Yes. The evaluation logic is tailored to your individual call standards, internal processes, and business objectives.
Manufacturing & E-commerce
From Gut Feeling to Data: How AnKo Planen Made the Quality of Every Customer Call Measurable
AnKo Planen replaced subjective spot checks with an objective data foundation. Today, every customer call is analyzed automatically and turned into actionable insights for quality management and employee development.
AnKo Planen GmbHPublished 21. Juli 2026Project Duration:May 2026Implementation Time:2 weeksCompleted30–50 employeesGermany, PinnebergGDPR-compliant
2,700
Customer calls analyzed per month
€0.046
Analysis cost per call
€125
Monthly operating costs
130–180 hours
Time saved / month
Executive Summary
Problem
AnKo Planen was already recording all of its customer calls, but lacked a structured process for evaluating the data. As a result, quality management, coaching, and employee development were largely based on isolated spot checks and subjective assessments.
Solution
Within two weeks, DACH AI Solutions developed an AI-powered quality assurance system that automatically transcribes every customer call, anonymizes personal data in compliance with GDPR requirements, evaluates the conversation against predefined quality criteria, and visualizes the results in a central management dashboard. The first 436 analyzed calls already provided a reliable data foundation for coaching and quality management.
Result
Based on current call volumes, approximately 2,700 customer calls are now analyzed automatically each month—with ongoing operating costs of only around €125. This transformed a collection of previously unused call recordings into an objective management tool for quality assurance and employee development.
Key Insights
Many companies already record their customer calls. Data collection was never the real problem.
The actual bottleneck was making that data economically usable.
This project demonstrates that AI does more than replace manual analysis. It makes implicit experience and knowledge measurable, standardizes the entire quality assurance process, and creates a reliable data foundation for continuous improvement through coaching, employee development, and process optimization.
Starting situation
AnKo Planen GmbH employs approximately 30 to 50 people, including six to eight customer service employees.
Around 2,700 customer calls are handled every month. These range from product consultations and quotation requests to inquiries about individually manufactured products.
Although all calls were already being recorded, there was no structured evaluation process.
The company had neither an objective scoring system nor a consistent data foundation for measuring call quality or identifying targeted coaching measures.
A complete manual analysis of every conversation would not have been economically viable.
Tech Stack
n8n (self-hosted)OpenAI WhisperOpenAI GPTData StudioProsgreSQLGoogle Sheets
Process Overview
- 1
Call Upload
New call recordings are imported automatically.
- 2
Transcription and GDPR-Compliant Anonymization
Each conversation is transcribed, and personally identifiable information is automatically anonymized.
- 3
AI Analysis
Every call is evaluated against seven predefined quality criteria. The AI also identifies the reason for the call, the course of the conversation, customer sentiment, and potential areas for improvement.
- 4
Data Storage
All results are stored in a structured format in PostgreSQL and Google Sheets.
- 5
Dashboard
A central management dashboard visualizes all relevant metrics in real time.
Results
Before the automation was introduced, customer calls were recorded but provided the company with very few actionable insights.
Today, every conversation is analyzed automatically.
Management can immediately see which issues customers are actually contacting the company about, which employees have development potential in specific areas, and how call quality changes over time.
Instead of relying on isolated spot checks, the company now has a complete data foundation for quality management and employee development.
Business Value
Before the automation was introduced, call quality assessments were largely based on experience, individual observations, and occasional spot checks.
Today, management can objectively track developments across all customer calls and focus coaching measures on the areas where they have the greatest impact on call quality and customer satisfaction.
The AI does not replace the team leader. It provides the team leader with a complete basis for making informed decisions for the first time.
A comparable manual evaluation process would require approximately 130 to 180 working hours per month and generate personnel costs of around €3,300 to €4,400.
The automated system performs the same task for ongoing operating costs of approximately €125 per month.
Qualitative Value
The automation creates an objective foundation for quality management for the first time.
Every customer call is evaluated according to the same criteria and can be compared across employees, time periods, and reasons for contact.
In addition to measuring call quality, the system also reveals why customers are contacting the company and which topics place the greatest demand on the customer service team.
This creates better coaching opportunities while also generating valuable insights for product development, internal processes, and the customer service operation as a whole.
“For the first time, we have an objective foundation for employee development. We knew there was potential for improvement, but the dashboard showed us exactly where it was. Product knowledge and how conversations are brought to a close are now our two clear priorities.”
Frequently Asked Questions
The solution supports formats including WAV, MP3, and MP4. It can also automatically distinguish between different types of customer conversations.
Yes. Personally identifiable information is automatically anonymized before the analysis begins. The solution can also be operated entirely on self-hosted infrastructure.
The dashboard can display metrics including overall call quality, reasons for contact, customer sentiment, employee development, individual strengths, and specific areas for improvement.
Yes. Because the analyses are performed automatically, the operational workload does not increase proportionally with the number of employees or the volume of calls.
Related Content
Are you already recording customer calls but not yet using the information they contain systematically?
We analyze how your existing data can be turned into an economically viable resource—creating a reliable foundation for quality management, employee development, and data-driven decision-making.