These 5 GenAI Use Cases Prove it’s the Next Step for Modern E-Commerce
Leaders across practically every industry have spent the last two years laser-focused on generative artificial intelligence (GenAI). So laser-focused, in fact, that Gartner predicts the technology is sliding into the “Trough of Disillusionment,” where confidence starts to waver as the most talked-about GenAI products struggle to meet expectations.
There’s light at the other end of the tunnel, however. We’re starting to see which GenAI use cases are best positioned to survive the next few years. And in the retail industry, there are five that have the potential to usher in a new era of e-commerce. We’ll explain how in this piece as well as make the case for why GenAI fits naturally into the broader arc of modern e-commerce innovation.
Use Case No. 1: Intelligent Customer Support
Many retailers already use chatbots to handle basic customer support queries. However, customer satisfaction tends to be mixed, in part because these bots rely on canned responses that don’t feel tailored to customers’ specific needs.
With GenAI, you can make chatbot interactions far more helpful. The chatbot can connect to the rest of your tech stack to answer questions about an order status or help troubleshoot a product issue. Furthermore, it can use sentiment analysis to dynamically respond to customers based on emotional signals.
If a customer still wants to speak to a human agent, GenAI can also support on the back end. It can give the agent a summary of the support interaction thus far and offer guidance for complex troubleshooting.
Platforms like Zendesk have rapidly deployed GenAI in their customer support solutions, and for good reason. They’re helping retailers deliver faster and more satisfying service.
Use Case No. 2: Automated Content Generation
Your marketing and sales teams spend a lot of time writing content, whether it’s for product descriptions, blog posts, marketing campaigns, etc. All that time can quickly add up and take employees away from higher-value work.
GenAI can fast-track the content writing process. You can train a model on your style guide and existing content samples to produce new material that aligns with your brand’s voice. And most importantly, you can produce that content at scale.
This GenAI use case is so promising that many CRMs, like Salesforce, have already built out native capabilities. However, there are a growing number of highly specialized options to consider. No matter which tool your employees use, they’re bound to realize enormous time savings that can boost overall efficiency.
Use Case No. 3: Hyperpersonalization at Scale
GenAI doesn’t just expedite content generation; it also enables deep personalization. That’s a must-have for today’s customers. Our research shows that 59 percent are excited by the prospect of a data-driven, personalized shopping experience. And nearly 50 percent want to see custom discounts on frequently purchased items or product recommendations based on past purchases.
These expectations can be challenging to meet with traditional retail tech. But GenAI can use customer data to auto-generate personalized discounts, product suggestions and more. It can also produce different site copy for an endless number of personas.
There’s more, though. Today’s most innovative retailers are using GenAI to …
- Let customers design their own products. Lingerie brand Adore Me lets customers use an image generator to make custom lingerie designs so they can buy the exact set they want.
- Offer styling recommendations. It’s one thing to suggest which products to buy, but a GenAI chatbot can suggest how to wear the clothes in shoppers’ carts — just like a personal stylist.
- Let shoppers visualize products in their own home. Augmented reality has supported this capability for years, but shoppers could typically only view a single product design. With GenAI, users can visualize a sofa in their space and test out different colors and patterns for easier shopping than ever.
- Localize store layouts. Brands with a brick-and-mortar presence can use GenAI to analyze shopping patterns at individual stores. Then, they can generate thousands of possible layouts to present the right products to shoppers at the right time.
The overall benefit to customers? A more inviting shopping experience powered by hyperpersonalization at scale.
Use Case No. 4: Smarter Product Search
Some retail customers visit e-commerce sites with specific products in mind. However, many shoppers only have a general idea of what they want. You can probably picture a shopper who knows they want to put together an outfit for a wedding, but they might not know exactly what style suit is on trend or whether to buy derbies or loafers.
With GenAI-powered search, consumers can enter natural language queries and the AI will connect them to the best products for their needs.
The shopper above, for instance, might search for “trendy menswear for a wedding” and immediately receive accurate recommendations (e.g., a double-breasted suit jacket, straight-leg slacks, Italian loafers, and so on). They could even ask an AI chatbot questions like, “What tie material would look best with this specific suit?” and get helpful suggestions to guide their product discovery.
Earlier this year, Amazon.com zeroed in on this GenAI use case with its Rufus chatbot launch. We expect other retailers will soon follow suit.
Use Case No. 5: Dynamic Price Negotiation
Picture this scenario: a consumer is shopping an online sample sale but hesitates to click the checkout button — the prices are just too steep. After a few seconds, a GenAI chatbot pops up with an offer for 10 percent off and the option to negotiate a better deal. There’s a bit of back and forth. But after a few counteroffers, the customer gets a price they’re happy with and checks out moments later.
This tech may sound futuristic, but earlier this year ASOS partnered with Nibble to deploy an AI price negotiator just like the one we described (and during a sample sale, no less). Some customers were able to score discounts of up to 40 percent.
GenAI negotiators are useful for more than customer-facing applications, though. Walmart worked with Pactum to deploy a bot for supplier negotiations last year. The AI can interact with over 2,000 suppliers at once and has closed a deal 68 percent of the time, saving Walmart an average of 3 percent per contract.
Whether you’re interested in customer- or vendor-facing chatbots, you have the freedom to choose parameters that keep negotiations in check. For instance, you can set a maximum allowable discount or define your ideal supplier terms. This way, you can offer a satisfying negotiation experience and avoid high-risk outcomes.
For Forward-Thinking Retailers, GenAI is a Natural Evolution
Traditional AI isn’t new to retail; brands have used customer support chatbots, predictive analytics software, and other AI tools for years. However, GenAI opens a new realm of possibilities — and we’ve only seen the tip of the iceberg.
If your brand is on the front edge of e-commerce technology, a GenAI investment is a logical next step. The question is how to gauge the highest value use case for your business.
Our recommendation? Identify the specific business problems you want to solve or capabilities you need to improve your customer experience. Map them to potential GenAI solutions. Then decide whether you want to build a custom AI tool (perhaps with a coding agent) or integrate an off-the-shelf solution. With a well-defined strategy, you’ll be prepared to skip past the fluff and choose GenAI that benefits your customers, employees, and bottom line.
Marcelo Vessoni is senior vice president, digital and head of retail at CI&T, a global technology transformation specialist.
