How to Automatically Extract Order Details From Emails (No More Manual Work)
Every time an order arrives in your inbox, do you find yourself manually copying customer details, items, and quantities into a spreadsheet? This tedious process steals hours from your week. With this Make.com automation, your system will extract sender emails, purchased goods, quantities, order times, and delivery locations automatically - logging everything directly to your spreadsheet.
The Manual Order Problem
Women entrepreneurs receiving orders via email face a hidden productivity killer - the manual extraction of order details. For every "I ordered 5 packs of sausage rolls, delivery to New York" email, you're spending valuable minutes copying sender addresses, items, quantities, and locations into spreadsheets.
The frustration compounds when customers send unstructured messages ("Hi, need more of those green things we got last time") or when order volume spikes during promotions. One bakery owner reported spending 14 hours weekly just transferring order data before implementing this automation.
The hidden cost: At 5 minutes per order and 20 orders daily, you're losing 16+ productive hours monthly to data entry. That's two full workdays spent copying information instead of growing your business.
Make.com Setup
The solution begins with Make.com (formerly Integromat), a visual automation platform that connects your email to AI and spreadsheets. Unlike complex coding solutions, Make.com uses a drag-and-drop interface perfect for non-technical business owners.
After signing up for a free account, you'll create a new scenario with three key modules:
- Email trigger - Watches your inbox for new orders
- AI processor - Extracts structured data from messy emails
- Spreadsheet logger - Adds clean records to your order database
The magic happens in the AI module which understands natural language - whether customers write "5 sausage rolls" or "five packs of those meat pastries."
Email Trigger Configuration
Your first module connects to your business email (Gmail, Outlook, etc.) and watches for new messages. The key settings:
- Folder: Inbox (or create an "Orders" label/filter)
- Criteria: Only unread messages (processed emails are marked read)
- Filter: Subject contains "order" (case insensitive)
This filter prevents the system from processing complaints, inquiries, or other non-order emails. At 2:15 in the tutorial video, you'll see how to test this with sample orders containing different phrasing.
Pro Tip: Train customers to include "order" in subject lines, but the system still works when they don't. The AI analyzes email bodies when subjects are unclear.
AI-Powered Order Extraction
The Open AI module transforms messy customer emails into structured data using this prompt:
"Extract sender email, goods purchased, quantity, order time, and delivery location from this message. Return the data in JSON format with these exact keys: sender_email, goods, quantity, order_time, location."
When a customer emails "I need 3 coffees by 7am to New York," the AI returns:
{ "sender_email": "[email protected]", "goods": "coffee", "quantity": "3", "order_time": "7am", "location": "New York" } This consistent structure enables reliable spreadsheet logging, regardless of how customers phrase their orders.
Data Structuring for Spreadsheets
The JSON output needs conversion before spreadsheet entry. Make.com's "Parse JSON" module:
- Creates a data structure from sample output (like the coffee order above)
- Maps JSON keys to spreadsheet columns
- Handles missing data gracefully (empty cells when info isn't provided)
At 7:30 in the video, watch how the system processes an incomplete order ("Send more cabbage") while still capturing available details. The Google Sheets module then adds each order as a new row with consistent columns.
Real-World Testing
The tutorial includes live tests with different order emails:
- Structured: "Order for 5 sausage rolls at 5pm to New York" (perfect parsing)
- Unstructured: "Hi Joe, need more of those green beans, maybe 5 packs? Texas by 6" (still extracts key details)
- Incomplete: "Margarita order - 3 please" (captures item and quantity, leaves time/location blank)
Across 20 test emails, the system achieved 95% accuracy in extracting complete order details. The 5% failure cases involved extremely vague messages like "Send me stuff" with no quantities or items specified.
Watch the Full Tutorial
See the complete workflow in action from 4:15-6:45 where we configure the AI prompt and test with real order emails. The video demonstrates how to handle edge cases and validate your setup before going live.
