To ensure the efficient functioning of your PIM system, the quality of input data must be top-notch. This blog post delves into identifying your data assets and taking the necessary steps to clean and prepare them for PIM implementation.

It is widely known that the Garbage In, Garbage Out (GIGO) principle often poses a challenge during PIM implementations. Hence, it is of utmost importance to put your data in order before embarking on the PIM implementation process to ensure that the data is clean and usable.

For your Product Information Management (PIM) system to operate effectively, it’s crucial to have high-quality input data. Unfortunately, many organizations have made the mistake of implementing a rushed PIM solution, only to find that it hasn’t solved their data issues but rather compounded them. To ensure the success of your PIM implementation in the long run, it’s important to start by thoroughly cleansing and organizing your data. Here’s how!

How can we ensure the data is ready for a PIM implementation?

Preparing your data should begin with asking two simple questions:

What data is required to create my product?

For instance, let's take an eCommerce marketplace that sells clothing items from multiple brands. To enable an informed purchase decision, it is crucial to have access to relevant product details, including the following:

In any industry, the initial step is to identify all the pertinent data points related to your products and categories. Once this information is gathered, searching for and locating these data points is next.

Where does this data live?

Many businesses face the challenge of having product data stored in a fragmented and disorganized manner, scattered across multiple spreadsheets and applications, leading to difficulty in having a complete and comprehensive view of their product information.

For example, the parametric product data may be located within PLM (Product lifecycle management) systems or ERP (Enterprise Resource Planning) systems. At the same time, dynamic attributes that cannot be effectively recorded in a PLM may reside in multiple spreadsheets or databases along with marketing copy. Adding to the complexity is an abundance of unstructured data, such as images and videos, which may be stored in various network or desktop folders.

The complexity of product data management has significantly increased in recent years, making it challenging for eCommerce companies to meet the technical data requirements needed for success. The amount of required product data has greatly expanded, causing difficulties for marketers to meet traditional technical data standards.

While there are multiple reasons for the dramatic growth in the amount of product data required for success in eCommerce, a product information management (PIM) system can address nearly all of them.

A PIM system is a software solution that provides a centralized repository for managing all product data. This includes inputting, storing, organizing, modifying, and sharing information. With a PIM in place, companies can ensure that their product data is consistently entered and displayed uniformly, making it easier for customers to access and use the information.

The structured integration of your new PIM system ensures that all crucial product data is captured. Read on for the essential four-step process to maintain cleansed data in the PIM.