ChatGPT represents a new generation of advanced AI technology.
A new artificial intelligence (AI) platform holds the potential to transform retail.
By now, you have most likely heard of ChatGPT, a new AI model from research and deployment company Open AI. Using 570 GB of publicly available data on the Internet, ChatGPT interacts with users in a conversational style that mimics human interaction and uses machine learning (ML) to continually refine and improve its responses.
And other companies, including retailers, are already launching efforts to develop their own AI engines with ChatGPT functionality. These include Chinese e-commerce giant JD, as well as Microsoft and Google.
ChatGPT is clearly coming to retail, sooner rather than later. Here are three key enterprise areas the technology is likely to have a significant impact.
Customer service/help desk
The most obvious retail application for ChatGPT technology is customer service, especially the help desk function. AI-based chatbots are nothing new in the retail help desk space. Retailers have been using them for years to automatically handle lower-level inquiries and filter higher-level requests for human intervention.
However, many consumers are not sold on the chatbot model of customer service. According to data from a recent Ipsos poll, 77% of respondents who have used a customer service chatbot prefer interacting with a human for customer service needs. In addition, 77% of these respondents report that customer service chatbots are frustrating.
ChatGPT holds the promise to enable next-generation chatbots that can truly mimic human understanding and interaction during a customer help desk session, resulting in more satisfying resolutions and fewer follow-up inquiries.
Chatbots using ChatGPT technology will also be able to handle much higher-level customer service requests, giving human agents more time to focus on truly complex issues that are beyond the scope of AI (at least for now).
The conversational nature of ChatGPT also makes it an ideal marketing and promotional tool. A ChatGPT-based marketing solution could generate much of a retailer’s more broadly targeted promotional content, with the input of some basic information and proofreading by a human.
In addition, a ChatGPT-enabled promotional engine could streamline the process of segmenting promotional messages and offers by specific customer demographic. Marketers could feed granular customer data into the solution to receive detailed suggestions on the structure and wording for promotions aimed at different consumer segments.
Furthermore, ChatGPT analysis could assist marketers in maximizing the effectiveness of cross-sell and upsell prompts, as well as aid the development of longer-form “storytelling” efforts.
ChatGPT functionality holds tremendous promise as an enabler of HR/workforce management activities. Many retailers screen job applications with AI-based solutions; leveraging ChatGPT they could also automate virtual interviewing and onboarding tasks.
In addition, ChatGPT offers the potential for retailers to offer highly personalized training at scale. Retailers are already streamlining training efforts with tools such as mobile apps and video. ChatGPT could allow employees to ask specific, individual questions in response to virtual training sessions that could be instantly answered via AI or screened and forwarded to a human for rapid response.
In the store, associates with ChatGPT apps could obtain instant support to ensure they are properly answering customer questions and providing correct information on topics such as product specifications.
Racing with the machines
Although the emergence of ChatGPT brings up familiar warnings that AI will replace humans in the workplace, it is worth noting that in many instances, retailers will be using ChatGPT technology to complement, rather than replace, human employees.
This strategy, which has enabled teams comprised of human chess players working with computers to beat both human and computer opponents working alone, has been dubbed “racing with the machine” by MIT professor Erik Brynjolfsson.