Understanding Call Centre Analytics

Although the definition is generally somewhat broader than this, at their most basic, call centre 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 centre 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.

Successful centres use advanced call centre 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 centre. Here are the six most common approaches to analytics:

• Call Centre 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 centre agents to utilise in order to achieve the desired call outcome.
• Call Centre 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-centred 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 centre 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 analysing past results, companies can plan and strategise for the future.
• Self Service Analytics Forward thinking businesses today are finding ways to incentivise self service channels. Instead of having a customer call a contact centre 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 Centre Desktop Analytics A comprehensive desktop analysis programme can go hand-in-hand with real time call monitoring to capture inefficiencies, improve call centre 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 centre, 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 centre 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 most-common complaints about call centres 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 centre 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.