Training course · n8n · E-Commerce

n8n for E-Commerce Teams

Workflow automation with n8n and AI: master nodes, the AI Agent node, integrations and GDPR-friendly self-hosting in practice.

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

“n8n for E-Commerce Teams” is a hands-on course for roles such as E-commerce managers and shop owners, Marketplace and category managers and Product data and PIM managers. Rather than learning n8n in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from E-Commerce.

n8n is a flexible workflow automation platform that combines visual flows with language models and hundreds of integrations. Unlike many cloud services, n8n can also be self-hosted, so your data can stay in your own data centre or with a European hosting provider. Over two days you will learn how triggers, nodes and data flows fit together, how to transform data between applications and how to automate recurring tasks from your day-to-day work reliably.

The core of the course is the combination of automation and AI. Using the AI Agent node, chat models, memory and tools, you build workflows that classify emails, summarise documents, enrich records or answer enquiries. You learn to catch errors, test workflows and document them properly. Finally, you look at hosting options, credential management and data protection, so that your automations run stably, securely and in line with GDPR once they go into everyday operation.

In e-commerce, every product page, search query and customer enquiry counts. Generative AI opens up new possibilities for online retailers and brands: AI assistants create and optimise product descriptions, translate catalogues, structure product attributes, analyse customer reviews and support marketplace listings. Automation and AI agents maintain product data, monitor prices and stock, answer routine questions and prepare campaigns for sales events. Shop analytics also become more accessible, because questions about conversion, baskets and returns can be asked in natural language. Success requires clean product data, clear quality rules for generated copy and compliance with the many information obligations in online retail. Then AI becomes a lever for visibility, conversion and efficient operations.

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?

  • E-commerce managers and shop owners
  • Marketplace and category managers
  • Product data and PIM managers
  • Digital marketing and SEO specialists
  • Founders and owners of online shops

Typical challenges we address

  • Keeping thousands of product records complete, consistent and multilingual
  • Increasing visibility in search engines and on marketplaces
  • Analysing and handling returns, reviews and customer enquiries efficiently
  • Delivering sales events and range changes with limited resources

What you will be able to do

  • You can build n8n workflows independently using triggers, logic nodes and data transformations.
  • You can connect n8n to the applications you use every day and fall back on the HTTP Request node where needed.
  • You can use the AI Agent node and other AI building blocks for classification, extraction and summarisation.
  • You can safeguard workflows with error handling, validation and human approval steps.
  • Create and maintain product content efficiently, in several languages and at consistent quality with AI.
  • Analyse shop, review and returns data with AI and derive concrete actions.
  • Design AI-supported shop processes in compliance with consumer protection and data protection law.

Course outline

Day 1

Module 1 Fundamentals: workflows, triggers and nodes
  • Getting to know the n8n interface, canvas and execution view
  • Trigger types: schedules, webhooks, incoming email and app events
  • Understanding items and JSON data and working with expressions
  • Using core nodes such as Edit Fields, IF, Switch, Merge and Loop Over Items
Module 2 Integrations and data processing
  • Connecting common applications: email, spreadsheets, CRM, collaboration and cloud storage
  • Using the HTTP Request node for APIs without a ready-made integration
  • Creating, managing and sharing credentials securely within the team
  • Filtering, merging and reshaping data and writing it to target systems
Module 3 AI in n8n: the AI Agent node and LLM building blocks
  • Connecting chat models from different providers as well as locally hosted models
  • Configuring the AI Agent node with a system prompt, memory and tools
  • Automating classification, structured data extraction and summarisation
  • Using your own documents via vector stores for retrieval-augmented generation
Module 4 Error handling, testing and maintainability
  • Setting up error workflows, retries and failure notifications
  • Validating AI output and defining fallbacks for unusable responses
  • Working with pinned test data and tracing past executions
  • Modularising, naming and documenting workflows for colleagues

