Training course · Google Gemini · E-Commerce

Google Gemini for E-Commerce Teams

Make productive use of Google Gemini and Gemini in Workspace: Docs, Sheets, Gmail, Meet, custom Gems and NotebookLM for your sources.

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

“Google Gemini 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 Google Gemini in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from E-Commerce.

For organisations running on Google Workspace, Gemini is the natural AI assistant: it is available as a standalone app and is also built directly into Gmail, Docs, Sheets, Slides, Drive and Meet. In this practical day you learn to combine both access points deliberately. You summarise email threads and draft replies, create document drafts based on existing files in Drive, structure and analyse spreadsheets in Sheets and have Meet take meeting notes automatically – always with a focus on your own day-to-day workflows.

You also build your own Gems: specialised assistants with fixed instructions and knowledge files that standardise recurring tasks across the team. With Deep Research you produce well-founded research reports, and you use NotebookLM as a source-grounded workspace that answers only from your own documents and cites the relevant passages. A dedicated module covers data protection and administration in Workspace environments. You leave with tested prompts, a working Gem and a clear picture of which Google tool suits which task.

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 use Gemini in Gmail, Docs, Sheets, Slides and Meet for your recurring tasks.
  • You write prompts that bring existing Drive files and emails into the context.
  • You build a custom Gem and share it with your team.
  • You work source-grounded in NotebookLM and obtain referenced answers from your own documents.
  • 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

Module 1 Gemini fundamentals and effective prompts
  • The Gemini app and Gemini in Workspace: access points and use cases
  • Prompts with task, context, format and references to Drive files
  • Web search, Deep Research and checking sources
  • Limitations, hallucinations and critical evaluation of output
Module 2 Gmail, Docs and Slides
  • Summarising email threads and drafting context-aware replies
  • Drafting, rewriting and tailoring documents in Docs
  • Pulling in and combining content from Drive files
  • Creating presentation content and images in Slides
Module 3 Sheets and Meet
  • Structuring tables, generating formulas and cleaning data
  • Analyses, summaries and charts in Sheets
  • Letting Meet take meeting notes automatically
  • Deriving action items and decisions from meeting notes
Module 4 Gems and NotebookLM
  • Creating custom Gems with instructions and knowledge files
  • Testing, improving and sharing Gems with the team
  • NotebookLM as a source-grounded workspace for your own documents
  • Generating summaries, study aids and audio overviews from sources
Module 5 Data protection, administration and rollout
  • Privacy commitments for Workspace customers versus personal accounts
  • Drive sharing settings and how they affect Gemini results
  • Handling personal and confidential data in line with GDPR
  • Usage policies and quality assurance within the team
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

Confident everyday use of Google Workspace (Gmail, Drive, Docs, Sheets); no prior AI knowledge is required. You work in an online shop, on marketplaces or in digital retail and have a basic understanding of your shop system.

Technical requirements

A laptop with an up-to-date browser and a Google Workspace account with Gemini features enabled; alternatively a Google account for the Gemini app and NotebookLM.

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.

  • Fri, 27 November 2026 Online Request
  • Tue, 1 December 2026 Augsburg Request
  • Mon, 14 December 2026 Online Request
  • Wed, 20 January 2027 Kaiserslautern Request
  • Tue, 2 February 2027 Online Request
  • Fri, 19 February 2027 Bremen Request

Frequently asked questions

What is the difference between the Gemini app and Gemini in Workspace?

The Gemini app is a standalone chat assistant for research, writing and analysis. Gemini in Workspace works directly inside Gmail, Docs, Sheets, Slides and Meet and can draw on your emails and Drive files. In practice they complement each other: the app for open questions, the integrated version for work on specific documents.

Why would I use NotebookLM in addition to Gemini?

NotebookLM restricts its answers to the sources you upload – policies, studies or project files, for example – and points to the relevant passages. This reduces hallucinations and works well for getting up to speed on a topic, building internal knowledge collections or preparing training material. Gemini is broader in scope and can also draw on the web.

Is my Workspace data used to train Gemini?

For Google Workspace customers, Google commits that content from Gmail, Drive and other services is not used to train models outside your domain without permission. Different rules apply to personal accounts. Either way, GDPR and your internal policies remain decisive – in the course we review the relevant settings together.

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 “Google Gemini for E-Commerce 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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