enProduct attribute generation automation: ETIM, ECLASS and marketplaces. A guide for manufacturers.
- See how much you can save with getName.ai
- The challenge of product attribute preparation in multi-channel sales
- Key transformation points
- Specific challenges for manufacturers in preparing attributes for different platforms
- Jak getName.ai transformuje proces generowania atrybutów
- Traditional methods of product attribute preparation
- Example data preparation process using getName.ai
- How getName.ai transforms the attribute generation process
The challenge of product attribute preparation in multi-channel sales
As a manufacturer, you face the necessity of preparing data compliant with the requirements of numerous systems simultaneously - from marketplaces like Allegro, Amazon, or Kaufland, through distributors, to industry standards like ETIM or ECLASS. Each of these systems requires a specific set of attributes, in different formats and often in various languages.
getName.ai transforms this process by using artificial intelligence to automatically generate product attributes. Operating as a specialized API, it analyzes internal product data and creates attributes compliant with the requirements of target platforms and standards.
By implementing getName.ai, you can:
- Reduce data preparation time for export by up to 90%
- Cut product attribute management costs by 70-80%
- Enter new markets and sales platforms 5-10 times faster
- Automatically handle standard changes without additional work effort
- Generate attributes compliant with any international market requirements simultaneously
Specific challenges for manufacturers in preparing attributes for different platforms
As a manufacturer, you face unique challenges in the digital commerce world. Unlike pure e-commerce businesses, you must handle a much broader spectrum of distribution channels and data standards.
Diversity of marketplace requirements
Managing product data across multiple marketplaces means navigating a complex landscape of category-specific attribute requirements. Each product category may demand a unique combination of technical specifications, descriptive fields, and compliance data. As the number of marketplaces grows, handling these diverse and ever-changing requirements with traditional methods becomes increasingly unmanageable. Handling 10 or 20 marketplaces with traditional methods becomes an almost impossible task.
Complexity of industry classifications
Beyond marketplaces, as a manufacturer you face the challenge of handling industrial classification standards that are crucial for B2B sales:
ETIM - European Technical Information Model is an international classification standard for electrical, HVAC, and building materials industries, featuring over 5,600 product classes and tens of thousands of technical attributes. For manufacturers in these industries, ETIM compliance is not an option but a business necessity.
ECLASS is an even more comprehensive standard with over 40,000 product classes and hundreds of thousands of attributes, particularly important for machinery and industrial component manufacturers.
GS1/GPC is a universal product identification system used by the largest retail chains worldwide.
Costs of traditional methods
Preparing product attributes compliant with such diverse standards using traditional methods generates enormous costs of personnel, training, and lost opportunities. One specialist can process an average of 200 products per day, which creates significant cost burden when dealing with thousands of products and the need to handle multiple sales channels.
Traditional methods of product attribute preparation
Manual attribute completion
The simplest approach is manually filling product attribute values based on descriptions provided by suppliers. A specialist analyzes product descriptions and manually enters appropriate values into required fields for each platform. One specialist can process only 150-200 products daily, which becomes unfeasible with thousands of products and multiple sales channels.
Creating and maintaining data transformation rules
A more advanced approach is creating a system of data transformation rules that automatically converts internal attributes to formats required by target platforms. This process includes two key elements:
- Structural attribute mapping - one-time definition of correspondence between internal attributes and platform requirements (e.g., "our attribute 'engine_power'" → "Amazon: power_consumption", "ETIM: EF001950").
- Dictionary value mapping - creating conversion tables for text values (e.g., "black/noir/schwarz" → standard value required by the platform).
While it allows automation, any change in data structure requires rule updates, and creating complete rules for one platform can take from several weeks to months. Additionally, the appearance of new values in source data often requires extending existing mappings.
Dedicated specialists
Large enterprises often hire experts to handle individual platforms, which generates significant fixed costs and creates dependency on specific employees.
Using external services and agencies
Outsourcing product data preparation to specialized agencies can be beneficial, but comes with limitations such as high variable costs, communication delays, reduced quality control, and dependency on external partners. It works best mainly for companies with stable product catalogs and a limited number of sales channels.
All traditional approaches encounter the same fundamental problem - lack of scalability with increasing market complexity.
