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Generative AI chatbots that respond to natural language questions with cogent sentences have the potential to help retailers grow faster.
If chatbot responses are consistently accurate and effective, customers will happily use them at all hours of the day. If the chatbots too frequently hallucinate — confidently reply to user questions with incorrect answers — customers could stop doing business with the retailer.
The power and peril of generative AI for customer service
Consider the experience of Rick McConnell, CEO of Dynatrace, a Massachusetts-based software company. Dynatrace is optimistic about the use of generative AI-powered chatbots to improve customer service. “A couple of preliminary killer apps will emerge for generative AI. Based on my recent experiences, one of them will be customer service,” McConnell told me in a February 2024 interview.
“One went very well: I was trying to fix a billing issue with a cellular provider and the chatbot solved the problem fast,” he noted. “The second one went so badly that I will never do business with the company again. I was trying to correlate the contact lenses I received with the prescription. The contact lens provider’s chatbot couldn’t get me a solution. After three different segments, I never got it resolved.”
McConnell sees two keys for companies seeking to deploy generative AI for customer service. “First, they should train their large language models with high-quality data that includes relevant questions and great answers,” he says. “Second, the underlying data source for answering customer questions is essential to the process. The LLM must be accessing accurate and up-to-date data about each customer — that companies do not want to share with ChatGPT,” he said.
Retailers should invest in the highest payoff applications of generative AI. Rather than focusing on helping employees overcome creator’s block or boosting the productivity of coding or other business functions, retailers should use AI chatbots to drive revenue growth, according to my Value Pyramid concept.
Bearing McConnell’s caveats in mind, here are three ways retailers are using generative AI to drive revenue growth.
1. Personalized shopping experiences
Generative AI can use a customer’s prior purchasing behavior to suggest new purchases likely to appeal to each individual. Amazon uses a customer’s entire interaction with the e-tailer — from browsing to buying and paying — to refine recommendations to match each customer’s unique preferences, according to Closeloop.
Amazon is not the only retailer using generative AI to personalize shopping experiences, Carrefour’s Hopla chatbot uses a consumer’s budgets, dietary preferences, and menu ideas to offer real-time grocery suggestions and makes shopping more engaging, according to Oracle.
2. AI-enhanced virtual reality experiences
When people shop for furniture, they worry whether what looks good in the store or online will work when it arrives at their home. By pairing virtual reality and generative AI, furniture retailers are boosting confidence and achieving higher conversion rates for online shoppers. For example, Ikea lets customers see how furniture and décor will look in their homes, noted Closeloop.
Wayfair, the Boston-based online furniture retailer, introduced Decorify, a free generative AI tool to help customers redesign their living rooms. Customers upload a photo of their living rooms and Decorify creates “photorealistic images” of proposed designs and prompts consumers with real products similar to the ones in the photo, said Fiona Tan, Wayfair’s chief technology officer, according to Brain Rush: How to Invest and Compete in the Real World of Generative AI.
3. Dynamic Pricing and Promotions
Generative AI can help retailers boost revenue by setting the right price at the right moment. By analyzing “demand fluctuations, competitor activity, customer preferences, and historical sales trends,” according to Closeloop, retailers can boost revenue by quickly adjusting prices and promotions.
For example, Macy’s — which projects AI will drive over $7.5 billion in new business by 2029 — adjusts prices across its online and physical stores. The retail giant uses generative AI to increase or decrease prices dynamically based on how certain items are sold and offers “targeted discounts to customers based on their past shopping habits and preferences,” Closeloop noted.
If these three uses of generative AI help retailers exceed investors’ revenue growth expectations, other retailers will try to replicate these AI applications.
Turning customers into advocates
I recently attended the Mystery Shopping Professionals Association annual meeting last week. Once of the speakers was a repeat from last year, which I think is the first time we’ve had a repeat speaker. He returned mainly to share the advances AI has made in just one year. It was mind blowing seeing the progress in quality within 12 months.
One very important point that was shared is the importance of connecting with your customers. AI can predict customer needs, based on shopping pattern, but AI can not build a relationship, the kind of relationship where customers become your advocate by sharing their personal experience with others.
Need help in making your customer advocates, we’re here to help. Reach out, lets chat.
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PETER COHAN AND CARL PHILLIPS