Research shows more and more shoppers choose to conduct site searches with just a single word.
For its recent E-commerce Performance Indicators and Confidence Report (a.k.a. EPIC Report), SLI recently analyzed a global sample of more than 1.5 billion search queries during the last 4 years and found more than half of searchers only use one word. What’s more, over 80% of site searches were two words or less.
In fact, site searches are actually getting shorter over time. Year-over-year, the number of searches with three or more words is decreasing while the number of one-word searches is increasing. In 2013, 24% of searches included three or more words. This year, only 18% have three or more words.
SLI’s EPIC Report supports recent trends indicating shoppers expect relevant results immediately. In other words, if relevancy and personalization are not part of your e-commerce search strategy (and searchers can’t find what they’re looking for with one word), then shoppers will simply move on.
This is why machine learning is absolutely critical in search and where the magic happens. E-commerce search powered by machine learning “learns” from visitors’ search activity to deliver busy shoppers the most relevant results quickly.
The result is a search function that becomes more intuitive and relevant the more it’s used.
Machine learning is driving more personalized shopping experiences where just one word should be all a shopper needs to find what he’s looking for; without it, you risk losing shoppers to another site with a better, faster experience.