What are the most critical data points to make a good product description? And which data points can help you get excellent product descriptions? Get our recommendations here.
When you are creating product descriptions based on data it is important that you have a good structure and the right data points. But if you have not worked with it before it can be difficult to know where to start and to know which data points are relevant. That is why we are here to help!
The following recommendations and statements are based on our experiences after helping several companies get started with IC Robotics and data to text in general.
To give you a clear overview of the most useful data points when creating product descriptions based on data we have divided them into three groups: need to have, nice to have, and good to have.
| Need to have | Nice to have | Good to have |
| 📝 Title | 📏 Size | 💸 Price |
| 🤖 Type | 🌈 Color | 📢 Product count |
| 🏢 Vendor | 🛠️ Materials | 👫 Gender |
| 🎁 Categories | ☀️ Season | |
| 👶🏻 Age group | ||
| 🐅 Patterns/print |
It may not be all of the above data points that will make sense for your products but we hope that it still gives you an idea of relevant data points.
Need to have
Title, type, and vendor are data points you need to have when creating dynamic, unique, and automatic texts. It applies to almost every company no matter the industry.
Not only are they the baseline data for a good structure in your template, but they are also the most important data points to place in your texts. Looking at SEO it will in most cases also be your key search words.
Nice to have
Data points such as size, color, materials, and categories will help make your texts more informative and reduce the risk of duplicate content. This data will vary depending on the industry and the type of products. With a good structure across the different categories, these will make your texts go from good to great.
Good to have
To make your texts go from great to excellent you can enrich your data with data points such as price, product count, gender, season, age groups, patterns, prints, or anything else that is relevant to the reader. We really see no limits for the amount of data. The more data available the more fun it will be.
Best practice when setting up the data
The way you structure your data depends on the CMS. Shopify, WooCommerce, Magento, etc all have different ways to handle data. But here is some advice no matter the CMS.
When setting up the data in your CMS there are two ways to structure it to make sure it works as effectively as possible when creating your product descriptions.
Place the data in separate fields
It is a huge advantage when writing your text if the data points have their own fields. It means that you can use the data directly in the text. This will probably seem like a lot of work to do with all your existing products but we promise it will be worth it. But do not worry - if it is too much work, there is another way.
Place the data in the same field and make a system
For many webshops, it is common to put all the data in one field. This could e.g. be as a list in tags and collection (Shopify) or in categories (WooCommerce etc.). It is not wrong but it makes it more difficult when building your template and writing the text. It takes a lot of scenarios and conditions to make sure, the software writes the right sentences.
To make it easier we recommend that you make a system with the data in your list. This could either be by 1) being consistent in the order of the data points or 2) naming the data points e.g. color with “Color: Grey”.
This makes it possible to extract data points from the list and use it in the text. Cool, right?