This project focuses on analyzing call center operations to identify inefficiencies in response time, agent performance, and customer satisfaction. The goal is to provide actionable insights that improve operational efficiency and customer experience.
The call center lacks visibility into performance metrics such as response time, resolution rates, and customer satisfaction. Management is unable to identify underperforming agents, inefficient departments, and operational bottlenecks.
To analyze call center operations and identify key drivers of customer satisfaction, response efficiency, and resolution rates, and provide data-backed recommendations to improve overall performance.
| Column | Description |
|---|---|
| Call_ID | Unique call identifier |
| Date | Call timestamp |
| Agent | Agent handling call |
| Department | Department name |
| Answered | Call answered (1/0) |
| Resolved | Issue resolved (1/0) |
| Speed_of_Answer | Time to answer (seconds) |
| Talk_Duration_Seconds | Call duration |
| Satisfaction_Rating | Customer rating |
The dataset contained inconsistent formats, missing values, and non-standardized columns. Using Power Query, the data was cleaned by standardizing column names, converting data types, handling null values, and creating new KPI columns such as Answer Rate and Resolution Efficiency.
Data loaded in Power Query
Changed Data Types
Changed Column Names
Replacing Values In columns for better data readability
Inserting New date, day year columns
Inserted KPI’s Column
Overall Call Center Performance
Significant variation was observed between agents, indicating inconsistency in performance.
Certain departments showed lower resolution rates and satisfaction levels.