3 Ways AI Enhances Contact Center Reporting

Evaluating performance is a core requirement for making business decisions. In a contact center setting, there are distinct challenges when compared to other operations within an enterprise. Customer service is subjective by nature, and since most contact centers do not directly drive revenue, performance metrics are centered on operations and agent KPIs.

These metrics have served contact center leaders well, but technology has evolved beyond what legacy tools can measure with richer forms of reporting, especially with the advent of AI. As a result, the adoption of contact center analytics is forecast to grow over 20% annually over the next few years. Not only can contact centers get more and better metrics for what they already track, but they can also gauge performance on more aspects of operations. Reporting and analytics can provide greater business value than ever before; here are three ways contact centers can go beyond agent KPIs for richer reporting.

A Comprehensive Range of Reporting Capabilities

With labor being the largest cost factor for contact centers, agent KPIs remain central for measuring operational performance. The mix of KPIs is evolving, however, as the emphasis on CX means that customer outcomes can be just as important as how fast calls are answered or how quickly a problem is resolved. This requires reporting to address more than the transactional elements of customer service, such as customer sentiment. Legacy technology has limited capability for measuring these more qualitative attributes, but much more is possible with AI-driven applications.

Reporting is also more comprehensive now in terms of who else is involved. Supervisors rely on reporting to manage agents, and when they have better agent metrics, their own performance will improve. Agents benefit from getting better coaching and support from supervisors, and supervisors benefit from a more manageable workload. AI can manage performance datasets for all agents and all interactions, providing a more complete and accurate picture of agent activity, and allowing supervisors to make better decisions.

All of this rolls up to bigger picture reporting for contact center and operations management teams. Just as reporting for agent performance drives supervisor performance, reporting for both helps management get a holistic view of the contact center – not just to evaluate operations, but also its overall impact on the business.

Tying all this together is much harder using legacy systems. Omnichannel is a big step forward to help draw data from various silos across the organization, but for reporting to be fully effective, the metrics must be consistent. This means having a uniform approach for datasets across various vectors, such as all the channels used by agents, remote work, and the various regions or geographies your operations are based.

Real-Time Analytics

The more comprehensive scope that comes with today’s technology will elevate the value of reporting, but other factors can take it even further, and real-time analytics may be the biggest value AI brings to contact center reporting. Customer expectations will keep rising, and contact centers will need to deliver service faster and provide better outcomes. CX may be subjective by nature, but every customer interaction will ultimately be determined by how effectively agents respond in the moment.

AI-driven analytics help both agents and supervisors perform better in real time, and reporting ensures the right insights are delivered to the right person at the right time. Legacy systems cannot process the volumes of data, analyze it and provide specific guidance to each agent or supervisor in real time. These are the inherent strengths of AI. Every second counts when interacting with customers, so this level of reporting can make all the difference for CX.

To illustrate, consider how contact centers need to know when lesser experienced agents do not stay on script or are not being compliant; or when customers show early signs of anxiety that could derail a call; or when a caller is about to defraud the contact center. These are just a few examples where real-time analytics would alert supervisors and lead to actions to mitigate these situations and stop them in their tracks.

Support the Adoption of AI

While there’s a rush to adopt AI, contact center leaders are rightfully cautious. The upside of automating many aspects of customer service is too great to ignore, and reporting has a key role to play in measuring the performance of AI. With AI being so new, the ROI is difficult to measure, but the applications are data rich and reporting can be used to capture metrics to assess the impact of AI applications. Without these metrics, contact center leaders may set unrealistic expectations that can slow the adoption of AI. Given how quickly technology is changing, this could prove to be a costly mistake.

For many contact centers, chatbots are the starting point with AI. However, there will be a lot of trial and error before widespread adoption can occur. Beyond helping customers rely more on self-service, chatbots can also help improve agent performance.

For agents, reporting can provide insights on where chatbots are providing the most support to improve their performance. For supervisors, reporting can compare the effectiveness of chatbots on CX against agent-only customer interaction, as well as other channels that can be AI-driven, such emailbots.

Finally, for overall operations, reporting can help decision-makers evaluate chatbot performance from multiple vendors. The value of AI is best assessed by data-driven inputs, and this is how contact center leaders should be thinking about reporting.

Learn more about Upstream Works’ AI-driven reporting and analytics here.