the company.
In data privacy, ethical consideration involves providing customers with the liberty to disclose their personal information and allowing them to choose the extent to which they disclose the information. Some customers are only willing to provide their names and email addresses; asking for more details such as date of birth and location may spur some suspicion. Therefore, companies must understand the uniqueness of customer behavior, which is strongly linked to their diversity and cultural background.
Having understood the importance of data privacy and how much importance customers place on it, let’s consider the strategies that could be implemented to incorporate it.
Privacy by design: In this case, you’re solving the problem from the root. It has to do with designing the BI system in such a way that importance is given to privacy and respect for individual choices and decisions. This system incorporates safeguards and control measures that prioritize data protection throughout its entire life cycle.
Employee Training: In business, employees are usually in direct interaction with customers and also operate BI systems. Therefore, organizations should give proper training to employees on how to operate the system in a way that shows respect for people’s privacy. There should also be detailed awareness about customers’ concerns about privacy and the implications that follow any disregard for privacy.
Regular audits and assessments: Regular assessments of data processes should be conducted to identify potential risks in data systems that could threaten the privacy of customers. On detection, immediate action should be taken to correct the error in the system. BI systems are prone to changes; therefore, regular audits must be done to ensure that they meet privacy standards.
Though you’re making background efforts to protect the privacy of customers, you must also create an avenue to help customers understand the measures you’re taking and how you’re working towards their best interests. This is achieved first through accountability. Let customers know the purpose for which their data is being used and how it helps the company improve its decision-making tactics. Then, customers will be encouraged to provide their personal data without fear or prejudice.
Also, companies should be transparent about their data policies. Customers should not be made to provide personal data that would later be used for purposes outside their approval. Companies should also learn to minimize data collection, collect only the data that is needed, and delete data that is no longer useful for operations. In cases where sensitive data is required, anonymization and pseudo-anonymization techniques should be used.
Advanced technology that involves data collection and analysis is used to discover the interests of customers and how to satisfy their needs. However, ethical considerations in data collection and processing should be incorporated to earn the wholehearted participation of customers in data collection, building long-term loyalty along the way. Balancing data privacy and business intelligence is a holistic approach that requires a lot of intentionality, as some organizations might be so focused on creating BI systems that they forget to incorporate the ethical considerations that ensure data privacy. Not minding what it takes, companies should continually strive to create a balance between data privacy and business intelligence.
