With the plethora of agent performance data available today, it can be challenging to determine where to focus. That doesn’t apply to agent performance in isolation; it also applies to how that performance affects customer satisfaction.
For years, Workforce Optimization (WFO) applications have tracked agents with tools such as quality, performance, and desktop management. As artificial intelligence (AI) becomes more integrated into these and other applications, the data that emerges because more useful and insightful.
Nearly three-quarters of companies are suffering from a Metrics Gap, meaning they are falling short on adequately measuring and using key data points that could dramatically improve their customer experience. To fully benefit from customer—and agent—data, CX leaders must adopt a lifecycle approach toward identifying metrics, gathering the data, analyzing it, and taking action. At this point, only 26.2% of companies have adopted such an approach, according to Metrigy’s Customer Experience MetriCast study of 1,846 organizations globally. I have written a detailed report on this topic that you can find here.
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