Design considerations for your data
4 min
Consider the design and organization of your product data before you start your Optimizely Product Information Management (PIM) configuration. This will save you time and simplify the implementation process.
General considerations
- Define your PIM team – Identify key members to help you get your data in place. They can begin collecting any data or assets you need.
- Keep data clean – Identify inconsistencies in your data, such as misspelled words, irregular capitalization, or abbreviations that someone might not understand. Clean data is important to the integrity of your products. You can edit your product information in the PIM, but it may be easier to edit the data in your current system or spreadsheets.
Property and property group considerations
Set up properties and property groups for a successful PIM experience.
- Give specific names to properties – Property names must be specific and unique, but the display names can be shared. For example, your properties could be Faucet_Finish and Countertop_Finish, both with a display name of Finish.
- Create property groups by product family – If you have properties that run across multiple products, such as color and style, create separate property groups by product family and then add their respective properties specific to each. For example, create separate property groups for Faucets and one for Countertops, then add Faucet_Finish and Countertop_Finish to the respective group.
- Create specific properties for easier attribute filtering – Separating property groups lets your users filter based on the properties of that group. For example, you may have chrome or nickel options for faucets but matte or glossy for countertops, even though both are part of the Finish property.
- Consider your site pages – Consider where properties that are attributes land on the Product Detail page on your site.
- Consider product templates – You may want product templates to make editing product types easier.
Product template considerations
You can create product templates from the property groups with properties you created.
- Consider your product families – Design product templates by product family. For example, a merchandiser may create a Shoe product template containing essential data elements for that product type, such as color and style.
- Adjust properties by template – You can create separate templates for Athletic Shoes and Dress Shoes. If you have a shared Shoe property group, you can include this on both templates and then adjust required and recommended properties within the property group for each template.
Category and category tree considerations
Categories and category trees are the taxonomies for a site and your site navigation.
- Consider how your customers navigate – Categories are how users visit your website. Categories can be regular product or parent categories for other (child) categories. Parent categories display a category list page, while product categories display a product list page.
- Avoid too much depth – Too many levels of categories can cause navigational issues on your site and can be cumbersome for your users. Try to stay within three levels in your category structure.
Asset considerations
Organize asset folders before you load any assets.
- Be specific with folder names – Avoid creating a traditional file structure with vague folder names such as Images or Specifications when organizing your digital assets.
- Follow a structure – Consider product categories, brands, or documents you maintain.
- Use subfolders – Use subfolders to organize assets further.
- Consider auto-assigning – Use an asset name with a product number to auto-assign assets.
Import considerations
- Create import templates – Use an import template if you get data from specific suppliers in a consistent format.
- Do not worry about a consistent spreadsheet format – Because you are creating your own templates, you do not have to modify the spreadsheets before importing if your column headers (source fields) map to target properties in the PIM.
- Resolve errors after import – Data does not have to be perfect. If some data is not mapped properly and produces import errors, you can resolve them after the import. The system imports products without errors and isolates those with errors.