Guide to preparing product data and assets for PIM implementation

Posted by Maria West on Jul 30, 2020 2:51:35 PM

Are you are implementing a PIM system, or do you have one already running? A critical consideration in PIM implementation is sourcing, cleaning, and preparing your product data before it enters the PIM. 

 

The data preparation for PIM implementation can be complicated and involved.

It includes:

1/ Identifying the information needed to populate the PIM 

2/ Locating where all of the product data and assets you need are sourced 

3/ Bringing it together into one product file and normalizing the data

4/ Organizing the data into the right classification of attributes, categories, and variants

5/ Validating the data for errors and missing information.

 

Following the steps covered below, will ensure your product catalog is ready for it’s new and better home. How well this is done will either set you up for a rewarding experience with your new PIM or chaos and disappointment for the long term.

 

If you follow these key steps to get your data ready for the PIM, you will likely have a great experience - 

 

Step1: Identify the information needed to populate the PIM

You first need to think about your business goals and what you want to achieve with your PIM. This prework will help you identify what products you will manage in the new system, and what attributes and assets will need to be gathered, such as pricing, images, case quantities, etc.

 

Step 2: Locate where all of the product data & assets you need are sourced

Where have you got all of your product information and assets? You will need to get it all together in one central place before moving it into the PIM.

 

Different information might be in different locations like ERP systems, DAM, in your eCommerce platform, or stored in folders in your company drive. Some may also need to be sourced from vendors, who often hold the richest and most up to date information on products.

 

Step 3: Bringing it together into one product file and normalizing the data

You may have some of the same product attributes for a specific product located in different systems. Sometimes, if your data sources are siloed and out of sync - this information may not match. In which case, you will need to choose which source to use. Or the same attribute may have different naming conventions or formats in the various systems. You will need to normalize the data into one, consistent catalog that aligns with your PIM.

 

For all spreadsheets, images, and videos you gather, be sure to have the attributes named in a way to make them easily linked with a specific product.  

 

Step 4: Organizing the data into the right classification of attributes, categories, and variants

Before you can migrate your data and assets into a PIM, you must define your catalog taxonomy (i.e., organizing the data into layers). Correct classification of your catalog is essential to ensure your information will fit into the system to which you are migrating. Some key steps are:

  • Find out the types of data accepted by the PIM system you are implementing. For example, what sorts of attribute types do they allow? 
  • Determine the attributes and variants you need for each product - Are there any attribute options like sizing or color variations? 
  • Determine the product Categories - What categories and sub-categories make sense for your product range? (check with your PIM how many category levels you can have?)
  • Come up with a standard naming structure that you can use to define products, attributes, assets, and organizational items like categories.
  • Each product in your catalog must have the attributes and variants assigned clearly to them. You must assign each product to categories also. Take the time to make sure these are all configured correctly.

 

Step 5: Data validation

One of the key benefits of a PIM is having a single source of truth for product data. This only works if the data put into the PIM is accurate, complete, valid, and trustworthy. All sorts of things from misspellings, different abbreviations for the same words (pc, pcs, piece, PC) and characters like hyphens and bullet points lower your data quality.

  • Find and remove any duplicates, out of date or inaccurate information.
  • Get all of the data for each attribute aligned with standard formatting and naming. I.e., are all your numbers formatted the same way? What about measures? Check if the PIM you will use has any specific requirements for formatting.
  • Do you have any strange characters in your text?

 

At this stage, it’s understandable if this might be starting to feel overwhelming. There is a lot of product data and assets to find, coordinate, and manage. 

But not doing it and putting poor quality, out-of-date information into a PIM is a risky business that will affect your return on investment. Luckily, there are solutions to help make this process of preparing data for PIM faster and easier.

 

Vesta - providing the support and automation tools to prepare your data for PIM

Vesta are experts in sourcing and cleaning product data. We can cut the heavy load for you in preparing your data for PIM implementation. We specialize in setting up automatic feeds to source product data from vendors over time. Through a range of tools within the Vesta platform, the data can be organized into the product classification or taxonomy needed for your PIM, changed into the form you need through Vesta's product data transformation engine, and validated for duplicates and errors.

 

To talk with a Vesta consultant about PIM implementation services - book a call

 

To find out more about how Vesta can help you implement your PIM faster and keep it up to date with quality product data over time, you can read more here.

 

Topics: ecommerce, PIM, Pre-PIM, Product taxonomy, Product classification

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