How a Regional Electrical Contractor Stopped Guessing About Customer Calls—and Fixed Two Major Revenue Leaks in 60 Days

The Setup

Western North Carolina electrical contractor. 100+ employees. Three business lines: residential service, residential construction, commercial development.

Their department head was trying to monitor call quality by literally overhearing conversations from across the office.

Problem? He could only hear one side of the conversation.

The Real Problem

Look, they had confidence in their team. This wasn't about catching anyone doing something wrong.

But between intake protocols, their specific pricing model, service fee explanations, and rapport building—there was a lot happening on those calls that management couldn't see or measure.

And here's the thing: What you can't measure, you can't improve.

Translation? Revenue was slipping through cracks they couldn't even identify.

What We Built

A custom AI call grading agent that analyzed the stuff that actually mattered to their business:

→ Intake protocol compliance - Were reps asking their required questions?
→ Pricing model explanations - How were they presenting their specific structure?
→ Fee communication - Were service fees landing well or triggering objections?
→ Rapport building - Was the team establishing real connection or just checking boxes?

The best part?

They were already recording calls for marketing purposes. We just automated the entire workflow:

Call happens → Auto-transcription → AI analysis → Summary lands in a Google Doc

Zero additional work for the phone team. Zero intrusion for customers. Minimal management time.

Real Talk: The Results

Within 60 days, they uncovered two massive operational blind spots:

Blind Spot #1: The Answering Machine Money Pit

The AI revealed they were losing calls—lots of them—when the answering machine picked up. They'd been defaulting to automated answering during business hours.

Their fix: Switched back to live answering.

Blind Spot #2: The Lunch Hour Black Hole

Nobody was answering phones during lunch. Potential customers were calling, getting nothing, and presumably calling competitors.

Their fix: Adjusted staffing to cover lunch hours.

Bonus Intelligence

→ Specific patterns in how different fee explanations landed with customers
→ Concrete examples of language that reduced friction vs. language that triggered pushback
→ Validation that their team actually follows protocol and builds good rapport

The Numbers

• 178 calls analyzed in January (81 substantive calls over 30 seconds)

• 75 calls in October → 81 in January (8% increase)

• Two major process changes implemented based on AI insights

• 60 days from deployment to operational changes

"This has given us insights we've never had before and is one more tool to help us improve our customer service game."
— Operations Manager

Why This Actually Works

Most contractors record calls for "compliance" or "quality assurance" and then... do nothing with them.

But here's what happens when you automate the analysis:

1. Scale Without Pain

Analyzing 80+ calls monthly would eat hours of management time. AI does it automatically.

2. Objectivity

No subjective interpretations. Just consistent evaluation against the criteria that matter to your business.

3. Actionability

The system doesn't just report—it reveals specific patterns that drive concrete business decisions.

The Bottom Line

For service businesses where phone interactions drive revenue, understanding both sides of customer conversations isn't nice-to-have intelligence.

It's money on the table.

This contractor found two revenue leaks in 60 days. They fixed both. And now they have ongoing visibility into what's working and what's not—without adding work to anyone's plate.

The magic?

We built this on infrastructure they already had (call recordings for marketing) and customized it to evaluate their specific business criteria—not generic quality metrics that don't move the needle.

Want to see what's happening on YOUR customer calls?

If you're recording calls but not analyzing them, you're sitting on intelligence you're not using. Let's fix that.