The generative AI microchannel: Approximately 63 percent of U.S. consumers begin their product search on Amazon, while only 3 percent start their search on a website—like a retailer-owned website—instead of on social media or search engines. How can retailers gain more customer headspace at the discovery stage of the customer journey?

Ravuri predicts that generative AI plug-ins being implemented into platforms like ChatGPT, Google Bard, Amazon or Apple could take shoppers all the way to checkout through a live link within the chat interface.

For example, Klarna’s ChatGPT plug-in already allows shoppers to search for products across thousands of stores through natural language and creates live links to products that meet the customers’ search requests.

Apparel and big box store retailers have a natural opportunity for these plug-ins, as many are already expanding into owned ChatGPT-powered shopping assistants, like Mercari’s Merchat AI and Zalando’s own fashion assistant. As larger tech companies expand their ChatGPT-style product search offerings, retailers can follow along and meet customers where they are at the ground level of their search.

Conversational shopping assistants: The dream of fully conversational commerce is still far from a practical reality, but in 2024, it’s time for grocers to begin experimenting with conversational shopping plug-ins on their own e-commerce websites.

Grocery retailers have a unique opportunity with conversational shopping assistants, as customers are open to new brands, products and ingredients that fit into their diet, budget and lifestyle—and this channel can also become a key part of retail media networks.

For example, Instacart’s search feature “Ask Instacart” allows shoppers to get personalized shopping recommendations through natural language questions, like “What’s a good, easy, healthy dinner recipe?” CPG brands can then partner with retailers to sponsor products that fit customers’ needs within this chat-like style of search.

Grocers can experiment with generative AI bots that would allow shoppers to create grocery lists based on their budget, dietary preferences, history and tastes through a quick conversation. As inflation continues to impact shopping decisions, especially in the U.K., shopping assistants that can empower shoppers to save money and time will stand out.

Virtual selling knowledge assistant: A majority of B2B buyers—86 percent, to be exact—expect companies to be well-informed about their personal information during sales interactions, according to a Gartner survey, yet a lack of intelligent, connected sales support tools leaves B2B retail employees struggling to meet this expectation.

Generative AI can help employees more quickly access internal sales knowledge and respond to common customer questions with the most effective language.

For example, Publicis Sapient experts are testing a prototype for a “colleague AI bot” that can answer questions that a new or even experienced sales hire would have. For example, a salesperson could ask, “I was told to check the warehouse NCR for issues, what does that mean?" Or “Can you draft an email to [insert customer name] asking if they would like to upgrade to the new product model for their next purchase?”

This virtual selling knowledge assistant would be helpful across sectors but particularly for B2B clients that aren't homogenous, often require bespoke solutions and are dealing with complex transactions that use industry jargon.

Dynamic Pricing Optimization: For convenience store (c-store) retailers, the conversational power of generative AI may prove its value later in the future than in 2024. However, other types of artificial intelligence, like dynamic pricing algorithms, can help c-store retailers improve margins right now.

While dynamic pricing has been in the c-store conversation for many years now, 2024 is a crucial year for action. Unlike other retail sectors, customers are extremely price sensitive and have been even more so during periods of higher inflation this year.

Because c-store customers are highly sensitive to price changes, it’s important for c-stores to implement machine learning when it comes to dynamic pricing, in order to keep trust and avoid alienating loyal customers with price changes that are too frequent, or too drastic.

Electronic shelf labels that are used to implement dynamic pricing can also help reduce waste—automatically discounting products that are close to hitting their expiration date.

There are a variety of valuable use cases for generative AI within the customer shopping experience—but retailers need to create a customer data foundation to make sure that AI pilot projects are part of the 54 percent (by Gartner) that actually move into production.