A practical guide to Magento AI voice and conversational search

Let’s be honest, Magento’s native search function can feel a bit… dated. You’ve probably spent hours (and a fair bit of money) optimizing your store, only to watch customers give up because they can't find what they're looking for. A rigid search bar that demands perfect keywords is the digital equivalent of an unhelpful sales associate who just points vaguely and walks away. It’s frustrating, impersonal, and a fast track to an abandoned cart.

The next real leap forward for e-commerce isn’t about slightly better filters or flashier banners. It’s about making online shopping feel more human. This is where Magento AI Voice and Conversational Search comes into the picture. It’s about letting customers find what they need by simply asking for it, just like they would in a real conversation.

This guide will walk you through what this tech actually is, why old-school search extensions just can’t keep up, and a practical plan for bringing a truly conversational experience to your Magento store.

What is Magento AI Voice and Conversational Search?

This technology really comes down to two ideas that work together to make shopping smoother. It’s not just about turning spoken words into text; it’s about figuring out what someone actually means.

AI Voice Search is all about understanding intent. When a customer says, "find warm coats for skiing," a smart AI doesn’t just hunt for the words "warm" and "coat." It understands the context of "skiing" and knows to look for product attributes like "waterproof," "insulated," and "wind-resistant," even if the customer never used those specific terms. It translates natural, everyday language into a precise product search.

AI Conversational Search takes this a step further. It turns a single question into a helpful, back-and-forth dialogue. This is usually handled by an AI chatbot that doesn’t just return a list of results. Instead, it might ask clarifying questions like, "Are you looking for men's or women's sizes?" or "What's your budget for the coat?" It can offer personalized recommendations based on the chat and guide the shopper through their entire journey, from discovery to checkout.

When you put them together, you get a seamless experience where customers can just ask for what they want, however they want to ask for it.

The old way: The limits of traditional Magento search extensions

For years, Magento store owners have relied on search extensions to patch up the platform's native search. While many of these tools were an improvement, they were built for a different time and come with some serious limitations in today's world.

They're search tools, not conversation partners

Most Magento search extensions, like Klevu or Amasty Advanced Search, are very good at what they were built for: improving search results. They offer features like typo tolerance, synonym management, and advanced filtering, which definitely helps customers find products more easily than the default search bar.

But that’s where their skills end. They can't handle a real conversation. They process one query at a time and have no memory of what was asked a second ago. If a customer searches for "hiking boots" and then asks, "which of these are waterproof?," the extension treats it as a completely new, unrelated question. This makes the whole interaction feel robotic and forces the customer to start over with a long, specific search term.

Their knowledge is stuck in the product catalog

Here’s the biggest problem: these tools are almost exclusively trained on your Magento product data. Their entire world is made up of your product titles, descriptions, and attributes.

This means they’re completely useless for answering the important, non-product questions that often make or break a sale. A customer might love a leather jacket on your site but needs to know, "What is your return policy for international orders?" or "How do I care for this jacket so it lasts?" Since that information lives in your help center, a blog post, or a PDF, the search extension can't find it. The customer has to leave the product page and go digging for answers, which breaks their shopping flow and gives them a perfect excuse to get distracted and leave.

Setup and upkeep headaches: A barrier to implementation

Getting many of these advanced search tools up and running isn’t a simple plug-and-play process. It often requires a good chunk of developer time to get things working right. This can involve complex initial setups, configuring the extension to play nicely with technologies like Elasticsearch, and performing regular maintenance to keep it running smoothly.

This creates a high barrier to entry for businesses that don't have a dedicated tech team or a big budget for development. It’s a world away from modern AI platforms designed to be set up by anyone.

Feature	Traditional Extensions (e.g., Klevu, Doofinder)	Limitations for Conversational Commerce
Primary Function	Keyword-based site search & filtering	Lacks true conversational dialogue and context.
Knowledge Source	Magento product catalog	Cannot answer questions from help centers, docs, or FAQs.
Interaction Model	One-way query and response	Unable to ask clarifying questions or guide users.
Setup	Often requires developer configuration	Can be time-consuming and expensive to implement.

The modern approach: Unifying knowledge for a true conversational experience

To get past the limits of simple search, you need to think differently. The goal isn’t just to find a better search tool; it's to build an AI that has a complete understanding of your entire business.

It all starts with a unified knowledge base

A truly smart AI can't be stuck in a silo. It needs to learn from all of your company's knowledge, not just a product list. This is where a modern platform like eesel AI changes things entirely. Instead of only looking at your Magento catalog, it connects to your whole knowledge ecosystem, including:

• E-commerce Platforms: Your product data from Magento, Shopify, and more.

• Help Desks: Your conversation history from Zendesk, Freshdesk, or Gorgias. This lets the AI learn from how your team has already solved real customer issues.

