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Everything I've learned about AI QA after 2 years of building OttoQA and being one of the first companies to fully automate contact center quality assurance with AI.

I'm breaking down the biggest lessons, the biggest mistakes I see people making, and what actually works when you're implementing AI powered QA in a contact center.

I cover why you should never reinvent your scorecard on day one, what "false hustle" questions are and why they're killing your QA program, why most AI QA companies won't publish their accuracy rate, how statistical sampling means you don't need to score 100% of calls, why human QA evaluators disagree 30 to 40% of the time and how AI fixes that, how aggregate data turns QA from a scoring exercise into a real coaching tool, and the REDO feature we built at OttoQA that lets agents practice failed calls with an AI customer.

30 years of contact center operations. 2 years of building an AI QA platform. This is what I know.

 Through Expivia Digital, Tom works with contact center leaders on CCaaS platform selection, AI implementations, and NICE Studio and integration services. 

Same honest, vendor-neutral advice you hear on the Call Center Geek podcast, applied directly to your specific operational challenges. 

Schedule a consultation at ExpiviaDigital.com to discuss your contact center technology strategy. 

Click here:

expiviadigital.com

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