Misinterpreting Data May Be Costing Your Call Center More Than You Think

The proliferation of digital technology has made data more accessible and transparent than ever. A data-driven approach is especially important in a contact center, where agents field thousands upon thousands of calls in a day.

When proper systems are in place, data can be used to guide decisions about operations, training, and other facets of the business. Teams function more efficiently and you can minimize wasted time and effort. So why do experts remind leaders to not slavishly rely on data?

A more nuanced understanding

It’s worth noting that data is not infallible. After all, it’s just a set of numbers — how you interpret it determines its value.

As often happens, though, supervisors and managers take data at face value which can hinder instead of help improve customer experience ratings. To avoid this scenario, steer clear of these mistakes:

  • You assume you have enough data – Many call centers have customer experience software that automatically issues caller surveys and collates responses. As such, it’s easy to assume that you have the data you need to make sound decisions. In reality, however, less than one-third of all customers ever bother to fill out the questionnaire. With such a huge blind spot, any conclusion you arrive at is inaccurate at best — or detrimental at worst. Luckily, you can implement a customer analytics dashboard such as Zacoustic, which requires agents to answer the same survey with the goal of accurately predicting the caller’s response. With this system, each and every call is audited and calibrated, giving you the full story.
  • You miss the bigger picture – Given the sheer volume of calls your contact center receives, the industry has developed metrics that serve as handy benchmarks for performance. If you manage agents, terms such as Net Promoter Score (NPS), average handling time (AHT), and first contact resolution (FCR) are no doubt familiar to you. However, don’t forget that these are quantifications of human interaction and thus don’t always reflect the quality of engagement. For example, your employee experience analytics suite may show that an agent exceeded the ideal AHT, but it doesn’t show that he or she provided quality support that resolved the caller’s issue. If you’re basing decisions solely on the numbers, you may end up retraining rather than rewarding this agent — and that can seriously damage employee morale and loyalty.
  • You perform randomized audits – QA teams simply cannot audit each and every call. Hence, many rely on randomly evaluating a certain number of calls to get a sense of their team’s performance. While this method certainly has its merits, auditors could better use their time by reviewing high-value interactions (best or worst-case scenarios) rather than the routine calls that often get selected. With Zacoustic’s expanded pool of survey data, QA leads can pinpoint the calls that yield the most insight — insight that can actually help improve operations.

Needless to say, data is crucial to any business. But as David Ogilvy once said: “Data should not be used as a drunk uses a lamppost: for support rather than illumination.” In short, careful and thoughtful interpretation should always be practiced.

You may request a free consultation if you’d like to learn more about Zacoustic’s employee experience software.