Data Analytics: Merchandise by Numbers

For all the emphasis the e-commerce industry places on big data, the benefits of data are proportional to its quality. Think of it this way: big data is crude oil and rich data is refined fuel. Now let’s apply it to product data: when it’s unstructured, it’s useless, but once it’s organized and enriched, it can fuel the e-commerce experience. Regardless of the size of the organization, retailers know better data means better decision making and, ultimately, better performance. The same goes for online shoppers, where improved data has a direct correlation to conversion and the bottom line.

When we talk about data, we’re really talking about two types: one, structured product data that fuels the e-commerce experience and, two, the insights retailers can gain by measuring how shoppers interact with product data once it’s exposed on the site. Retailers can’t measure interaction with product data that doesn’t exist, so they must start with quality product data to gain the insights they need. Investing in rich product data will deliver a better online shopping experience, uncovering insights about products and customers, and, ultimately, increasing revenue. What follows are the key business cases for better data.

Consumer Demand for Better Product Data Grows

Better product data to fuel navigation is increasingly important as the limitless space on the digital shelf continues to expand. The ability to filter or narrow search results easily becomes more critical as the number of products in a category increases. Shoppers don’t want to scroll through thousands of products or play hide-and-seek with the search bar trying to guess what keywords might get them to the product they want. This challenge is growing exponentially, especially for retailers adding drop-ship and “online only” inventory to their e-commerce assortment.

It’s not just about the number of products. High-consideration products like sofas and televisions require richer product data to help shoppers navigate and compare the numerous dimensions and features associated with each item. The surefire way in which retailers can create value for customers with data is by decreasing their search and evaluation costs. Retailers can do this simply by being more relevant and informative with product search results. Filters, product finders and recommendation engines all depend on the quantity and quality of structured product data to give online shoppers the tools they need to make decisions.

Inaccurate, Incomplete Product Data Hides Inventory

When structured attributes are missing from products, merchandise won’t be included in search and filtered navigation results. Research shows that most e-commerce sites are challenged by missing structured product attributes, which not only hides inventory, but also is often so frequent that it trains shoppers not to trust filters or search technology. Some shoppers describe this phenomenon as “filter FOMO,” or the fear that if they use filters, products they know the retailer sells will be hidden. Consumers don’t view it as a fundamental data problem, but rather a frustrating experience that doesn’t help them find the products they want to buy.

Translating ‘Merchant Speak’ for Consumers

Every retailer has its favorite examples of “insider baseball,” where its merchandising or “spec speak” is so unique to its business that no one outside its four walls would ever guess what specific terms mean. Sometimes, the specification is accurate, but simply meaningless to a normal shopper.

For example, a shopper might be looking for a “family size tent,” but is only able to search by the number of people the tent will hold. Retailers must translate their vocabulary into the language of consumers to connect them with the right products. Furthermore, on-site search, filtered navigation, product recommendations and personalization engines all require quality, structured data to deliver a great user experience. Since merchandising and sorting rules are driven by structured attributes, many merchants are naturally limited by the quality of the product data available.

Enabling More Innovative Merchandising Strategies Via Shared Data

All too often, interesting new campaigns or e-commerce strategies are limited not by a lack of creativity, but by the inability to execute with the constraints of existing product data. The ability to launch new, innovative campaigns with, for example, targeted landing pages is directly tied to the ability to quickly and easily sort products by shared attributes. With this approach, retailers can unlock creativity previously trapped under the weight of immovable and inaccessible product data.

Better Product Data = Improved Results

Put simply, enriching structured product data drives significant increases in engagement, conversion and revenue per visit by helping shoppers find the products they want to buy. In addition to these top-line metrics, enriched product data has a huge impact on retailers’ ability to execute and expand their merchandising and marketing strategies. It’s general knowledge that when a shopper struggles to find what they’re looking for on a site, they leave frustrated and look somewhere else. However, that doesn’t have to be the case when using enriched product data.

Based on aggregated data from our own customer base, we consistently see that after retailers use product intelligence to power their e-commerce sites, they see an average increase in revenue of 10.7 percent per visit and an average 7.6 improvement in conversion rates.

Most recently, JoS. A. Bank announced it has used enriched data to unlock operational efficiencies. With product intelligence, JoS. A. Bank reports that it has been able to create more than 60,000 new product attributes, resulting in a 7.8 percent improvement in filter engagement. Other key results for JoS. A. Bank delivered by product intelligence include the following:

• Immediate, agile product enrichment for nearly 8,000 products across the JoS. A Bank site in 30 days — a process that would have required 11 full-time resources if attempted only by human resources alone.
• Expansion to 43 total product attributes across the JoS. A. Bank site, a 617 percent increase beyond the same six attributes per category per page, including fit, size, color, material and collection.
• Continually curated daily product feeds for 7,500 new product values per month.

Language, customer sentiment and merchandising strategies change. We know that retailers have no shortage of ideas for creative ways to present and market their products, they just lack the resources and flexibility to quickly execute those strategies at the product attribute level. The bottom line is this: Enriched data allows retailers to create a powerful shopper experience and impacts every element of your e-commerce experience, from search to navigation, to personalization, to SEO and SEM. That means higher engagement, as well as higher conversion and revenue. Most importantly, it also means happier (i.e., more loyal) customers.

Roland Gossage is the CEO of GroupBy Inc., a provider of relevancy-focused e-commerce solutions.