Training course · ChatGPT · Customer Service

ChatGPT for Customer Service Teams

Use ChatGPT safely and productively at work: projects, custom GPTs, data analysis, Canvas and privacy settings in team workspaces.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“ChatGPT for Customer Service Teams” is designed for roles such as First and second-level service agents, Team leads and service managers and Knowledge managers and service trainers and shows step by step how to use ChatGPT productively, safely and transparently in Customer Service – from the fundamentals to advanced workflows.

For many business teams, ChatGPT is the first AI tool they use every day – yet there is a methodical gap between asking the odd question and achieving real productivity gains. In this hands-on day you learn to apply ChatGPT deliberately to recurring work: drafting and editing text, summarising documents, analysing spreadsheets and structuring decision papers. You work with Projects that keep files and instructions together, with Canvas for reworking longer documents, and with data analysis for Excel and CSV files. Every exercise is based on genuine tasks from your own function.

The second focus is scale and responsibility. You build a custom GPT that knows your templates, tone of voice and review rules, and that colleagues across the workspace can use. We also clarify which data belongs in ChatGPT and which does not, how Team and Enterprise workspaces differ from personal accounts, and which settings matter for model training, memory and sharing. You leave with a personal prompt library, a working GPT and clear ground rules for using ChatGPT responsibly across your organisation.

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 write structured prompts that reliably produce usable results for your day-to-day tasks.
  • You organise your work in Projects and revise longer documents efficiently with Canvas.
  • You analyse spreadsheets and files with data analysis and critically verify the results.
  • You build a custom GPT for a recurring task and share it with your team.
  • 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

Module 1 Foundations and effective prompting
  • How language models work: strengths, limitations and hallucinations
  • Building effective prompts with role, context, task and output format
  • Refining iteratively instead of starting over: follow-ups and correction loops
  • Choosing models and using web search and deep research appropriately
Module 2 Projects, Canvas and document work
  • Setting up Projects to group files, instructions and chats by topic
  • Summarising, comparing and interrogating long documents
  • Using Canvas to revise text and drafts section by section
  • Templates for emails, reports, minutes and presentation outlines
Module 3 Data analysis with spreadsheets and files
  • Uploading, cleaning and analysing Excel and CSV files
  • Calculating KPIs, replicating pivot logic and explaining variances
  • Generating charts and preparing them for presentations
  • Verifying results: checking calculation steps and sanity checks
Module 4 Custom GPTs for recurring tasks
  • Identifying and scoping good use cases for GPTs
  • Configuring instructions, knowledge files and conversation starters
  • Testing, improving and sharing a GPT within the workspace
  • Maintenance, change tracking for instructions and ownership in the team
Module 5 Privacy, workspaces and governance
  • Personal accounts versus Team and Enterprise workspaces
  • Settings for model training, memory, temporary chats and sharing
  • Handling personal and confidential data in line with GDPR
  • Internal usage policy and quality assurance for AI output
Module 6 Practice lab: Customer Service
  • Reply suggestions
  • Ticket classification and routing
  • Case summaries
  • Knowledge base building
  • Self-service assistant
  • Quality analysis and coaching
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.

Prerequisites

Confident use of office applications and a web browser; no prior AI knowledge is required. Feel free to bring your own non-confidential sample tasks from your daily work. You work in customer service or customer success and know the ticketing or CRM systems your team uses.

Technical requirements

A laptop with an up-to-date browser and a ChatGPT account; a paid plan or access to your organisation's Team or Enterprise workspace is recommended for custom GPTs, Projects and data analysis.

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.

  • Mon, 23 November 2026 Online Request
  • Tue, 1 December 2026 Hanover Request
  • Fri, 18 December 2026 Online Request
  • Wed, 13 January 2027 Munich Request
  • Thu, 21 January 2027 Online Request
  • Tue, 2 February 2027 Stuttgart Request

Frequently asked questions

Do I need a paid ChatGPT licence for the course?

You can follow the fundamentals with a free account. However, features such as custom GPTs, Projects with larger files and advanced data analysis are tied to paid plans or come with far more generous limits there. Ideally you join with access to your organisation's Team or Enterprise workspace, so you practise under real conditions.

May I enter confidential company data into ChatGPT?

That depends on your plan, your contractual terms and your internal policy. In Team and Enterprise workspaces, content is not used for training by default, but GDPR and confidentiality obligations still apply. In the course you learn how to classify and anonymise data and how to choose the right settings.

How is a custom GPT different from a saved prompt?

A GPT bundles persistent instructions, knowledge files and optional tools such as web search or data analysis into a dedicated assistant. Colleagues can use it without any prompting skills and get consistent results. A saved prompt, by contrast, has to be copied and supplemented with context every time, which is far more error-prone.

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 “ChatGPT for Customer Service Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 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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