Many retailers have invested in rich data for product pages, as well as tools that are capturing product likes/dislikes from shoppers through content like ratings and reviews. This data generally lives deeper in the site, but has proven to be incredibly effective in driving increased sales when integrated with site search and navigation.
Think about the extensive click path to find a relevant review on a product of interest:
Browse or search for product → Go to product page → Click on the Reviews link/tab → Peruse all reviews to find the one(s) from someone you identify with → Not the right product? Start all over again at the product page or search box.
Most retailers are very aware of this inefficiency, but their hands are often tied. This type of data usually lives in an unstructured format across various databases. Merchant teams don’t always have the time or the tools to mine for relevant product attributes to pull into their data management systems, or infuse it into site search and navigation.
One of Edgecase’s primary goals is to help clients get the goodness out of all of the content and tools they have already invested in. The Edgecase Curation team audits site content for new product data opportunities. Do “finders” exist? How about Lookbooks or User Guides? Are there ample customer reviews? How extensive is the content on the product details page? Simply put, what’s already there that isn’t being used?
New recommended product attributes are also included in the product data strategy, and that’s when the Edgecase Curation Engine gets working. Technology and machine curation may be leveraged to mine structured attributes in content like ratings and reviews, while humans may read through lookbooks, for instance, and subjectively determine attributes that are relevant to each specific look.
Urban Decay shoppers are extremely socially-driven and contribute countless product reviews. When they do, they are asked about their eye color and skin tone to add context to their experience with the product. This is incredibly valuable information that can only be consumed product page-by-product page and review-by-review. Edgecase was able to mine this information and create product data attributes that define whether each product is well suited for particular eye colors and skin tones. Shoppers can now select their own eye color and skin tone in the navigation and see all relevant products at once! It’s no wonder that this has become the most highly converting set of product attributes and filters for on UrbanDecay.com, contributing to their 16% lift in CVR.
Another Edgecase client in the Homegoods category had invested heavily in a product page redesign, including development of richer product descriptions and specifications. Very little of this content was tied directly to the product in any structured way, therefore was not being leveraged in the site’s search and navigation. 72% of the new product data created by the Edgecase team was pulled directly from product pages and will power a much more relevant and efficient product discovery experience on the site.
This post is part of our blog series, ‘Pitfalls of Poor Product Data: The Top Pains That Under-Optimized Product Data Is Causing Retailers Today’. Read the previous post in the series, Using Merchant Speak Instead of Shopper Speak and stay tuned as we continue to explore additional pitfalls.
Download the “The Pains of Poor Product Data: How to Evolve the Data That’s at the Heart of Your Business” whitepaper for a collection of tactics that can cure your product data pains.