Product Data Management vs Product Information Management: What You Need to Know

Product data management and product information management might sound like the same thing – how different is product data from product information? However, the terms are not used interchangeably. The industry considers them to have different types of functionality, serve different stakeholders, and support different processes.

How is Product Data Management Different from Product Information Management?

Product data management (PDM) refers to the management of data and information throughout the lifecycle of a product from ideation through product design, engineering, and manufacture. Product data management improves the efficiency of product development, which leads to reduced costs. Product data management manages collaboration and creates audit trails for design decisions. Product lifecycle management (PLM) software serves a similar function. Each of these tools also creates a knowledge repository to capture institutional knowledge and lessons learned from prior product development programs, which successful product management depends on.

Product information management (PIM), in contrast, serves the upstream needs of product information managers and the downstream needs of marketing teams that are supporting sales and ecommerce. So this software focuses on fulfilling the information needs of individuals in the company need to describe products or interact with product information. A PIM solution can manage data feeds from multiple sources – internal sources merged with suppliers’ data -- and can syndicate data out to sales or distribution channels. A PIM solution manages the product taxonomy and attributes of product data that are important for finding the right product through searching and filtering a large number of products in a product catalog on an ecommerce site, for example.

Some PIM software manages product information that is related to the interactions that individuals in different roles (customer support, sales, or marketing) might have that involve the product. Images, product sheets, and specification sheets are all digital assets that might be stored in a PIM system. They may also be stored in a digital asset management (DAM) system. The line between DAM and PIM systems can blur when a decision must be made about where product content for ecommerce should be stored and managed. Many ecommerce platforms manage related product information such as product reviews, instructions for installation or use, warrantee information and other content that help with customer engagement.

A PIM solution can also store product content to support the customer experience. Frequently, different versions of product descriptions tailored to the needs of different customers are managed in a PIM system. A PDM system would rarely contain this type of marketing or ecommerce assets, however, just as a PIM system would not typically contain engineering change documentation.  

Broadly speaking, PDM and PIM together can handle all data aspects of a product’s lifecycle and use, providing a complete product experience management method. The user might be a U.S.-based engineer looking for relevant CAD files created by trading partners in India, a product marketer hunting for material for a promotional campaign. , or a customer browsing an online catalog. All the information about the your products should be readily available to whomever needs it, when and where they need it.

That is the ideal situation. However, the use cases involving products are diverse – commerce is the final objective of product development, but is far downstream from engineering and design. A PIM solution is likely more closely integrated into an ecommerce platform than a PDM platform, given the usual functions of each one. The result is that getting all the needed information into one system can be difficult. Integration of PIM and PDM would be of value, of course. PDM typically includes new product data and details that are potentially important to customers and commerce applications. After all, customer stories inform features and functions. In some cases, the content may be more technical and become part of related product content rather than being incorporated into the PIM tool. Sourcing and organizing data about your products-accurate and complete descriptions, technical specifications, images, and related content needs to be harvested from multiple sources and managed in the appropriate systems – some in the PDM solution, some in the PIM solution, and some in the digital commerce system that handles the actual sales.

More Alphabet Soup - ERP, MDM & PIM

Within an organization multiple other systems may be associated with this process, including enterprise resource planning (ERP) and master data management (MDM). Too frequently, these systems are disconnected, slowing down the flow of information among them. Top performing brands understand that they cannot achieve operational excellence without integrating and harmonizing the data within these multiple systems – ERP, MDM, and PIM. Accurate product information requires the correct business process for onboarding and managing new products in order to optimize the customer experience.

PIM software can act as a connector to these different tools. It can be the source of product information management for ecommerce and be a source of product information truth for master data management technology In turn, the MDM tool can integrate with ERP. Collectively, these systems contain a company’s most valuable assets - the information about their products and the corporate knowledge related to their inner workings. To be competitive, leading brands find ways to leverage that information and make it work harder by investing in the information architecture that supports seamless processes.

The PIM market is diverse. Product information management software vendors include Akeneo PIM, Stibo systems, Riversand, InRiver, Jasper PIM, Enterworks, Informatica, Agility PIM, and Salsify, to name just a few. Each PIM platform has strengths and weaknesses or areas of specialization. Some are more specialized for B2B ecommerce applications, others for B2C. Others support vertical such as in grocery stores, or functionality such as complex product configuration management. A collection of reviews of PIM can be found at the

Product Data Management, Product Lifecycle Management and Master Data Management

Given that PDM software is closely related to PLM software, some consider PDM to be a subset of PLM. But there are many examples of standalone PDM software. Providers of PDM software include Dassault Systèmes, Synergis, and Stratasys. Other providers include PDM capabilities within PLM software, such as AutoDesk. A PDM system is a beneficial tool that can help manage design data, reduce errors and costs, and use resources effectively. It helps ensure there is a common understanding about a product through its entire lifecycle, and the impact of multiple designs and engineering change order requests on the manufacturing process.

A PLM system is an especially critical information technology in the manufacturing space. Big data and machine learning are for creating digital twins – the software engineering model represents physical products in operation. These models contain multiple applications, including CAD data to simulate all aspects of complex real-life conditions and scenarios.

