Is there anything that Generative AI (GenAI) cannot do? Data synthesis, semantic image-to-text translations, code generation, course design—everything seems just another day in the office for GenAI. But its transformative power is visible in the most obvious, immediate, and significant manner in everyday shopping.
Leading the way is Amazon’s Rufus, a shopping assistant that uses text and natural language to chatter non-stop, answer questions, dole out tips, freely offer insights on the latest products, helpfully compare products, dig into earlier orders, and track packages. Trained on Amazon’s repository of customer interactions, catalogs, and sales data, Rufus uses GenAI to understand customer intent and context to provide intelligent human-like responses. Rufus is an indication of how GenAI will be the most powerful, not-so-secret weapon of the retail industry, ushering in a new era of customer satisfaction.
Everyone in retail—fashion brand H&M, luxury brand Burberry, food chain Whole Foods, online e-commerce platform Etsy, Brazil’s retail giant Magazine Luiza, and discount chains Target and Lidl—is quickly adopting GenAI. The potential of GenAI to significantly improve customer experience is too big to miss.
According to McKinsey, GenAI presents a $400 billion to $600 billion a year opportunity in the retail and CPG segments. An NVIDIA survey shows that almost 50 percent of retailers in the study believe that GenAI will be a differentiator, revolutionizing customer experience, marketing, and content generation. As many as 60 percent plan to increase their AI infrastructure investments in the next 18 months, with 80 percent having deployed three or more of the use cases and over 50 percent saying they have six or more use cases in production.
For retailers, conversational virtual agents like Rufus can be a game-changer. They have the potential to significantly improve conversions, build customer loyalty, and reduce the cost of customer engagement and support. Analyst studies show that the conversational AI market, valued at $9.9 billion in 2023, is expected to grow at a CAGR of over 21.5 percent between 2024 and 2032, reaching $57.2 billion by 2032. The retail and e-commerce segment is a major player in this market, accounting for 22 percent of all conversational AI applications.
Even in 2016, when 1-800-Flowers introduced Gwyn, the retail industry’s first well-recognized AI-powered chatbot, it was a sensation. Gwyn contributed almost $10 million in revenue growth for the company in 2017. As the flower shop grew into a multi-brand gift-shop retailer—requiring shoppers to navigate thousands of products scattered over bewildering brands and categories—Gwyn took on the role of a gift concierge, making the customer journey simpler.
In May 2023, no surprise, 1-800-Flowers adopted ChatGPT, ahead of Mother’s Day, with a feature called MomVerse that created personalized poems and songs to go with gifts for recipients—going beyond what any shopping assistant, human or otherwise, could do. In one stroke, 1-800-Flowers was using a GenAI-driven virtual agent to respond to customer needs while creating unique, on-the-fly customized content. From simplifying the customer journey with Gwyn, 1-800-Flowers went on to being outrageously delightful with MomVerse.
There are subtle differences between the traditional chatbots we know and the intelligent, GenAI-powered virtual agents now becoming available. Traditional chatbots are rules-based, cannot learn from new interactions, and cannot manage complex or contextual interactions. GenAI-powered virtual agents can manage complex questions, detect and analyze sentiment, shape conversations based on customer intent, and continuously improve using ML.
There are several reasons to invest in GenAI-powered conversational virtual agents—they support sales efforts, reduce response time, and deliver better customer experience. But three reasons go beyond these:
24/7 intelligent customer support becomes possible. ‘Intelligent’ is the key here. Customers are reaching out across all hours of the day, wanting to speak to intelligent support executives. It is impossible to deploy teams around the clock, speaking a variety of languages, to hold meaningful, consistent, contextual, personalized, and outcome-oriented conversations with customers. GenAI bots can do this at scale, using their self-learning capabilities to improve with every iteration.
Improved data collection is another key advantage of conversational AI. Data is the heart of retail strategy, operations, and sales. It provides insights to ensure retail executives and customers make informed, data-based decisions. Conversational AI has the potential to build data beyond identity, purchases made, date and time of purchase, volume, and frequency of purchase, payment method, and so on.
It offers the chance to understand customer sentiment and intent—two aspects of retail that can make or break a business. This is because humans are more comfortable talking—instead of filling forms—and usually provide much richer information in conversations.
Conversational AI is ideal in such situations because it can bring a depth of listening that few humans can. Listening is the key to moving conversations toward inquiry, insight, and advocacy. Human support teams do not have the time or the skills to develop rich conversations. Their interactions are optimized for time, which limits their opportunity to acquire data that lives outside checklists, surveys, and drop-downs.
Brand enrichment is an unquantifiable benefit of GenAI-powered conversational virtual agents. These agents are leading the charge for genuinely interactive experiences. Adopting conversational AI in retail environments gives brands a unique differentiator. By leveraging advanced, cutting-edge technology, retail brands can show they are ahead of the competition, attracting more customers (and employees). When GenAI platforms become widely available, retail domain expertise and GenAI experience/implementation will become the differentiators.
Conclusion
Retailers can continue to deploy traditional rules-based chatbots that rely on limited datasets in environments that are not complex and where human interaction is minimal. In all other environments, GenAI-powered conversational virtual agents are the future. In a few years from now, perhaps as little as a year, traditional chatbots will look a shade retrofuturistic—cool, but steampunk. The march into the future for retail will be with knowledgeable, multimodal, adaptable, curious, and empathetic GenAI-powered conversational virtual agents.
