Guide to Product Information Management Data Models in 2024

Do you want to understand Product Information Management Data Models and why they are important? Then you are at the right place. The ever-changing retail landscape has seen dramatic changes in recent years. Online shopping has exploded bringing a profound shift in the way that consumers make purchasing decisions. Despite the e-commerce boom, the vast majority of shoppers still opt to shop in brick-and-mortar stores. This all comes down to the fact that many consumers still want to enjoy the face-to-face interaction on the path to purchase along with the instant gratification of going home with their new product immediately after completing the purchase.

However, according to a study conducted by Rothstein Tauber, Inc., a marketing research company based in Stamford, Conn., more than 80 percent of consumers go online to research and compare prices, and product reviews. Financing offers before heading out to the store. The study also found out that 64 percent of adult shoppers in the US say they shop online because they can see more product data than they can in stores. 

One of the major pain points in online retail is that it does not afford shoppers the convenience of touching and inspecting the product so that they can experience it just as they would in person. To bridge this gap, there’s a lot of quality information that is needed to support a single product. Online consumers make purchase decisions based on the information they read, see, and hear about a product online — the product’s specs, text descriptions about its benefits, images, feature videos, PDF manuals, reviews, social proof, and so much more.

According to another study conducted by Forrester, online merchants attach roughly ~200 attributes to each product on their catalog. Staying on top of all this product data is often a daunting challenge. Regardless of the number of products in your product line, there is often a lot of product information that you have to manage. It could be that you have only 10 distinct products, but then those products have many complex data points or many assets linked to them. 

In the context of a large e-commerce company with hundreds or thousands of SKUs, this problem becomes even more intractable without a Product Information Management (Product Information Management) system. As a merchant, you need to provide accurate, robust, up-to-date, compelling product information for you to gain a competitive advantage in terms of product information management across the marketplace.

In this post, we’ll discuss what Product Information Management entails and how you can create product information management data models that can capture product-related information consistently and in real-time. If you’re considering implementing a product information management solution, and want to know how to go about data modeling, then this is the right resource for you.

Table of Contents

• What is Product Information Management?
• What is a Product Information Management Data Model?
• The Importance of Product Information Management Data Models
• How to Create a Product Information Management Data Model?
  • Step 1: Data Gathering
  • Step 2: Data Validation
  • Step 3: Set the Data Governance Policy
  • Step 4: Build Data Taxonomy
  • Step 5: Define Product Attributes
• Product Information Management Data Model Example
• How Can a Product Information Management Tool Solve Your Product Information Management Problems?
• Conclusion

What is Product Information Management?

Product information management (Product Information Management) refers to the processes and technologies that are used for collecting, managing, and distributing all of the information needed to market and sell products to one or more distribution channels from a central location without manually re-entering any of this information in another system so as to create a single version of truth for every product.

When implementing a product information management system, your main goal should be to ensure that product data is always correct and available to internal and external collaborators, systems, and partners. Through advanced integrations and standardizations, these could be distributors, vendors, content service providers, and marketplaces. 

By creating a system where the right people and systems source information directly from your Product Information Management (Product Information Management) system, you get to eliminate the risk of disseminating outdated product information across the distribution value chain in an efficient and cost-effective way.

The product information in this context is all the data that you need to build your product catalog. This could be structured data stored in a spreadsheet or a SQL database. In addition to structured product data, your Product Information Management also needs to support text descriptions and translations stored in a CMS (Content Management System), as well as rich media like images, videos, and PDFs stored on a CDN (Content Delivery Network), and taxonomies to help group your products might all be managed by your Product Information Management.

While it’s possible that your product data may be sourced from disparate data stores and content management systems, your Product Information Management should consolidate it all together in a central hub and act as your single source of truth. From a centralized hub, your marketing and sales teams can then update and customize the product content while maintaining compliance with the established business rules and quality standards.

What is a Product Information Management Data Model?

For most organizations that want to implement a Product Information Management Data Model, the most crucial piece of the puzzle is data modeling; the process of creating a data model. It goes without saying that data models are at the core of successful Product Information Management projects. 

A product data model is the conceptual representation of sellable goods or services and how they relate with other diverse data objects as well as the business rules and constraints that govern them.

Product Information Management Data Model is about representing how the product information will be organized in the database. It’s all about describing the entity, attributes, fields, completeness, and validation rules so that the product data is correctly captured and displayed in the Product Information Management database.

The product data captured involves not just marketing data but should also account for regulatory requirements, logistics, and syndication needs where applicable. For your Product Information Management Data Model project to be a success, it is of the utmost importance that these considerations be incorporated at the beginning of your implementation plan.

