We’ve talked a bit about why product data needs to be structured, but we believe you’ll find it helpful if we dive a bit deeper into why it’s just so important in commerce. First, let’s define it. According to Webopedia, structured data includes data from relational databases and spreadsheets that can be easily entered, stored, queried, and analyzed. In other words, structured product data means characterizing items in a standard way, providing additional use and meaning in both brick-and-mortar and online contexts.
When it comes to structured product data, the most obvious benefit is its ability to enhance where your products show up in search results. Structured data provides companies with an added SEO benefit, as well as a competitive advantage. Those products that appear higher up in Google’s search results will ultimately experience higher click-through rates. You’ve heard this before, but without structured product data, your efforts to get to the top of the search results page will be fruitless.
Structured product data also enables product-related interaction between humans and non-human actors, such as chatbots or other Artificial Intelligence-powered personal assistants. When structured data is combined with chatbots or other forms of AI-powered assistants, consumers can do anything from purchasing a product to comparing and contrasting different versions of the same product.
Not only that, but AI that has access to structured product data can also help fill in incomplete product information, such as color, location, size, etc. Think of an entire catalog of product information and imagine it missing key pieces like the material or the brand of a shirt. A consumer viewing the product presented through that catalog will be less interested in purchasing it versus from a competitor that has more complete information. However, with access to structured product data from a universal source, businesses are enabled to fill in the gaps in their own product catalogs. As a result, customers find it much easier to make purchasing decisions.
We understand that at the end of the day, not everyone has the capability or the time to structure their data. Take Netflix, for example. The company pays hundreds of people to watch films and tag them with all kinds of metadata. This process is so sophisticated and precise that taggers receive a 36-page training document that teaches them how to rate movies on their sexually suggestive content, goriness, romance levels, and even narrative elements like plot conclusiveness.
But with access to quality product information along with the ability to scale that product information across applications, the move to structured product data, and ultimately Pervasive Commerce, will be much easier, and you’ll be well on your way to targeting ads more accurately and delivering more relevant search results to consumers.