Call Center KPI Analytics

Why This Resource Matters

Evaluating contact center operations requires standardized, defensible business metrics. Naive computations (such as calculating average talk time across abandoned calls or computing CSAT as a simple average of uncleaned survey responses) distort operational performance and mislead executive leadership.

Source Summary

The Gemini Notebook analytics curriculum defines the standardized operational metrics governing modern customer support operations:

• First Contact Resolution (FCR): Proportion of inbound inquiries completely resolved during the initial contact, eliminating repeat calls. Global industry standard benchmark: 70% to 75%.
• Service Level Agreement (SLA): Industry standard 80/20 Rule (80% of inbound calls answered within 20 seconds).
• Abandonment Rate: Percentage of callers who disconnect before being connected to an agent. Healthy operational benchmark: < 5% to 8%.
• Speed of Answer (ASA): Average queue wait time in seconds prior to agent connection.
• Customer Satisfaction Score (CSAT): Typically measured on a 1-5 Likert scale, computed strictly over completed interactions where survey responses were submitted.

My Understanding

In our Call Center Performance Analysis dataset (5,000 records from PwC), uncleaned data contains 946 abandoned calls. In these 946 records, Speed of answer, AvgTalkDuration, and Satisfaction rating are null. A critical data analysis rule is: never impute 0 for missing durations or CSAT scores when calls were abandoned. Doing so artificially drags down agent performance averages. Metrics must distinguish between Total Inbound Calls (5,000) and Answered Calls (4,054).

Key Takeaways

1. Denominator Discipline:
   • Total Resolution Rate = 3,646 / 5,000 = 72.92% (Executive view of all incoming demand).
   • Operational Resolution Rate = 3,646 / 4,054 = 89.94% (Agent effectiveness on answered calls).
2. Handle Abandonment Forensically: Abandonment rate is 946 / 5,000 = 18.92%, indicating severe queue bottlenecking during peak morning windows (9 AM – 11 AM).
3. CSAT Reliability: Net CSAT is 3.40 / 5.00 across answered surveys, revealing an opportunity to lift customer satisfaction by reducing queue times.

Important Examples

Example 1: Excel Formula for Operational Resolution Rate

=COUNTIFS(CallCenter[Answered (Y/N)], "Y", CallCenter[Resolved], "Y") / COUNTIF(CallCenter[Answered (Y/N)], "Y")

Example 2: DAX Measure for Average Speed of Answer (Excluding Abandoned)

Average Speed of Answer (Sec) := 
AVERAGE(FactCalls[Speed of answer])

(Note: VertiPaq engine automatically ignores BLANK cells in AVERAGE calculations, preserving metric integrity).

Example 3: SLA Compliance Check

=IF([@[Answered (Y/N)]]="Y", IF([@[Speed of answer]]<=60, "SLA Met", "SLA Breached"), "Abandoned")

Practical Application

These metric definitions serve as the foundation for:

1. The KPI scorecards in the PwC Call Center interactive workbook.
2. The strategic recommendations presented in 10 Portfolio/Call Center Analysis Portfolio Case Study.

Practice

Task: In the PwC workbook, calculate the Agent Ranking by CSAT score. Is the highest CSAT agent also the fastest at answering calls? Build a scatter plot comparing Speed of answer against Satisfaction rating to evaluate correlation.

Concepts Supported

• Data Analysis Life Cycle
• Dimensional Modeling
• Dashboard Design Principles

Related Course Lessons

• 01 Visual Analytics and Chart Selection
• 01 Dimensional Modeling Principles
• 03 DAX Fundamentals Calculated Columns vs Measures

Practice Opportunities

• Ex04 Pivot Table Summaries
• Ex07 Supplementary Dynamic Lookups and KPIs

Project Connection

• KPI Architecture
• Analytical Findings
• Executive Recommendations

Original Source

Open Gemini Notebook Source

Notes

Observed during analysis: Call abandonment peaks simultaneously with ticket volume spikes, confirming that the primary driver of customer dissatisfaction is staffing mismatches rather than agent technical competence.