If you go to your favorite fashion and apparel website and type a typical, specific search term for something you need or want into the search bar, what do you typically find?
For me – the shopper looking to spend money – I am met with a surprising amount of resistance. “Men’s summer pants,” a common, warm-weather theme, is met with zero search results. Of course I can navigate with several more clicks through my favorite site’s shelf hierarchy – searching for airy cottons and lightweight linens – but why should I have to? Why doesn’t anything relevant, even a best guess, appear in my search window? The answer is simple: thin and inconsistent product data.
The Importance of Product Data
Under the hood of each of the millions of product listings online is data that describes the item being sold. That information, whether present or not, is helpful in providing relevant search results for shoppers. For my e-commerce friends, Amazon advertisers, Google Search specialists, and marketers out there—think keywords or hidden keywords—it’s any of those seemingly inconsequential strings of text that you’re asked to associate with your product detail pages or web address, or bury in your site’s many webpages.
That product data is the single most important requirement for capturing the attention of and then converting today’s highly intentional online shoppers.
You might be thinking to yourself, “Why do I care? Only 5% of my site’s conversions take place in search.” That may be true; however, there are a few things to consider before writing off the value of search.
- Search bar shoppers are 2.4x more likely to buy and spend 2.6x more money.
- 80% of consumers are more likely to make a purchase when brands offer personalized experiences.
- 77% of consumers have chosen, recommended, or paid more for a brand that provides a personalized experience.
- 68% of shoppers would not return to a site that provided a poor search experience.
These salient data points paint the clear picture that retailers who ensure a seamless and relevant site search experience will be able to better engage and convert high-intent, deep-pocketed search-bar shoppers.
Go Beyond the Basics
Typical retailer product attributes tend to stop at the basics, and can even possess some inconsistencies or inaccuracies due to traditional manual labeling processes. In the above case, describing a gray, nylon puffer jacket as just a gray, nylon puffer jacket (maybe it’s also red).
With this basic level of product detail, shoppers who are only ever looking for those attributes are the only people who will be presented with this item.
What about all of the shoppers who know what they’re looking for, and when they find it, they know they are probably going to buy it? With Lily AI, our customers are enjoying 10x more attributes for each of the products in their assortment – and those attributes are allowing them to present search results for all of the more subjective and thematic searches that high-conversion shoppers are making on their website.
How Can Retailers Ensure a Consistent and Seamless Search Experience?
With Lily AI’s Product Attributes Platform, we’re ensuring that retailers can meet the unique needs of each of their shoppers. This means providing a relevant shopping experience whether the customer is in the research phase, or if they’re visiting a website with a specific purchase in mind. To provide exactly that experience, retailers are leveraging Lily AI’s highly-trained, seven-plus year-strong machine learning pipelines—built and trained by a diverse team of industry and domain experts. With over a billion training data points collected, and 2,000,000+ new ones added daily—our product attribution technology provides the richest, deepest, and most accurate data available on the market today.
Additionally, we’ve built the Lily AI Product Attributes Platform from the ground up to be completely flexible in its application across diverse retail tech stacks. We avoid rip and replace, instead opting to augment your current set of applications with a highly accurate and robust set of inputs. We firmly believe that “quality in equals quality out” – and achieving that level of quality is driving eight-and nine-digit revenue lifts for some of our favorite retail brands!
