12 Sep 2018
Product Information Management (PIM): Food for AI?
Joel Layton
Joel Layton
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Product Information Management or PIM is a systematic approach to organizing all the data an organization uses about its products.

Last week I discussed how organizations could improve experiences by adding discipline through enhanced use of their Product Lifecycle Management (PLM). This article will examine how using the train depot of PIM can drive more effective use of product information when machine learning or artificial intelligence gets involved.

How Product Information Management and AI work together?

At its core, PIM systems take the organization's data about its products and organize it within a system for use on ecommerce platforms. A PIM can activate ancillary systems in use on a broader level, such as Site Search, Recommendations or Personalization engines, Outfitting, Fit algorithms, etc.

These systems are typically driven by complex algorithms to enhance the customer experience and ultimately drive conversion. The PIM is the restaurant that will serve up the food for the AI-driven mechanism to do its work.

Let's dig a bit deeper.

In the PIM, the data within it range from the ordinary, such as Product Descriptions and Summaries, to the more complex, such as category relations or metadata relations. Taking this arsenal of data, the PIM can directly interface with the ecommerce platform and via APIs or data feeds that can populate the AI-based systems.

Let's use Site Search and Out-fitting as an example. First, the PIM system will populate the ecommerce platform with base-level product data that it has stored to allow a customer to purchase the product.

We could stop here, and a customer would be able to buy a product but to enhance the customer experience, let's go further.

Taking Product Information Management to the next level

Sophisticated, AI-based site search tools will also interface with PIM to get as much information about the product as possible and begin the learning process as customers engage with site search to find what they are looking for.

While this is happening, PIM will also interface with outfitting to pull together the appropriate outfits based on the criteria and relationships established within the PIM. Pairing a hat, gloves, and scarf with a jacket and pants, for example, completes the outfit.

The Site Search program will use the customer's input not only to find results for "Winter Jacket" but also to suggest a complete outfit based on the relationships between products that have been established in the Product Information Management (PIM) system. As more customers use the site to search and browse, the Site Search and Outfitting algorithms become more intelligent, and the conversion rate increases, thanks to the well-organized and up-to-date data in the PIM.

Building the ecommerce ecosystem with PIM

So ultimately, as companies are building out their ecommerce ecosystem. They want to think about how the hierarchy of needs progresses. What I mean by this is they all sell products or services. They want to get the information about those products as organized as possible to make the most of that. A PIM will do that.

The product goes to the website for customers to find and purchase.

On top of that, the company will seek out and buy the coolest and fanciest tools to make finding and buying even more accessible, faster, smarter, etc. It starts with the PIM and quickly makes its way to the cool stuff, i.e., AI and machine-learning systems.

Bingo-Bango, just like that, you have a sophisticated ecommerce ecosystem that marries the diligence and efficiency of Product Information Management with the wonders of Artificial Intelligence.

To learn more about what PIM can do for your online store catalog, book a demo.