Day 2

Module 5 Self-hosting, data protection and operations
  • Cloud versus self-hosted: effort, control and licensing model compared
  • Assessing data flows to AI providers against GDPR requirements
  • Managing access rights, logging and retention of execution data
  • Adding human-in-the-loop approval steps to automated processes
Module 6 Practice lab: E-Commerce
  • Product description generation
  • Product data enrichment
  • Catalogue translation
  • Reviews and return reasons
  • Marketplace listing optimisation
  • Natural language shop analytics
Module 7 Data protection, quality & transfer to daily work
  • Online retail is subject to extensive consumer information duties, price indication rules, unfair competition law for product claims and the Digital Services Act for platforms; AI-generated copy must not contain misleading statements. Customer data from orders and reviews must be processed in line with the GDPR.
  • 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

Product description generation

Using manufacturer data, attributes and brand guidelines, AI creates search-friendly product copy, bullet points and meta descriptions, which the team spot-checks and approves.

Product data enrichment

AI extracts attributes such as material, dimensions or compatibility from data sheets, normalises spelling and assigns products to the right category to improve filters and on-site search.

Catalogue translation

Product copy is translated and localised for new markets using a glossary for brand terms and units, with native-speaker review for key pages.

Reviews and return reasons

Customer reviews and return reasons are clustered by topics such as fit, quality or delivery, so buying, product development and content teams can make targeted improvements.

Marketplace listing optimisation

AI adapts titles, bullet points and keywords to the requirements of individual marketplaces and checks listings for missing mandatory information or policy violations.

Natural language shop analytics

Exports from the shop system and web analytics are analysed with AI, for example conversion rate by category, basket abandonment or best-sellers, including hypotheses for optimisation tests.

Prerequisites

You should be confident with common office applications and have basic experience with AI assistants. No programming is required, although a basic grasp of structured data is helpful. You work in an online shop, on marketplaces or in digital retail and have a basic understanding of your shop system.

Technical requirements

You will need a laptop with an up-to-date browser. We provide an n8n environment for the exercises, or you can use your own instance; API keys for a language model are set up together during the course.

Data protection & compliance

Online retail is subject to extensive consumer information duties, price indication rules, unfair competition law for product claims and the Digital Services Act for platforms; AI-generated copy must not contain misleading statements. Customer data from orders and reviews must be processed in line with the GDPR.

Suggested dates

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

  • Thu, 26 November 2026 – Fri, 27 November 2026 Online Request
  • Wed, 9 December 2026 – Thu, 10 December 2026 Stuttgart Request
  • Mon, 11 January 2027 – Tue, 12 January 2027 Online Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Berlin Request
  • Tue, 2 February 2027 – Wed, 3 February 2027 Online Request
  • Thu, 11 February 2027 – Fri, 12 February 2027 Munich Request

Frequently asked questions

Do I need to code to work with n8n?

No. Most workflows are built visually by connecting nodes. During the course you also learn simple expressions to reference and reshape data precisely. A Code node is available for special cases but is not essential. A logical understanding of processes and data fields is entirely sufficient to get started.

Why is n8n attractive from a European data protection perspective?

n8n can be self-hosted, for instance on your own servers or with a European hosting provider. This keeps you in control of where workflow and execution data is stored. What still matters is which data you send to external AI services. On the course you learn to assess these data flows and, where appropriate, connect locally hosted models.

How does n8n differ from Make or Power Automate?

All three automate processes across applications. n8n stands out for its self-hosting option, its fair-code licensing and particularly flexible AI building blocks such as the AI Agent node. Make offers a very approachable cloud interface, while Power Automate excels at deep Microsoft integration. The course puts these differences into context for typical scenarios.

Does AI-generated product copy hurt SEO?

Not if it is helpful and unique. The problem is interchangeable copy that merely rephrases manufacturer information. Precise attributes, usage examples, answers to frequent customer questions and a quality check produce copy that convinces search engines and shoppers alike. We practise exactly these prompting and review routines.

Who is liable for errors in AI-generated copy?

The retailer is liable for all product information, regardless of how it was created. Incorrect dimensions, materials or efficacy claims can lead to legal warnings. AI copy should therefore be based only on verified product data, and sensitive claims such as health or environmental statements should be approved separately.

How much does “n8n for E-Commerce 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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