This is the fourth (and final) column in my metadata series. We’ve talked about using metadata to automate product recommendations and drive product configurators. We also explored using metadata to provide correlations between products and other pieces of site content.
Today we’ll look at a problem that afflicts many companies: differentiating between product categories and product attributes. A product category is part of the hierarchical ontology that describes how your products differ from each other. Though this is a simple idea toward the top of the ontology (e.g., “video games,” “lawn furniture,” or “books”), the distinction between a category and an attribute blurs at the lowest levels.
Consider video games. Video games have a relatively simple category structure, organized by genre (arcade, fighting, strategy, etc.). Should they also be categorized by platform (Playstation, Xbox, etc.)? Should there be two different category hierarchies, one starting with platform and one starting with genre? What about categorizing based on price (under $20, $20-40, over $40)?
Carve up product categories all these ways, and it’s likely (due to human error) some products will fall through the cracks or be mis-categorized. In other words, the categories “Action > Xbox” and “Xbox > Action” should have the same products in them.
To solve this problem, be very strict about product categories. Don’t go overboard creating multiple overlapping categories. In the above example, either decide users will have to browse first based on platform (Amazon.com chose this option) or genre.
The next big distinction is between categories and attributes (metadata). A quick look at CircuitCity.com’s video game section shows several different ways to drill down into video games: platform, price, release date, and customer ratings. At first glance, it might seem as if CircuitCity has fallen victim to over-categorizing. Really, these are “virtual categories” and merely sort criteria. Price and release date are not actual categories in the site’s ontology, just metadata attached to each product. This can help the user drill down into the main category (the video platform) in different ways.
Amazon also uses virtual categories. Its bracelet department seemingly has a million subcategories, such as “gold,” “diamond,” and “emerald.” A closer inspection reveals these are product attribute listings that can be used to sort products.
The meta-data layer is arguably one of the most important components of a Web site. With it, you can automatically generate product recommendations and help guide users toward similar items, based on item attribute.
Metadata, when describing product attributes, can also help create simpler categorization schemes. It allows users to drill down virtual categories, in any order they want, without requiring them to understand needlessly complex hierarchies of products that seemingly overlap.
Do you use product attributes for categorization? Do you have other best practices you use when categorizing your products? If so, let me know. I’ll write a follow-up column on categorization schemes.
Until next time…
“You cannot succeed in analytics and marketing unless they are central to business operations and are helping business answer the questions that will drive dollars to the top or bottom line,” says Kerem Tomak, Sears Chief Digital Marketing & Analytics Officer.
The use of psychology in marketing and sales is not new, but it may be more useful than ever in an attention economy where time is precious and focus is rare. How can you tap into a demanding consumer to check whether there is an actual interest in your product?
According to a survey conducted as part of OnBrand Magazine's State of Branding Report 2017, marketers are well aware of the new technologies that are expected to be important to their brands in coming years, but the majority aren't rushing to invest in them before they're fully-baked.
Two weeks ago, Foursquare announced what could be the most important component of its data business: the Pilgrim SDK. So what does it do, and what does it mean for location-based marketing?