While there’s nothing wrong with selling purely through your ecommerce store’s website in 2026, the most successful merchants have realized that with a properly structured PIM, getting products out to other marketplaces is infinitely easier than it used to be, making doing so almost a no-brainer for anyone looking to increase sales these days. 

In today’s blog, we’ll share some best practices for organizing product attributes, variants, and families in a PIM system. You’ll learn how to structure data so it flows smoothly into Shopify, Amazon, and point-of-sale (POS) systems, setting your brand up for omnichannel success in 2026.

Why Structured Product Data is so Important for Omnichannel Commerce

Omnichannel commerce requires that product details are identical and up to date across all platforms, giving customers a unified experience. Consistent product information across channels maintains a unified brand image and reduces the risk of outdated or conflicting information appearing in any one channel. 

When you have a well-structured, centralized approach to organizing your product data, you reduce manual work and errors, making it easier to expand into new channels. Using a single source of truth, like a product information management (PIM) system, means you update your product information once, and it propagates everywhere: your website’s product pages, Amazon listings, POS, etc. This product data consistency allows for faster product launches and ensures omnichannel agility, which is incredibly important in 2026 and beyond. 

When your data is clean and complete, you avoid mistakes that can frustrate customers (such as product listings that don't match in-store details). This results in more repeat shoppers and fewer returns, something we can all strive for. On the other hand, well-structured data means a faster time-to-market and easier expansion into new markets or channels. 

Structuring Your Product Data: Product Attributes, Families, and Variants

Ecommerce product data management doesn’t have to be difficult. Modern PIMs like Akeneo come with feature sets that make product data enrichment, management, and team collaboration as easy and efficient as possible.  

Defining Product Attributes

Attributes are the individual pieces of information that describe a product (e.g., Name, SKU, Price, Colour, Size, Description, Material, etc.). Start by listing out all attributes needed to sell your products effectively. 

This includes basic info, marketing content, technical specs, and any channel-specific fields. For example, you might have a standard “Description” and a shorter “Mobile Description” to optimize content for mobile viewers.

Use Product Families as Templates

In Akeneo, a Family is essentially a template of attributes for a group of similar products. For example, you might have a family for “Shoes” where every shoe product must have “Size”, “Colour”, “Material”, and “Brand” attributes, whereas another family for “Electronics” might require attributes like “Voltage” or “Warranty”. Defining families helps ensure consistency: all products in a family share the same attribute structure. 

This makes enrichment easier because if you add a new attribute (say, “Sustainability_Certification”) to a family, it applies to all products in that family. Families should correspond to logical groupings in your catalogue (product types or categories) and ensure nothing important is missing for any product of that type.

Handling Product Variants

Many products come in variants (e.g., a T-shirt with 4 sizes and 3 colours yields 12 distinct SKUs). Rather than treat each SKU as a completely separate product, structure them under a parent product. Akeneo allows you to create product models (parents) and variant products (children). 

The parent (your “product model”) holds all the information common to all variants (like the T-shirt’s overall name, description, brand, base price, etc.), while the children hold the specific differences (their own SKU, the specific Colour and Size value, stock level, etc.). Each variant still exists as an individual item, with its own SKU/barcode, but it inherits common info from the parent.

Decide which attributes belong at the parent level vs. the variant level. Common attributes stored with the parent might include things like product descriptions, category, base dimensions, or anything that applies to all variants. 

Variant-specific attributes stored with each child variant would include size, colour, individual SKU, and, if each variant has its own image, variant images. Akeneo’s family variant feature lets you configure this distribution of attributes between levels.

Preparing Data for Multiple Channels (Shopify, Amazon, Retail)

Omnichannel success relies on ensuring that all your data is properly mapped to every platform you currently use, as well as any that may pop up in the future. Every sales channel has its own quirks and required fields, however. 

For example, Amazon might require an “Item Type” or specific keyword sets, while Shopify might allow custom metafields for extra info. In your PIM, it’s smart to store the superset of all attributes needed by any channel. You can always filter out what a given channel doesn’t use. 

If your store lives on Shopify, you can use the Akeneo App for Shopify to map your Akeneo attributes to Shopify fields. At Blue Badger, we also developed a custom middleware solution, the Akeneo Data Connector, to further improve the process and unlock additional functionality, catch errors, and ensure product completeness in your data syndication with fewer headaches. 

Ensure that your PIM’s structure accounts for things like: a Product Title, the Description, Images, and Variant Options (Shopify typically allows 3 option attributes like Size, Colour, Style. Your PIM variant attributes should correspond to these). By structuring data in Akeneo first, your Shopify storefront stays in sync, and you avoid manual editing in Shopify’s admin. 

Similarly, selling on Amazon requires adhering to its listing standards, which often means providing extensive data. Amazon uses parent/child ASINs for variations, so it’s important to ensure that once you set up your variant structure in your PIM, that one is always tagged to act as the “parent” when exporting to Amazon. 

You’ll also want to capture Amazon-specific attributes in your PIM, possibly in a dedicated attribute group like Amazon Bullet Points, Search Terms, etc., since Amazon’s categories have a few unique data fields. 

Unless you’re on Shopify and also leverage their POS, which already uses your online catalogue as a source of truth, you won’t want to neglect your retail stores when it comes to structuring your data. 

Ensure your PIM includes attributes such as UPC/Barcode, MSRP, In-Store Description (which might be shorter), and any internal codes your POS uses, so the price on the shelf matches the price online and the product name on the receipt matches what’s on the website.

For best results when exporting data from your PIM to other ecommerce platforms, use channel-specific export/sync profiles, as most PIMs include this functionality. This kind of capability will allow you to define, for each channel, which attributes to include or exclude, and even apply transformations as needed. For example, you might create an “Amazon Export Profile” that pulls all Amazon-required attributes, concatenates some fields, or formats the data as Amazon expects.

Ensuring Data Quality and Consistency

Structuring data is not only about where data lives, but also about maintaining its quality. Leverage your PIM’s validation features: set data types, use controlled vocabularies (e.g., a dropdown for Colour to avoid one product being “Grey” and another “Gray”), and set attribute requirements. Akeneo, for example, lets you mark certain attributes as required for completeness on a per-family or per-channel basis to ensure that nothing can be marked “complete” until all fields are filled.

Depending on the size of your operation, many different people may interact with your PIM regularly, including those in marketing, customer service, merchandising, and legal. Take advantage of the teamwork, permission, and workflow capabilities offered by your PIM to ensure that no one steps on each other’s toes or makes changes to data they shouldn’t be touching. 

Many PIMs, like Akeneo, allow setting up a validation step, i.e, a manager must approve changes to certain fields to ensure that nothing gets published anywhere without approval.

Conclusion

A good omnichannel strategy starts with well-defined attributes, families that enforce consistency, and a variant structure that keeps shared data at the parent level while allowing each SKU to carry its unique data. From there,  store the full set of channel requirements in your PIM, and use channel-specific mappings and export profiles to deliver the right fields in the right format, no matter where you sell or show up. 

As an Akeneo partner agency, we at Blue Badger have seen firsthand how our mid-market and enterprise clients transform their omnichannel performance by adopting these best practices. Get in touch with us today to learn more about PIM implementation or maintenance.