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What is a PIM and why should you want one?

A Product Information Management (PIM) system provides a central location for product data that is used in downstream systems. It is where you can collect and manage product data such as technical specifications and descriptions. Companies that do not yet have PIMs use various methods of data management. Some use spreadsheets managed by the product manager; others use homegrown databases, or perhaps simply rely on the catalog management software they use to publish printed catalogs. Moving to a PIM is a big step, so it should be considered carefully, as a lot of preparation is required to make that move successful.

Data consistency

So why get a PIM? The best feature of a PIM is its ability to manage product data consistently. We recommend creating an attribution taxonomy that allows specific attributes to be assigned for each category. Then the products classified in that category will inherit those attributes, along with any attributes assigned at the global level. This data will be used in various downstream systems, and it will be consistent both across the systems and across the category.

Ensuring that the same attributes and values are used in the catalog, eCommerce site, and distributor sites will avoid end user confusion.

Data completeness and governance

A PIM ensures that the data fill can be complete by providing metrics such as KPIs that detect any missing data. Data fill completeness allows all your company’s products to be visible online. If your website has a filter such as Brand, but some products are missing the value for Brand, the products with blanks in that field will then be invisible to that filter.

PIMs have systems in place for governance to ensure that the data is complete and reviewed across all categories by the right people. User groups are established to set rules as to who can see, read, and write specific sets of product data. Product managers can be assigned to specific categories and then assigned tasks to review or fill in data for products in those categories. The marketing department may have responsibility for assigning the specific attributes for content such as long descriptions and images.  This creates accountability for the data fill, ensuring that it is complete.

Downstream product management

The PIM allows for multiple taxonomies so products can be mapped to the appropriate locations in downstream systems. Your website may have a specific product taxonomy focused on navigation, and a secondary taxonomy focused on Industry. A separate taxonomy may be created to organize products going to the catalog or syndicated to distributors.   The primary taxonomy can be mapped to these downstream taxonomies and be seen from a specific product view to verify that the products and its specific data is streamed everywhere desired.

Customer satisfaction

Customers researching a product need different sets of data, that data should be accessible. Having category-specific attributes tailored to product categories ensures that the data can produce the answer to any research questions. If specific attributes or values are unavailable, customer trust in the data is diminished, and this uncertainty can extend to the product as well. Data should be complete, and should have category-specific attributes.

Personalization of data can also improve customer satisfaction. Descriptions and use cases for different user personas can enhance the online user experience. If the taxonomy is based on industry, the description can be tailored to the different industries, allowing marketing to tell the product story in different lights. A temperature sensor, for example, can have a different story for a laboratory setting versus the use of that sensor in an industrial plant. A PIM can manage descriptions in this fashion.

All of these things affect the user experience and internal process efficiencies. A PIM adds to both sides of the product data experience (external customers and internal employees) and is an important addition to the technical stack. We can help you analyze your product set and choose a PIM system that best fits your company’s needs, as well as preparing your product data for optimal PIM use. 

For a deeper dive into how we use customer data models, product data models, content models, and knowledge architecture to create a framework for unified commerce download our whitepaper: Attribute-Driven Framework for Unified Commerce


Chantal Schweizer
Chantal Schweizer
Chantal Schweizer is a taxonomy professional with over 10 years of experience in Product Information and Taxonomy. Prior to joining Earley Information Science, Chantal worked on the Product Information team at Grainger for 9 years, Schneider Electric’s PIM team for 2 years and had some previous work in PIM consulting.

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