Overview
| Goal | Deploy a Conversation AI bot that handles order status lookups, return initiation, product recommendations, and abandoned cart follow-up |
| Time to build | 60–90 minutes |
| Prerequisites | Conversation AI enabled, knowledge base populated, workflows configured, e-commerce integration connected |
| AI features used | Conversation AI + Knowledge Base + Workflows |
| Difficulty | Intermediate |

Architecture overview
The e-commerce support bot handles four primary flows:- Order status — Customer asks “Where is my order?” The bot looks up the order using the customer’s email or order number and provides tracking information.
- Returns and exchanges — Customer wants to return or exchange an item. The bot verifies the return window, collects the reason, and initiates the process.
- Product recommendations — Customer asks for help choosing a product. The bot asks about their needs and recommends items from your catalog.
- Cart recovery — A workflow detects an abandoned cart and triggers the bot to re-engage the customer with a personalized message.
Step-by-step build
Connect your e-commerce integration
Navigate to Settings > Integrations and connect your e-commerce platform (Shopify, WooCommerce, or other supported platforms).This connection enables:
- Order data syncing to contact records
- Purchase history visibility
- Abandoned cart detection
- Product catalog access
If your e-commerce platform is not directly supported, you can use the HoopAI API or Zapier to sync order data to custom fields on the contact record.
Build the e-commerce knowledge base
Navigate to AI Agents > Knowledge Base and add:Store policies:
- Return and exchange policy (timeframes, conditions, exceptions)
- Shipping options and estimated delivery times
- Warranty information
- Price match or adjustment policy
- Product categories and descriptions
- Sizing guides and fit recommendations
- Material and care instructions
- Frequently compared products
- How to track an order
- What to do if an order is damaged or missing
- International shipping details
- Gift wrapping and gift card options
- How to create or reset an account
- Accepted payment methods
- How to apply discount codes
- Subscription management (if applicable)
Create custom fields for e-commerce data
Navigate to Settings > Custom Fields and create:
| Field name | Type | Purpose |
|---|---|---|
| Last Order Number | Text | Most recent order ID |
| Last Order Status | Dropdown | Options: Processing, Shipped, Delivered, Returned |
| Customer Lifetime Value | Number | Total spend to date |
| Return Count | Number | Number of returns initiated |
| Cart Abandoned | Checkbox | Whether an active cart was abandoned |
| Product Interests | Text | Categories or products the customer has browsed |
Create the Conversation AI bot
Navigate to AI Agents > Conversation AI and create a bot:
- Name: “E-Commerce Support”
- Type: Auto-pilot
- Channels: Web Chat (primary), SMS, Facebook Messenger, Instagram, WhatsApp
- Calendar: Leave unassigned
Write the bot prompt
Paste the full prompt from the section below. The e-commerce prompt handles multiple conversation types (order status, returns, product help, general questions) and routes between them based on the customer’s intent.
Configure bot actions
Set up Conversation AI actions:
- Update custom fields: Record the order number, issue type, and resolution
- Add tags: “order-inquiry,” “return-request,” “product-recommendation,” “cart-recovery”
- Create task: For issues that need human intervention (e.g., damaged items, refund approvals)
- Send internal notification: Alert the support team for high-value customers or complex issues
Build the order status workflow
Create a workflow to handle order status inquiries:Trigger: Tag added — “order-inquiry”
- Look up the contact’s most recent order from synced data
- If order found: Update the conversation with tracking information
- If order not found: Ask for the order number or email address
- If the order is delayed: Proactively apologize and offer a discount code for their next purchase
- Add tag “order-status-resolved” when complete
Build the returns workflow
Create a workflow triggered by Tag Added — “return-request”:
- Verify the order is within the return window
- If eligible: Send return shipping label via email, provide return instructions
- If not eligible: Explain the policy and offer alternatives (store credit, exchange)
- Create a task for the fulfillment team to process the return
- Send a follow-up in 7 days to confirm the return was received
- Process the refund and notify the customer
Build the abandoned cart recovery workflow
Create a workflow triggered by Cart Abandoned (via your e-commerce integration or custom event):Sequence:
- Wait 1 hour after cart abandonment
- Send SMS/chat: “Hi
{{contact.first_name}}, I noticed you left some items in your cart. Can I help with any questions about [PRODUCT]?” - If reply received: Enable the bot to answer questions and guide them to checkout
- Wait 24 hours: If no purchase, send a follow-up with a 10% discount code
- Wait 3 days: Final reminder with urgency: “Your cart items are selling fast!”
- If purchased: Remove from sequence, add tag “cart-recovered”
Build the product recommendation flow
When a customer asks for product help, the bot should:
- Ask what they are shopping for (category, use case, occasion)
- Ask about preferences (size, color, price range, material)
- Recommend 2-3 products from the knowledge base that match
- Include a direct link to each product page
- Ask if they need help with anything else
Full prompt
Testing your e-commerce bot
Order status test
Provide an order number and ask for status. Verify the bot retrieves and displays correct tracking information.
Return request test (eligible)
Request a return for an order within the return window. Verify the bot walks through the return flow and offers refund, exchange, or store credit.
Return request test (ineligible)
Request a return for an order outside the return window. Verify the bot explains the policy and offers alternatives.
Damaged item test
Report a damaged item. Verify the bot asks for a photo and offers to expedite a replacement.
Product recommendation test
Ask for help choosing a product. Verify the bot asks qualifying questions and recommends relevant items with links.
Cart recovery test
Trigger an abandoned cart event. Verify the follow-up sequence fires at the correct intervals and the bot engages naturally when the customer replies.
Discount code test
Ask about current promotions. Verify the bot shares only valid, active codes from the knowledge base.
Optimization tips
- Track top inquiry types. If 60% of conversations are order status, invest in making that flow seamless. If returns dominate, focus on reducing return reasons (better product descriptions, sizing guides).
- Add proactive order updates. Instead of waiting for customers to ask, send proactive SMS updates when orders ship, arrive, or are delayed. This dramatically reduces inbound support volume.
- Personalize product recommendations. Use purchase history and browsing data (stored in custom fields) to make recommendations more relevant. “Based on your last purchase of [PRODUCT], you might also like [PRODUCT].”
- Optimize cart recovery timing. Test different intervals (30 min vs 1 hour vs 2 hours for the first message). The optimal timing varies by industry and price point.
- Measure bot resolution rate by category. The bot may resolve 90% of order status inquiries but only 40% of return requests. Focus improvement efforts on the lowest-performing categories.
- Add a satisfaction survey. After each bot interaction, send a quick 1-question survey: “How did I do? Reply 1-5.” Use the results to identify weak spots.
KPIs to measure success
| KPI | Target | Where to find it |
|---|---|---|
| Bot resolution rate | 70%+ of inquiries resolved without human escalation | Conversation AI dashboard |
| Average response time | Under 30 seconds | Conversation AI dashboard |
| Cart recovery rate | 10–15% of abandoned carts recovered | E-commerce analytics + workflow tags |
| Return rate | Track and aim to reduce over time | E-commerce reporting |
| Customer satisfaction | 4.5+ on post-interaction survey | Workflow survey results |
| Revenue from recommendations | Track purchases attributed to bot recommendations | Custom reporting |
| Support ticket volume | 30%+ reduction after bot deployment | Comparison reporting |
Next steps
After-hours support
Handle e-commerce support inquiries outside business hours.
Lead qualification
Qualify high-value wholesale or B2B inquiries.
Knowledge base
Expand your product and policy knowledge base for higher resolution rates.
Workflow automation
Build more sophisticated e-commerce automation workflows.