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Using PowerClass for product classification and feature mapping
Purpose: In this article, you will learn how to use PowerClass to automatically classify your product data and map features to your desired data models. You will discover how this AI-powered tool saves time by accurately categorizing products and standardizing product information.
What is PowerClass?
PowerClass is an intelligent module within PowerSuite that helps you automatically classify products and map product features to standardized data models. The tool uses advanced AI algorithms that learn from previous classifications and analyze text to accurately assign products to the right categories.
The module offers two main functions: automatic product classification based on product descriptions, and feature mapping where product features are matched to standards from data models like ETIM, GS1, or your own webshop or marketplace structure.
Use PowerClass when you want to:
- Classify large amounts of product data without manual work.
- Standardize product information according to specific data models.
- Save time categorizing your product portfolio.
- Map product features to industry standards like ETIM, GS1, or any other data model.
How to use PowerClass
With PowerClass, you can quickly and intelligently classify and convert large volumes of product data according to a selected data model. The steps below show how to provide a dataset, assign columns, run classifications, and review and export the results.
Set up a data model
Before you can start using PowerClass, a data model must be provided and configured. Contact your account manager to have your preferred data model (ETIM, GS1, custom webshop structure, bol.com, Amazon, etc.) configured. This is a one-time setup per data model.
Upload an Excel File
- Go to the PowerClass module and click Uploads.
- Click the upload button to add a new file.
- Fill in the required fields: Dataset name, Dataset file, and Supplier.
- Click Upload to submit the file.
Note: Make sure your Excel file contains at least two essential columns:
One column that uniquely identifies each product (such as article number, GTIN, or EAN)
One column with descriptive text (product description or title) for AI analysis
(blue box)
Perform Column Mapping
- Go to Column Mapping and select your uploaded dataset.
- Assign the key columns: Product ID and Description.
- Configure the remaining columns as needed.
Explanation of all mapping options:
Product ID: Select the column that uniquely identifies each product
Description: Choose the column with product descriptions (used by the AI for classification)
Class: For existing classification information
Feature: For relevant product features
Image URL: For product images
Ignore: For columns you do not want to include
Run Classification
- Go to Classification (or Multi Classification if available).
- Select your dataset and desired data model.
- Click Classify to start the classification process.
Processing times:
< 1,000 products: approx. 5 minutes
1,000 – 10,000 products: approx. 15 minutes
> 10,000 products: more than 15 minutes
Note: You need to contact your account manager to activate the Multi Classification feature.
Multi Classification allows a single product to be assigned to multiple categories at once, instead of just one main category.
Difference with standard classification:
Standard classification:
One product = one category
iPhone 15 → Mobile phones
Multi Classification:
One product = multiple categories
iPhone 15 → Mobile phones + Photography equipment + Gaming devices
Review and adjust results
After classification, you will see the following for each product:
- Status: Checked (approved), Unchecked (not yet reviewed), In Progress (under review).
- Suggested classification: The product category assigned by the AI.
- Set by: Indicates whether the classification was done by AI or a user.
You can now:
- Edit individual products: Click a classification to change it.
- Apply bulk updates: Select multiple products and use the bulk update feature.
- Change status: Mark products as approved or in progress.
The system learns from your edits and continuously improves future classifications.
Match features
- Go to Match Features
- Select your dataset and data model.
- Choose a 'Supplier feature' and a 'Data model feature', then click 'Add new match' to create manual matches.
- Click 'Convert' when you are satisfied with the mapping.
Good to know:
For numerical features, you only map the attribute itself
For alphanumeric features, you can also map values
Export results
Once classification is complete, export your results as follows:
- Go to the Exports tab.
- Choose your export method: Excel or BMEcat.
- In the export window, select the Dataset, Data model, and Export method.
- Click the export button to generate the file.
Export methods explained:
Classification: Only classification information
Conversion: Classification plus feature mapping to the data model
Your exported files will appear in the list with date and download options. These files contain your original product data enriched with the new classifications and mapped features according to the selected data model.
