Where to Use Gen AI to Boost Retail and Brands

According to Google Cloud, generative artificial intelligence has crossed the threshold from hyped novelty to a high-powered business tool, and the tech is proving its chops with concrete results.

The group apparently has the receipts — or at least results from its latest survey of hundreds of retail and brand executives.

Most of those leaders aren’t just dabbling with gen AI, but “actively deploying it to drive immediate, demonstrable results across their organizations,” wrote Paul Tepfenhart, global director of retail industry strategy and solutions at Google Cloud, in a company blog.

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Only two percent said they hadn’t even begun to explore the tech, while 32 percent are evaluating or testing it. That leaves a whopping 66 percent who have taken the plunge, shifting pilots into actual production, with some crediting the tech for driving revenue growth.

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Eighty-seven percent of those executives reported an increase of six percent or more in overall annual revenue. Thirty percent said that the gains exceeded 10 percent growth.

They’re using generative AI in different ways to get these results. So Google Cloud looked into the top areas for gen AI deployment and here’s what it found.

Customer Service and Experience

Fifty-seven percent of respondents reported that gen AI drove better customer experiences by connecting people to desired information with more accuracy and speed. Specifically, they cited automated call transcripts and summaries, smart replies and responses to frequent customer questions.

Product Search and Styling

Gen AI is considered something of a magic ingredient in search, and it’s easy to see why. It allows for contextualized search, which is about more than just connecting shoppers to product. It’s about helping people find the right product at the right time.

Think of it as another mode of personalization. The logic is easy to follow — there’s a direct line between better, more useful results and higher sales.

For a subjective field like fashion, a business driven by tastes and preferences, personalization is the holy grail. And in that arena, styling is essentially an assisted, contextualized product search.

“Imagine AI stylists that combine customer data with a retailer’s products and promotions to offer personalized style recommendations across multiple visits and channels,” Tepfenhart said. “These AI stylists can even create visual representations of the suggested looks, using gen AI to generate images or videos.”

Employee Productivity, Especially in Marketing

Nearly half of the executives surveyed said gen AI doubled productivity, particularly for staffers in marketing.

Where gen AI is used in production, 59 percent are applying it to tasks like generating marketing copy or product descriptions, images and other creative content for campaigns and editorial use. They can do so quickly, allowing them to jump on trending news, events or viral moments.

Security

The ever-shifting threat landscape looks daunting, so there’s little wonder why more than half of respondents are using AI to help safeguard their businesses from data thieves.

In retail, the risk goes up considerably when fraudsters get added to the mix. In this area, gen AI is a double-edged sword. It may power scams, but it can be used as a weapon to target them as well.

The tech comes in handy for spotting fraudulent activity, as well as bolstering security and defenses.

The insights come from a Google Cloud survey of 376 senior executives in global retail and consumer packaged goods companies with at least $10 million or more in revenue. Its implications matter to the way retail is evolving, and for specific sectors like fashion, the impact is hard to overestimate.

Victoria’s Secret chief information officer, Murali Sundararajan, summed it up in a commentary for the report.

“A customer can now go to our website or mobile app, upload a picture of any product (from Victoria’s Secret or another brand), and receive personalized product recommendations,” she said.

“AI enables us to simulate the in-person shopping experience on our digital platforms without having to scroll through countless pages to find what a shopper might be after — or not even know they might want.”

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