Team X's performance over a 3-month period in Billing Department of Customer's Service

The analysis in this Power BI dashboard combines call volume metrics, agent performance data, and call categorization to identify and assess patterns of repeated customer interactions. Here’s an overview of the analytical techniques used:

Repeat Rate Calculation:

The 24-hour repeat rate is calculated as the percentage of calls that customers made within 24 hours of an initial call, helping quantify how often customers needed to contact again soon after their first call. A high repeat rate signals potential service or process issues.

Agent Performance Analysis:

By breaking down repeat rates by agent, the analysis highlights individual performance. Agents with high repeat rates are easily identified, indicating where additional support or training may be needed. This analysis helps pinpoint specific areas for performance improvement.

Categorical Analysis of Repeated Calls:

Call categories are analyzed to understand which types of inquiries (e.g., billing-related, appointment-related) have the highest repeat rates. Visualizations like pie charts display the distribution of call types that lead to repeated interactions within a 7-day period, helping prioritize which issue types need more attention.

Resolution Code Impact:

Top resolution codes causing repeated calls are identified to find patterns in call handling or resolution quality. By analyzing these resolution codes, the dashboard pinpoints specific issues that lead to repeated customer contact, offering insights into areas where policy or process adjustments could reduce repeat calls.

Filtering and Drill-Down Capabilities:

Interactive filters allow for targeted analysis by call type, resolution code, and time period. This flexibility enables users to investigate specific factors contributing to repeated calls and explore the data from multiple angles.

Overall, this analysis provides a comprehensive view of the factors driving repeat customer contacts, guiding management toward actionable insights for improving service quality and efficiency.