Training course · Perplexity · Retail & E-Commerce

Perplexity for Retail

AI-powered research with Perplexity: cited answers, source control, Spaces, Deep Research and systematic fact-checking.

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

“Perplexity for Retail” is a hands-on course for roles such as E-commerce and online shop teams, Buying and category management and Store and area managers. Rather than learning Perplexity in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Retail & E-Commerce.

Perplexity combines language models with live web search and delivers answers backed by numbered citations. That makes it particularly suited to work where currency and traceability matter: market and competitor monitoring, research into regulation and standards, supplier and partner due diligence, or preparing decision papers. In this practical day you learn to phrase research questions precisely, steer the choice of sources deliberately and use follow-up questions to turn an initial answer into a robust research result.

You work with Spaces, where you group research on a topic, add your own files and set instructions for the team. With Deep Research you produce extensive reports that evaluate many sources and bring them together in a structured way. Quality is a key focus: you learn to assess sources, cross-check claims and recognise typical failure patterns such as outdated or misattributed information. We also address data protection and licensing questions for business use. You leave with a reusable research process tailored to your own function.

Whether bricks-and-mortar stores, online shops, wholesale or omnichannel, retail works with large ranges, thin margins and high customer expectations. Generative AI helps wherever there is lots of text, lots of data and lots of customer contact. It writes product descriptions and category pages, maintains product master data, answers customer service enquiries, analyses reviews and return reasons and supports promotion planning and campaigns. AI agents can check order status, pre-sort complaints or bundle supplier requests. For buying and category management, AI becomes a tool for commenting on sales data and preparing range decisions. The key is balancing efficiency, brand voice and legally accurate product information.

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 and online shop teams
  • Buying and category management
  • Store and area managers
  • Customer service and returns management
  • Retail marketing and CRM

Typical challenges we address

  • Large ranges requiring heavy effort for product copy and master data
  • High volumes of customer enquiries, complaints and returns
  • Seasonal peaks and short-notice promotions
  • Data from tills, web shop and merchandise systems that is hard to combine

What you will be able to do

  • You phrase precise research questions and steer the choice of sources deliberately.
  • You assess sources by origin, currency and reliability and trace claims back to the original.
  • You organise research in Spaces and combine web sources with your own documents.
  • You use Deep Research to produce structured reports and decision support.
  • Produce product copy and campaign content at scale with AI in a consistent brand voice.
  • Analyse customer feedback, returns and sales data with AI in a structured way.
  • Identify service cases and processes that can be automated with AI agents.

Course outline

Module 1 Foundations of AI-powered research
  • How it works: language model, live web search and citations
  • How it differs from a classic search engine and a general chat assistant
  • Framing research questions precisely: time frame, region, source type
  • Follow-ups and drilling down instead of one-off queries
Module 2 Steering and assessing sources
  • Narrowing sources: web, academic literature, your own files
  • Targeting primary sources, official websites and specialist publications
  • Assessing source quality: origin, currency, vested interests
  • Tracing quotes and figures back to the original source
Module 3 Spaces and teamwork
  • Setting up Spaces for topics, projects or client requests
  • Uploading your own documents and combining them with web sources
  • Storing instructions for consistent output formats
  • Sharing research and turning it into pages or reports
Module 4 Deep Research and structured reports
  • Tackling broad questions with Deep Research
  • Producing market overviews, competitor comparisons and topic briefs
  • Turning results into tables, side-by-side comparisons and executive summaries
  • Recognising the limits of in-depth research and refining results
Module 5 Fact-checking, data protection and workflow
  • Systematic fact-checking: counter-research and spotting contradictions
  • Typical failure patterns: outdated, misattributed or fabricated details
  • Data protection, enterprise licences and handling confidential queries
  • A reusable research process and source documentation
Module 6 Practice lab: Retail & E-Commerce
  • Product copy at scale
  • Cleaning master data
  • Supporting customer service
  • Analysing reviews and returns
  • Promotions and campaigns
  • Commenting on sales data
Module 7 Data protection, quality & transfer to daily work
  • Customer data from web shop, CRM and loyalty programmes is subject to the GDPR, and marketing activities to consent and unfair competition rules. Product information, price displays and advertising claims must comply with consumer protection law, and customer-facing AI chatbots must be disclosed as such under the EU AI 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

Product copy at scale

Manufacturer data and attributes become consistent, search-optimised product descriptions, bullet points and category pages in several languages, with mandatory details carried over accurately. Spot checks happen before publishing.

Cleaning master data

AI helps standardise product data, detect missing attributes, normalise colours and sizes and assign products to the correct categories – with spot checks by the team.

Supporting customer service

Enquiries about delivery status, exchanges, warranty or product details are classified and given draft replies; AI agents can handle standard cases directly. Complex cases are handed to staff with a summary.

Analysing reviews and returns

Customer reviews and return reasons are grouped by themes such as fit, quality or inaccurate descriptions in order to improve copy, range and suppliers in a targeted way.

Promotions and campaigns

Promotion plans, newsletters, social posts and copy for leaflets or displays are created for each target group and aligned with seasonal occasions. Results of past promotions inform the planning.

Commenting on sales data

For buying and category management, AI summarises sales data, explains variances against last year and plan and prepares arguments for supplier negotiations. Figures come from the merchandise system.

Prerequisites

Experience with online research in a professional context; no prior AI knowledge is required. Professional experience in store-based or online retail; no technical background required.

Technical requirements

A laptop with an up-to-date browser and a Perplexity account; we recommend Pro or Enterprise access to use Spaces with files and Deep Research in full.

Data protection & compliance

Customer data from web shop, CRM and loyalty programmes is subject to the GDPR, and marketing activities to consent and unfair competition rules. Product information, price displays and advertising claims must comply with consumer protection law, and customer-facing AI chatbots must be disclosed as such under the EU AI Act.

Suggested dates

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

  • Mon, 23 November 2026 Online Request
  • Wed, 9 December 2026 Stuttgart Request
  • Tue, 12 January 2027 Online Request
  • Mon, 18 January 2027 Berlin Request
  • Mon, 1 February 2027 Online Request
  • Fri, 12 February 2027 Munich Request

Frequently asked questions

How does Perplexity differ from ChatGPT or a search engine?

A search engine returns a list of links, and a general chat assistant often answers from its training data. Perplexity searches the web at the moment you ask, summarises what it finds and backs each statement with citations. That makes it particularly well suited to current, verifiable research – although you still need to assess the sources yourself.

Can I rely on Perplexity's citations?

Citations make verification much easier, but they do not replace it. Occasionally a statement is attributed to a source that does not say quite that, or an outdated page is used. In the course you learn a lean fact-checking routine that lets you quickly verify critical statements against the original source.

Is Perplexity suitable for confidential research within a company?

Enterprise plans offer additional commitments on data use and administration. Even so, you should not put trade secrets or personal data into queries unless your internal policy explicitly allows it. We discuss how to phrase queries so that sensitive details stay protected while the research remains useful.

How do I make sure AI product copy is accurate?

Feed the AI only verified product data, specify which details must not be changed and run systematic spot checks. Dimensions, materials, mandatory labelling and advertising claims are critical. In the course you develop a workflow with templates and review steps for producing copy at scale.

Is AI worthwhile for smaller retailers too?

Smaller teams in particular benefit, because AI takes on tasks there is otherwise no capacity for – such as product copy, newsletters or customer replies. Many features can be used without major investment. The course shows pragmatic starting points that work without an IT department.

How much does “Perplexity for Retail” 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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