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Technical Support Analysis

(Power BI)

Recommendations

  • Address SLA Resolution Bottlenecks: Reduce the 34% SLA violation rate by streamlining workflows for high-volume topics like product setup (1,060 tickets) and pricing/licensing (954 tickets). Implement automation tools to expedite repetitive tasks and prioritize agent training for underperformers (e.g., Connor Danielovitch, Nicola Wane).

  • Optimize Staffing During Peak Hours - Align support teams with demand spikes:

    • Increase staffing on Mondays and during 3 PM (Hour 15).

    • Extend after-hours coverage to handle 63% of tickets created outside work hours.

  • Revamp Phone Support Quality: Investigate the 1.5 satisfaction score (August) for phone support. Provide targeted training, script enhancements, and real-time escalation protocols to address critical gaps.

  • Leverage Regional & Product Insights:

    • Allocate resources to high-volume regions (Germany, Italy, Poland) for faster resolution.

    • Proactively address recurring issues with ready-to-use software (July peak: 101 tickets) and custom software (May spike: 63 tickets).

  • Enhance First Response-to-Resolution Alignment: Close the gap between 87% SLA compliance for first responses and slow 33.74-hour resolution times by assigning complex tickets to top performers like Sheela Cutten (254 resolved within SLA) and improving cross-team collaboration.

Introduction

In today’s world, businesses of all sizes rely heavily on technology for daily operations. Technical support plays a crucial role in maintaining these systems efficiently. This month's challenge provides a real-life scenario for you to explore: analyzing the functioning of technical support. It’s a great chance to learn from fellow participants, improve your analytical abilities, and broaden your professional experience.
This dataset consisted of 2330 rows and 22 columns

Key Findings

  • Peak Demand Periods: Ticket volumes are highest on weekdays (85%), especially on Mondays and Fridays, with peak hours at 3 PM. Weekend activity is significantly lower at 15%.

  • Geographical Trends: Germany, Italy, and Poland generate the highest ticket volumes, indicating a need for focused support in these regions.

  • Topic Popularity: "Product Setup" and "Pricing & Licensing" are the most common topics, accounting for a large share of tickets.

  • SLA Compliance: Most tickets meet SLA for first responses (87%), but SLA violations for resolutions remain a concern, particularly for agents like Connor Danielovitch and Nicola Wane.

  • Agent Performance: Sheela Cutten leads in resolving tickets within SLA, while Connor Danielovitch and Nicola Wane have the highest SLA violations.

  • Channel Effectiveness: Chat consistently achieves the highest customer satisfaction, while phone channels show variability with extreme highs and lows.

  • Revenue-Driving Topics: High-ticket topics such as "Product Setup" and "Pricing & Licensing" dominate, reflecting their importance in customer engagement.

  • Customer Satisfaction Trends: Chat satisfaction peaked in October (4.43) and February (4.5), while phone satisfaction varied significantly, reaching a low of 1.5 in August.

  • Resolution Delays: While first responses are timely, resolution times often exceed acceptable limits, indicating systemic inefficiencies.

  • Weekend Support Gaps: Reduced activity on weekends could lead to delays in addressing critical issues.

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