Cimulate Modernizes Online Shopping With Smarter AI Assistants

Conversational AI is playing a larger role in e-commerce, but many digital shopping assistants still fall short, plagued by clunky pop-ups, generic responses, and rigid keyword-based searches that often miss the mark.

Nearly half (48%) of AI chat tools fail to resolve customer issues or accurately understand their intent, according to recent research. For retailers, the real opportunity lies in AI that supports product discovery, not disconnected chatbots. More competent conversational shopping assistants can deliver personalized recommendations by understanding customer needs, product context, and brand voice in real time.

John Andrews, CEO of Cimulate, believes the key to fixing underperforming AI shopping assistants is moving beyond keyword reliance. His platform replaces rigid chatbot scripts and simplistic search logic with a more dynamic, intent-aware experience.

“We’ve been trained by Google for 25 years to use keywords. What we have enabled now is the ability to describe in more free form what shoppers are looking for,” he told the E-Commerce Times.

Whether it’s finding something for a bridal shower or an outdoor wedding where it might rain, consumers enter the concept and hit the Enter key. The AI-powered assistant returns contextual results, enabling a more natural, personalized interaction, free from rigid, scripted responses.

Instead of relying on keyword triggers, retailers can now process natural-language questions and respond with relevant, thoughtful answers, moving beyond the limitations of keyword-bound interactions.

Smarter AI Is Changing Online Shopping

Cimulate’s generative AI platform helps businesses enhance customer experiences while aligning with key business goals — the outcome: more relevant and profitable engagement with every click.

Cimulate’s technology lets website visitors ask questions freely, without having to guess the right keywords to begin a search.

For example, Andrews detailed how he could show a picture of a shirt and say, “I love this shirt, but I blew out the arm. Find me something that’s similar.” The assistant would then scan available sources and return options with context about how they’re similar or different.

“You don’t just have to say ‘flannel shirt’ and then sift through the list of items presented in response,” he added about how improved AI-powered shopping agents would work.

The Future Digital Shopping Mall

Imagine a future where consumers no longer scroll through multiple online stores. AI shopping agents will handle that work — searching, comparing, and curating options behind the scenes.

A consumer’s shopping agent might discuss purchasing requests directly with the stores’ AI catalog agents to find requested products, compare prices and product details, and deliver an updated results list to the shopper. The consumer would make a selection and authorize the shopping agent to handle the purchase.

Andrews suggested that in the near future, AI agents will be able to interpret any query and respond conversationally. More importantly, they’ll pass that understanding to a product catalog agent or retail search engine to complete the task.

Today’s retailers are already using the Cimulate platform to process e-commerce transactions via an API connected to a large language model (LLM)-based system.

“That is what our company provides to bring back the right products when a shopper visits our retail customer websites connected to our platform. You cannot do that with a keyword search system,” he said, acknowledging the explanation may sound futuristic.

“But honestly, we are not far off from that. I don’t believe you’ll be able to find a website in six to nine months that does not have something like this type of conversational AI-agent experience,” he predicted.

Andrews predicted that nearly all retail websites will have an early-adoption version of a shopping assistant that answers customers’ questions in a compelling way.

“We have no idea what user experience [UX] will look like. We believe it will be much more focused on integrating it into the full panel of the website. It’s not just going to be a pop-up box that lets you chat with an agent to ask ‘Where’s my order?’ or reset my password,” he offered.

Product Search Remains a Challenge

According to Andrews, conversational AI has become increasingly effective at understanding what customers want. The bigger challenge — still improving — is delivering accurate product search results.

“It’s not a rules-based engine like customer service chatbots. They are very much rules-based,” he explained about the primary differences in the driving technologies.

“The customer service chat agent is going to be encapsulated into the overall user experience,” he added.

He said the company is focused on equipping retailers with robust shopping assistants that make customers feel comfortable relying on a digital personal assistant during their shopping experience.

AI Shopping Tools Won’t Replace Stores

Andrews likens the rise of AI shopping assistants to the early days of Amazon, when many believed physical mall stores might become obsolete.

“People still like browsing websites, and they’re going to want a really compelling experience. They want to see what the trends are,” he said. “The AI agent is going to do all of that for you. But not everybody’s going to want that for every use case.”

Andrews emphasized that shopping agents aren’t meant to replace hands-on experiences. Online and in-store options should complement each other, not compete.

“People love to shop. They still want to go to the store and feel the merchandise,” he said.

How AI Fits Into the Retail Journey

Cimulate has spent the past two years developing its keywordless shopping search system. With 25 years of experience in retail tech, Andrews now sees a shift in how organizations respond to these innovations.

Previously, companies told him the approach was interesting but not part of their near-term roadmap.

“Nobody is saying that to us, now. Everybody’s trying to deal with this right now — it’s top of mind for everyone,” he shared.

Andrews noted that the market for AI-driven shopping agents is highly competitive, and Cimulate isn’t the only company pursuing a post-keyword search solution.

Still, Andrews believes Cimulate is ahead of the curve in addressing AI-related adoption challenges. One key distinction: the company doesn’t store shoppers’ personal data.

“We don’t want personal information delivered to us from retailers. We don’t store that PII information or use it to build our model,” he said.

The platform is designed to interpret customer intent as accurately as possible, but without storing personal details.

He recognized that concerns about personal data run deep, especially fears that PII could be embedded in AI models and later exposed.