Training course · Prompt Engineering · Sales

Prompt Engineering for Sales Teams

Vendor-neutral prompt engineering: roles, context, few-shot examples, prompt chains, prompt libraries and systematic quality checks.

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

This course connects Prompt Engineering with the everyday processes of Sales. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Whether you use ChatGPT, Claude, Copilot, Gemini or Le Chat, the quality of the output depends largely on how the task is framed. Prompt engineering is the skill of conveying goal, context, constraints and desired format to a language model so that it reliably produces usable results. In this vendor-neutral practical day you learn proven techniques that work across all mainstream AI assistants: defining roles and audiences, selecting relevant context, working with examples and breaking complex tasks down into traceable steps. You try out every technique directly on tasks from your own working day.

The second part focuses on repeatability and quality across the team. You develop prompt templates with placeholders, build multi-step prompt chains for analysis, writing and review processes, and set up a shared prompt library. You learn to evaluate output systematically – with review criteria, test cases and targeted self-checks by the model – and to avoid typical pitfalls such as hallucinations, ambiguity and missing context. By the end you have a structured approach that works regardless of the tool you use and continues to pay off as new models arrive.

In sales, the quality of preparation and customer communication decides whether a deal closes. Generative AI helps sales teams spend more time with customers and less on admin. AI assistants research companies and contacts from public sources, prepare call guides, draft personalised emails, summarise meeting notes and create proposal drafts. AI agents and automation maintain CRM data, prioritise leads and remind reps about follow-ups. For sales leaders, pipeline analysis and forecasting become faster and more transparent. The key is to use AI to support genuine relationships rather than mass, impersonal outreach. With clean CRM data, clear processes and privacy-compliant tools, AI becomes a productivity lever across the entire sales cycle.

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?

  • Account managers and key account managers
  • Business and sales development representatives
  • Sales managers and directors
  • Inside sales and sales operations
  • Pre-sales and solution consultants

Typical challenges we address

  • Finding time for research and preparation alongside day-to-day business
  • Keeping CRM data complete and up to date
  • Creating tailored proposals and tender responses quickly
  • Assessing pipeline and forecast realistically

What you will be able to do

  • You understand how language models process prompts and derive effective wording from this.
  • You structure prompts with role, context, task, constraints and output format.
  • You use few-shot examples and prompt chains for complex, multi-step tasks.
  • You create reusable templates and build a shared prompt library.
  • Prepare customer meetings faster and more thoroughly with AI.
  • Create personalised outreach, proposals and follow-ups efficiently and authentically.
  • Automate CRM maintenance and pipeline analysis in compliance with the GDPR and marketing rules.

Course outline

Module 1 How language models process prompts
  • Core principles of language models: probabilities, context window, limitations
  • Why wording, order and examples change the result
  • What causes hallucinations and how prompts reduce them
  • Differences and common ground between mainstream AI assistants
Module 2 Building blocks of an effective prompt
  • Defining role, audience, task, context and output format
  • Stating constraints, exclusions and quality criteria
  • Structured input with sections, delimiters and tags
  • Asking the model to raise questions instead of making assumptions
Module 3 Advanced techniques
  • Zero-shot, one-shot and few-shot: setting style and structure with examples
  • Requesting step-by-step reasoning for complex tasks
  • Prompt chains: separating research, drafting, review and revision
  • Using change of perspective, counter-arguments and model self-critique
Module 4 Templates and prompt libraries
  • Creating reusable templates with placeholders and variables
  • Storing persistent instructions in projects, custom assistants and agents
  • Building, naming, maintaining and sharing a team prompt library
  • Documenting templates: purpose, inputs, expected output, owner
Module 5 Quality assurance and responsible use
  • Defining review criteria and scoring rubrics for AI output
  • Setting up test cases and systematically comparing and improving prompts
  • Verifying facts, figures and sources; establishing the four-eyes principle
  • Data protection, confidential content and transparency under GDPR and the EU AI Act
Module 6 Practice lab: Sales
  • Account research
  • Personalised outreach
  • Call preparation and objections
  • Meeting notes and CRM updates
  • Proposals and tenders
  • Pipeline analysis
Module 7 Data protection, quality & transfer to daily work
  • Customer data in sales is subject to the GDPR and to rules on unsolicited marketing by email and phone, which in Germany are particularly strict; researching and enriching personal data requires a legal basis. Confidential customer and pricing information belongs only in approved AI environments.
  • 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

Account research

An AI assistant summarises public information on target companies, such as annual reports, press releases and job ads, and derives likely challenges, stakeholder roles and conversation starters.

Personalised outreach

Research and product knowledge are turned into individual emails, LinkedIn messages and follow-ups that address the customer's situation instead of sending generic templates.

Call preparation and objections

AI creates call guides with discovery questions, typical objections and suitable responses and simulates sales conversations as role plays to prepare for difficult meetings.

Meeting notes and CRM updates

Notes or transcripts are turned into structured summaries with next steps, decision-makers and budget information and entered into the CRM as a draft.

Proposals and tenders

AI helps assemble proposal text, value arguments and answers to RFP questionnaires from existing content blocks and tailor them to the customer's requirements.

Pipeline analysis

CRM exports are analysed, stalled opportunities identified and forecast risks commented on, so pipeline reviews focus on concrete actions rather than on updating spreadsheets.

Prerequisites

Some initial experience with at least one AI assistant such as ChatGPT, Claude, Copilot or Gemini is helpful; no technical background is required. You work in sales or inside sales and use a CRM system in your daily work.

Technical requirements

A laptop with an up-to-date browser and access to at least one AI assistant, ideally the tool approved within your organisation.

Data protection & compliance

Customer data in sales is subject to the GDPR and to rules on unsolicited marketing by email and phone, which in Germany are particularly strict; researching and enriching personal data requires a legal basis. Confidential customer and pricing information belongs only in approved AI environments.

Suggested dates

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

  • Wed, 25 November 2026 Online Request
  • Mon, 30 November 2026 Hanover Request
  • Tue, 15 December 2026 Online Request
  • Fri, 8 January 2027 Online Request
  • Fri, 15 January 2027 Munich Request
  • Thu, 21 January 2027 Online Request

Frequently asked questions

Do these techniques work with every AI assistant?

Yes, the course is deliberately vendor-neutral. The principles – a clear task, relevant context, examples, structured output and review steps – work equally well in ChatGPT, Claude, Copilot, Gemini, Le Chat and other tools. Where assistants differ in detail, for example with projects or custom assistants, we show the corresponding features in each.

Won't better models soon make prompt engineering obsolete?

Models are getting better at interpreting vague requests, but they still cannot know what you do not tell them: audience, quality standards, internal requirements or relevant background. Good prompts are therefore mainly good task descriptions. Templates, prompt chains and quality checks also keep their value for teams as new models arrive.

What is a prompt library and how do we maintain it as a team?

A prompt library is an organised collection of proven templates for recurring tasks, each with its purpose, required inputs, a sample result and an owner. It can live in a shared document, a wiki or directly in the AI tool's projects. In the course you set up a first library and agree simple rules for maintenance and approval.

May we use AI for automated cold outreach?

AI can prepare and personalise outreach, but the legal framework stays the same: in Germany, marketing emails generally require prior consent and B2B cold calling at least presumed consent. We show how to integrate AI into your prospecting process in a legally sound way across your target markets.

How do we connect AI to our CRM?

Many CRM systems offer built-in AI features or interfaces that automation platforms can use to read and write data. To get started, exports and copy-and-paste workflows are often enough. In the course we discuss which level of integration suits your team and how to safeguard data quality.

How much does “Prompt Engineering for Sales 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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