The 5 AI Models Every CX Analyst Must Know
AI is reshaping customer service—but not all AI models are created equal. For customer experience (CX) analysts, understanding the mechanics behind these models isn’t just helpful—it’s critical.
Top use cases for human and AI collaboration in customer experience
The integration of AI in the contact center is driven by a growing demand for rapid responses and deeper insights. This technology can parse massive amounts of customer interactions, detect patterns, and highlight emerging issues long before they impact large numbers of customers.
What’s the Right Mix of AI Agents and Human Agents for Customer Service?
It’s 2025, and the conversation around customer service automation has matured. The hype around replacing support teams with chatbots has met the friction of reality. Now, leading companies are asking smarter questions: not “How can I automate more?” but rather
5 Steps to Understanding & Improving DSAT
Understanding how dissatisfied your customers feel might not be at the top of your to-do list, but keeping an eye on DSAT (customer dissatisfaction) can provide valuable insights for call center managers and QA professionals. Here are three reasons why DSAT matters:
Case Study: Food Ordering and Delivery Platform uses AI to Predict & Prevent Customer Churn
As customer experience leaders move beyond AI pilot programs into scaled AI agent deployments, they’re asking: What share of conversations should be handled by AI, and which should stay with human agents?
Understanding Call Center Cost Per Call (and Why You’re Measuring It Wrong)
Call Center Cost Per Call (CPC) is one of the most tracked metrics in customer support. It’s easy to calculate (total cost/# of calls), quick to benchmark, and gives an impression of efficiency. But here’s the catch: optimizing for a lower CPC doesn’t