The Problem: Morning Email Chaos
A B2B team received 200+ buyer inquiry emails daily. The challenge: all messages landed in a single inbox. New inquiries, repeat orders, price negotiations, order modifications, and complaints were all mixed together.
"I spent 30 minutes every morning just sorting emails. I needed to set priorities, but every message seemed equally important."
The team lead thought this workflow could be automated, but didn't know how to code.
Before: Manual Classification Process
Time spent: 35 to 45 minutes daily
• Manually opening and reading each email in the mail app
• Making judgment calls based on subject line and content
• Manually entering data into different tabs of a spreadsheet (new inquiries, reorders, technical issues, complaints, etc.)
• The same buyer's multiple emails scattered across sheets, making context unclear
• Working late into the night, repeatedly searching "where was that email I saw yesterday?"
Automation Design: 3 Steps
Step 1: Emails Feed into Spreadsheet
Using Gmail's basic filtering and Google Apps Script (supported by Claude Code), we set up automatic recording of buyer emails to the spreadsheet.
Email received → Apps Script trigger → Auto-entry into spreadsheet
(Sender, Subject, Content summary, Arrival time)
Step 2: Claude Code Identifies Email Intent
Whenever a new row was added to the spreadsheet, Claude API (through Claude Code) automatically analyzed the email content.
• New Inquiry
• Reorder
• Technical Question
• Price Negotiation
• Issue/Complaint
• Other
The analysis result was automatically entered into the "Category" column.
Step 3: FILTER Function for Dynamic Views
On a separate sheet, we used FILTER functions to automatically generate category-based views.
=FILTER(SourceData!A:F, SourceData!G:G="New Inquiry")
Now team members only needed to open their assigned category sheet.
After: Automated Workflow
Time spent: 2 to 3 minutes daily (verification and exception handling only)
• Emails automatically classified within 2 minutes of arrival
• Each team member only reviews their assigned category sheet
• Buyer email history automatically connected for better context
• Overnight emails already sorted by morning
• Only ~1 misclassification correction needed per month (data accumulates for learning)
The 48-Hour Journey
Day 1: Team lead meets with Claude Code for the first time. Describes the problem and sketches it out. "When emails arrive, they need to be categorized into 5 priority levels."
Day 1 afternoon: Google Apps Script structure designed for email triggers and basic data input. Five test emails manually entered.
Day 2 morning: Claude Code writes a script that reads spreadsheet content and learns classification patterns. Team lead adjusts rules and collaborates.
Day 2 afternoon: FILTER functions added. Testing how team members access category-specific sheets. Validation with 50 real emails (90% accuracy achieved).
Day 2 evening: Operations guide written. Instructions shared for correcting any misclassifications. System goes live.
Unexpected Wins
1. **Discovered buyer patterns**: As data accumulated, it became clear which buyers typically ask about what topics. This led to creating FAQ documents and preparing response templates.
2. **Improved response time**: With clear categorization came clear priorities. New inquiries get 4-hour responses, technical questions are assigned to specialists. SLAs could now be properly defined.
3. **Reduced overtime**: With email sorting stress gone, team mental health improved. (Not just anecdotal, later measured with an automated dashboard showing reduced stress hours.)
Future Expansion
Currently testing these additions based on the categorization data:
• Automatic buyer credit scoring (first-time vs. repeat customers, payment history, etc.)
• Auto-suggested response templates (suggested answers based on category)
• Weekly/monthly dashboards (inquiry trends, buyer satisfaction scores, etc.)
Conclusion
A non-programmer team lead, combining Claude Code with Google Sheets' basic features (FILTER, conditional formatting, Apps Script), significantly improved business workflow. The key was discovering what repetitive tasks happen every single day.