Real time analytics means data on calls and cases in progress is shown as it happens, rather than compiled into a report the following day. In customer service that means seeing how many people are waiting right now, how long they have waited, which agents are free, and whether you are about to miss your service target. The point is not to watch numbers, but to act while the outcome can still be changed. Historical reporting tells you what went wrong. Real time analytics tells you what is going wrong.
What you see in real time
- Calls in queue and the longest wait right now.
- Staffing, meaning who is logged in, free or busy.
- The share answered within target, that is service level for the day so far.
- Abandoned calls, meaning those who hung up before anyone answered.
- Current average handle time compared with normal.
Real time analytics compared with historical reporting
The two answer different questions and do not replace each other. Real time analytics is a tool for whoever runs the shift, triggering decisions such as opening an extra call queue, calling in more people or temporarily closing a channel. Historical reporting is a tool for whoever plans, showing patterns across weeks and months that inform staffing and recruitment. A common mistake is using real time data to evaluate individuals. It drives the wrong behaviour, because the numbers then become a measure of speed rather than of quality.
How real time analytics is used in practice
Most teams show real time data on a wallboard everyone can see, alongside a personal view for whoever runs the shift. In Lynes the real time views and the historical statistics sit in the same platform, and the AI is built in and developed in house, so it can summarise and categorise cases while they are still running, all in one single app. Read more about analytics and statistics.
Frequently asked questions about real time analytics
What is the difference between real time analytics and a wallboard?
The wallboard is the screen showing the numbers. Real time analytics is what happens behind it, meaning data being collected and calculated continuously.
How often do the numbers update?
Usually every second or every few seconds. Any longer delay and the data loses its purpose, because the decision comes too late.
Which measures matter most in real time?
Queue length, longest wait and the number of free agents. Those three go a long way towards running a shift.
Do small teams need real time analytics?
Yes, though a simpler version. Even a team of three benefits from seeing that four customers are waiting, rather than discovering it in the statistics the next day.
Want to see customer service as it is right now instead of as it was yesterday? Book a Lynes demo.
