Call_Center_Excel_Dashboard
A mini excel project, to gain insights on the performance of a call center with the use and exploration of different charts and insights to be more insightful of the data.
Core Elements of the Call Center Dashboard
Call Day and State Filters: Implement dropdowns or slicers to allow users to filter data based on specific days of the week and states. This can help in analyzing call patterns and volume geographically and temporally.
Calls Trend Over Time: Use a line chart to display the trend of calls over the month. Include options to filter this trend by call reason, state, or call day for more detailed insights.
Sentiment of Calls: A pie chart or a donut chart to show the sentiment breakdown of calls can be very illustrative. Consider using varying shades of a color to represent different sentiments from negative to positive.
Response Time Analysis: Use a bar chart to compare response times, categorizing them as 'Above SLA', 'Below SLA', and 'Within SLA'. This can quickly show areas needing efficiency improvements.
Calls by Channel and Reason: Pie charts or stacked bar charts can be effective here to show the distribution of calls by different channels (Call-Center, Chatbot, Email, Web) and reasons (Billing Question, Payments, Service Outage).
Calls by State: Integrate a geographical map to display the number of calls by state. Use color gradations to indicate volume, providing a quick visual reference of regional call activities.
Key Performance Indicators (KPIs): Display the total number of calls, average satisfaction score, and average call duration prominently using gauge charts or large font metrics for immediate visibility. Expanded Analytical Features
Detailed Call Analysis: Include a drill-down feature in the geographical map or in a separate table to view more specific data when a state is clicked, such as top reasons for calls in that state, average handling time, and satisfaction scores.
Trend Lines and Forecasting: Add trend lines to the calls trend chart to predict future call volumes based on historical data.
Customer Segmentation: Segment customers based on call frequency and satisfaction scores to identify high-risk or high-opportunity segments.