Case Study: CallMiner achieves faster, more accurate customer insights with Appen's data annotation platform

The Appen Data Annotation Platform enables CallMiner to better serve its customers

CallMiner, a pioneer in AI-powered speech analytics, needed a better way to scale its sentiment and emotion analysis for customer service calls. Its research team faced the challenge of annotating large volumes of conversational data accurately, especially for nuanced cases like sarcasm and mostly neutral calls that could bias models. They turned to Appen and its data annotation platform to help expand their training data effort.

With Appen’s security-compliant annotators and annotation platform, CallMiner was able to offload manual labeling work, gain greater control over project setup, and access reporting features instead of relying on spreadsheets. Appen helped CallMiner scale from analyzing about 3,000 samples over a few months to tens of thousands of samples, improving speed, accuracy, and diversity of perspectives while supporting responsible AI and model explainability.

CallMiner

Rick Britt

Vice President of AI