Training course · Make · Marketing

Make for Marketing Teams

Automation with Make (formerly Integromat) and AI modules: build scenarios, routers and AI steps while keeping data protection in check.

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

“Make for Marketing Teams” is designed for roles such as Marketing managers and heads of marketing, Performance and digital marketing specialists and Product and brand managers and shows step by step how to use Make productively, safely and transparently in Marketing – from the fundamentals to advanced workflows.

Make, formerly known as Integromat, is a visual automation platform that lets you connect applications and automate recurring processes without writing code. Over two days you will learn to build scenarios systematically, from triggers and modules through routers and filters to iterators, aggregators and data stores. You will understand how data flows through a scenario, how to reshape it with functions and how to keep an eye on operations consumption.

The second focus is AI. You connect language models through Make’s AI modules and provider integrations to classify text, extract information from emails and documents, draft replies or enrich content. You learn to catch errors with error handlers, test scenarios and document them clearly. Finally, you address data protection topics such as hosting region, data processing agreements and data minimisation, so that your automations can be run safely within your organisation.

Marketing teams now cover more channels, audiences and formats than ever, often on the same budget. Generative AI is fundamentally changing the work: AI assistants support market research, persona development and positioning, draft campaign concepts, landing page copy and ad variants and analyse campaign data. AI agents and automation take over routines such as adapting content for different channels, reporting or enriching leads. The value does not come from mass production but from faster testing, better personalisation and more time for strategy and creativity. Clear brand guidelines as the foundation for prompts, careful handling of customer data and editorial review keep content accurate, legally sound and on brand.

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?

  • Marketing managers and heads of marketing
  • Performance and digital marketing specialists
  • Product and brand managers
  • Marketing operations and CRM owners
  • Agency staff

Typical challenges we address

  • Delivering a consistent brand message across many channels and formats
  • Testing campaigns quickly and drawing meaningful conclusions
  • Sharpening target groups and personas with data
  • Organising content production and approvals with limited resources

What you will be able to do

  • You can build Make scenarios independently using triggers, routers, filters and data transformations.
  • You can process lists and records with iterators, aggregators and data stores.
  • You can integrate AI modules for classification, extraction and text generation into your processes.
  • You can safeguard scenarios with error handlers, validation and human approval.
  • Use AI for audience analysis, campaign concepts and copy variants within your brand guidelines.
  • Analyse campaign data with AI support and make well-founded decisions.
  • Automate marketing routines in a privacy-compliant way with clear approval steps.

Course outline

Day 1

Module 1 Fundamentals: scenarios, modules and data flow
  • Interface layout, scenario editor and execution history
  • Triggers, actions and searches: module types and their role in a scenario
  • Understanding bundles, mapping and data types and using them deliberately
  • Choosing between schedules, webhooks and instant triggers
Module 2 Logic: routers, filters, iterators and aggregators
  • Using routers and filters for branching and conditional flows
  • Splitting lists with iterators and combining them with aggregators
  • Applying text, date and maths functions to transform data
  • Using data stores and variables for interim values and duplicate checks
Module 3 AI building blocks in Make
  • Connecting language models via AI modules and provider integrations
  • Automating classification, structured data extraction and text generation
  • Building prompts from scenario variables and processing output as JSON
  • Combining AI agents in Make with tools and scenarios as actions
Module 4 Integrations, error handling and testing
  • Connecting common business applications and any API via the HTTP module
  • Applying error handlers such as Resume, Ignore, Break and Rollback
  • Validating AI output and routing unusable results to a person
  • Testing scenarios, optimising operations and documenting them for the team

Day 2

Module 5 Data protection, governance and operations
  • Assessing hosting region, data processing agreements and data flows to AI providers
  • Applying data minimisation and pseudonymisation within scenarios
  • Managing connections, teams and permissions across the organisation
  • Defining approval steps, monitoring and ownership for live operation
Module 6 Practice lab: Marketing
  • Audiences and personas
  • Campaign concepts
  • Ad and copy variants
  • Campaign reporting analysis
  • Competitor monitoring
  • Marketing automation
Module 7 Data protection, quality & transfer to daily work
  • Marketing use of AI must comply with the GDPR and ePrivacy rules on tracking, consent and personalisation; customer data belongs only in approved tools. Unfair competition law applies to advertising claims, copyright and trademark law to generated content, and the EU AI Act's transparency duties to AI-generated media.
  • 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

Audiences and personas

An AI assistant condenses market studies, customer feedback and sales notes into personas with needs, objections and buying criteria, then derives key messages and value propositions for campaigns.

