How Brands Can Leverage Generative AI to Deliver a Better Customer Experience, Boosting Visibility and Revenues as a Result

By Tristan Barnum, CMO. Wildfire Systems

You've likely heard a lot about generative AI in the past year and a half, with the launches of OpenAI's ChatGPT, Microsoft's Bing Copilot, Google's Gemini, and Anthropic's Claude dominating the tech news cycle. But these are just the vanguard of what's to come - a generative AI revolution that is expected to transform how businesses connect with customers.

The next phase of generative AI development will be more “verticalized” applications, tailored to specific industries and particular use cases. For retail brands and marketers, this means a new wave of tools, such as shopping assistants, product advisors, content creators, and more - all powered by generative AI.

These emerging generative AI retail solutions can dramatically enhance the customer experience. In fact, according to a recent Adobe study, 41% of consumers already expect brands to use AI in their customer experiences today - and 59% of the marketers included in that survey report they’re already using generative AI to deploy personalized customer experiences.

Using generative AI, retailers can leverage the treasure trove of first-party user data they have on hand. Sources that provide rich sources of consumer behavioral data include purchase history, returns (and potentially, reasons for returns), site and product browsing history, responses to emails, customer service chat histories, and much more. Each data point enables brands to connect the dots for each customer at scale –delivering more personalized experiences across the entire path to purchase.

Before the customer even gets to the retailer’s website, generative AI has the potential to transform digital marketing strategies. It can analyze vast amounts of existing retailer data to identify trends and predict consumer behavior, enabling brands to craft more effective ads, with content, placement, and timing customized to the most appropriate user segments. Plus, it can optimize digital campaigns on the fly, by synthesizing the data and results as they come in and modifying multiple aspects of a campaign to continually improve.

Generative AI-powered shopping assistants can act as knowledgeable, trustworthy, and on-demand advisors to help customers discover new products, research options, and answer questions based on their unique needs and preferences. Rather than static search functionality or basic filters, AI assistants will be able to leverage retailers’ existing user data and engage in true dialog to understand exactly what each shopper wants more quickly. With this knowledge layered on top of the AI’s understanding of a merchant’s product catalog, better, more well-targeted products can be quickly suggested to the shopper as a result.

This knowledge can also be applied into personalizing future email content. Products that are relevant and most likely to appeal to individual consumers, can be included to every unique email recipient, resulting in more productive emails. And taking it a step further, retailers’ websites themselves can also be personalized similarly.

Once a generative AI shopping assistant truly gets a given shopper's tastes and requirements, it can curate highly personalized content and recommendations that provide inspiration and education. Whether it’s makeup, clothing, cookware, or jewelry, brands can move beyond generic buying guides to foster much deeper engagement with personally tailored product recommendations and content at the individual level.

Retailers can also consider taking these product recommendations to the next level, and, in the case of clothing, makeup, accessories, shoes, and other wearables, encourage customers to virtually try them on. In the Adobe survey, shoppers seem open to this with 70% of respondents reporting they believe that using generative AI to produce images of them wearing a product could boost their confidence to make a purchase.

Post-purchase, generative AI customer support chatbots can deliver premium customer support, providing helpful advice on product usage, assembly, care instructions, and troubleshooting. This lowers customer service costs while driving satisfaction and retention. Many retailers may be hesitant to fully automate their customer support; however, 65% of consumers in the Adobe study believe that generative AI can help improve their experiences with faster and better customer service. For the more hesitant brands, generative AI chatbots can be deployed to augment and empower the human customer service reps with faster response times and more satisfactory customer problem resolutions.

While leveraging generative AI to improve customer experiences and drive better results, brands must be cautious with their approach. For one, AI models must be properly trained on the right data with careful human oversight and controls in place. Brands will need robust data strategies, potentially including customer data, product data, existing content, and more to ensure their generative AI marketing applications deliver accurate and on-brand experiences. The National Retail Federation’s suggested guidelines for the appropriate use of AI in the retail industry, “Principles for the Use of Artificial Intelligence in the Retail Sector,” can be helpful to the development of safe and ethical generative AI best practices.