Some 71% of US retail decision-makers have invested in data and AI-enabled content for personalization, according to an August 2023 survey by Coresight Research. As more brands adopt AI to scale tailored content, they’re also confronted with the challenge of protecting—and respecting—their audience’s privacy.
More under the microscope: AI isn’t new, nor is it new in retail. So why is it such a buzzword?
“A lot of what's been happening in AI previously has been happening under the hood,” in the background of features such as personalized product recommendations and enhanced search, our analyst Carina Perkins said on an episode of the “Behind the Numbers: Reimagining Retail” podcast. Now generative AI tools are consumer-facing, so they are more savvy at detecting them.
That may make consumers more suspicious of AI use, too. Seven in 10 US adults have little trust that companies will use AI responsibly, per May 2023 data from Pew Research Center.
When it’s done right: “Certainly there is an appetite for AI and shopping, especially among Gen Z, but only if it's actually going to reduce frictions and not just create more frustration,” Perkins said.
Here are three ways—and real-world examples—retailers can implement AI without overstepping customer boundaries.
1. Be transparent about using AI
“Consumers need to know that you're using AI,” our analyst Suzy Davidkhanian said. “They don’t want to feel duped.”
AI in practice: Newegg, an ecommerce company for technology, uses ChatGPT to produce Review Bytes, consolidated customer reviews in a cohesive, quickly digestible snapshots that details everything from ease of installation to functionality. Review Bytes are labeled “SummaryAI” so customers know they aren't reading direct feedback from other customers.
2. Avoid the feedback loop
“[Brands] should look at technology enablement in a way that widens the scope,” Davidkhanian said. If AI models are set too narrowly, then it only shows you what you already know you like, hindering product discovery. “Instead, it should suggest products that may not have been on your radar,” she noted.
AI in practice: Last year, European fashion retailer Zalando rolled out an AI-powered assistant that provides product recommendations through conversational queries. Shoppers can ask, for example, “Do you have any dresses for a black-tie wedding in August?” or “Help me put together an outfit for a work event.” Suggestions can be further personalized by combining information about the customer’s size and favorite brands.
3. Lean on data at every step of the customer journey
Sometimes there's too much data siloed across different systems, and sometimes there are simply gaps of missing data that prohibit retailers from seeing the full buying journey, Davidkhanian said. A retailer, for example, may waste money by advertising products that a customer has already purchased, because it has the data that shows intent but not the actual transaction.
AI in practice: Partnering with retail analytics firm Intelligence Node, Kroger is using generative AI to enhance its product listings for third-party marketplace sellers. The integration not only helps deliver a consistent digital experience for customers but also fuels data on product performance, pricing, and trends for sellers.
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