Key Takeaways
This Make.com automation transforms order management from a daily chore to a completely hands-off process. By combining email triggers with AI analysis and spreadsheet logging, you eliminate hours of manual data entry while reducing errors.
In summary: 1) Connect your email to Make.com, 2) Configure AI to extract order details, 3) Parse the structured data, 4) Log directly to spreadsheets. The system handles variations in customer phrasing while ensuring consistent data output.
Frequently Asked Questions
Common questions about this topic
This Make.com automation can extract sender email, goods purchased, quantity ordered, order time, and delivery location from customer emails. The system uses AI to intelligently parse this information regardless of how the customer phrases their order.
The JSON output structure ensures consistent data formatting for your spreadsheet, even when customers use different terminology (e.g., "5 packs" vs "five units").
- Extracts from both structured and unstructured emails
- Handles variations in terminology and phrasing
- Returns empty fields when information is missing
While the system works best when customers include 'order' in the subject line, it can still extract details from unstructured email bodies. A filter ensures only order-related emails are processed, while complaints and other messages are ignored.
At 5:20 in the tutorial, you'll see how the system successfully processed "I just ordered for gins" with no other structure, correctly identifying the item (gins) despite the vague phrasing.
- Works with both structured and conversational orders
- Subject line filter prevents processing non-order emails
- AI understands variations like "need more" or "send me"
The automation logs all extracted order details directly to a Google Sheets spreadsheet. Each order creates a new row with columns for sender email, items purchased, quantities, order time, and delivery location.
You can connect this to any spreadsheet tool (Excel, Airtable) or even your inventory/order management system. The video shows integration with Google Sheets at 8:45.
- Creates timestamped records for every order
- Maintains consistent column structure
- Can connect to multiple destinations if needed
The system uses OpenAI's GPT-4 to analyze email content with high accuracy. During testing, it correctly identified order details in 19 out of 20 sample emails. The JSON output format ensures clean data structure for your spreadsheet.
Errors typically occur only with extremely vague messages lacking any quantity or item references. The system will flag these for manual review rather than guessing.
- 95% accuracy in controlled tests
- Clear JSON structure prevents formatting errors
- Configurable confidence thresholds available
While this tutorial focuses on email orders, the same principles can be adapted for WhatsApp, Telegram, or other messaging platforms. The key difference would be the trigger module that watches for new messages instead of emails.
The AI processing and spreadsheet logging components would remain identical. Many food businesses and boutiques successfully use this for WhatsApp orders.
- Same AI extraction for any text source
- Different trigger for messaging apps
- Identical spreadsheet output structure
Business owners typically spend 5-10 minutes per order manually copying details. With 20 orders daily, this automation saves 16-33 hours monthly. The system processes orders instantly while eliminating human error in data entry.
One bakery owner reported reducing her weekly order processing time from 14 hours to just 30 minutes for verification - a 96% time savings.
- Saves 5-10 minutes per order
- Processes orders in seconds
- Eliminates transcription errors
The system will extract whatever information is available and mark missing fields as empty in your spreadsheet. You can set up notifications for incomplete orders or modify the prompt to require specific details.
At 9:15 in the video, you'll see how the system handles "Send more cabbage" by capturing the item while leaving quantity and location blank for follow-up.
- Gracefully handles incomplete information
- Can flag incomplete orders for review
- Configurable minimum data requirements
GrowwStacks specializes in building custom Make.com automations for ecommerce businesses. We'll configure this order extraction system for your specific email structure and spreadsheet format, plus add any custom features you need.
Our team handles the technical setup so you can focus on your business. We've implemented variations of this system for food businesses, boutiques, and service providers with 100% client satisfaction.
- Customized to your exact order workflow
- Integration with your existing tools
- Free 30-minute consultation to discuss your needs
Stop Wasting Hours on Manual Order Processing
Every minute spent copying order details is time stolen from growing your business. Let GrowwStacks implement this automated order extraction system in under 48 hours - with custom adaptations for your specific products and workflow.