Call Center Analytics

Understanding Call Center Analytics

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Compared to underperformers, the best service teams are 3x more likely to be outstanding or very good at using analytics.

Compared to underperformers, the best service teams are 3x more likely to be outstanding or very good at using analytics

In today's global marketplace, many companies have turned to a call center model to assist, streamline and maximize customer service and sales needs at scale.

With one eye focused on providing excellent support and the other on efficiency, an ideal call center needs to strike that perfect balance of care and resources.

While call centers require an increase in overhead, they also sacrifice valuable "face to face" customer interaction. The current state of call center analytics provides employers the ability to improve service quality and doing so with the bottom line in mind.

Call center analytics allows for an unparalleled opportunity to monitor and improve a variety of service metrics from call times, efficiency, employee performance and customer satisfaction.

What is Call Center Analytics?

Although the definition is generally somewhat broader than this, at their most basic, call center analytics are a variety of tools that companies can employ through multiple support channels to keep their operation at peak performance.

The challenge with a call center operation of any size is that management on the floor only has access to a limited amount of information. With multiple agents dealing with scores of customers every day, only highly escalated situations (such as a system outage, a customer complaint, or an employee in need of coaching) would alert management to possible issues.

As such, under the old way of measuring, many opportunities for improvement would fall through the cracks.

The Advantages of Analytics

Successful centers use advanced call center analytics software to monitor and review performance, not only from a customer lens, also from the employee’s perspective, as well as a business-owner lens.

Each of these approaches offers its own advantages and together satisfies each angle. The key to choosing the correct analytics combination lies in understanding the approaches, and how they can be used to improve your call center. Here are the six most common approaches to analytics:

  • Call Center Speech Analytics Speech Analytics is a fairly new and relatively rare field, but one that many early adopters are finding significant success with. Using a team of analysts to monitor calls in real time, a company can unearth inefficiencies in their current model, and make process improvements, such as moving to a call script, or developing systems for call center agents to utilize in order to achieve the desired call outcome.
  • Call Center Text Analytics The last several years have seen an an explosion in the social media universe, and most forward thinking companies have developed a brand presence online. This paradigm shift has rendered text analytics ever more important, as we are no longer communicating with our customers through written documents, but also through email, secure messaging, Facebook, Twitter, and other text-centered media. Text analytics can review and monitor not only the messages sent to customers, but also the message they are sending to the company. This is vital in seeing any potential issues through the customer lens.
  • Predictive Analytics The modern predictive analysis engine is an invaluable tool in the call center environment. Using in-depth review of past performance in areas as diverse as call volume, service level, handle time, and customer satisfaction, predictive analysis makes it possible to apply past solutions to upcoming problems. How many agents will we need staffed on Christmas Day? How will your new product rollout affect call volume on weekends? What will this change to your fee structure do to your customer satisfaction score? By analyzing past results, companies can plan and strategize for the future.
  • Self Service Analytics Forward thinking businesses today are finding ways to incentivize self service channels. Instead of having a customer call a contact center agent to update their address, why not have them do it online on your website? Doing so reduces opportunity for error, incoming call volume, and company cost. While some customers can be resistant to this change, many are discovering that self service is an efficient and hassle-free option. Unlike many other analytics tools, self service requires minimal human involvement. Companies, however, must ensure that their self service analysis software is compliant with their current technological structure.
  • Call Center Desktop Analytics A comprehensive desktop analysis program can go hand-in-hand with real time call monitoring to capture inefficiencies, improve call center security, and explore potential coaching opportunities for phone agents. By not only viewing the phone agent's activity during the call, but also capturing all activity on the agent's desktop, a company can ensure that the agent is using their systems most effectively, and that the systems themselves are functioning properly. This analysis can also lead to significant process improvements for the call center, as an analyst can find and remove redundant tasks that increase call handle time, and frustrate both agents and customers alike.
  • Cross Channel Analytics A well-managed call center needs to have a way to determine what channels any of their customers are using at a given moment, and tailor their service options toward that. If a phone agent has this information at their fingertips, they can provide a more personal, pleasing customer interaction. Does a customer do most of their banking online? A real-time script update can alert the agent to let the customer know that their problem can also be solved using that channel in the future. As with speech analytics, this field is relatively new, but will almost certainly be a necessity in the coming years.
The best service teams understand that analytics not only helps to reveal a 360-degree view of the customer to the entire organization, it also enables service teams to work faster and smarter.

The best service teams understand that analytics not only helps to reveal a 360-degree view of the customer to the entire organization, it also enables service teams to work faster and smarter

The Direct Impact of Analytics on Customer Relationships

The most-common complaints about call centers are the duration of being on hold, slow turnaround times, having to explain an issue multiple times to different agents, and lack of a satisfactory resolution.

Let’s take a look at how analytics can be leveraged to flip these oft-cited call center problems into opportunities to improve.

By reviewing each of these aspects, businesses can look at call volume data by hour to ensure they have the proper staffing level for all of their operating hours, thus reducing (and even eliminating) customer hold time.

With enough resources to deal with incoming calls, this allows for more time spent with each customer and ultimately more call time to resolve the issue. When systems are operating at peak efficiency, service level agreements are being met more often.

Start with Simple Numbers, Get Advanced with Data

This is but one simple example of how call center analytics can help you identify the holes in your call center operation. Armed with the data and intelligence from your service analytics software, you’ll be able to more easily find patterns and make educated business decisions based off real customers behaviors and activity en masse.

Through advanced call center analytics and intelligence software, service your customers with the call-center experience they expect. By analyzing all of the available call center customer data, you’ll be able to quickly locate flaws in your process, and improve upon the advantages that your call center is already offering.

As a result, your clients will be able to get the solutions they need, as quickly and easily as they could ever want. There’s nothing more valuable than taking what is generally associated with as a negative product experience to an overwhelmingly smooth, and potentially pleasant, interaction. That’s what’s possible with call center analytics.

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