Human versus machine. It’s a conflict that’s existed in society in the form of books, research, film and art for decades, and it’s still at the heart of many up and coming technologies on the market today. From drones delivering packages that used to be carried by postal workers 30 years ago, to new biotech wearables alerting us on basic health metrics instead of doctors, or even those vending machines that serve you dinner on a plate instead of the struggling college student waiting tables at the neighborhood cafe, the balance between human and machine aptitudes and potential is a constant point of contention across industries and perspectives. Think retail is outside of these concerns? Think again! But what if there was a happy medium?
At Edgecase, we think there is. Our technology does just that, in that it combines the power of human cognition, context and variety with the powerful search and navigation capabilities of innovative technologies, making up the magic that is adaptive navigation. We recently polled our social networks to find out how product attribution would be fundamentally different, and better, if curated by how shoppers really think and speak, versus how merchandisers are currently describing them online – the results were remarkable!
We asked our network to describe in their own words two apparel products – a sports coat and a dress, using the actual words they would choose if they were describing the item to a store associate.
We then compared the attributes from our poll results to what’s typically found when shopping for these items online. The typical number of filter options for each product was 5. The shoppers in our poll provided a staggering 75 new attributes. That’s a 1400% increase in the number of terms that shoppers would use to search for a product, versus what retailers are using on their sites! Data disconnect, anyone?
This is a prime example of one of the fundamental disparities we recognize in our philosophy at Edgecase: that humans are capable of reading between the lines to interpret a multitude of meanings, feelings and context, while technology primarily sees the world in black and white. The current state of online shopping cannot compute the subtle nuances that a real-life sales associate would be able to decipher from a customer in the aisle of a brick-and-mortar store, and shoppers are responding accordingly: the global ecommerce market is experiencing a 68.53% average cart abandonment rate and a lowly 2.84% conversion rate. When compared to the 20–40% average in-store conversion rate, it’s obvious that it’s high time to fix this disconnect.
Online retail has a communication problem, and the first step to improvement is admission! Retailers must rethink their merchandising strategies if they want to serve their customers the way they want to be served, or else risk losing precious sales and revenue if they don’t.
Luckily, there are opportunities for retailers to improve their online search and navigation experiences by starting with richer structured product data. Digging into existing content to find relevant product descriptions, reviews, images and videos can help retailers get more out of their current investments. Translating raw merchandising feeds into “shopper speak” can help you build out expanded data sets. Creating context for products within the navigation system brings meaning and perspective to shoppers looking for just the right dress for the summer wedding they are attending next month.
At Edgecase, our collaboration between human curation teams and the power of machine-driven digital experiences is constantly filling the gaps in merchandising data to inspire more personal and inspiring product discovery experiences for online shoppers.