Is a separate product information system required if most of the data is already in ERP?

If ERP conveniently manages all the attributes, options, images, documents and publication rules needed, a separate PIM may not be required. It becomes meaningful when product information has multiple sources, many category-specific attributes, and must be equally prepared for multiple channels.

Where should the price and share of the product be managed?

The responsibility of this decision is product information, not pricing rules. PIM can transfer the fields required for price representation, but the final price and terms of the share must come from a pricing decision or other clearly designated source.

How do you manage categories that require different attributes?

Common product identifiers and publication status may be the same, but category technical attributes have their own meanings, units, and approval rules. Category specialists determine mandatory facts and dependencies; only matching requirements are shared.

How does PIM help you prepare a range faster for sale?

The Product Information Management System (PIM) helps to collect, verify, and transmit to channels the data needed for a specific category. The catalog team sees flaws before publication. The sale can use the same confirmed information online and in stores.

Retail chain product information management system (PIM)

The product team prepares a description of the item and forwards it to the sales channels. When the supplier changes the data, you can see where the information is yet to be updated.

The supplier's specified dimensions, composition, set-up or images are individually changed in e-commerce and descriptions used by employees. The consultant and the customer rely on different information, and the catalog team rechecks the data already arranged.

How the solution works

Getting supplier's product data and separating specific goods
Category verification distinguishes between missing or conflicting information
Responsible employee approves publication version
Channels return the receiving result, and errors are forwarded to fix

Key challenges

Product information and attributes vary between channels

Solution capabilities

Product Model and Its Features

The category data separates the main model from the size, color or set so that the channels do not mix different goods sold.

Information necessary for publication

The category's responsible employee determines what parameters, images and documents are required for the customer to decide and describe the product properly.

Approval of changes to supplier

The resulting adjustment is compared to the valid description. Controversial information is returned for clarification before it is published.

Publication and its result

The team sees which version of the product description is passed to each channel and what transmission errors need to be removed.

Business context

Product information and attributes vary between channels: The supplier's specified dimensions, composition, set-up or images are individually changed in e-commerce and descriptions used by employees. The consultant and the customer rely on different information, and the catalog team rechecks the data already arranged.
The range is more quickly ready for sale: The new product requires an accurate description of the properties, images and channels. By managing this data together, it is possible to shorten the path from supplier information to the offer visible to the buyer. Consistent delivery helps compare goods and reduces questions for consultants before purchase.

Core features

Product Model and Its Features
Information necessary for publication
Approval of changes to supplier
Publication and its result

Key integrations

ERP / Commodity Accounting System: SKU codes, suppliers, packaging, accounting units and other commercial bases.
Supplier Data Sources: Attributes, documents and updates provided by the manufacturer or supplier.
E-commerce and the app: Approved product names, attributes, variants, images and documents.
POS and label systems: The store requires product description, codes, units of measurement and labeling data.

Potential impact (%)

The ranges indicate an illustrative relative change in the metric under the stated assumptions. Results depend on the starting position and actual use of the solution. Percentages for different metrics must not be added together.

Part of manual product data corrections in channels

12–42%Decreasing

This illustrative scenario assumes that 30-60% of errors can be addressed through the data and rule checks described. That share is assumed to fall by 40-70%. Company data is needed to verify both the addressable share and the resulting change.

Product data corrections made already after publication in the sales channel are counted. The percentage is calculated on the number of all products that have been published.

Time from Product Data Retrieval to Full Publication on Selected Channels

6–25%Decreasing

This illustrative scenario assumes that 20-50% of waiting caused by missing information or unclear responsibility can be addressed. That share is assumed to fall by 30-50%. Company data is needed to verify both the addressable share and the resulting change.

Comparisons are made between obtaining a minimum vendor or internal dataset and publication of the product on all channels involved in the selected stage.

Share of product reviews completed with purchase

4–19%Increasing

Sample starting portion - 5%. Assumption: 2-5% of the remaining cases involve insufficient product information at the time of purchase; a solution would help solve 10-20% of these cases.

Sessions that have ended the purchase are divided by all comparable sessions with product preview. Prices, advertising, availability and returns are taken into account.

Conditional calculation scenarios. The assumptions have not been validated against client measurements.

When this solution is relevant

Descriptions, parameters and photos of the same item are maintained separately across several sales channels.
It takes time to prepare new goods for sale as employees collect and check supplier data manually.

Implementation requirements

For catalog management, product fact sources, mandatory attributes and publishing responsibilities are determined. Data fixes must achieve a realistic product display across all channels used while maintaining the change and validation history.