Retailers are increasingly using the power of data analytics to gain insights into customer behaviour and refine their marketing strategies in accordance with it. Retailer analytics has proven valuable in enhancing shopping experience and maintaining a competitive edge. However, these benefits in retail come with rising privacy concerns. Consumers worry about how their personal information is being collected, used, and also protected. This is a challenge for retailers, who must balance the benefits of data-driven insights while ensuring customer privacy.
A Gartner report states that by 2024, 40% of privacy compliance technology will rely on AI, and that by 2025, 60% of large organizations will use at least one privacy-enhancing computation technique in analytics, business intelligence, or cloud computing.
Here are some privacy concerns in retailer analytics and also how retailers can address them:
1. Transparent data collection: Customers frequently worry about how their data is being collected and used. Retailers must ensure clarity by clearly communicating what data is being gathered, why it is needed, and how it will be used. That is the only way to be transparent. For instance, if a customer signs up for a loyalty program, they can be informed in advance about the types of information that will be required, why it has to be collected, and how it will enhance their future shopping experiences. This approach helps build trust and ensures customers are making informed decisions about sharing their data.
2. Consent based approach: Customers ought to be given control over their personal information and how it is being utilised. Retailers should frame a few questions regarding the data collected and the choice to share this information should be a consent-based approach where customers are asked for permission before any data is collected. One might have noticed how when we visit a website, an option to accept or decline cookies that track our online behaviour pops up. This must be followed by all online retailers for the shoppers online.
3. Anonymous data collection: To protect customer privacy, retailers can anonymously collect data by removing any personally identifiable information such as name, phone numbers, government identification numbers etc. This means that data is collected and analysed without identifying individual customers.
4. Safe data storage: Retailers should take steps to ensure that customer data is stored securely to prevent unauthorized access. Encryption must be used to protect data. Also, implementing access controls to limit who can access sensitive information, and regular monitoring of internal systems for any security threats must be done.
5. Transparent data use: Retailers should be transparent about how customer data is being used for marketing purposes, personalization etc. If a customer is receiving monthly newsletters from a brand based on the email id provided while making a purchase, they should be given the option to opt-out if they prefer to do so.
In this digital era there’s also a need for digital privacy laws for people to place their trust. Recently, data protection laws have gained momentum and these laws will help in protecting one’s rights. The Government itself has access to a lot of private data of citizens, so data protection laws will keep both the Govt. and private companies in check.
As a matter of fact, in August 2023, the government introduced the Digital Personal Data Protection Bill, 2022 (Referred to as DPDP Act). After multiple consultations and changes, the Digital Personal Data Protection Bill of 2023 was finally passed and it received the President’s approval after six years. This is a good start for sure.
In retail analytics, addressing privacy concerns play a major role in building trust with customers and also in acquiring new customers. Being transparent about data collection shows the efforts of retailers to protect customer privacy while still getting the benefits of data analytics to improve the shopping experience. By making sure that customers’ personal information is protected, retailers can improve their customer retention as well.
Recent Posts
How Alteryx Empowers Non-Technical Users?
So, by now everybody is familiar with Alteryx and how it works, but what is important to know is how it is helping non-technical users to make informed decisions. Since not everyone who needs to analyze data has a technical...
How to Automate Repetitive Tasks with Alteryx
For any business to flourish, efficiency and accuracy are very important. Repetitive tasks consume a lot of time and resources and also add to the slower progress of organisations. Automating these tasks lead to significant productivity gains and cost savings. ...
A Comprehensive Guide to Row Level Security (RLS) in Tableau
By MANDAR MORAJKAR Senior Business Analyst - Data Analytics Services What is Row Level Security (RLS)? Row Level Security (RLS) is a security feature in Tableau that allows you to restrict access to certain rows of data within a dataset,...
Leave a Comments
You must be logged in to post a comment.