Modern call centers have bigger challenges than ever before. Not only is the call center industry heavily crowded, there are numerous regulatory burdens and staggering staff attrition rates to deal with.
To meet key performance goals and build success, modern call centers need to have the best tools and technologies. Call Analytics and business intelligence tools, in particular, can have a significant impact on the success of todays call centers.
Here are a few examples of critical tools that modern call centers need and how they can help:
1: Speech Analytics Tools
Speech analytics tools that can transcribe the audio of a conversation to text have been a staple of the industry for years now. Many call centers use speech analytics to aid in enforcing adherence to a preapproved conversation script.
This tool can be especially important for call centers in the collections industry, where regulatory standards on what can and cannot be said are particularly strict. With speech analytics, if a phone agent is saying things that are patently inappropriate, it is easy to spot the issue and correct the behavior.
2: Aggregate (Big Data) Analytics and Reporting Tools
To set goals for improving performance, you first have to have a clear understanding of your call centers overall performance.
Big data analytics tools help you collect both structured and unstructured data. Many tools can also help you organize, and interpret the mountains of data your call center generates each and every day. These tools can take many forms, from organizational dashboards that give at a glance analyses of overall call center performance metrics, to specific data mining software that collects information for the dashboard to display.
Not all big data analytics tools are equally useful to all call centers, as some may display a tremendous amount of irrelevant data, requiring the user to sort through and identify the most promising pieces of information.
With an appropriate system in place for aggregating and interpreting critical data, you can gain insights into your call centers current performance and identify your biggest opportunities for improvement.
3: Predictive Voice Analytics
While voice analytics could be considered a subset of big data, predictive voice analytics has very specific applications for call centers that make it worth mentioning separately. These analytics programs take the recordings made by call centers and analyze them to predict human behavior. Call Centers use predictive voice analytics to make assessments and predictions about phone agents or customers on each call.
A predictive voice analytics program will break the vocal features of each speaker on a call into feature vectors that the program will plug into special machine learning algorithms to assess the emotional changes related to each of the speakers.
This analysis can be applied in different ways based on the focus of the analytics solution. When used for assessing phone agents, the emotional behavior and tone analysis is used to identify calls where agents were speaking to customers in ways that arent consistent with your business philosophy. Moreover, the analysis goes further to aggregate call patterns to identify agents who are in need of additional training. Customer service call centers frequently use predictive voice analytics in this way.
Another use of predictive voice analytics is to study the voice of the customer for emotional cues that can be used to predict future behaviors. Call centers use predictive voice analytics to target more profitable customers, identifying those who are more likely to convert with future contact; vastly improving their outbound calling campaigns.
The best part of using machine-learning algorithms is that as more examples of real-world results are collected, the accuracy of the predictive model improves, making the tool more powerful over time.
With the right business intelligence tools, you can collect all the information you need to improve phone agent performance, track your progress towards performance goals, and build a more successful call center.