Key terms in the Product Information Management data model include:

• Entity – The actual sellable good or service that you want to store data about.
• Attributes – Attributes provide a way of structuring and organizing unique characteristics relating to a particular entity/product. For example; Product name and Product price are attributes of the product entity.
• Variant – A variant is a concrete sellable good characterized by the use of attributes like color, size, weight, etc. Product Variants are usually mapped to specific SKUs. For example; the new Apple M1 iMac comes in 7 color variants.
• Category – Categories are a way of grouping products together based on characteristics, search concerns, etc.
• Relationship – Relationships refer to the dependency or association between two or more entities. They describe how one entity is linked to another. Entity relationships can be one-to-one, many-to-one or many-to-many.

The Importance of Product Information Management Data Models

There are numerous reasons why your business might need a Product Information Management data model. Let’s dive into some of the reasons now:

• You have a lot of products in your catalog and the process of regularly updating product information when necessary is becoming difficult and time-consuming.
• You need to eliminate the complex workflow of constantly creating and sending out product-related documents such as pricing lists, product catalogs, etc. when relaying information.
• You market your products through multiple channels such as independent retailers, online stores, or even marketplaces.
• You advertise your products using Facebook or Google Shopping.
• You need a reliable single source of product data for your team and the applications that make up your marketing stack.
• You want to enrich your product data with data from other sources.
• You want to have a system that can help you customize product data for different customers based on location, demographics, etc.
• Your team is spending a lot of unnecessary time searching for product information as opposed to spending this time on the job they were hired to do (sales, marketing, operations, etc.)

How to Create a Product Information Management Data Model?

Now that you’ve established a solid foundation on what a Product Information Management data model is and why it’s important, it’s time to learn how to create a Product Information Management data model. The question of how to determine what product data model is right for your Product Information Management project is one that can be solved in 5 steps.

Step 1: Data Gathering

The first step in the Product Information Management Data Model process is to establish what information is needed as well as where this information is located. You then need to standardize this data to ensure that its format is compatible with your Product Information Management Data Model software.

Step 2: Data Validation

The next step is to check the quality of the data that you want to import. This is done to eliminate errors such as misspellings, and missing fields, as well as to weed out duplicates. Any inconsistency in the data can negatively impact the quality of information that is disseminated to your customers.

Step 3: Set the Data Governance Policy

By setting up data governance rules in the Product Information Management Data Model, you can secure your data by ensuring that only authorized users have access to the data within the product information management platform. An effective data rights management layer should require data consumers to have privileged access to product information.

Step 4: Build Data Taxonomy

A structured hierarchical list makes it easy and quick for customers to search and find products and product information on time. Organizing products in categories is one way of offering an excellent user experience to your customers.

Step 5: Define Product Attributes

Product attributes are used to accelerate product data enrichment which is vital for driving more leads and sales. The best attributes combine multiple data points such as marketing copy, logistics, technical, etc.

Product Information Management Data Model Example

Let’s look at an example of a simple Product Information Management Data Model.

This image illustrated above shows a simple Product Information Management Data Model that captures information such as the product id, product name, product description, a link to the product image, as well as attributes and categories that are stored in external tables and referenced using related keys and values. 

This Product Information Management Data Model can be bootstrapped fairly quickly. However, there is a lot that it doesn’t cover. For example, your product might have many variants which obviously cannot be encapsulated using this model. You might also want to associate different products with a “product family” using a child-parent relationship.

The product data model shown below supports all those features:

This data model also supports tags, custom taxonomies, and a search index using a flat table. 

How Can a Product Information Management Tool Solve Your Product Information Management Problems?

From the previous example, you can probably start to appreciate the complexity inherent in building a robust custom product data model. Every single relationship between the data models introduces additional development overhead and more edge cases to consider.

To make the process of managing thousands of products relatively easier without the need for custom code, an alternative would be to use a proprietary Product Information Management software that has data modeling features. Some common features available on most platforms include support for product families, categories, attributes, and variants. 

Apart from product-related information storage, Product Information Managements offer additional features such as data enrichment and distribution across multiple downstream consuming channels such as marketplaces, e-commerce stores, print catalogs, and POS.

Product Information Management software can manage things like:

• Consolidating product information from suppliers, ERPs, distribution partners, and other sources in a central repository.
• Enriching product information quickly using mapping, cleaning, search and bulk edit options.
• Scheduling product data syndication to retail channels minutes.
• Generating product catalogs in PDF or Spreadsheet formats on the fly.
• Sharing product data across your organization and partner networks through privileged access.

The most popular Product Information Management systems are:

• Product Information Management core
• Akeneo
• InRiver

Conclusion

Product Information Management Data Model is one of the most important tasks in the design of a Product Information Management system. It lays the foundation of how the product data will be collected, organized, stored, retrieved, and presented. These systems can be used to create a centralized repository of well-structured and verified product data. A Product Information Management system is a centralized repository responsible for storing, controlling, and managing the data you need to market and sell products. A Product Information Management Data Model is the conceptual representation of sellable goods or services and how they relate with other diverse data objects as well as the business rules and constraints that govern them.

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