It’s retail’s long-running illness: Retailers are suffering from poor product data within their online stores and they can’t find the cure.
Without great product data, even the most incredible product selection and user experience in the world can’t help shoppers find what they’re looking for. The fact is, it’s not just small retailers who are suffering; even the most established retailers struggle to optimally develop and utilize product data so that shoppers can find the “right” product. Unfortunately, the vast majority of retailers recognize that improving their product data is core to their business and will directly lead to higher revenue, yet most don’t have a clear plan of attack or resources to execute it.
Based on Edgecase’s research of 300 retailers in the Internet Retail 500 list, below are the four key problems that under-optimized product data causes for retailers—both within their organizations and for their shoppers—and recommendations for overcoming them:
Ouch! Missing and Inconsistent Product Attribution
This is a pain for every retailer but especially prevalent in those who sell other brands’ products and depend on third parties for their product data. In our own customer base, we’ve seen as much as 71% of a retailer’s original product data feed has inconsistencies and/or gaps. As a result, relevant products often disappear or irrelevant products present themselves to the shopper when navigating, searching or using filters. For example, a furniture retailer may have 30 green couches in its inventory, but when a shopper types “green couch” in the search bar only two couches show up. Because of incomplete product meta-data, 66% of the shoppable green couches were not visible.
This issue is not only frustrating for shoppers, it makes them nervous: according to Edgecases’s research 73% of shoppers have a fear of their product view being artificially limited and 40% express a distrust of search due to continuously irrelevant result sets. The problem is pervasive: 75% of the websites analyzed clearly had missing, inaccurate or inconsistent product attribution.
Ouch! Using Merchant-Speak Instead of Shopper-Speak
Product data is the communication layer between the retailer and shopper. This “product language” often becomes stale and irrelevant when fueled only by merchant data, which reflects how retailers think about a product rather than how a shopper might describe it. Worse, staying up to date with the consumers’ vocabulary is tough and time-consuming. Doing so means quickly and regularly mining and curating structured and unstructured content on and off a retailer’s website, which is an unrealistic effort given the bandwidth of most merchant teams.
Our research has identified opportunities to increase navigation options to reflect current shopper sentiment by an average of 689% across all categories. As you can see in our Speak My Language infographic, apparel and accessory ecommerce sites have an average of three filter options whereas their optimal attribute categories is 26, while sporting goods have an average of five filter options with an optimal category count of 28!
Ouch! Underutilized Product Content
Detailed product content is the No. 1 most important element of purchase decisions for 73% of shoppers, according to a recent study by Comscore and UPS. Unfortunately, while retailers have made wonderful investments in developing rich content and tools to help shoppers make decisions—including product imagery, videos, descriptions, spec sheets, buyer guides, recommendations and reviews—that rich content lives deep within their website and is frequently not structured in a way that’s useable for search or navigation. That means all that time and energy creating amazing content leads to little or no impact on shoppers’ decisions.
In our research, on average 95% of websites had seven or more unique and useful product attributes available to shoppers on their product pages alone, while only 40% had seven or more filter options available for shoppers to navigate by. While retailers are aware of these inefficiencies, their hands are tied: Merchant teams don’t have the time or tools to mine, structure and input proper attributes to make them usable in site search and navigation.
Ouch! Uninformed Merchant Teams and Under Optimized Product Data
Few, if any, retail systems give feedback on what influences a buying decision, leaving merchant teams to make decisions based on intuition or not optimize at all. The time and effort required to find these insights on their own is not available and the result is often a “set it and forget it” attitude, which leads to missed opportunities for improvement and revenue being left on the table. In fact, according to our research, 79% of retailers had no ability to understand how successful filters were in helping shoppers, despite the fact that 89% expressed a desire to understand preferences and how they influenced shopper decision-making.
Try a Cure
Retailers should stop suffering and start feeling well, and the sooner the better. Easing this pain leads to amazing results. Crate & Barrel updated its product data and achieved a 128% higher revenue per visit for shoppers that leveraged enriched product data made available through next-generation filters and faceted navigation. Another retailer, Urban Decay, incorporated data from product reviews into its product data and now allows visitors to select their own eye color and skin tone in the navigation, which has resulted in a 16% lift in CVR.
There are four quick things retailers can do to decrease the pains of poor product data. First, start with a solid strategy for ensuring each product gets accurately and consistently tagged. Next, speak the shopper’s language. Ask questions about how shoppers look for products and develop attributes and categories that incorporate these trends. Then, take advantage of content investments by incorporating rich product information into site search, navigation and other product discovery tools. Lastly, retailers cannot afford to set it and forget it. It is important to take advantage of insights that are uncovered and make the necessary changes.
Edgecase provides technology designed to enrich and personalize the product data online retailers present to consumers.
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