Campaign concepts

From the brief, goals and budget, AI develops several campaign ideas with a central idea, channel mix, messages and KPIs, which the team evaluates, combines and refines.

Ad and copy variants

AI creates variants of headlines, ad copy, subject lines and calls to action within brand guidelines and prepares A/B tests whose results are then analysed.

Campaign reporting analysis

Exports from ad platforms, web analytics and CRM are combined, anomalies explained and recommendations drafted, so reporting meetings can focus on decisions rather than data gathering.

Competitor monitoring

AI summarises publicly available information on competitors, such as website messaging, product launches and pricing communication, and highlights differences from your own positioning.

Marketing automation

Workflows enrich new leads, segment contacts, draft personalised nurture emails and notify sales as soon as a lead meets defined qualification criteria.

Prerequisites

You should be comfortable with common office and cloud applications and have some experience with AI assistants. No programming skills are required. You work in marketing or at an agency and understand the basics of campaign planning and digital channels.

Technical requirements

You will need a laptop with an up-to-date browser and a Make account; the free plan covers most exercises. API access for a language model is set up together during the course.

Data protection & compliance

Marketing use of AI must comply with the GDPR and ePrivacy rules on tracking, consent and personalisation; customer data belongs only in approved tools. Unfair competition law applies to advertising claims, copyright and trademark law to generated content, and the EU AI Act's transparency duties to AI-generated media.

Suggested dates

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

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Mon, 7 December 2026 – Tue, 8 December 2026 Bremen Request
  • Thu, 7 January 2027 – Fri, 8 January 2027 Augsburg Request
  • Tue, 19 January 2027 – Wed, 20 January 2027 Online Request
  • Thu, 28 January 2027 – Fri, 29 January 2027 Salzburg Request
  • Thu, 4 February 2027 – Fri, 5 February 2027 Online Request

Frequently asked questions

Is Make the same as Integromat?

Yes. Integromat was renamed Make and substantially developed along the way. The core principle of visual scenarios made of connected modules remains, while a redesigned interface, many new integrations and AI building blocks have been added. If you used Integromat in the past, you will quickly feel at home and discover the new capabilities on the course.

How do I keep operation costs under control?

Every module that runs consumes operations or credits, and AI calls also use quota with the respective model provider. On the course you learn to design scenarios so that filters apply early, unnecessary runs are avoided and data is processed in batches. This keeps your automations economical and predictable as volumes grow.

Can Make be used in a GDPR-compliant way?

In principle yes, provided you set up the framework deliberately. This includes choosing the hosting region, signing a data processing agreement, reviewing connected AI services and applying data minimisation. On the course you work through these points with a checklist and learn to filter or pseudonymise sensitive data within scenarios.

How do we keep AI-generated content on brand?

Start with well-documented brand guidelines covering tone of voice, sample copy and banned terms, and provide them as context to AI assistants. Combined with reusable prompt templates and editorial approval, this produces consistent copy. In the course we build such templates together for your channels.

Who owns the rights to AI-generated content?

Purely machine-generated content is generally not protected by copyright in many jurisdictions, including Germany, whereas works substantially shaped by people can be. You also need to check that outputs do not infringe third-party rights such as trademarks or well-known imagery. We discuss practical rules for approval and labelling.

How much does “Make for Marketing 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.

More courses for Marketing Teams

More Make courses

All 45 Make courses

Make · MunichMake · SalzburgMake · BerlinMake · AugsburgMake · HanoverMake · BremenMake · StuttgartMake · KaiserslauternMake · Online