Financial services firm MoneySolver doubles contact center close rate with AI-powered quality management
By automating call scoring across 100% of interactions, MoneySolver doubled its close rate and improved return on ad spend by 30%, turning QA from a compliance exercise into a direct revenue driver.
Background
MoneySolver's 100-agent contact center was running QA on a small random sample of calls — less than the industry-standard 1% reviewed manually per agent per month. This left supervisors unable to identify systemic script violations, provide timely coaching, or accurately evaluate individual performance. On the marketing side, the company lacked call attribution visibility to distinguish which campaigns and affiliate partners were driving qualified leads.
What Was Implemented
- Deployed Invoca's AI-powered conversation intelligence platform across the contact center and marketing team
- Created two AI scoring scorecards: one structured scorecard for fronters (10 qualifying questions), one outcome-oriented scorecard for closers
- Integrated Invoca with Google Ads to push call-conversion data into smart-bidding algorithms
- Used PreSense to route high-converting affiliate calls to top agents and surface caller digital-journey data via screen pop
- Published an agent-performance leaderboard based on AI quality scores to create accountability and friendly competition
Results
Close rate doubled at the contact center following the shift to 100% AI-scored call coverage. ROAS from digital marketing and affiliate programs increased 30% through better attribution and Google Ads bid optimization. Agents became proactively engaged in their own performance improvement, with a 13-year employee contacting operations leadership to ask how to improve her leaderboard score — an outcome attributed to the objectivity and transparency introduced by automated scoring.
Lessons
- Moving from sample-based to 100% automated QA eliminates evaluator bias and creates an objective performance baseline that agents accept
- Separate scorecards calibrated to each role (fronter vs. closer) are more actionable than generic scorecards
- Tying AI call-conversion data directly to paid-media algorithms (e.g., Google smart bidding) compounds the ROI of conversation intelligence beyond the contact center
- Leaderboards tied to AI scores — rather than supervisor judgment — shift agent culture from defensiveness to ownership