inside blame the brand

It’s no big secret that artificial intelligence (AI) is transforming retail. It can be used in almost every phase of the product life cycle. More and more consumers around the world are using large language models (LLMs) like ChatGPT and Gemini to shop online. They use AI to discover, compare and select products and brands. LLMs are becoming an increasingly influential part of the buying experience. Fashion brands and retailers should therefore invest in this technology.

To better understand how AI is impacting online retail, cloud-based retail platform Rithum and Studio’s Retail Dive conducted a survey of 1,046 consumers in the US and UK. The results were published in the report “The New Discovery Engine.” Here we summarize some of the key findings. They show the potential of LLMs to reach and address the right target group. As long as a brand’s content, prices and inventory data are correct, the potential for attracting customers is high. However, if the data is incorrect, caution is advised. The AI ​​will tell its own story about your brand, whether true or not, and present it to buyers.

Consumers from many target groups are already using AI for shopping

The use of LLMs for shopping is widespread among consumers in the US and UK. However, it varies depending on age and income. The report found that more than eight out of ten shoppers under the age of 44 used an LLM for their purchase in the last three months. Over half said they trust AI tools as much as brands and retailers’ websites.

Not surprisingly, younger demographics use and rely on AI the most. The report found that 80 percent of 18- to 43-year-olds have used AI to shop in the last three months. In the age group 60 and over it was 51 percent. Many younger consumers said they would miss the benefits of AI when shopping. More than one in four 28- to 43-year-olds said they would feel a “huge” loss if they didn’t have access to AI tools. Among those over 60, the figure was nine percent.

Most buyers surveyed said they primarily use AI for research. They use it to explore product details and compare options, with over 90 percent relying on it for these tasks. More than half also said they use AI to decide where to buy. Instead of leaving the final purchase decision to AI, buyers use their information to narrow down the selection. It highlights the best options and draws attention to specific products, retailers and brands. 37 percent of respondents also said they use AI when purchasing clothing, shoes and jewelry. This is slightly less than for electronic items at 45 percent.

Households with greater purchasing power rely more heavily on AI

Household income is another factor driving AI usage. The survey found that higher-income households, i.e. those with more purchasing power, use AI more often for shopping. Usage reaches 84 percent among households earning between $100,000 and $150,000 (€87,000 and €130,000) annually. Among households with lower incomes of less than $30,000, AI usage fell to 56 percent.

Income differences also influence how shoppers use AI. Lower-income households use AI as a price comparison tool to find the cheapest deals possible. In fact, 43 percent of households earning less than $30,000 use AI primarily to “find the best price” when shopping. Higher-income households, on the other hand, use AI to save time when shopping. This way you avoid having to search through multiple websites to find the product you want. They are also twice as likely to trust AI without visiting another website.

AI helps small brands compete with well-known names

AI tools give buyers more security when shopping. At the same time, they also make consumers less loyal to the brand. 43 percent of respondents compared more product options with AI. 36 percent made purchasing decisions faster and 34 percent felt more secure with their purchases.

AI connects shoppers with brands they may not know. 19 percent – ​​almost one in five – said they had bought from a brand they were previously unfamiliar with because the AI ​​recommended it. 13 percent also said they are more willing to change retailers, brands or products because of AI suggestions. 32 percent spend less time browsing other websites when they use AI. Not surprisingly, power users and high-income buyers are most likely to respond to AI recommendations without additional research or a second opinion.

When AI makes mistakes, your brand is to blame

Although LLMs are a powerful product discovery tool, the accuracy of product data is equally important. This includes prices, availability, materials, sizes and other specifications. 53 percent of survey participants trust AI tools as much as brands’ websites.

What AI shares about your brand and product is incredibly important. When AI provides poor or incorrect product information, consumers don’t just blame the LLMs. In fact, 58 percent of consumers said their overall trust in a brand or product decreased when an LLM provided incorrect information. 16 percent even canceled the purchase completely.

Price accuracy is most important in AI recommendations

Price proved to be the most important factor in AI-powered recommendations. 67 percent of buyers prioritized its accuracy, followed by product reviews at 35 percent and availability at 34 percent. However, 44 percent of consumers surveyed also said that AI tools still need to improve the accuracy of key product details. This particularly affects pricing and inventory levels.

At the same time, shoppers rarely review AI-generated information on brands’ websites. Only five percent of respondents do this, suggesting that decisions are largely made before reaching the brand’s own channels. Instead, they rely on search engines (28 percent), friends and family (17 percent) or previous experiences (17 percent). 64 percent of 18- to 27-year-olds buy based on AI recommendations without further verification.

“AI turns consumer trust into a product data issue. As agent-based commerce becomes the basis for how shoppers research and evaluate products, brands will need to think more strategically about how their product information appears across their commerce ecosystem,” said Sam Griffin, VP, Strategy and Engagement at Rithum, in a statement. “Accurate, consistent product data will play an important role in how brands are discovered by AI and trusted by consumers in agent-based shopping experiences.”