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Our Bot Started Calculating 'Buyer Trust Scores' in Google Sheets Every Night. Here's What Changed

시리시리·2026-08-12
⚙️ Nest Article #229

Our Bot Started Calculating 'Buyer Trust Scores' in Google Sheets Every Night. Here's What Changed

A non-developer built an automation system with Claude Code that analyzes buyer response speed, reorder rate, and communication patterns to automatically generate trust scores. Now the sales team can instantly identify priority buyers every morning.

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The Beginning: Counting by Hand

One day I realized something troubling. Our spreadsheet had over 100 buyers, yet every time the team needed to decide who to contact first, someone would say, "Let me check their emails manually."

"People who respond quickly should go first. Buyers who reordered last year should go first. Those without issues should go first." But this was all gut feeling, no system behind it.

We had all the data in Google Sheets, but no way to synthesize it into a single judgment.

The Solution: Automated Trust Score

I asked Claude Code:

Can you calculate this from our Google Sheets buyer list?

Days since last response (shorter = higher score)

Number of reorders since last year (more = higher score)

Shipping problems (none = higher score)

Contract size history (larger = higher score)

Combine these into a 0-100 trust score and update it automatically every night at 11 PM.

The bot completed the automation script in just ninety minutes.

After: Mornings Are Different Now

Every morning at 8 AM, the spreadsheet updates automatically. Next to each buyer appears a trust score, color-coded in red (40 or below), yellow (41-70), or green (71+).

Our team starts with green-coded buyers, reserves extra care for yellow ones, and investigates red flags when they appear (rarely).

Concrete Changes

**Decision time eliminated**: No more "who should we contact first?" The list is already prioritized

**Tracking accuracy**: Response speed, transaction history, and problem flags visible at a glance

**Team consistency**: Data-driven standards instead of individual memory

Unexpected Discoveries

When the bot first calculated scores, a few buyers showed surprisingly low trust ratings. We investigated and found they hadn't heard from us in three months. That led us to launch a fresh outreach campaign.

Somewhere else, one buyer's score kept hovering around 70. After digging in, we realized a minor shipping issue from months ago was still affecting their rating. We reached out to clarify the misunderstanding, and their score climbed.

Now

Every night at 11 PM, we sleep while the bot works. When morning comes, the priority contact list is already sorted by trust score. We simply start from the top.

Thanks to Claude Code and Google Sheets automation working together, our sales team now stands on data instead of intuition.