AI Steps into the Retail Arena

Generative AI has put the retail industry at yet another inflection point. 2023 was a period of experimentation for retailers, and many thoroughly assessed where this new technology could have the biggest impact. As the use cases for this technology have become more clear, in 2024 we’ll see generative AI step into the arena as retailers move from experimentation to production, unlocking both efficiency and revenue opportunities — securely and at scale.  

Just as with the acceleration of digital in the dawn of ecommerce, and again during the early days of COVID when companies that took a “wait and see approach” were left far behind, we’re again at a pivotal moment. Retailers must move quickly to deploy transformative technologies or risk putting relevancy and their brand experience at risk. Now is not the time to be in analysis paralysis. 

In new research that Google Cloud led in the U.S. across retail C-suite executives, information technology leads and business development managers, we found that 81% of retail decision makers feel urgency to adopt generative AI technologies, with 72% ready to deploy generative AI in the coming year. 

But for many retailers the question remains, “Where can this new technology best help my organization now?”


5 Ways Retailers will see Impact from Generative AI 

In 2023, generative AI emerged as one of the fastest-growing technologies to date, with retailers moving quickly to pilot and explore generative AI tools. Our recent study also revealed that the majority (75%) of surveyed retail decision makers believe generative AI can be practically deployed in their business, and 78% believe generative AI will impact their industry in the next 12 months. 

A common question we get across industries is, “What makes generative AI different from other forms of AI that have come before?” Put simply, generative AI offers unprecedented ease of use to help solve everyday problems. Today’s shoppers expect real-time responses, seamless omnichannel shopping, virtual shopping assistants, customized offers and more. Generative AI is poised to help retailers deliver on these expectations while also providing internal benefits like productivity gains and a better employee experience. In fact, nearly all (95%) of retail decision makers in our recent research say that generative AI will have an impact on customer experience. 

At Google Cloud, we’re betting that in 2024 retailers will see the greatest impact for generative AI in five  specific areas:

1. Support and scale customer service.
As some retailers know all too well, a brand is only as good as its customer service. Generative AI can not only support customer service reps with helpful answers to shopper enquiries, but it can help scale other areas of operations too. For example, virtual agents can take the load off a retailer’s contact center by enabling instant, natural-language chatbots to help shoppers easily find the answers they need, whether it’s determining the differences between products or exchanging an order.

And with an estimated 75% of shoppers using multiple channels in their ongoing experience, generative AI helps extend great customer service across touch points — from digital self-service channels to agent-supported options in branches, call centers, and social media channels.

2. Streamline product catalog management.
Product catalog management has been the thorn in retail’s side for decades due to managing inventory that rotates frequently, and the stakes are high for this department. Generative AI can assist with common time-consuming tasks like updating inventory with accurate quantities and styles in real time, getting images from vendors, sorting and categorizing products by popular search terms and relevant descriptions and writing product copy. By automating these often tedious tasks, retailers can accelerate product catalog management and ensure products are easily searchable, all of which ultimately helps with product discoverability, customer personalization and merchandising. 

3. Automate conversational commerce.
Conversational commerce empowers ecommerce brands and retailers to use messaging and conversational technology to improve the shopping experience. It is increasingly becoming a popular way to help shoppers find what they’re looking for and avoid search abandonment, which can cost retailers over $2 trillion each year. For example, having a virtual stylist at the ready can help a shopper find dresses in their size and style 

However, the volume of queries and level of detail needed has made it challenging for retailers to stand up an effective conversational commerce solution. Generative AI’s ability to instantly create new content based on data and information means this technology can power a virtual personal stylist that is capable of interacting with shoppers and suggesting items tailored to a shoppers’ query or preferences. 

4. Amplify creative assistance.
In a world where 73% of shoppers expect brands to know their preferences, generative AI can help retailers deliver more engaging and personalized content faster and more efficiently. For example, a savvy marketer for a handbag company can use generative AI to create multiple variations of ad copy tailored to resonate with different consumer segments, whether that be eco-conscious shoppers, travel-loving millennials or new mothers, putting an emphasis on handbag qualities that appeal to each of these segments. From there, that same marketer could use generative AI to assist in creating different product photo backdrops for the handbag and A/B test these versions with different audiences. 

These are just a couple of the endless examples of how generative AI can help marketers refine new ideas, scale their personalization strategy and ultimately improve shopper engagement. 

5. Expedite new product development.
Retailers are constantly under pressure to innovate and evolve their products; however, sifting through research like consumer surveys and product test results can be tedious and time-consuming. By bringing generative AI into the R&D process, retailers can accelerate this process to find insights across multiple data sources, reduce costs and zero in on successful product concepts faster. They also can enhance internal consumer research with easy querying, summarization and insight generation. 

When a new technology moves as fast as generative AI is moving, it can be intimidating to keep up. We see definitive value in this next evolution, and my advice is to start to gradually apply some of these use cases, as it will set a foundation that you can continue to build upon.

Similar to those who delayed  innovation during the dawn of ecommerce, waiting to take action can create a snowball effect, making it difficult to catch up as the technology itself and shoppers’ preferences evolve in tandem. 

In the end, the breadth of capabilities offered by generative AI presents retailers the opportunity to not only do more business, but deliver new avenues for shoppers to engage with a retailer’s most important asset, their brand.

Amy Eschliman is Managing Director, Strategic Consumer Industries, Retail at Google Cloud, responsible for shaping our Americas Retail solution strategy. Eschliman has extensive experience in retail, focused primarily on ecommerce and customer engagement. Most recently, she was at Sephora where she served as the SVP of Client Engagement and previously as the SVP of Ecommerce. Prior to joining Sephora, Eschliman was the VP of ecommerce of Pottery Barn within Williams-Sonoma, Inc. and responsible for ecommerce and retention marketing.

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