Call Center Dashboard Power BI Report

Requirement Document for Call Center Dashboard Power BI Report

1. Introduction

The Call Center Dashboard Power BI Report provides real-time insights into customer support operations, helping teams track performance, optimize response times, and improve service quality.

2. Objectives

Monitor Call Center Performance – Analyze call, chat, and email volumes and trends.
Improve SLA Compliance – Track resolution times and service-level agreement (SLA) adherence.
Analyze Ticket Distribution – Categorize and evaluate support requests.
Identify Performance Gaps – Optimize operations by reducing response time and increasing resolution efficiency.

3. Data Components

3.1 Call Data

Call Volume – Number of calls received.
Month-over-Month (MoM) Change – Percentage increase/decrease in calls.
Average Resolution Time (Days) – Time taken to resolve a call.
SLA Compliance Rate (%) – Percentage of calls resolved within the SLA.
Ticket Volume by Category – Distribution of calls by issue type (e.g., Billing, Login Problems, Account Issues, Technical Support).

3.2 Chat Data

Chat Volume – Number of chat requests handled.
MoM Change – Increase/decrease in chats.
Average Resolution Time – Time taken to resolve chats.
SLA Compliance Rate – Chat resolution compliance.
Ticket Volume by Category – Breakdown of chat support requests.

3.3 Email Data

Email Volume – Number of email queries received.
MoM Change – Change in email volume.
Average Resolution Time – Resolution duration for email tickets.
SLA Compliance Rate – Email response compliance.
Ticket Volume by Category – Categorization of email support requests.

4. Data Sources

Call Center CRM Database – Stores customer interactions via calls, chats, and emails.
Ticketing System – Records issue resolutions, categories, and timestamps.
SLA Compliance Logs – Tracks response times and resolution adherence.

5. Performance Metrics

Total Support Volume (Calls, Chats, Emails)
MoM % Change in Volume
Average Resolution Time (Calls, Chats, Emails)
SLA Compliance Rate (%)
Ticket Distribution by Issue Type
Response Rate & Escalation Rate Trends

6. Expected Outputs

Power BI Dashboard with Interactive Visuals
Historical Trends Analysis
Real-time SLA Monitoring
Agent Performance Reports
Customer Issue Trends Over Time

7. Use Cases

Customer Support Managers – Optimize team performance.
Call Center Agents – Improve response efficiency.
Business Analysts – Identify operational bottlenecks.
Executives – Track high-level performance insights.

8. Constraints & Assumptions

Data Accuracy Depends on CRM Integration – Timely updates are crucial.
Power BI Access is Required – Only authorized personnel can view reports.
Service Delays May Impact Data Trends – Unexpected events could skew results.

Call Center Dashboard Download

9. Project Completion Method

Step 1: Data Extraction (SQL Queries)

The report extracts data from the call center database using SQL queries.

1. Call Data Extraction

sqlCopyEditSELECT 
    CallID, 
    CallDate, 
    ResolutionTimeDays, 
    SLA_Compliance, 
    TicketCategory
FROM Calls
WHERE CallDate BETWEEN '2023-01-01' AND GETDATE();

2. Chat Data Extraction

sqlCopyEditSELECT 
    ChatID, 
    ChatDate, 
    ResolutionTimeDays, 
    SLA_Compliance, 
    TicketCategory
FROM Chats
WHERE ChatDate >= DATEADD(MONTH, -12, GETDATE());

3. Email Data Extraction

sqlCopyEditSELECT 
    EmailID, 
    EmailDate, 
    ResolutionTimeDays, 
    SLA_Compliance, 
    TicketCategory
FROM Emails
WHERE EmailDate >= '2023-01-01';

Step 2: Data Transformation (Power Query – M Language)

Power Query cleans and structures the data for Power BI visualization.

Power Query Transformations

Remove DuplicatesmCopyEditTable.Distinct(Source)
Replace Null ValuesmCopyEditTable.ReplaceValue(Source, null, "Unknown", Replacer.ReplaceValue, {"TicketCategory"})
Convert Resolution Time to Numeric FormatmCopyEditTable.TransformColumnTypes(Source, {{"ResolutionTimeDays", type number}})
Calculate Monthly TrendsmCopyEditTable.AddColumn(Source, "Month-Year", each Date.ToText([CallDate], "MMM-YYYY"), type text)

Step 3: Data Modeling & Relationships

Tables are linked in Power BI to create relationships between datasets:

Table 1 (Calls)	Table 2 (Chats)	Table 3 (Emails)	Relationship
`CallDate`	`ChatDate`	`EmailDate`	One-to-One
`TicketCategory`	`TicketCategory`	`TicketCategory`	One-to-Many

A Date Table is created to enable time-based filters.

Step 4: Data Visualization (DAX Measures & Calculations)

DAX measures track performance KPIs in Power BI.

1. Total Call Volume

DAXCopyEditTotalCallVolume = COUNT('Calls'[CallID])

2. Total Chat Volume

DAXCopyEditTotalChatVolume = COUNT('Chats'[ChatID])

3. Total Email Volume

DAXCopyEditTotalEmailVolume = COUNT('Emails'[EmailID])

4. Month-over-Month (MoM) Change

DAXCopyEditMoMChange = 
VAR PreviousMonth = CALCULATE(SUM('Calls'[CallID]), PREVIOUSMONTH('Date'[Date]))
VAR CurrentMonth = SUM('Calls'[CallID])
RETURN 
IF(PreviousMonth = 0, BLANK(), (CurrentMonth - PreviousMonth) / PreviousMonth)

5. SLA Compliance Rate

DAXCopyEditSLACompliance = 
DIVIDE(
    COUNTROWS(FILTER('Calls', 'Calls'[SLA_Compliance] = "Yes")), 
    COUNTROWS('Calls'), 
    0
) * 100

6. Average Resolution Time

DAXCopyEditAvgResolutionTime = AVERAGE('Calls'[ResolutionTimeDays])

7. Ticket Volume by Category

DAXCopyEditTicketByCategory = COUNT('Calls'[TicketCategory])

Step 5: Power BI Report Development

Power BI Visuals Used

KPI Cards – Total Calls, Chats, Emails, MoM Change, SLA Compliance.
Bar Charts – Monthly Trends for Calls, Chats, and Emails.
Pie Chart – Ticket Volume by Category.
Line Chart – SLA Compliance Over Time.
Table Visual – Agent-wise Call Resolution Performance.

10. Deployment & Maintenance

Scheduled Data Refresh – SQL queries update data daily.
Power BI Service Deployment – Reports accessible to management.
Data Accuracy Monitoring – Regular validation of KPIs.
Enhancements – New insights and additional performance tracking.

Conclusion

This structured Power BI Report enables real-time monitoring of call center operations, ensuring efficient issue resolution, SLA compliance, and customer satisfaction.

Sample data files based on the Call Center Dashboard Power BI Report.

Call_Data_Sample Download

Chat_Data_Sample Download

Email_Data_Sample Download