How getName.ai transforms the attribute generation process
getName.ai introduces a fundamental paradigm shift. Instead of relying on manual mapping or rigid rules, it leverages artificial intelligence to understand the context and semantics of product data.
Automatic generation of attributes compliant with multiple classifications
The main innovation of getName.ai is the ability to simultaneously generate attributes for multiple classifications without the need to create separate processes for each one. You provide basic product data, specify target classifications, and the system analyzes source data using advanced AI models and generates complete attribute sets.
Intelligent product feature recognition
The system "understands" the semantics of product data, identifies key technical parameters even when written in different formats, and recognizes relationships between attributes. For example, from the description "Impact drill GSB 18V-50, brushless, 2 Li-Ion 5.0Ah batteries" it automatically recognizes the tool type, voltage, motor type, battery type and capacity.
Unit conversion and value normalization
getName.ai automatically detects units in source data and converts them to units required by target classification. The system also maps text values to standard dictionaries (e.g., "black", "noir", "schwarz" → "Black") and standardizes notation formats.
Integration withexisting systems
The system doesn't require a revolution in existing IT infrastructure. Flexible REST API enables communication with most PIM systems.
Example data preparation process using getName.ai
Let's examine an example data preparation process for a medium-sized power tool manufacturer with a catalog of 2,500 products.
Source data preparation
getName.ai doesn't require special formatting of source data. The system can work with various formats and extract information even from unstructured descriptions.
Example source data:
DeWalt DCD709N-XJ 18V XR Brushless Combi Hammer Drill Driver is a compact and powerful tool designed for renovation and construction work—ideal for drilling, screwdriving, and hammer drilling in wood, steel, and other materials. Its brushless motor ensures longer runtime and greater energy efficiency, while the two-speed gearbox and high torque of up to 65 Nm deliver reliability even in the most demanding tasks. It features an LED work light for use in poorly lit areas and a convenient belt clip for easy transport. Compatible with 18V XR battery system (battery not included). Comes with a 2+1 year warranty upon online registration.
- Compact dimensions: 189 × 79 × 231 mm
- Brushless motor – greater durability and efficiency
- 2 speeds and modes: drilling, screwdriving, hammer drilling
- Impact rate: up to 28,050 bpm
- Max torque: 65 Nm
- LED work light
- Max drilling diameter: 13 mm in steel, 30 mm in wood
- 13 mm keyless chuck
- Compatible with 18V XR Li-Ion batteries (not included)
- Belt clip for convenient transport
- Warranty: 12 months + 2 years with online registration
Target classification configuration
For each product, we define the target classification and appropriate product class:
- ETIM 10: EC001371 / Drilling machine/screwdriver (battery)
- Allegro: 147662 / Screwdrivers
- Amazon: DRILL / Drill
- GS1/GPC: 10003653 / Drill/Drivers (Powered)
This configuration can be defined once for entire product groups, significantly simplifying the process - especially for large catalogs.
