Every business leader needs good data to inform their decision making.
They need to know how well their products work, how effective their teams are, and how customers really feel about them.
This is the goal of call center analytics.
Examples of Call Center Analytics
There are many ways that customers interact with your company and many chances to collect information and to turn it into actionable insights.
It’s important to understand how different kinds of analytics can be incorporated into your business.
These voice-based analytics detect certain words, phrases and tones. When difficult situations arise, more experienced agents or supervisors can intervene smoothly to solve complex problems.
Call Center Text Analytics
Like speech analytics, text analytics use artificial intelligence to detect keywords and patterns in customer conversations. They work by collecting feedback from social media, messages, and surveys.
These tools model customer behaviors and preferences, often with the goal of predicting the contact volume which will be driven by specific events. In other words, they estimate the peak times of calls so that more employees can be made available.
Self-service analytics are a growing trend for analytical data that is readily available to non-experts. A common example of this is Google Analytics which can empower numerous people – not just data scientists! – to make an assessment of website use.
These aim to help improve all agents’ performances. As an agent’s desktop is monitored, it is possible to provide feedback and to uncover ways to raise productivity.
Businesses are increasingly interested in making sure customer experiences are omnichannel. This means that a customer’s experience is seamless throughout all departments in the business. Cross-channel analytics can help to reveal how different channels are used, and where they feature in the customer journey.
The Importance of Call Center Analytics
Call center analytics are a vital factor in successfully meeting your customers’ needs.
With the right data on your side, you can expect to improve productivity, reduce costs and dramatically boost customer satisfaction.
Call center analytics also make a huge contribution to resource planning. It’s typically a big challenge for contact centers to predict call volume, leading to long queues and negative experiences.
Analytical data can’t remove this as an issue entirely, but does give businesses a basis on which to make resource decisions.
Finally, call center analytics give a strong basis for investment decisions by highlighting where service weaknesses exist to be challenged.