Before: The Cycle of Manual Labor
Every Monday was the same. Open Google Sheets with 3,000 stored buyer contacts, manually check when we last reached out, how many emails we sent, and whether we got any response.
I'd switch between the email send date column, response column, and last reply date column, manually marking entries like 「This buyer has been silent for 2 months」 or 「Never replied once」.
I could only check 200 entries per day before our time ran out. We'd miss patterns constantly, and sometimes accidentally exclude key buyers from our re-contact list.
After: Claude Code's Automatic Classification
「Can Claude Code read our buyer data in Google Sheets and automatically pull out contacts who haven't replied in 90+ days or have zero responses into a new tab?"
I asked Claude Code.
Requirements:
• Read columns A through G from the 「Buyer List」 tab
• Calculate last response date (column E)
• Filter rows where response count (column F) is 0 OR no response period exceeds 90 days
• Create new tab called 「Re-Contact Targets」 and auto-populate results
Five minutes later, the code was ready.
When we ran it, 347 out of 3,000 rows were automatically classified. Work that should have taken us a month was done in 10 minutes.
The Surprising Discovery
Looking at the auto-classified results, I spotted a pattern we'd never caught with manual work.
Buyers in a specific region had an average non-response period 45 days longer than other regions. It could be timezone differences, or language barriers.
Thanks to this insight, we created a new strategy: reach out to that region's buyers in their local language first. This was a business insight impossible to get from manual sorting.
Next Automation
Now, every Monday Claude Code automatically refreshes the 「Re-Contact Targets」 tab. We just look at the results and set priorities.
Non-developers don't need to write code. Ask AI your business question clearly, and it will find patterns in your data. That's our small automation journey.