Six Warning Signs Visible Only with Call Center Analytics

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The world has already generated over 79 zettabytes of data—and forecasters say we’ll more than double that by 2025.

The best part about this?

Data can help us make better decisions. Businesses can benefit from data analysis by understanding their customers better, improving efficiency, and identifying new opportunities.

The even better part?

Phone systems today gather tons of data. Some phone systems even come with dashboards that make reporting key metrics easy. Used wisely, all this information can be a lot more than just numbers you pull into a spreadsheet for quarterly reports. It can be the crystal ball you need to make sound business decisions.

Call center supervisors and managers are the ones who can help you harness the power of all this data. So, what should your crew keep an eye on when it comes to data?

Call center analytics trends showing 4 different numbers and a graph from Nextiva.

1. Call Abandonment Nearing 3%

Call abandonment is a key performance indicator (KPI) that measures the percentage of callers who hang up before they interact with an agent. A high call abandonment rate says that a lot of customers are dissatisfied with their experience.

You should strive to keep your call abandonment rate under 3%, as this is compliant with TCPA (Telephone Consumer Protection Act) regulations. Anything above 3% indicates that there may be a problem with your call center operations.

A high call abandonment rate can be the result of long wait times, a confusing phone menu, or other discomforts your callers go through. But you should be asking what, more specifically, is causing long wait times.

Are you understaffed? Are you using a predictive dialer that’s not properly aligned with your resources? Data analysis can come in here to help you find concrete solutions.

If you find that your call abandonment is nearing 3%, make this metric the North Star of your call center analytics dashboard. Analyze the data, pinpoint the root cause, and take action to improve your operations.

2. Potential Staffing Issues

There are many metrics that could tell you why you have staffing shortages, or overstaffing, for that matter. For instance, you could look at:

  • Service level: Whether you are meeting your service level agreement or not
  • Average speed of answer: Average wait time for the customer before an agent answers
  • Occupancy rate: How much time agents spend on calls compared to their available working hours

Each of these data points could indicate a different staffing problem. For instance, a high occupancy rate tells you that your agents are constantly busy and unable to pick up on any more calls. Not to mention, they won’t have time to submit proper reports, participate in internal meetings, or take on training.

Similarly, a poor average speed of answer shows you that your agents are busy or that your pre-qualification and routing process is not as effective as it could be.

Carefully monitoring these metrics will allow you to take action before an issue becomes critical and it starts to affect customer satisfaction or staff morale. Using predictive analytics can help you automatically determine staffing shortages before they happen.

3. Increased Number of Complaints

A high number of complaints points to an issue in either service or product. To get to the root cause of the problem, you should look at metrics that tell you how many times customers have interacted with your agents.

For one, first contact resolution (FCR) is a statistic that measures the percentage of customer interactions resolved within one call. A lot of call centers make the mistake of making average call durations their main KPI, but FCR is a much better metric for measuring the quality of your customer care.

If complaints are related to products, you might need to go back into the lab and interview current customers, send out surveys, and find out what is causing frustration. When you understand the main cause, you can use this information to improve both your product and your customer service scripts.

4. Too Many Call Transfers

The more call transfers you have, the more unsatisfied your customers are and the more likely it is you have a bottleneck that needs addressing.

When agents transfer a call, it can be for various reasons:

  • The initial agent could not help the customer fix their issue
  • The call was sent to the wrong department
  • The customer asked for a specific person or department

Tracking and analyzing the frequency of call transfers lets you identify which types of transfers happen most often so you can take the right action, such as:

  • Better training for your agents
  • Improving department workflows and pre-qualification processes
  • Implementing a call routing system that sends calls directly to the right department or agent

The more you minimize call transfers, the happier your customers will be. Plus, your agents can be more productive with their time—all of which contributes to a thriving business.

5. Low Customer Satisfaction Scores

If satisfaction scores are tanking, one of the most efficient ways to figure out what’s really going on in your call center is by using speech analytics.

Speech analytics refers to a series of metrics that look at the verbal interactions between customers and agents. Using speech analytics tools, you can automatically transcribe and analyze calls to gather insights on customer satisfaction, call quality, and agent performance.

Speech analytics allows you to track keywords or phrases that come up frequently during customer interactions, such as “long wait time” or “rude agent.” Or, it points out positive messages like “thank you very much” or “this was helpful!”

Identifying these patterns and measuring how often they appear in conversation can help you take corrective actions to improve the customer experience and reduce the odds of call abandonment and customer complaints. It also helps you encourage good behavior by rewarding agents for using positive keywords.

Corrective actions can include:

  • More or better training for your agents
  • Using predictive analytics to forecast staffing needs
  • Adjusting your call routing process to more effectively handle customer inquiries
  • Implementing a self-service IVR (Interactive Voice Response) system

Speech analytics allows you to look into how your agents handle calls without having to listen to every recording. The key lies in making sure you’re searching for the right keywords and phrases. They should be tailored to match your business, industry, and customer base.

6. Fewer Customers Calling In

On the surface, this may seem like a good thing. Maybe your business is running so smoothly that customers don’t need to call in to get their issues resolved.

Or, they’ve given up on your call center because it’s proven time and time again that it doesn’t give them the help they need.

Either way, it’s worth looking into. One of the easiest ways to gauge why customers aren’t calling is to run a call sentiment analysis on the ones that do.

You can do this by prompting users to answer one or two questions at the end of each call or agent interaction. These questions should be short and very straightforward, such as:

  • How would you rate your interaction today?
  • Did our agent successfully resolve your issue?
  • How likely are you to recommend our product/service to others?

Make it easy for customers to respond to these surveys. Emojis, star-rating systems, or simple yes/no answers can help you gather valuable feedback without taking too much of their time.

Once you’ve collected enough data, you can use it to analyze customer sentiment. A negative customer sentiment could indicate issues with your workflow, product, or service. A positive one, however, shows you’ve done something right and you’re satisfying customers.



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