• Documentation: Your internal knowledge from places like Confluence, Google Docs, and Notion.

• Help Center: Your entire collection of existing FAQ articles and guides.

By pulling all this information together, the AI becomes a single source of truth. It can give one-stop, accurate answers to any question a customer has, from their first product search all the way to post-purchase support.

This infographic illustrates how eesel AI centralizes knowledge from different sources to power support automation for Magento AI Voice and Conversational Search.

Go from a search bar to an intelligent AI agent

Once you have this unified knowledge base, you can deploy a true AI agent, not just a slightly better search tool. An AI Chatbot powered by this deep knowledge can handle the entire customer journey. It can help a customer find the right product, answer a tricky question about your shipping policy, and even look up their order status in real-time using API calls, a neat feature you can set up with eesel AI’s custom actions.

Go live in minutes, not months

Maybe the biggest difference is the setup. Forget the heavy, developer-led projects of the past. Modern platforms are built so you can do it yourself. With eesel AI, you can connect your helpdesk and knowledge sources with one-click integrations. You can have a working AI agent up and running in minutes, and it fits right into your existing workflow without forcing you to rip out and replace the tools you already rely on.

A 4-step plan for implementing Magento AI Voice and Conversational Search

Adopting a conversational approach doesn't have to be some massive, intimidating project. You can get there with a few smart, high-impact steps.

Step 1: Bring all your knowledge together

This is the foundation. Before you can have intelligent conversations, you need to build the "brain." Use a platform like eesel AI to connect all your separate knowledge sources, from your helpdesk tickets to your Google Docs. This creates the unified knowledge base that will power every single answer.

This flowchart outlines the quick, self-serve implementation of a modern AI CRM agent, from connecting data to going live, which is essential for Magento AI Voice and Conversational Search.

Step 2: Put a catalog-aware AI chatbot on your store

Next, add an AI chatbot to your Magento store. The key here is to make sure it's trained on both your new knowledge base and your product catalog. This is a big deal. It lets the chatbot handle both support questions ("Where do you ship to?") and sales-focused chats ("Do you have this in blue?") in the same conversation.

Step 3: Tweak your content for Magento AI Voice and Conversational Search queries

Voice search is naturally conversational, so your content should be too. To start pulling in this growing traffic, you should:

• Think about long-tail keywords: Structure your product descriptions, blog posts, and FAQs to answer full questions. Instead of just targeting "running shoes," optimize for phrases like, "What are the best running shoes for flat feet?"

• Use structured data (Schema): Properly marking up your product pages with schema helps voice assistants like Google Assistant and Siri easily read key details like price, stock availability, and reviews, which they can then pass along to the user.

• Speed things up: Voice search users expect answers right away. A slow-loading site will get ignored by both users and search algorithms.

Step 4: Test your Magento AI Voice and Conversational Search with confidence before you launch

You shouldn't have to launch a new tool and just cross your fingers. One of the best things about a modern AI platform is the ability to test everything in a safe, controlled environment.

For example, eesel AI's simulation mode lets you run your configured AI agent against thousands of your past customer support tickets in a sandbox. It shows you exactly how the AI would have responded, giving you an accurate preview of its performance and resolution rate. This lets you fine-tune its behavior and launch with confidence, knowing you’re delivering a great experience from day one.

A screenshot of the eesel AI simulation mode, showing predicted performance for Magento AI Voice and Conversational Search based on historical data.

Pricing comparison: Extensions vs. a unified platform

The cost of traditional search extensions can be tricky. For example, Doofinder’s pricing starts around $35 per month but climbs quickly based on the number of search requests. Klevu has a free tier, but its paid plans also scale with traffic and features. This model can lead to unpredictable bills, especially during busy sales periods like Black Friday.

Unified platforms usually offer a more straightforward model. eesel AI’s pricing, for instance, is based on a set number of monthly AI interactions. All products, the AI Agent, Copilot, and Chatbot, are included in one plan. This means your costs don't suddenly spike just because your store is doing well. It’s a flat, predictable fee you can actually budget for.

A visual of the eesel AI pricing page, showing clear, public-facing costs for Magento AI Voice and Conversational Search.

Stop searching, start conversing

The future of e-commerce on Magento isn't about endlessly tweaking an outdated search bar. It's about building real, helpful conversations with your customers at scale. A clunky, keyword-based search is a roadblock to sales, while a natural conversation is an invitation to connect.

This shift is well within your reach. By moving away from siloed search extensions and embracing a unified AI platform that understands your entire business, you can create a much better customer experience. This approach not only helps with conversions but also builds lasting loyalty and frees up your support team to focus on the conversations where a human touch is needed most.

Ready to see how a unified AI can transform your Magento store? Set up your first AI agent with eesel AI in minutes.