Training course · Claude Code · Customer Service

Claude Code for Customer Service Teams

Agentic coding with Claude Code in the terminal and IDE: CLAUDE.md, subagents, hooks, MCP, CI pipelines and secure permissions.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Claude Code with the everyday processes of Customer Service. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Claude Code is not only for professional developers. Business users with no programming background can use it to analyse data, clean up Excel and CSV files, generate reports or build small internal tools, all in plain language. You describe what should happen, and Claude Code writes and runs the necessary scripts itself. This course variant shows you how to put these capabilities to work in your daily job without needing to understand code, and how to check the results reliably before anyone relies on them.

You will work through realistic office scenarios: merging exports from several systems, producing analyses with charts, generating documents and mail merges automatically, or turning repetitive file chores into a single command. Working safely is a central theme: which data may be processed, how you stay in control of approvals, and when to involve your IT department. The result is a set of useful helpers that take load off your team while remaining transparent and easy to hand over.

Customer service teams are the voice of the company: they answer questions, solve problems and have a major influence on customer satisfaction. Generative AI is changing service in many ways. AI assistants suggest replies to tickets and emails, summarise long conversation histories, translate enquiries and search knowledge bases in seconds. AI agents and chatbots answer routine requests around the clock and hand complex cases over to agents with full context. Automation classifies requests, sets priorities and detects sentiment. This gives service staff more time for demanding cases and empathetic conversations. The prerequisites are a well-maintained knowledge base, clear escalation rules, transparency towards customers and careful handling of the personal data in every ticket.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • First and second-level service agents
  • Team leads and service managers
  • Knowledge managers and service trainers
  • Customer success managers
  • Contact centre and service process owners

Typical challenges we address

  • Handling high ticket volumes while maintaining response quality
  • Keeping knowledge up to date and quickly accessible for everyone
  • Onboarding new staff quickly
  • Handling customer requests consistently across languages and channels

What you will be able to do

  • You commission data analyses and file tasks from Claude Code in plain language.
  • You clean and combine Excel and CSV data and check the results for plausibility.
  • You automate recurring document and reporting tasks with reusable instructions.
  • You have small internal helper tools built and refine them step by step.
  • Use AI for reply suggestions, summaries and ticket routing in your service process.
  • Build an AI-ready knowledge base and define clear escalation rules for chatbots.
  • Deploy AI in customer service transparently and in compliance with data protection rules.

Course outline

Day 1

Module 1 Getting started without coding skills
  • What a coding agent is and what it is allowed to do on your computer
  • Launching Claude Code and setting up a protected working folder
  • Describing tasks in everyday language: goal, input files, expected result
  • Understanding approval prompts and consciously accepting or declining them
Module 2 Analysing data in Excel and CSV files
  • Cleaning exports: duplicates, date formats, missing values
  • Combining several tables and calculating key figures
  • Producing charts and summaries as Excel files or images
  • Sanity-checking results with spot checks and cross-calculations
Module 3 Automating documents and routine tasks
  • Generating reports, minutes and mail merges from templates and data
  • Renaming, sorting and converting files automatically
  • Saving recurring procedures as reusable instructions
  • Writing a simple team guide in CLAUDE.md
Module 4 Building small scripts and internal tools
  • From idea to working helper: stating requirements clearly
  • Having simple input forms or local web interfaces created
  • Improving step by step: describing problems instead of debugging yourself
  • Documenting results so colleagues can use them

Day 2

Module 5 Working safely and responsibly
  • Handling personal and confidential data correctly
  • Limiting permissions and working only in approved folders
  • Recognising limits: when a tool should be handed over to IT
  • Coordinating with IT, data protection and business owners
Module 6 Hands-on project: your own solution for Customer Service
  • Reply snippet assistant – A small app that takes a customer request, suggests suitable approved text snippets and combines them into a personalised reply.
  • Ticket trend dashboard – An internal dashboard that clusters ticket exports by topic, shows rising issues and generates a weekly summary.
  • Agent onboarding quiz – A learning tool that generates practice questions and realistic customer cases from knowledge articles to onboard new agents in an engaging way.
Module 7 Data protection, quality & transfer to daily work
  • Tickets contain personal data, so processing them in AI tools requires a GDPR-compliant data processing agreement; under the EU AI Act chatbots must be clearly identifiable as AI. If conversations are recorded or agent performance data analysed, works councils must be involved, for example under the German Works Constitution Act.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Reply suggestions

An AI assistant analyses the request, searches knowledge articles and past resolutions and suggests a reply in the company's tone of voice, which agents adapt and send.

