Retail & E-commerce · AI Chatbot Development

Ecommerce Chatbot Development

A chatbot that finds the right product, checks a real order, and adds to cart, not a FAQ widget wearing a shopping cart icon.

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Clothing store interior with mannequins and blue-lit displays

Smiling woman at a wooden table looking at her phone

NDA before discovery

You own the code and IP on payment

Code in your repository from day one

A working demo every two weeks

Senior engineers do the work

How we work

A shopper typing "waterproof jacket under $100 for hiking in the rain" into a search box gets filtered results if the storefront's facets happen to cover rain rating and price at once. The same request typed into a chatbot should work regardless of how the catalog's filters are structured, matching against actual product attributes and current stock rather than keyword overlap with a product title. That's a different engineering problem than answering a support FAQ, and it's where a lot of ecommerce chatbots quietly fail: they can discuss policy but can't actually shop with the customer.

The rest of the value sits in connecting the conversation to systems that already exist rather than talking around them. A "where's my order" question needs to pull the real shipment status from the order management and shipping system, not a generic estimated delivery window. Adding a recommended item to the cart from inside the chat removes a step that otherwise loses the customer to a new tab. Sizing questions need answers grounded in that specific product's fit notes and size chart, not general advice that reads the same for a snug base layer and a relaxed-fit jacket.

We build ecommerce chatbots around live catalog and inventory search, real order status lookups, in-chat add-to-cart, and a clear handoff to a human agent for anything involving a dispute, a defect, or an exception to standard return policy.

Requirements

What retail & e-commerce teams need from it

Conversational product discovery grounded in the live catalog
A shopper describing what they want in plain language needs matches against real product attributes and current stock, not a keyword search that only works when the phrasing happens to match a product title or an existing filter.
Order status lookups tied to the real shipping system
A question about a specific order needs to pull that order's actual status from the order management and carrier tracking system, since a generic estimated delivery window erodes trust the moment it doesn't match what the customer sees on the carrier's own tracking page.
In-chat add-to-cart and checkout handoff
Recommending a product without a way to add it to the cart from inside the conversation loses the customer to a new tab and, often, the purchase entirely, so the chatbot needs a direct path from suggestion to cart.
Sizing guidance grounded in product-specific data
Fit advice that reads the same for a snug base layer and a relaxed-fit jacket isn't useful, so sizing responses need to draw from that specific product's size chart and fit notes rather than generic apparel guidance.
A clear boundary around returns, disputes, and defects
A chatbot that improvises on a damaged-item claim or a policy exception creates the kind of customer-facing error that ends up as a complaint, so those conversations need to route to a human agent with context attached rather than a generated answer.

Scope

Features we build

Conversational product discovery
Natural-language requests match against real product attributes, price, and current stock in the live catalog, surfacing relevant items even when the phrasing doesn't match a filter or a product title.
Real-time order status and tracking
Order questions pull live status from the order management and carrier tracking system, giving an accurate answer instead of a generic delivery estimate.
In-chat add-to-cart
A recommended product can be added directly to the customer's cart from within the conversation, removing the step of leaving chat to search for it again on the site.
Product-specific sizing and fit guidance
Sizing questions answer from that product's own size chart and fit notes, distinguishing a relaxed cut from a snug one rather than giving generic apparel advice.
Abandoned cart follow-up conversation
A customer who leaves items in their cart can be re-engaged through a conversational follow-up that answers hesitation points, like a sizing question or a shipping cost concern, rather than a generic discount email.
Return and exchange initiation
Standard returns and exchanges start directly through the chat, pulling the relevant order and generating a return label, while anything outside policy routes to a human agent.
Multi-language storefront support
The same product knowledge and order lookup capability serves customers in multiple languages without maintaining a separate bot per storefront locale.
Escalation to human support for disputes
Damaged-item claims, policy exceptions, and anything the bot isn't confident about hand off to a human agent with the full conversation and order context attached.

Compliance and standards

PCI DSS (no card data captured in chat)
CCPA/CPRA
GDPR

Systems it connects to

Shopify
Gorgias
Zendesk
Twilio
Klaviyo
Google Merchant Center

Build vs buy

When to build it and when to buy it

Gorgias and Shopify Inbox cover FAQ deflection and basic order-status lookups well for a storefront that mainly needs support automation, and their tight native integration with Shopify makes them the faster path when the catalog and support needs are fairly standard.

Custom development earns its cost when conversational product discovery needs to reason over a large or highly attributed catalog those tools search only shallowly, when the chatbot needs to tie into a proprietary recommendation engine or loyalty system, or when in-chat checkout needs a level of cart integration those support-focused platforms weren't built to provide.

Technology

Typical stack

FAQ

Frequently asked questions

Can a chatbot help customers find products using natural language instead of filters?

Yes, a request like a waterproof jacket under a certain price matches against real product attributes and current stock in the catalog, rather than requiring the phrasing to line up with an existing filter or a product title, which lets the bot surface relevant items a keyword search would miss.

Can customers check their order status through the chatbot?

Yes, order questions pull live status directly from the order management and carrier tracking system, so the answer matches what the customer would see on the carrier's own tracking page rather than a generic estimated delivery window.

Can customers add an item to their cart directly from a chat conversation?

Yes, a recommended product can be added to the cart from inside the conversation itself, which keeps the customer in the flow rather than sending them to search for the same item again on the site.

Does the chatbot give sizing or fit advice for specific products?

It can, when sizing responses are grounded in that specific product's size chart and fit notes rather than generic apparel guidance, since a relaxed-fit jacket and a snug base layer need different advice even at the same labeled size.

Can the chatbot follow up on an abandoned cart?

Yes, a customer who leaves items in their cart can be re-engaged through a conversation that addresses likely hesitation points, such as a sizing question or a shipping cost concern, rather than a generic discount email sent to everyone regardless of why they left.

Should we use Gorgias or build a custom ecommerce chatbot?

Gorgias and Shopify Inbox are strong choices for FAQ deflection and basic order-status support on a fairly standard storefront. Build custom when product discovery needs to reason over a large or highly attributed catalog, or when the chatbot needs to connect to a proprietary recommendation or loyalty system.