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Despite 71% of online shoppers being unaware they are interacting with generative artificial intelligence, about half say they see value in the technology when it comes to personalizing the online shopping experience and would be willing to share personal data to receive a more customized shopping experience, says a recent survey from Bain & Co.
Personal data online shoppers say they would be willing to share includes information about personal interests such as hobbies, their favorite products, and demographic data, according to the survey. In return, consumers say they expect generative AI to help them with the discovery and decision-making phases of their purchasing journey, such as finding products aligned with the timing and context of their purchase, past purchases, and preferences.
Sharing such data with merchants can help merchants guide consumers to product reviews that can influence a purchase. For example, a retailer that knows an online shopper looking at children’s car seats is a new parent and can highlight relevant comments from other new parents about a car seat’s quality or ease of installation on the product page.
“Customers see the potential for getting something valuable back in exchange for their data, and they’re getting more accustomed to having control over what data gets shared,” the study says. “Building feedback loops helps to gather more information about what customers do and don’t like while also providing data that helps retailers refine their recommendation algorithms.”
Bain surveyed 700 online shoppers in the United States about their knowledge of and experience with generative AI.
Brand reputation goes a long way when it comes to reassuring consumers that the use of generative AI will not lead to a negative experience. Some 41% of customers say they would feel comfortable using a generative AI tool from a brand they trust the study found.
Still, many consumers prefer not to use generative AI. The leading reason online shoppers provide for not using generative AI tools is that they are satisfied with the current online shopping methods, 47%. In addition, 39% of respondents say they do not see a need for new online shopping tools and 22% say they do not trust the technology.
Another factor that can cause consumers to distrust generative AI is that the technology can create misleading, inaccurate or biased content. Some 56% of respondents cited inaccurate product information as one of their biggest concerns about the use of generative AI in the online shopping experience, while 57% cited obvious errors.
For those reasons, the study recommends e-commerce merchants using generative AI be transparent with customers about its use on their Web sites.
“Clear policies on data usage and protection can assuage customers’ concerns by building trust and showing them where information comes from. No need to overexplain: Customers don’t need to understand everything about the technology, but they’re likely to be more comfortable using it with some transparency,” the study says.
In addition, merchants should provide ways for customers to dismiss and flag unwanted content produced by generative AI. One option is to scrutinize customer feedback to flag unwanted content and use that data to build analytical models to spot unwanted content before it is placed before a shopper, the study says.
While generative AI provides a bridge to a more interactive and personalized retail experience e-commerce, merchants need to remember that applying the technology to meet customer needs and being transparent with customers about the use of the technology “will unlock new levels of engagement and loyalty among their customers,” the study concludes.
In related news, fraud prevention platform provider Sift Science Inc. released insights to its Fraud Industry Benchmarking Resource, which highlights key fraud metrics across industries, geographies, and time.
While credit and debit cards account for 85% of fraudulent transactions, their use in defrauding iGaming and online gambling websites drops to 64%. Electronic fund transfers, 20.5%, and digital wallet payments, 15.5%, comprising the remaining mix of fraudulent payments in this category.
When it comes to fraud rates among payment methods for iGaming and online gambling electronic fund transfers top the list, 1.8%, followed by credit and debit cards, 1.4%, digital wallets, 0.9%, gift cards and vouchers, 0.2%, and cryptocurrency, 0.2%. Sift gathered the insights using data from its global data network.