Automatic attribute generation
Example getName.ai API call:
{
"classification": "etim_v10_en",
"class_id": "EC001371",
"description": "DeWalt DCD709N-XJ 18V XR Brushless Combi Hammer Drill Driver is a compact and powerful tool designed for renovation and construction work—ideal for drilling, screwdriving, and hammer drilling in wood, steel, and other materials. Its brushless motor ensures longer runtime and greater energy efficiency, while the two-speed gearbox and high torque of up to 65 Nm deliver reliability even in the most demanding tasks. It features an LED work light for use in poorly lit areas and a convenient belt clip for easy transport. Compatible with 18V XR battery system (battery not included). Comes with a 2+1 year warranty upon online registration.\n\nCompact dimensions: 189 \u00d7 79 \u00d7 231 mm\nBrushless motor \u2013 greater durability and efficiency\n2 speeds and modes: drilling, screwdriving, hammer drilling\nImpact rate: up to 28,050 bpm\nMax torque: 65 Nm\nLED work light\nMax drilling diameter: 13 mm in steel, 30 mm in wood\n13 mm keyless chuck\nCompatible with 18V XR Li-Ion batteries (not included)\nBelt clip for convenient transport\nWarranty: 12 months + 2 years with online registration"
}
{
"attributes": [
{
"id": "EF004351",
"name": "Battery technology",
"type": "select",
"unit": null,
"value": {
"id": "EV007507",
"name": "Lithium-ion"
}
},
{
"id": "EF000002",
"name": "Nominal voltage",
"type": "float",
"unit": "V",
"value": 18
},
{
"id": "EF000008",
"name": "Width",
"type": "float",
"unit": "mm",
"value": 79
},
{
"id": "EF000040",
"name": "Height",
"type": "float",
"unit": "mm",
"value": 231
},
{
"id": "EF001438",
"name": "Length",
"type": "float",
"unit": "mm",
"value": 189
},
{
"id": "EF002835",
"name": "Drill diameter steel 2nd gear",
"type": "float",
"unit": "mm",
"value": 13
},
{
"id": "EF002837",
"name": "Drill diameter wood 2nd gear",
"type": "float",
"unit": "mm",
"value": 30
},
{
"id": "EF002842",
"name": "Max. torque",
"type": "float",
"unit": "Nm",
"value": 65
}
]
}
Simultaneously, for the same description, the system generates attributes compliant with Allegro marketplace requirements:
{
"attributes": [
{
"id": "237222",
"name": "Seria",
"type": "string",
"unit": null,
"value": "XR"
},
{
"id": "11323",
"name": "Stan",
"type": "select",
"unit": null,
"value": {
"id": "11323_1",
"name": "Nowy"
}
},
{
"id": "128551",
"name": "Napięcie (V)",
"type": "select",
"unit": null,
"value": {
"id": "128551_6",
"name": "18 V"
}
},
{
"id": "128552",
"name": "Informacje dodatkowe",
"type": "multiselect",
"unit": null,
"value": [
{
"id": "128552_16",
"name": "podświetlenie"
},
{
"id": "128552_1",
"name": "udar"
}
]
},
{
"id": "129634",
"name": "Typ akumulatora",
"type": "select",
"unit": null,
"value": {
"id": "129634_2",
"name": "Li-Ion"
}
},
{
"id": "204657",
"name": "Rodzaj silnika",
"type": "select",
"unit": null,
"value": {
"id": "204657_221325",
"name": "silnik bezszczotkowy"
}
},
{
"id": "209202",
"name": "Zasilanie",
"type": "select",
"unit": null,
"value": {
"id": "209202_1769478",
"name": "akumulatorowe"
}
},
{
"id": "250685",
"name": "Zawiera baterie",
"type": "select",
"unit": null,
"value": {
"id": "250685_2006717",
"name": "nie"
}
},
{
"id": "205013",
"name": "Maksymalna średnica wiercenia w drewnie",
"type": "integer",
"unit": "mm",
"value": 30
},
{
"id": "205017",
"name": "Maksymalna średnica wiercenia w metalu",
"type": "integer",
"unit": "mm",
"value": 13
},
{
"id": "205021",
"name": "Maksymalna liczba udarów",
"type": "integer",
"unit": null,
"value": 28050
}
]
}
The system would not only recognize the appropriate attributes and values, but also:
- Assign the correct identification codes
- Identify and apply standardized dictionary values
- Apply the appropriate units of measurement
- Properly format ranges (min–max)
Integration with syndication platforms
In a typical scenario, the process includes importing generated attributes to the PIM system, exporting to syndication platforms that manage final formatting and validation, and preparing export files in various formats for trading partners.
Key transformation points
Automation of product attribute generation introduces fundamental changes:
Transition from manual mapping to automatic context understanding - eliminates the need to create complex transformation rules that were the main bottleneck of traditional approaches.
From isolated channels to integrated data ecosystem - allows transition to central management of source data with automatic distribution to all channels.
From reactive to proactive data management - enables advance preparation for entering new markets and quick adaptation to standard changes.
From scale limitations to unlimited scalability - breaks the scalability barrier, offering the possibility to expand catalogs by thousands of products without proportional cost increases.
See how much you can save with getName.ai
We offer two paths to help you understand the value of getName.ai:
- Free potential savings analysis - send us information about your product count and supported channels, and we'll prepare a detailed analysis of potential savings
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