What Is Call Center Analytics, And How Do You Analyze Calls?

Call center analytics collects and interprets customer interaction data from phone, chat, email, SMS, and self-service channels to improve customer experience, agent performance, and operational efficiency. It includes performance, speech, predictive, omnichannel, and self-service analytics, using technologies such as AI, machine learning, natural language processing, transcription, sentiment analysis, and forecasting to uncover call drivers, customer intent, compliance risks, recurring problems, and future demand. Key metrics include Net Promoter Score, Customer Satisfaction, Customer Effort Score, First Contact Resolution, Average Handle Time, Cost per Contact, and Abandonment Rate, which together measure satisfaction, ease of service, resolution quality, efficiency, and cost. Organizations are advised to select analytics based on defined business goals, connect data across systems, and translate findings into improvements such as better routing, staffing, coaching, self-service content, and product decisions. The material also presents Retell AI as a platform that can automate routine inquiries, authenticate callers, route calls based on intent, provide post-call summaries and follow-up workflows, and consolidate analytics to help support teams scale while maintaining service quality.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.