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INTERIM MANAGEMENT · SaaS / Compliance E-learning · Berlin · ~80 employees · ~€15M revenue

Customer support driven by data

Interim customer support management - from setting up measurement through team development to preparing a system migration.

Measurable results
100% ticket categorization
86.4% First Response within 8 hours
-10% Email volume

How it started

The company brought me in as interim customer support manager after completing the onboarding audit. The team was handling a high volume of tickets, but there was no data on why customers were actually contacting support. Without this information, it was impossible to systematically reduce contact volume or prioritize improvements.

What I did as interim manager

2 days a week. 6 months. Working on all fronts simultaneously.

Categorization system from scratch

I designed and implemented a complete ticket categorization system - by user type, platform and contact reason. For the first time, the company knew exactly what its customers were dealing with.

Reporting and data sharing

I regularly reported categorization data to management and the product team. Gut feelings became numbers - and numbers became concrete improvement steps.

Cross-functional collaboration

I launched weekly syncs with Tech, Product and Account Managers. Stuck tickets started getting resolved faster, ownership became clear.

SLA redesign

I redesigned SLA measurement from an internal perspective to end-to-end customer experience. The new measurement included time spent across all teams, not just support.

Team development plans

I created individual 30-60-90 day development plans for each team member with clear goals and metrics. Everyone knew what they were working on and where they were heading.

Support software migration preparation

I mapped team needs, contacted vendors, led presentations for management and prepared a recommendation for switching to a new tool. After my engagement ended, I handed the project to their team to implement.

BEFORE
  • No ticket categorizationThe team knew what they were dealing with, but the data didn't exist - nothing could be measured or improved.
  • Decisions made without dataPrioritization depended on gut feeling, not numbers.
  • Siloed teamsSupport, Product and Tech worked separately without regular synchronization.
  • SLA measured only internallyCustomer experience wasn't part of performance measurement.
  • Team without clear development directionIndividual goals and growth plans for team members were missing.
AFTER
  • 100% of tickets categorizedEvery ticket has a user type, platform and contact reason - the data is available.
  • Data-driven decision makingManagement and the product team receive a regular report with concrete numbers.
  • Weekly cross-functional syncsSupport, Tech, Product and AM resolve stuck cases together every week.
  • SLA covers the whole customer journeyPerformance measurement reflects the real customer experience, not just internal handling.
  • Every team member has a 30-60-90 planClear goals, metrics and development direction for every team member.

First Response SLA - before and after

% of tickets with first response within 8 hours

76.8%
Before
86.4%
After
ticket categorization 100%
Email volume -10%

The 10% drop in email volume came as a result of better understanding contact reasons and targeted improvements in collaboration with the product team. First Response SLA grew from 76.8% to 86.4% through clearer processes and cross-functional collaboration.

Similar situation?

In a 30-minute call we'll look together at whether and where I can help.