Closing the Feedback Loop: Integrating AI QA with Gushwork’s Sales Stack

The Objective: Beyond Random Sampling

For high-velocity sales organizations like Gushwork, data is everywhere, but insight is rare. They were already using Sybill to record and transcribe calls, but they faced the "5% Audit Trap."

Even the most diligent sales managers only have time to listen to a tiny fraction of their team's output. This means that 95% of customer interactions—the very moments where deals are won or lost—happen in a total "blind spot." Gushwork needed a way to ensure that their sales playbook wasn't just a document, but a lived reality on every single call.

The Solution: The Integrated QA Engine

The deployment focused on building a seamless bridge between Gushwork’s existing recording infrastructure and Sellerity’s analytical brain.

Step 1: Seamless integration

Through a direct sync with their recording stack, every recording was automatically pushed into Sellerity customised to their neds to only filter down to the calls needed by them.

Step 2: Custom Playbook Calibration

We didn't use a generic "good/bad" filter. We mapped Gushwork’s specific sales methodology—including their unique discovery questions and pricing talk tracks—into digital scorecards. The AI was trained to look for their specific winning behaviors.

Step 3: The Automated Audit

The AI reviewed 100% of the ingested calls. It flagged specific timestamps where:

• A rep missed a critical discovery cue.
• An objection was handled using outdated talk tracks.
• The "Next Steps" were left vague or unconfirmed.

The Impact: Scaling Excellence

By automating the "Review -> Feedback" loop, Gushwork transformed their management style. Instead of spending hours "hunting" for mistakes, managers now wake up to a prioritized dashboard. They can see exactly which reps need coaching on which specific skills.

This isn't just about catching errors; it’s about creating a "closed-loop" system where feedback is instant, objective, and applied to 100% of the team's output.