Having a site search engine that’s fulfilling of your needs in a scalable capacity is essential and in many cases, this means having a semantic search function that’s loaded with features. Take a look at some of the ways an optimized site search function can assist ecommerce sites, both big and small:
Smaller ecommerce sites
If your ecommerce site is smaller or has a more targeted range of products, the demand of a site-search function is less about finding a specific product and more about assisting customers in choosing to buy a product.
For example, if your site carries a selection of 20 paintings, customers will likely use your on-site search function to pinpoint specific variables, rather than a broad, overhanging product: they won’t search for “painting,” but will likely search for “watercolor” or “oil painting” instead. As a result, you’ll need a site search function that can pinpoint variables over just categorical designations.
Another great example of how semantic site search can benefit small inventories comes in the ability to search content, instead of just products. If a customer wants to know what a “giclée print” is versus an “acrylic print,” they need to be able to search this on your website outside of just product listings. Content Site Search is just as important as searchable products!
Finally, for smaller product selections, being able to process specialty terms and qualifiers is essential, as well as displaying these results appropriately. If a customer is looking for a “print with frame” or a “painting without frame” they need to see these products immediately, merchandised in a way that makes them singularly appealing in lieu of a wide variety of search results.
Larger ecommerce sites
In dealing with more expansive inventories, a site search function needs to be able to parse a huge number of potential results down into a range that’s helpful to a customer and representative of their exact needs. This is where semantic search shines over text-based searches and those simply reliant on keywords.
First and foremost, semantic search offers features like processing Boolean functions: if your customers need to root out a specific trait, semantic search returns only these results, saving your customer the frustration of sorting through pages of results that might not apply. On top of this, things like true color recognition and variable processing make it even easier to sort through not only products, but their infinite potential for variables as well.
Also of the utmost importance for larger-spanning inventories is the ability of on-site search to recognize spelling mistakes, colloquialisms and the like. In parsing thousands of products and options down to a segment of applicable results, all it takes is for one misnomer or error to skew the entire process—something semantic search prevents on all fronts. For example, a search for “purple t-shirts” needs to return only applicable products—if it includes purple sweatshirts, all color t-shirts or anything else that’s not inclusive of the searched terms, customers aren’t going to see the value in searching further!
Finally, something like Advanced Machine Learning (AML) is required to help larger ecommerce sites better anticipate the needs of customers. Without the data and behavior metrics of past shoppers, every new potential sale is a shot in the dark—it’s better to have comprehensive data that delivers, rather than throwing darts at the wall with search results that may or may not stick!
Scalability is key
No matter if you’re a huge ecommerce platform with thousands of products or you’re a budding shop with a handful of items, an investment in search is an investment that’s bound to pay dividends. When your customers are able to find what they need quickly, with little strife and few detours, they’ll be more apt to not only buy, but also to shop again. Ultimately, this means positive growth for your store and the peace of mind that comes with a scalable search function that can keep up.
