Cyber Chasse- Manage Call Center Data Logs

How to Manage Call Center data logs Using Splunk?

It is highly important for every call center company to store, control, and scrutinize the organization’s central data. Here let’s see how to do this task efficiently. There are two different aspects to process the core data and manage the same in the best way possible. 

 What Can Be Achieved By Effective Data Management? 

 The call center data is indeed extremely complicated. However, it is informative with real-time knowledge of business processing. This data needs to be analyzed as it will be favorable to protect the time, resources and capital. Besides, we can also have good visualization of every case by working on predictive analysis. This would lead to a great customer experience. 

 Why Use Big Data Tool Splunk over Traditional Excel pivot Chart? 

 Splunk, software technology is usually preferred to furnish illustrative, diagnostic, predictive, and prospective analysis. This is done by searching, analyzing, and visualizing the machine-generated data collected from various resources such as websites, devices, sensors, and applications. In this way, we can expect Splunk to bring merit to call center customer experience by managing the stored core data.  

A pictorial view depicting a scenario of how a focused team can handle multiple offices and their staffs by analyzing the core data generated internally using Big data Analysis. 

Here a telecom company with 4 call centers at specific geographies is shown. Also, the employee count differs based on the location and space-wise. 

Call Center data logs Using Splunk

 Different parameters are available for the management to have a higher-level overview, to obtain a precise and evident insight of operations of the company. Ultimately, it should provide certain meaningful results with regards to the below points  

· Recession Phase Data Analysis  

· Review – Office Expenses Annual  

· Review – Employee Performance  

· Optimization of Resources (Manpower & machines) 

· Review – Policy Amendment (To see how a policy can affect the growth of a company/individual)  

· Rewarding for Contribution to Company 

Depicting Visualization and Study of Call Centre Data using Excel 

Call Center data logs Using Splunk

Demerits of studying a large volume of data that is generating continuously. 

· Consumes more time for preparation and edit often. 

· Resources (Manpower) need to gather and submit core data to the centralized team. 

· Manual efforts and lay-offs. 

· Error margin because of the manual task which requires multiple rechecks by the management. 

· Consumption of infrastructure resource. 

· Only limited data can be managed using Excel as it may crash when overdone. 

· A Large volume of core data processing and storage will cause an issue. 

Displaying Visualization and Analysis of Call Centre Data using Splunk. 

Now, let us see how similar outcomes can be achieved with better outputs using Splunk. Also obsoleting the excel dashboard manual attempts and incorporating them into automation with the help of Splunk. With Splunk’s internal indexing mechanism, data archiving can be achieved for a longer retention period. 

Call Center data logs Using Splunk
Call Center data logs Using Splunk

Splunk does not only support but also enables various advanced visualization techniques, which allows core data representation to be more effective. Splunk is considered as the widely accepted data analytics tool as real-time data processing can be done with fewer resources.   

· Single value panel dashboard 

· Token and dropdown 

· Column Chart 

· Bar graph  

· Radio buttons 

· Radial gauge 

· Sparkline. 

Below are the proofs that state how we have incorporated automation and high efficiency in Call center data to get over the cons of Excel analysis. 

· Consumption of time in Preparation and Edit is decreased significantly with the help of automation and commands. 

· Resources (Manpower) needed to gather and submit data to the focused team becomes obsolete as Splunk archives and indexes real-time data without manual interference.  

· Minimum manual attempts and lay-offs. 

· Error margin is minimized due to automation in data processing and analysis. 

· A Large volume of data can be processed using Splunk depending upon the license. 

· Indexes in Splunk are available for data storage. 

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