5 Ways Data Privacy Can Improve a Retailer’s Competitive Edge
It’s no secret that retailers like Amazon.com and Walmart have leveraged the power of big data to tailor their customer experience and increase revenue, even amidst the dynamic market conditions of the COVID-19 pandemic. Brick-and-mortar and e-commerce giants benefit from a streamlined checkout process, targeted promotions, and innovative ways to leverage data with machine learning and artificial intelligence-driven algorithms to increase the likelihood of converting casual browsers into regular customers.
Surveys have shown us that over 90 percent of customers are more likely to shop with brands that provide personalized marketing, and almost 50 percent have purchased products they didn’t initially intend to buy after receiving a personalized recommendation.
The power of customer data comes with corresponding risk, however. Nearly half of U.S. consumers don't feel they have control over their personal data, and less than 25 percent of organizations in 2019 had optimally integrated data privacy plans within their business. With one-third of companies expecting a data breach to take place in the next two years, how can retailers use their critical customer data without damaging their brand? Here are five tips:
1. De-identify data.
Data security is critical, but not enough. Regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) were created to ensure strict control and protection of consumer data. Traditional security measures (e.g., firewalls, access controls) remain important, but cannot alone protect data from malicious attacks or inadvertent breaches, let alone adhere to the myriad of regulations. Many regulations insist that data retention is safest when de-identified, meaning a customer can not positively or reasonably be identified, even when combining different pieces of data together.
2. Link data only when necessary.
Retailers have different departments with different goals. Some care about cross-selling, while others are focused on reducing customer churn.
Often the most valuable insights from analyses and algorithms come from connecting different data sources, but identities can also be uncovered by linking data. De-identified data must allow for controlled enrichment of data to discover trends and insights, but it also must be tightly controlled to ensure that any unintended enrichment or linkability is prevented. Data privacy tools provide a seamless way to de-identify data for analysis while ensuring they cannot be linked (e.g., give one team access to de-identified data for customer churn analysis, while preventing it from being combined with data used by the team looking at cross-selling).
3. Factor in architectural flexibility.
With today’s rapidly changing market, it can be tricky to analyze the latest data. For example, Boston restaurants operated normally in February. By April, many of them had pivoted to selling groceries, and by June, they were focused on phased re-openings. Evaluating information that's days old involves understanding how data flows, and maintaining privacy throughout that process. De-identification can help retailers respond swiftly and maintain architectural flexibility, allowing them to make these necessary pivots during uncertain times.
4. Automate data privacy techniques.
As organizations scale, automating data privacy processes becomes critical. For example, if you have a customer’s demographic data or shopping history and want to use it in a quarterly analysis to determine your next campaigns, you can automate de-identification of this data to centrally determined policies so you don’t have to manually intervene each time. Automation can make data available measured in minutes to days, depending on the size of the dataset, rather than the months it could take if done manually.
5. Track and uniquely identify your datasets.
Given the risks associated with a breach or regulatory violation, it's critical to ensure that datasets are appropriately tracked and identified. Some data privacy tools can attach “watermarks” — indelible “fingerprints” encoded into the data. You can track why data was created, by whom, and for whom, along with an expiration date. Watermarks are especially helpful when data breaches occur to quickly identify when and where the breach occurred.
Retailers must retain customer data to be successful. Failing to use critical insights, particularly in such a rapidly changing market, is a recipe for failure. Exposing customers to a data breach or failing to comply with government regulations is a recipe for disaster. The steps outlined above will help you build a plan to protect your sensitive data, ensure thorough analyses, and obtain the strongest competitive advantages for your business.
Sydney Boncoddo is a senior product marketing manager at Privitar, a provider of enterprise data privacy software designed to minimize risk, achieve regulatory compliance, and help realize the promise safe and usable data.
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