What does ChatGPT’s new shopping capability mean for returns?

By Niels Krijnse Locker, VP Product at ReBound

ChatGPT adding shopping features to its growing powers has sparked fresh speculation about how AI will continue to reshape the retail sector. New tools designed to make it “faster to find, compare, and buy products” are already being rolled out. Users can now see prices and reviews more easily, and the chatbot can share direct links to personalised product recommendations.

Some retailers already have in-house generative AI shopping assistants, and customer service chatbots for handling queries or tracking orders are nothing new. But although ChatGPT doesn’t yet process purchases directly, it is playing an increasingly important role in how consumers discover, compare, and choose products. This shift has far-reaching implications for another crucial area of the customer experience: returns.

Large Language Models (LLMs) like ChatGPT are quickly becoming alternatives – or even replacements – for traditional search engines. For retailers, that means AI may be a customer’s first stop, before searching Google, visiting a brand’s website, or visiting a store.

This new path to purchase raises the bar. Smart shoppers won’t just ask for the best price, they will want to know which retailers offer the best customer experience, including flexible, free, or convenient return options. Two-thirds of consumers check returns policies before deciding to buy. Retailers need to ensure their returns policies and portals are not only up-to-date, but also visible and AI-accessible. If terms are buried in the fine print, ChatGPT may not be able to find them and share with potential shoppers.

In some cases, AI could even reduce return rates. As ChatGPT learns more about an individual’s preferences such as sizing, colours, and styles, it can provide increasingly personalised product suggestions. Better recommendations would likely lead to less buyer’s remorse and fewer returned items.

Looking further ahead, AI could play a bigger role in returns processing. Today’s chatbots can help to initiate a return, but interactions are often limited, with fixed scripts. Conversational AI could in theory allow deeper dialogue, gathering richer context on returns reasons, consumer motivations, and return method preferences. These insights could inform product development as well as logistics and operational decisions.

This future of AI-powered returns is not without complexity. Introducing another layer between retailer and customer could complicate what should be a seamless experience. AI can still make mistakes, and could misrepresent a brand’s tone of voice or provide incorrect information. It could even apply dynamic returns policies in ways that expose the retailers to compliance risks by inadvertently breaching regional consumer protection standards.

Ultimately, the rise of AI chatbots will affect the entire customer journey, not just how we discover products. Customers using ChatGPT for purchasing decisions will expect guidance on returns too. Retailers that make their policies clear and accessible not just to customers, but also the AI tools advising them, will have a significant edge.