It was inevitable. The fact that 'google' is now used as a verb than a noun, searching for stuff is an indelible part of 21st century life. Whether we're hunting for the closest Mediterranean restaurant or the cheapest dry cleaner in town or the answer to the Fibonacci series, search is officially our best friend.
According to Econsultancy, about 30% of all ecommerce site visitors use site search straightaway. It goes on to say that visitors who use site search convert at 4.63% compared to the average site conversion rate of 2.77%.
As a site owner, these are particularly interesting findings. Visitors typically use site search when they are already at an advanced stage of the purchase funnel. This means the probability of converting a user who begins their journey with site search is a lot higher than those who arrive on your site completely clueless about what they want.
It follows that focusing our energies on visitors who use site search would offer a lot better bang for our buck than getting a window shopper to plonk down some hard cash. The best brands in ecommerce understand this fact and incorporate these critical features in their site search with a single clear goal in mind conversions.
Semantic search does not have to be limited to search engines. In fact search engines have pretty much spoiled users for site owners by miraculously reading users' minds and offering them exactly what they were thinking of.
In an ecommerce set up, adopting semantic search means going beyond a search function that only understands keywords and those in their very straightforward avatar. A search function that can process the meaning of the words typed in and not the exact words themselves that is the answer to our site search woes. Let's see this with an example.
When I search for 'boots that can be worn in winter' instead of 'winter boots' Amazon pretty much gets what I'm looking for. It ends up showing me a series of winter boots and leg warmers which is pretty commendable.
You can see this in action even on travel sites. Try typing in a random city name in the flight search function of any user friendly travel site. If the city you have mentioned does not have an airport of its own, nine times out of ten, you will get an airport closest to the city that you've typed in. That's a variant of semantic search for you right there.
What do you do when you can't find something at first glance? Dig deeper, right? Faceted search basically allows users to 'dig deeper' into your site with very specific filters and sorting options. It combines your category structure with your search function and allows users to search using a variety of parameters.
In this example, eBay allows you to not just filter via product categories which is the simplest kind of faceted search. It also lets you drill deeper by brand, price, distance from the seller's location and so on.
What this does is puts the power of choice in the user's hands. Instead of just telling him "Hey, here's the item you wanted," you're letting him pick and choose an item based on his personal preferences which may or may not be possible via direct navigation.
An ecommerce search function is incomplete without autocomplete. Not only does autocomplete offer a helping hand to the customer who is in a huge hurry, it also serves as a source of inspiration for the user's purchase journey. Take a look at Wayfair's search option for example.
I intended to search for silk curtains on the site. Thanks to Wayfair's autocomplete options I now know that they also stock silk flower arrangements, silk comforters (ummm, cozy!), and silk curtain panels to go with my silk curtains.
If I were a user keen on redecorating my home, these search suggestions would plant a seed in my mind which would in all likelihood result in a higher AOV for Wayfair.
This is just one form of autocomplete. I love what Unbxd does in terms of a visual autocomplete option. Instead of simply throwing up text suggestions, this nifty feature offers the option of displaying thumbnails alongside your search suggestions. A picture does speak a thousand words after all!
Ability to Process Long Tail Keywords
An efficient site search engine has the ability to process extreme outliers in terms of search terms and bring up credible results. A long tail search capability is supremely important as the way you think and phrase a search query would be very different from how I do it, which would in turn be completely different from how the search engineers for the site would do it. Hence the aim is to be able to cover the entire spectrum of possible searches and not just the middle of the bell curve. The reason for this is simple. In ecommerce every search unanswered is a sale lost. With average conversions standing at 2 to 3%, losing all long tail search customers would push that conversion rate to near zero. Not a chance I'd be happy taking.
A variant on the long tail search is being able to search by item number or model number.
This again is a very specific kind of search query that not many people would be able to pull off. However the ones who do are clearly well informed about what exactly they want. Being able to offer them such an item would make conversion a much stronger possibility than with a user who randomly searches for a product type.
Search is constantly evolving. Newer capabilities keep getting added to its arsenal nearly every other day. Letting your site roll with one of the many free site search plug-ins which don't allow you to customize what you can offer your users means seriously shortchanging your site when others boast of the niftiest search functions around. Search is a site feature that is not just another pretty addition, it will literally pay for itself via conversions from the word go.