Going Live with Agentic Commerce? Here are 6 Things Every Enterprise AI Shopping Assistant Needs 

Conversational AI has already moved from experiment to expectation. But the difference between a shopping assistant that quietly disappoints and one that transforms performance comes down to what happens before launch, not after.  

The recent rollout of our AI Shopping Agent, built in collaboration with Google Cloud’s Gemini Enterprise Agent Platform, delivered an 8x higher conversion rate than site average, a 22% increase in average basket size, 5.5x higher first-time buyer conversions, and a 20.8% uplift in average order value. That didn’t come from simply switching on a chatbot, it came from a launch build on a specific set of foundations.  

If you’re an enterprise retailer or brand considering an AI shopping assistant, here’s the checklist worth talking through before go-live.  

1. Is it trained on your brand, not just your catalogue?  

A generic AI layer bolted onto your storefront will answer questions, but it won't sound like you, and it won't reason the way your best sales associates do. Before launch, your assistant needs deep training on your specific tone of voice, product logic, and brand nuances, so every interaction feels like a natural extension of your brand rather than a bolted-on tool. This is what separates a "digital expert" from a search bar with a chat interface.

2. Can it handle real-time, context-aware product discovery?  

Shoppers don't browse in straight lines. They ask follow-up questions, compare options, and change their minds mid-journey. Your assistant needs to deliver context-aware recommendations and conversational guidance in real time, not static, pre-scripted responses. Test it against the messy, non-linear questions real customers actually ask, not just the FAQ list.

3. Does it answer the questions that actually block purchases?  

Every retailer has a shortlist of recurring friction points: sizing uncertainty, ingredient or material questions, delivery timing, return policies. Before go-live, map these purchase barriers and confirm the assistant can respond instantly and accurately to FAQs and objections at scale. If it stumbles on the ten questions your support team hears every day, it isn't ready.

4. Is it built on an infrastructure that can scale and integrate?  

An assistant is only as good as the systems feeding it: your product catalogue, inventory, pricing, and customer data all need to sync cleanly. Before launch, confirm the assistant is properly integrated across your digital storefronts, not running as a disconnected bolt-on that goes stale the moment your catalogue updates.

5. Can you measure commercial impact, not just usage?  

Conversation volume and session counts are vanity metrics. What matters is whether the assistant moves the numbers that matter to the business: conversion rate, average order value, first-time buyer conversion, and returning customer behaviour. Before go-live, agree on the specific commercial KPIs you'll track, and make sure your analytics setup can isolate assistant-driven interactions from the rest of your funnel so you can prove (or disprove) impact quickly.

6. Does it generate insight your team can act on?  

Beyond direct sales impact, a well-built assistant surfaces what customers are actually asking, where they hesitate, and where product information is missing. That data should feed back into merchandising, content, and customer education strategies across every channel. If your assistant is a black box that answers questions and nothing more, you're leaving half its value on the table. Confirm before launch that conversation insights are captured and routed somewhere your team can use them.

The gap between an AI shopping assistant that generates headlines and one that generates revenue is preparation. Brand-specific training, real-time contextual reasoning, integrated infrastructure, and a clear measurement framework aren't nice-to-haves, they're the difference between a pilot that fizzles and results like Myprotein's, where returning buyers alone drove a 4.61% increase in conversion rate and a 9.6% AOV uplift.

If you're evaluating agentic commerce for your own storefront, work through this checklist with your team first. The technology is ready. The question is whether your launch plan is.