How to calm consumers’ fears about AI and data privacy
There is little doubt that artificial intelligence (AI) is shaping the future of the retail market. Recently, Macy’s announced it was testing an AI-powered in-store app that enables shoppers to get answers based on the store they are physically shopping in, rather than having to find a sales associate.
Sephora also jumped on the AI bandwagon when it launched a chatbot on messaging app Kik earlier this year, aimed at providing customers with personalised makeup tips and reviews.
Whether it’s AI chatbots becoming in-store and online customer sales assistants, or AI powering the future of retail personalisation, it’s clear that AI is having a dramatic impact on the way we do business.
However, as with any new technology, the embrace of AI comes with concerns, especially when it comes to consumer data privacy. Losing customer data – whether by human error or through a cyber security incident – can have significant consequences for any retailer.
In one recent poll, 85% of consumers indicated they would be less likely to do business with a company that failed to protect their data.
The concerns of personal data privacy are very real, and have been a part of AI conversations since its inception. However, this should not inhibit retailers from embarking on data-driven marketing programs that can increase customer loyalty and revenues.
There are steps brands can take to quell their customers’ concerns about AI, and encourage them to think differently about sharing their data.
Data is just a number
When it comes to customer data, retailers should think of themselves as a baker, using ingredients (i.e., data sets) from their customers, including demographic, location, product, loyalty and transactional information.
While they don’t own these ingredients, they are essential to bake the most delicious cake we can (i.e., exceptional offers that are tailored to a customer’s unique tastes, preferences and lifestyle).
In order to maintain strict customer data privacy, retailers must treat all of these data points purely as numbers, which will eliminate the chance of identifying information being released.
By taking sensitive data and transforming it into a series of numbers and algorithms, retailers can turn sensitive data into ingredient components that create the end product – personalised offers based on predictions on individual consumer purchase behavior.
Much like the ingredients in a cake – flour, eggs, sugar, milk, etc. – data ceases to be individually identifiable components as soon as they’re added together.
Educating consumers about how they will benefit from the data they share is another step to assuage data-sharing fears
This is important because the process can’t be reversed. Once you bake a cake, you can’t get the butter out. In the same way, you shouldn’t extract a data point that can be traced back to your customers once you’ve used the data to create a personalisd experience.
This is a win-win for both retailers and customers. With this approach, retailers can bake that cake to better service their customers, and their customers get to maintain their privacy.
Understanding retailers’ limitations
The desire for retailers to ease concerns around their customers’ data is an admirable pursuit. But problems arise when retailers try to manage data programs internally.
The reality is that few retailers are technically advanced enough to implement and maintain data-intensive programs that live up to their customers’ security expectations.
Thankfully, there are a multitude of sophisticated digital marketing technologies in existence today that understand how to deal with sensitive customer data throughout the entire data cycle – from gathering and storing data, to combining and testing the data in order to make accurate recommendations and improve the customer experience.
Technologies like these have complex methodologies and algorithms to anonymise data in a way that only makes sense to that AI system – making it impossible for anyone else to understand and, therefore, siphon any customer data.
Investing in these tools allows retailers to harness security capabilities that just do not exist in-house.
Educating consumers about how they will benefit from the data they share is another step to assuage data-sharing fears.
In a study conducted by Accenture, the majority of consumers in both the US and UK said they were willing to have retailers they trust use some of their personal data in order to present personalised and targeted products, services, recommendations and offers – despite data tracking concerns.
Specifically, of the 86% that said they were concerned that their data was being tracked, 85% said they realised that data tracking make it possible for retailers to present them with relevant and targeted content. Consumers just want a fair trade in exchange for their data.
As a retailer, maintaining consumer privacy is top of mind.
By taking steps to anonymise data and educate their customers, retailers can ensure privacy and peace of mind while using valuable data to improve customer experiences. This proves that when it comes to AI-driven marketing programs and privacy, retailers can have their cake and eat it too.