Product information management

• Product data management is the use of software or other tools to track and control information related to a particular product. The managed data usually involves the descriptions and technical specifications of a product.
• Product resource management is used by some software providers as a synonym for PIM, as well as product content management, mainly popular as a term in England and France.
• Product life-cycle management refers more to a management strategy than to a specific information technology, the goal of which is to optimize the entire life cycle of a product from inception, through engineering design and manufacturing over time.
• Media asset management or digital asset management refers to the management of unstructured multimedia objects such as images, graphics and presentations as well as ‘meta-information’ (data about data). The term is used primarily in the media business.
• Cross media publishing comes from the print and advertising industries, referring to the coordinated use of multiple media in complementary fashion. It also denotes the repeat usage of individual structural elements such as text, images or graphics within different media.
• Product Information Management & Syndication, which stresses the need for capabilities to seamlessly disseminate product content through (online) sales channels.[5]
• Product experience management is a practice for a company to deliver customers an experience around its products or services throughout the customer lifecycle.[6]
• Item Master is another term used to refer to the technology that collects, organises and controls the product information within a company.[7]

PIM systems consolidate all product information onto a single platform. It helps connect retailing and manufacturing channels to counter complex challenges in managing and maintaining product data quality. In terms of company information technology infrastructure, this means having a PIM platform running over or alongside a database with an application server, and/or XML-based exchange of product information. This forms a foundation upon which to build sales and procurement business processes. With PIM solutions, access and user authorizations for all database information, ordering processes linked with inventory management systems and the mechanisms for modular expansions are managed via a web-based administration interface.

Point of sales systems and online shopping platforms such as online marketplaces are based upon electronic catalogues. PIM systems can load descriptive product information as content into a catalogue management solution, where products are grouped and managed for specific target markets. Data exchange interface standards such as Open ICEcat allow seamless interchange of electronic catalogues between vendors on the one hand and purchasing firms and marketplace operators. E-procurement solutions are closely related, which automate the procurement process for purchasing goods and services. These create transparency for the product data of multiple vendors to support the centralized management of multi-supplier catalogues and facilitate price and quality research.

Data management systems are often not interoperable meaning that data exchange without PIM can lead to severe repercussions for a business. Some companies use master data management as an information technology resource in lieu of PIM. But master data management systems are not a business application and often lack usability, product data management capability including data enrichment, validation and workflow rules, which impact return on investment.[8][9]

PIM has witnessed a transformative synergy with Artificial Intelligence (AI), offering enhanced capabilities in the realm of product data management. AI serves as a virtual assistant, supporting product enrichment and decision-making across various business processes within PIM. A few high-impact use cases include auto attribution and writing product copy. AI plays a crucial role in auto attribution, employing neural networks and computer vision to validate attributes applied by team members while suggesting potentially overlooked or missed attributes. This not only ensures the accuracy of product data but also enables automated product categorization, enhancing assortment variety per category and powering search, navigation, and personalization/recommendation systems. Additionally, AI contributes to auto copywriting by swiftly generating product descriptions based on enriched attributes and user prompts. This aids in efficiently crafting diverse romance copy for product categories that share similar descriptions, allowing for rapid content creation and enrichment.[10]

Enterprise content management is a term encompassing technologies, methods and tools used for gathering, imaging, storing, archiving and providing electronic content. Distinction can be made between four separate sub-areas. Document management systems are deployed for archiving, and product data management involves the management of structured, technical data for such applications as parts diagrams and lists. Content management systems are more commercially oriented and provide a framework for knowledge management or informational service offerings through the management of unstructured, document-type content. PIM systems are used to manage structured data in a business context for feeding into any kind of distribution channel, from electronic catalogues to online shops to print catalogues.

• Identity resolution
• Open Icecat