If you are looking for, or considering a solution for product data and working through how to evaluate the different options available, this article can help.  

One of the key opportunity areas driving businesses to look for product data tools is to accelerate the pace at which supplier product and price files are processed. Achieving this can allow for rapid expansion of a product catalog, or the shifting of a high volume of your team's hours from manual spreadsheet work, to more value delivering areas for the business.  

Outlined below are some essential functionality and criteria to consider as you evaluate different options on your journey to finding the best fit solution for your business.  

“Garbage In, Garbage out…” or so the saying goes ...

The concept asserts that the quality of the information coming out cannot be better than the quality of the information going in. This saying is used in data science and manufacturing and often when talking about product data, like in this article, or this one. 

Today, we are here to bust that myth as it pertains to product data and eCommerce. With the right tools in place, you can put garbage product data in and output high-quality product data, ready for eCommerce. 

What’s in a name? Well, quite a lot, it turns out, when it comes to product naming in your online store. Product names have an impact on SEO, on-site search and how effectively a shopper is drawn to a product when scanning a category page. 

Product data quality on your eCommerce site is critical for SEO, on-site search, navigation, and the shopper experience. The product information available and its presentation strongly influence whether a shopper will buy or leave your website. For retailers with large product ranges and product information sourced from multiple vendors – cleaning the disparate data received into a normalized format is a challenge. A challenge, most often met by manual manipulation in spreadsheets – a highly inefficient and unrewarding task. Automating these processes lifts this burden of time and cost, ensuring vendor data is standardized efficiently into a format ready for your eCommerce site.  

For eCommerce store owners, managing variants and parent-child product relationships are essential for maintaining your store’s digital products and eCommerce success. Variant management combined with categorization can account for up to 20% of the time spent on content management. But it doesn’t have to take this much of your time. Knowledge is power, and in this article, we’ll dive more into how you can simplify variant management and what tools are available to cut down the manual work and improve productivity in this area.  

What are Product Descriptions?

A product description describes a product’s attributes or features when it appears on your product detail page in your online store. This gives consumers an understanding of the product’s value proposition. Product descriptions are a vital way for companies to explain products and fill in the gaps that the product images can’t capture. 

Product Photos are the Most Important Product Information on Your Product Detail Pages

eCommerce sites are rapidly replacing brick-and-mortar stores and showrooms, but this doesn’t mean that customers don’t need to see the product. Although eCommerce is becoming more and more popular, consumers still not only want to see the product, but they also want to take it off the shelf, feel it, and examine it. Because this isn’t possible when shopping online, product photos/images are vital for businesses to effectively connect with consumers through their online platforms and give them the closest experience possible to in-person shopping. Therefore, product images are the key tool for eCommerce stores to help shoppers make a purchase decision when salespeople and tangible products aren’t available.

What is product data?

Product data is all of the information that is available about a product. This information can be read, measured, and structured into an understandable format using product data transformation and management. The data for each of these products is made up of a collection of product attributes.