Lab Test:

Can GPT Save 10 Hours/Week on Support?

What We Were Testing

We set out to see if an internal GPT assistant could handle 80% or more of repetitive support questions—accurately, consistently, and without sacrificing the customer experience.

Why We Did It

One of our clients had a support team stuck answering the same questions over and over again—slowing down onboarding, draining productivity, and leaving little time for higher-value work. We wanted to see if AI could change that.

How we built and tested the assistant in the real world

What We Did

Each step was designed to reflect how teams actually work—so the results are practical, not theoretical.

Real-World Inputs

Collected 60 real support tickets.

Trained on What Matters

Trained a GPT on SOPs, help articles, and macros.

Delivered Where Teams Work

Delivered GPT in Slack for internal use.

Tracked the Impact

Measured accuracy + time saved for 2 weeks.

The Takeaways

What We Learned

Real impact, real numbers—and clear signals on where AI adds the most value.

High First-Try Accuracy

GPT answered 76% of questions accurately on first try.

Time Back in the Week

Estimated time saved: 12.4 hours/week.

Fewer Interruptions

Team reported a drop in Slack ping volume by 45%.

Knows Its Limits

GPT struggled with edge-case issues, but those were rare.

What’s Next

We’re adding GPT into HubSpot next to test end-to-end ticket deflection.