How to Set Up ChatLab for Your E‑Commerce Store

How to Set Up ChatLab for Your E‑Commerce Store

• How to Set Up ChatLab for Your E‑Commerce Store
• What Is Important in a Chatbot for E‑Commerce
• How to Provide Product Information to ChatLab
• Scanning vs Integration: Which Is Better?
• The Winning Formula: Combine Scan & Integration
• How to Properly Scan Your E‑Commerce Website
• Additional features worth enabling
• Language setup
• Monitor & Iterate Daily
• Optimizing Chatbot Responses

In the competitive e‑commerce environment, properly configuring ChatLab is key to ensuring your chatbot delivers precise product information and real‑time order updates. With the right setup, ChatLab can answer detailed product queries, fetch order statuses, and assist customers around the clock. This guide walks you through the steps of training, integrating, and optimizing ChatLab so it becomes an indispensable tool for product support and order management.

What Is Important in a Chatbot for E‑Commerce

• Accurate product information – ensure customers receive correct details about specifications and offers.
• Clear presentation of offers – highlight discounts, bundles, and promotions effectively.
• Up‑to‑date data – provide real‑time pricing, stock levels, and order status (with integration enabled).
• Order tracking & user data – allow customers to check order details, shipping status, and personalized recommendations when integrated.

Picture ChatLab as your always‑ready storefront assistant, combining precision, clarity, and live insights to instill confidence and drive sales.

How to Provide Product Information to ChatLab

Before teaching ChatLab about your store, decide how it will ingest product data:

• Website Scan: ChatLab crawls and indexes your product pages—descriptions, specifications, and images—into a static knowledge base. Ideal for rich context and detailed answers when your catalogue is relatively stable. Read more here:
Adding new website sources

• API Integration: Connect via Shopify, WooCommerce, or other platform APIs to fetch live product data, pricing, stock levels, and handle order lookups in real time. Best for frequently changing inventories and order management. Note: Products aren’t imported into ChatLab’s static knowledge base; instead, ChatLab dynamically queries your e‑commerce platform to fetch real‑time product details in response to user questions. Read more here (for Shopify):
Integration with Shopify

Or check out documentation specific for your e-commerce platform

• Combine Both: Use a scan for deep contextual knowledge and keep integration active for up‑to‑date accuracy.

Scanning vs Integration: Which Is Better?

Website Scan

• Pros:
• Full context AI research, rich answers
• Cons:
• Requires manual or auto retraining to capture new or updated products (Auto-retraining limits: Standard Plan: once/week, Premium Plan: once/day)
• May hit training-character quota when indexing large catalogs - requires scanning optimization, more below.
• Potential misinterpretation of detailed specs – may miss real-time availability
• Incomplete structured data parsing – may fail to extract information from tables or parameter lists

API Integration

• Pros:
• Always up-to-date prices & stock via direct API calls
• Real-time order look-ups for tracking status and history
• Cons:
• Keyword-based search only, lacking deep contextual understanding
• Dependent on API availability and rate limits, which can introduce latency or downtime
• Initial setup complexity, requiring proper credentials and configuration
• Use of higher level AI is strongly advised - in order for the chatbot to be able to properly navigate with calls to your e-commerce system we strongly advice using higher levels models (ie gpt 4o or gpt-4.1) This incurs higher costs but also results in much better quality of the chatbot responses.

The Winning Formula: Combine Scan & Integration

By combining a site-wide scan with live integration, ChatLab keeps your product catalog and store status in sync—so customers always see current stock levels, accurate pricing, and detailed descriptions without missing a beat. This dual approach also frees your support team to focus on complex issues rather than routine inquiries, while giving you a clear view of trending questions and popular products to refine your offerings over time. To achieve both deep contextual responses and live accuracy, configure ChatLab’s custom behavior under Bot Settings ▸ Role & Behavior - add following instructions:

When a user asks about products or categories, first invoke API tools to retrieve current data; fallback to the scanned knowledge base only for contextual enrichment. After fetching live data, augment responses with detailed descriptions and recommendations from the knowledge base when relevant.

This combined approach ensures your chatbot delivers both depth and accuracy, creating a seamless shopping experience.

Read more about role customization here:

Role & behavior settings and custom instructions

How to Properly Scan Your E‑Commerce Website

Before you scan, plan your approach to ensure efficiency and relevance:

1. Define proper scanning scope - use URL exclusion filter:
• Include only URLs for product and category pages (e.g., /products/ and /collections/).
• Exclude low-value paths like /blog/, /tags/, and archive pages using the URL Exclusion filter.
• For multilingual stores, restrict scan to a primary language
2. Exclude elements that are repeating on each page - ie header, footer, sidebar - use Html Element Exclusion filter.
3. Use Sitemap if you have one —with the sitemap you will be able to exclude menus, headers, sidebars, and other non-product elements

You can read more about optimizing your website scan here: 

How to Reduce Training Characters When Scanning a Website in ChatLab

Additional features worth enabling

• Products View: Enable this setting under Bot Settings ▸ Advanced to allow the chatbot to return product cards that include names, images, and prices. This improves visual presentation and makes product discovery more user-friendly - especially when used with real-time API queries. Read more here:
Products View

• Suggested questions: Pre‑populate quick‑reply chips (shipping, returns, opening hours) under Bot Settings ▸ Conversation, make sure that the option dynamic suggested follow-ups is enabled
Dynamic suggested follow-ups

• Human hand‑off: Activate the Contact Human form and provide your support email for escalations. Read more here:
Human Support Contact form

• Conversation & Client Summaries: When enabled, ChatLab automatically generates a summary for each conversation and maintains an up-to-date profile summary for every returning customer. This helps your team quickly understand past interactions and tailor their responses accordingly. Read more here:
Chatbot summaries and memory

• Use the Chat frontend API to pass information about the currently logged-in user (e.g., user ID, email, or security token). This allows the chatbot to securely access order history and status without requiring the user to re-enter their email during the conversation, resulting in a smoother and more personalized experience. Read more here:
Chat API

Language setup

ChatLab supports 90+ languages. Read more about proper language configuration:

Chatbot Language setup

In case you use integration with Shopify, WooCommerce or other e-commerce platform, always consider what is the language in which your system returns the products. As the users may ask questions in any language, add following instructions to your Role & Behavior settings:

When searching for products use [shop language] product and category names in singular form.

Monitor & Iterate Daily

To ensure ChatLab remains accurate and effective, implement a daily review routine:

• Review conversation logs regularly. Fine‑tune answers or add content where the bot hesitates.
Chatlogs

• Enable AI Conversation Insights (available in Standard Plan) Read more here:
AI Conversation Insights

• Leverage the automated Daily Activity Report
Daily Summary Email

By making daily monitoring a habit, you’ll keep ChatLab precise, responsive, and aligned with your evolving store needs.

Optimizing Chatbot Responses

Even well-configured chatbots can benefit from regular fine-tuning. Analyze conversation logs to identify weak spots, misinterpreted queries, or repetitive fallback answers. Refine prompts, update training material, and experiment with system instructions to improve how the bot handles nuanced cases.

For in-depth guidance, visit:

How to improve chatbot responses