Ticket classification and routing

Incoming requests are automatically categorised by topic, product, urgency and sentiment and routed to the right team, with critical cases prioritised.

Case summaries

Long email threads, chat logs or call notes are condensed into a short summary of the problem, steps taken and open issue, ideal for handovers and escalations.

Knowledge base building

From resolved tickets and expert knowledge, AI drafts knowledge articles and FAQs, spots documentation gaps and keeps existing articles up to date with suggested changes.

Self-service assistant

An AI-powered chat answers frequent questions based on approved content, collects structured information for complex cases and hands them over to agents with context.

Quality analysis and coaching

AI reviews ticket samples against defined quality criteria, identifies recurring customer issues and gives team leads pointers for coaching and process improvement.

Possible hands-on projects

Reply snippet assistant

A small app that takes a customer request, suggests suitable approved text snippets and combines them into a personalised reply.

Ticket trend dashboard

An internal dashboard that clusters ticket exports by topic, shows rising issues and generates a weekly summary.

Agent onboarding quiz

A learning tool that generates practice questions and realistic customer cases from knowledge articles to onboard new agents in an engaging way.

Prerequisites

No programming knowledge is needed; confident use of Excel, files and folders on your own computer is sufficient. You work in customer service or customer success and know the ticketing or CRM systems your team uses.

Technical requirements

Your own laptop with admin rights, Git, a Node.js runtime and an up-to-date editor; a Claude subscription or Anthropic API access is required for the exercises.

Data protection & compliance

Tickets contain personal data, so processing them in AI tools requires a GDPR-compliant data processing agreement; under the EU AI Act chatbots must be clearly identifiable as AI. If conversations are recorded or agent performance data analysed, works councils must be involved, for example under the German Works Constitution Act.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Thu, 26 November 2026 – Fri, 27 November 2026 Online Request
  • Tue, 8 December 2026 – Wed, 9 December 2026 Stuttgart Request
  • Thu, 7 January 2027 – Fri, 8 January 2027 Online Request
  • Tue, 12 January 2027 – Wed, 13 January 2027 Berlin Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Online Request
  • Tue, 2 February 2027 – Wed, 3 February 2027 Munich Request

Frequently asked questions

How is Claude Code different from traditional code completion?

Code completion suggests the next few lines, whereas Claude Code acts as an agent that handles whole tasks: it searches the repository, plans changes across several files, runs tests and commands, and corrects itself based on the results. You define the goal and review the outcome instead of steering every single line yourself.

Is Claude Code secure enough for enterprise use?

By default, Claude Code asks for approval before editing files or running commands. Permission rules, sandboxing, managed settings and hooks let you define precisely what the agent may do. During the course you learn to configure these mechanisms to match your security and data protection requirements and to assess risks such as prompt injection.

Does Claude Code work with my language and tech stack?

Yes. Claude Code is language-agnostic because it works with files, terminal commands and your existing build and test tooling. Whether you use Python, Java, TypeScript, Go, SAP-related code or infrastructure as code, what matters most is a well-written CLAUDE.md describing your commands and conventions. Each course variant adds the relevant domain focus.

Will an AI chatbot replace our service team?

No. Good chatbots take care of routine questions, but complex, emotional or unusual requests need people. What matters is a smooth handover with full context. In the course we show how to define which requests are automated and when a human takes over.

How do we prevent chatbots from giving wrong answers?

Restrict the chatbot to verified knowledge content, show sources and define topics that are always handed to agents, such as legal questions or cancellations. Regular reviews and tests with real requests keep quality high over time. Clear feedback loops from agents help close knowledge gaps quickly.

How much does “Claude Code for Customer Service Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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