Gaurav Mittal
AI reduces manual QA by catching what your team misses in the 98% of calls they never review. Right now, you’re flying blind through thousands of daily interactions, hoping nothing catastrophic slips through your 2% sample size. That compliance violation? The customer abuse incident? … Read more
Are your QA teams drowning in call reviews while missing critical customer insights? You’re analyzing maybe 2-3% of calls manually, coaching is limited to top performers, and customer sentiment trends slip through unnoticed. Meanwhile, compliance risks lurk in unmonitored conversations. This isn’t sustainable. Conversation … Read more
A. What are industry-specific terms? Industry-specific terms are words and phrases unique to your business domain. They’re the specialized vocabulary that defines how your team communicates with customers. These terms fall into several categories : Proper nouns include brand names, product titles, company names, … Read more
TL;DR Customer service quality assurance transforms contact centers from cost centers into growth engines. This comprehensive guide reveals how QA programs boost customer satisfaction by 5-10%, reduce costs by up to 50%, and improve agent performance by 25-30%. You’ll discover 11 proven strategies to … Read more
TL;DR Customer dissatisfaction analysis helps you understand why customers are unhappy with your service. You analyze DSAT scores, identify patterns, and fix root causes. This guide covers everything from calculating DSAT metrics to implementing improvements. You’ll learn practical techniques to turn negative experiences into … Read more
Sentiment analysis reads customer conversations and tags the mood. It scores language as positive, negative, or neutral – fast and at scale. Why does this matter now? You handle more feedback than ever – calls, chats, posts, reviews. Your team can’t read it all … Read more
Every dollar in finance depends on trust, and trust is built (or broken) during a sales call. Manual review of sales calls in financial services is slow, inconsistent, and often misses key details. Most contact centers can only manually evaluate 1-2% of interactions, leaving … Read more
