Due to the increased functionality of search engines over the years, customers today have high expectations for the search results that appear within eCommerce sites. While on sits, customers expect to find exactly what they’re looking for and in a timely fashion. The better they’re able to, the more likely they’ll convert. There is nothing worse then typing in a search query, to only discover the dreaded words: “No results found.” This is not only annoying to the user, but also detrimental to site owner; as no search results often pushes potential customers to shop competitors and sales are lost. For this reason, intelligent site search function is probably one of the most important components to increase sales or improved eCommerce success. So how can you ensure that our site search is optimized to where customers receive the best experience possible and find what their looking for? For starters, let’s discuss two common occurrences which are known for delivering those pesky no-results found pages.
According to many resources I’ve read, user misspelling is often the primary cause of no search results pages on eCommerce. Second to misspelling, comes over-constraining typically occurs. In brief, over-constraining is typing too many keywords within a search query. To mitigate these two common occurrences, a robust partial match strategy should be implemented.
Partial match strategy is essentially a piece of a users search query that matches what is available online. For example, if a customer types, “women’s size 8 tan ice skates”, the site output will show “women’s size 8 tan ice skates“. This is similar to Google, which bolds the relevant keywords on their SERP. Incorporating a robust partial match strategy into your eCommerce site is essential, because it often times keeps a user engaged on your site, even when a search attempt fails; for example, when zero matches populate. Often times what people initially search for, isn’t always what they end up at the checkout with. A partial match strategy offers you the opportunity to show your visitors not what you can’t offer them, but, what you can.
Second to developing a partial match strategy, I’d also look into a search function known as partial match or auto suggest. This feature will speed up the process of search while also showing the visitor a full range of what your website offers. For example, if a user has the intent to search for Bobbi Brown lipstick, the moment they start to type Bobbi, a list of all product titles beginning with “Bobbi” will populate in a window below the search bar. This auto suggest is basically partially matching the users search without the need to put on display the omitted keywords (as in the case with “size 8 tan” in the example above) that weren’t available. Additionally, an added benefit is this feature will reduce the number of misspelled searches which deliver a no search results found page drastically.
Although this is just a taste of what comprises of an intelligent site search function, it is a start. eCommerce sites today need a robust site search strategy because it means better usability; translating into increased sales, in addition to, higher conversion rates, increased site usage, positive customer experience, retention and loyalty, and finally, improved branding.