PDM also relates to MDM , which controls the usage of information throughout the enterprise. One of the main applications of MDM is in supporting a 360-degreeview of the customer as part of a strategic plan. This view provides insight into what customers are buying, which channels they're purchasing from, and their household or relationships with other customers and prospects.

What is Metadata Management?

Metadata is "data about data." Metadata describes a digital asset in a predefined and structured way. None of the systems discussed above can function without metadata.

There are three main types of metadata :

  1. Descriptive metadata: Descriptive metadata describes a resource for purposes such as discovery and identification. For example, the title, abstract, author and keywords are used to find documents of interest.
  2. Structural metadata: Indicates how compound objects are put together, such as how pages are ordered to form chapters.
  3. Administrative metadata: Provides information to help manage a resource, such as when and how it was created, file type and other technical information, and who can access it.

In a PIM system, this product data metadata is referred to as attributes. Product data attributes are commonly exposed on web sites in the form of search filters. If you are looking for a lawn mower, the filters offered might include power type, cutting width, and engine make, among others. The metadata that identifies the different categories also enables associations with other products such as replacement parts or accessories. The same principles apply for internal knowledge bases when the item being searched for is a statement of work or a CAD drawing.

Problems arise when product data is incomplete or inconsistent. Customers who can't find the right product because it isn't coming up in search results may go to your competitor. Having the right product data management process in place ensures that products are easily found, descriptions are always complete and accurate, images display consistently, related content helps guide buying decisions, and suggestions are always relevant.

What is Data Governance?

These days, no matter what industry you operate in, competitive advantage depends on the quality of the data that is flowing from the supply chain into your organization’s information systems. Many companies are undergoing transformational initiatives, often because their customers are demanding it. B2B customers who have grown accustomed to buying on Amazon now expect the same level of shopping ease when buying products for their company.

What is often overlooked is the fact that a digital transformation is not just new technology -- it is first and foremost a data transformation. If your data quality is poor, incomplete, incorrect, and/or disconnected from other technology such as the ERP system, part of the PIM implementation plan will require data remediation efforts. Data from all the sources needs to be cleaned, harmonized, and processed in order to power a transformation .

But going through that process is not the end of the story. Ongoing oversight and governance are crucial to long term success. Although governance is critical it can seem like mundane work. But a sustainable governance program that delivers results over the long term can be built by using a

Governance is different for every company, but there are some common steps to creating a strong data governance program:

  1. Establish a governance team. Data governance requires a team effort from all sides of the business. Assign various roles, including the taxonomist, data steward, and product manager, from different departments to ensure organization-wide understanding and adoption.
  2. Create a list of enterprise processes. Agreed-upon and thoughtful processes are essential for effective handling o institutional data.
  3. Identify metrics to measure success. The goals you set will determine the right performance metrics and guide the selection of analytics .
  4. Develop a RACI (Responsible, Accountable, Consulted, Informed) chart. The RACI chart will help identify who has what role for each process and ensure common agreement.
  5. Design process maps. Process maps lay out each task in the data governance process, including who owns each process and what systems should be used,all in a visual format.

Data governance means better, cleaner and more efficient data, which means better analytics, business decisions, and business outcomes.

Product Information Management Services

Product information management services can help your organization succeed and win more business by ensuring your data is well prepared to support your business goals.

Earley Information Science's approach to product information management can prepare your data for any technology by making it more adaptable, intuitive, findable and usable. Data can be messy, information can be incomplete, and errors will be found during this process. However, a strategic approach to product information management will help your organization fix all of that.

We help at key points of the product data journey

  1. We help you assess your readiness for a product information management initiative with a free, structured 30-minute readiness assessment
  2. We organize your product information through taxonomy and attribute design. This helps your team intelligently design digital experiences that reflect the wants and needs of your customers. We help personalize their experience by tuning attributes to delight them no matter the season, channel, device or regional market.
  3. We help you select the correct PIM software. A PIM system connects internal and external product data sources to various digital sales and marketing channels. Choosing the right PIM system is a critical decision because it will help get product data established correctly from the beginning, and - just as important - keep it right as time goes on. This is a decision you want to get right and we can help you select the right PIM software.
  4. We help harmonize and normalize your ecommerce product listings so your product catalog digital experience becomes easy to navigate through product catalog optimization. Each item must be findable in onsite search as well as optimized for Internet search engines. With a well-organized taxonomy and a rational top-down attribute inheritance model, you can get there.

This case study for a multinational conglomerate is a perfect example of how EIS's approach has been successful.

Are You Ready for Digital Transformation?

Getting your product data management in order for ecommerce is one important step to an overarching digital transformation. Do you have a roadmap to guide your digital transformation? Does it lay a solid foundation for the successful transition to your vision of a future digital business.

If you want to see success in your company's ecommerce initiative and product data management process, download our Digital Transformation Roadmap to get started.

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Meet the Author
Earley Information Science Team

We're passionate about managing data, content, and organizational knowledge. For 25 years, we've supported business outcomes by making information findable, usable, and valuable.