Retailers know the stakes: Shoppers expect the warmth and guidance of in-store service, even when they’re browsing on the couch at 10pm. For Australian retailers, Preezie’s AI Shopping Assistant offers a practical, revenue-focused way to bring that experience to life online with the ease and judgment of a great sales associate.

Turning your website into your best salesperson

Preezie CEO and co-founder Michael Tutek described the opportunity simply: “For us, it’s about putting the best sales assistant in the store online. The best in-store experience is never just about answering questions. It’s about guiding discovery, giving relevant advice, building confidence and helping the customer feel understood before they buy, and sometimes after.”  

Most retailers already have the basics in place – search, filters, FAQs and live chat – but those tools rarely feel like a conversation with your best person on the floor. Preezie’s platform is designed to close that gap, giving retailers a way to turn existing product and policy data into a cohesive, confidence-building digital experience.

From chatbots to true AI selling

If your current chatbot is essentially a decision tree, Preezie is playing a different game. A traditional bot answers predefined questions; an AI shopping assistant understands intent, reasons through context and takes the next logical action.  

Tutek explained the difference with a simple example: If a customer said, “Last year I bought the Cayman dress – show me matching shoes,” most basic bots will struggle because that request leans on memory, product relationships and judgment. Preezie’s system identifies the original item, recognizes that color may matter, asks a sensible follow-up if needed, and then surfaces relevant matching options. That’s the difference between answering a question and actually helping someone shop.

What this looks like on your product pages

On a typical product page, Preezie’s AI steps into the role of a trained sales associate, but in a way that’s fully digital and always on. Shoppers can:  

• Search using natural language, for example, “Find me waterproof jackets good for hiking in a size XXL under $500.”  
• Compare products directly: “What’s the difference between the first TV and the second TV?”  
• Recover from out-of-stock moments by finding similar products, such as alternative running shoes in the same size.  
• Build bundles around a hero product, from “find me matching bags, shoes and accessories with this dress” to “find wall brackets that will work with this TV.”  
• Ask detailed product questions like “I’m 5 feet 8 and normally a size 12, what size do you recommend and where will the dress finish on my legs?”  

The same assistant can answer shipping and returns questions, add items straight to cart and filter spam or off-topic requests – all within a single, brand-controlled experience.

Shopper-led AI that moves the numbers

For Australian retailers, the commercial story matters as much as the technology. Preezie’s approach is built around what Tutek calls “shopper-led AI” – letting the customer drive the conversation rather than forcing them down a scripted path.  

“They can ask for a cheaper alternative, raise a concern, request more options, check fit, compare products or move straight to purchase – all within the same experience,” he said. In A/B tests, Preezie typically sees 5 per cent to 10 per cent incremental revenue. Shoppers who use the AI convert five to six times higher than those who don’t, and about twice as high as traditional search users. For retailers, that’s a clear signal that guidance, context and confidence translate directly into commercial uplift.

Reducing sizing friction with retailer-specific data

Fit and sizing remain one of the biggest barriers to online conversion and a major driver of returns. Preezie attacks this with retailer-specific intelligence rather than generic answers. The platform ingests and structures size charts, product information and brand-specific fit rules, and combines them with shipping, returns and policy content.  

The assistant can then recommend a size, explain how a product is likely to fit, convert between UK, US and EU sizing, and answer the practical questions that decide whether a shopper buys or hesitates. “The point isn’t to give a generic answer quickly,” Tutek said. “It’s to give an informed answer that reflects how that retailer actually sells, which is what helps reduce friction – and ideally reduce unnecessary returns.”

Controlled AI that protects your brand

Many retailers are rightly cautious about AI going off-brand. Preezie’s answer is what it calls controlled AI shopping experiences – purpose-built for e-commerce and designed to understand complex product catalogs, functions, variants and more. The system is grounded in retailer-approved information, with tone of voice defined upfront and the experience broken into roughly 100 instructions and decision points.

That structure makes it much harder for the assistant to drift off-topic, and much easier for teams to fine-tune specific behaviors without rewriting the entire system. “In commerce, AI only works if it’s controlled,” Tutek noted. It’s one of the reasons brands like Puma, JB Hi-Fi and Arc’teryx have partnered with Preezie – they want the upside of AI without sacrificing brand control.

Fast, focused implementation for busy retail teams

One of the barriers to adopting advanced AI is the perceived implementation load. Here, Preezie has engineered for speed. Arc’teryx AU/NZ went live in just seven days, and most retailers can expect roughly eight to 20 hours of internal work. About 80 per cent of onboarding is automated via Preezie’s AI Onboarding Assistant, which takes a retailer’s product data and website URL and builds the initial experience in around 30 minutes.  

From there, Preezie’s team runs approximately 500 tests, hands the experience to the retailer for validation, refines it based on feedback and then goes live. The result is a fast but controlled deployment designed to fit within the reality of lean e-commerce and digital teams.

What’s next for agentic commerce in Australia?

Looking 12 to 24 months ahead, Tutek expects agentic commerce to become a natural layer across retail sites rather than a standalone feature. “It will be embedded more intelligently into search, product pages, cart and post-purchase, so the customer simply feels that the experience is more helpful,” he said.

For mid-market retailers, that will often mean full front-end solutions from providers like Preezie. Larger enterprises are more likely to plug into Preezie’s MCPs, APIs and agentic infrastructure behind their own front ends – making Preezie “the brain rather than the body.”  

For Australian retailers, the takeaway is clear: Now is the time to get product and policy data in order, identify the highest-friction moments in the customer journey and start testing controlled AI where it can drive measurable commercial value. As Tutek put it, “The question won’t be whether AI belongs in commerce. It’ll be how well it’s integrated.”

• Want your website to perform like your best store team member? Learn more about Preezie’s AI Shopping Assistant and how it can plug into your existing stack here.