Monthly Technical Support Analysis - Tires & Rubber Products

Track and analyze technical support performance metrics, issue patterns, and resolution effectiveness for tire and rubber products, focusing on case volumes, resolution times, and recurring issue categories to improve product quality and customer support efficiency.

Report Objective

Monitor technical support metrics and trends for tire and rubber products to identify recurring issues, optimize resolution processes, and provide insights for product quality improvements. This monthly analysis focuses on support case volumes, resolution efficiency, and issue categorization patterns.

Technical Support Performance Metrics

Time series analysis of key support metrics including case volumes and resolution times.

Questions to Consider:

Mar 2024Apr 2024May 2024month260280300320total_casestotal_casesHow are Monthly Support Case Volumes Trending?Technical support cases show seasonal variation with recent upward trend
  • What is the month-over-month change in total case volume?

  • Are there any seasonal patterns in case volumes?

  • How do current volumes compare to historical averages?

  • How is first-contact resolution rate trending?

  • What factors might be affecting resolution efficiency?

  • Are there correlations between volume and resolution rates?

Mar 2024Apr 2024May 2024month64.0%66.0%68.0%first_contact_resolution_ratefirst_contact_resolution_rateResolution Efficiency TrendsFirst contact resolution rates and average resolution times indicate support efficiency

Issue Category Analysis

Distribution and trends of technical issues by category.

Questions to Consider:

Tread IssuesAir PressureAlignmentMaterial DefectsWear Patternsissue_category02004006008001,000sum(case_count)sum(case_count)Distribution of Technical Issues by CategoryAnalysis of most common technical support issues
  • Which issue categories require the most support attention?

  • How has the distribution of issues evolved over time?

  • Are there emerging problem areas requiring investigation?

  • Are certain issues showing significant month-over-month changes?

  • What seasonal patterns exist in different issue categories?

  • How do issue volumes correlate with product lifecycle events?

Mar 2024Apr 2024May 2024month505560sum(case_count) vs. issue_categorysum(case_count)issue_categoryMonthly Trend by Issue CategoryTemporal analysis of issue categories reveals patterns

Areas for Investigation and Improvement