Product Data Basics

Product Data Basics is a six-hour, self-paced course about the information that makes products findable, understandable, and usable in an online shop. You will learn how to structure product data, check its quality, and organize maintenance so that important information does not disappear between teams or systems.

Product Data Basics at a glance

• Format: Self-paced, 4 modules
• Level: Basics
• Participants: unlimited
• Language: English
• Certificate: AEI certificate of attendance
• Investment: free of charge

What you take away

Product data is not just a collection of descriptions, prices, and images. It is the working information behind search results, filters, product comparisons, checkout decisions, shipping expectations, and customer service conversations. In this course, you look at the practical connection between the quality of a product record and what happens in a shop: whether a customer finds the right item, understands its properties, and receives what was expected.

You work through the basic building blocks of a reliable data setup. This includes attributes and their types, variants, categories, completeness checks, images, text, responsibilities, PIM systems, exports, and recurring maintenance. The aim is not to create a theoretical data model in isolation, but to recognize useful decisions in everyday shop work and to identify where unclear or missing information creates avoidable effort.

Your learning objectives

• You can explain how product data affects findability, product selection, and returns.
• You can distinguish attributes, attribute values, categories, characteristics, and product variants.
• You can describe a clean basic data model for products with different options or versions.
• You can check whether a product record contains the information needed for its category and sales channel.
• You can assess images and product text as structured parts of the customer experience.
• You can assign maintenance responsibilities and outline a practical routine for keeping data current.

The levers at a glance

Findability: Search and navigation can only use the information that is present and consistently labelled. If one product uses “blue” and another uses “navy” for the same filter, or if a key dimension is stored in the description for some products and in a separate field for others, customers may not see the full range. You learn to connect product fields with category pages, filters, internal search, and product comparisons.

Clarity: A customer needs to understand what is included, which properties matter, and how one version differs from another. A phone case with several device versions, a chair with multiple materials, or a shirt with many sizes can become confusing when variants are mixed together or named inconsistently. The course shows how clear attributes, values, and variant relationships reduce interpretation work for both customers and shop teams.

Completeness: A record can look finished while still missing information that is essential for a purchase decision. A product may have a title and price but no dimensions, compatibility information, care instructions, delivery-relevant details, or appropriate images. You learn to define what “complete” means for a category, rather than relying on a general feeling that a record contains enough information.

Consistency: Data quality also depends on repeatable rules. Units, spelling, naming conventions, image requirements, and allowed values should not change from one product to the next without a reason. Consistent data supports reliable exports, easier updates, and fewer corrections after publication. You examine simple checks that reveal empty fields, invalid values, duplicate entries, and differences between related products.

Ownership: Product data stays useful when someone knows what must be maintained, when it must be checked, and which system is responsible for the current version. A supplier, category manager, content editor, marketplace team, and customer service team may each see different parts of the record. You learn to turn these handovers into a manageable process with named responsibilities and a maintenance rhythm.

Who is this course for?

This course is for people who work with products or online shop content and want a shared foundation in product data. It can help shop and e-commerce teams, product managers, category managers, content editors, marketplace coordinators, customer service staff, and colleagues who prepare or review product information. It is also suitable for people who are beginning to work with a PIM system, exports, product feeds, or category-based content requirements.

It is not for people looking for advanced PIM implementation, complex data architecture, detailed feed programming, or a complete technical solution for a specific platform. The course does not replace category-specific legal review, system configuration, or an individual data audit. Instead, it provides the basic concepts needed to participate in those activities with clearer questions and a common vocabulary.

Cost and access

The course is free of charge. Sign-up takes place through the shop, and access is available immediately after registration. You can begin when it fits your work schedule and continue at your own pace across the four modules.

There is no fixed start date, live appointment, or required group timetable. The six hours are a guide for the complete course, including the lessons and time to review the examples. You can pause between lessons, return to earlier topics, and use the material when a product data question arises in your daily work.

After the course

A sensible next step is to choose one real product group and review it using the questions from the course. Check which fields are needed for a purchase decision, where values are inconsistent, which images or texts are missing, and who can correct each issue. Starting with a limited category makes it easier to distinguish a one-time cleanup from an ongoing maintenance task.

Once the first review is clear, record the rules that should apply to similar products and agree on a simple check before publication or export. This can provide a practical basis for conversations with colleagues who manage the shop, PIM, supplier information, or marketplace channels.

Programme: 4 modules

• Module 1: Why product data matters — Data decides findability; Data decides returns; The cost of poor data
• Module 2: The data model — Attributes and their types; Modelling variants cleanly; Categories and characteristics
• Module 3: Quality and completeness — What makes a record complete; Checking instead of hoping; Images and text as data
• Module 4: Maintenance as a process — Who maintains what; PIM and exports; A maintenance plan for daily work

Our approach

We work from concrete shop situations and explain the decisions behind them step by step. Examples focus on the connection between a product record and the tasks around it: preparing a new item, correcting a variant, checking a category, publishing an export, or responding to a customer who received an item that did not match its online information. The course separates useful principles from platform-specific details, so the concepts can be applied in different shop and system environments. Short explanations, practical checks, and clear terminology support learning without assuming prior data management experience.