man with a magnifying glass
If you aren't optimizing your site's search capabilities, you are missing out on ways to improve the customer experience and your bottom line. PHOTO: mari lezhava on unsplash

While the battle between traditional storefronts and ecommerce sites plays out, it’s clear we’ve entered a time where providing customers fast, reliable, convenient shopping experiences is paramount. 

Retailers have been shifting attention to their online channels to satisfy these desires, but one-on-one attention from a personal assistant or shopper has traditionally lagged online.

Site search is the online world’s equivalent of a personal shopper. Modern search technologies are intelligent, going beyond basic keyword-based matching to incorporate natural language processing (NLP), which allows shoppers to find the products they’re seeking. 

NLP overcomes nuances in search terminology (for example, searching for “slacks” or “pants”), reconciles synonyms and can deliver relevant results regardless of searcher intention — whether they are merely “window shopping” using vague terms or searching for specific items using SKUs, brands and models.

However, it’s imperative that ecommerce sites owners don’t focus only on what modern search can do for their shoppers (i.e., deliver efficient experiences), but what search can actually do for their business, from a bottom-line business perspective. Here are three ways ecommerce sites can maximize the power of search:

Get More Site Visitors Searching

Site search users are an ecommerce site’s most profitable traffic segment. Search visitors convert at a rate about 350 percent higher than nonsearch visitors, and the average search visitor also generates more than four times as much revenue per visit. This is because when a site visitor starts using search, they are pulled  into the conversion funnel. It’s similar to waving someone into a physical store — getting them inside is half the battle.

For most sites, search users represent a relatively small portion of site traffic, and as a result, search is often not prioritized. This is a huge mistake, because search is an area where simple design optimizations that can have the biggest direct impact on revenues. The key is to get more site visitors searching through simple design optimizations. For example, you can focus on these areas:

Use an open, white text entry field: The color and shape of the text entry field is important to increasing its use. Regarding shape, open text-entry fields (or search boxes) get about three times more use than icons. Regarding color, a white background outperformed every other color by an astounding 204 percent. A blank or white text field is considered to be open to receiving text, whereas other colors may be subconsciously perceived by site visitors as blocked.

Include sample text: This has also proven to be useful in prompting users to search. Simple “start typing” text is useful to draw the eye to the area, but including additional information can be useful too. For example, if your search box supports queries for product numbers or SKUs, you can use text such as “enter product name, number or SKU.”

Place the search bar in the center of the homepage: Traditional header navigational menus typically require three or more refinements (additional clicks) from the user to find the set of products they want. For example, if a shopper is looking for a red dress, she may have to select “women,” “dresses” and then filter by the color red. If the search engine is smart enough, this same set of products can be loaded with a single search query from the visitor. Placing the search bar in the center prioritizes the website’s search feature.

Leverage Profit-Aware Search to Play the Strongest Hand

Once an ecommerce site has succeeded in pulling shoppers into search, is it wiser to showcase the site’s least popular items or its best sellers? The obvious answer is the latter, which means sites must strategically display search results so to push products with the highest profit-generating potential to the forefront, rather than displaying these results randomly (there’s a reason the second page of Google search results is called, “the best place to hide a dead body.”)

This technique is known as product boosting. Once relevancy is established, ecommerce site managers can display results according to business priorities – for example, prioritizing house brands, best sellers, highest conversion and click-through rates, and so on. Recent advances have made product boosting more functional and flexible. For example, implementing the same product boosting rules across all the pages of a site (in this case, a search for “microwave” will generate consistent results displays whether the search originates from a big box retailer’s main search page or its “appliances” category page,) enabling greater merchandising consistency and control for retailers on a site-wide basis.

Alternatively, product boosting rules can be applied just to individual pages, or different rules can be applied to different pages. In the latter example, a site may find displaying results according to best sellers works best on the appliances category page, but sorting by house brands is preferred for their apparel category page. However you apply these rules, the outcome is the same — the sellers are in the driver’s seat.

Derive More Data Through Search

When ecommerce site product data managers enter product information, they typically include the basics such as product name, price, brand and so on. Including more specific product data may require a bit more work, but it can be  advantageous and go miles in terms of improving search relevancy. Examples of more specific data include descriptors like length (above the knee,) cut, sleeves and pattern type. Including more data makes it easier and quicker for shoppers to find exactly what they’re looking for, while also eliminating the need to search in the description field, which is often so cluttered with information that relevancy can suffer.

More expansive data collection helps ecommerce sites cull more data on shoppers likes and dislikes, which has two key benefits — delighting customers (and driving more conversions) as well as providing the groundwork for greater personalization for future visits. Personalization refers to the real-time tailoring of online customer experience to individual shoppers. 

Regarding search specifically, machine learning applied to individual shoppers’ past search data can more accurately predict what items are apt to resonate with shoppers, thereby prioritizing them in search results. The more data you can collect and analyze on individual shoppers, the better. Personalization supports the holy grail of customer interactions — speed, reliability and convenience — and search can be a prime vehicle for delivering it. The dividends can be significant: According to Smart Insights, 48 percent of consumers spend more when their experience is personalized.

In conclusion, there’s a lot of crystal-ball gazing when it comes to predicting the future of commerce. Personal shoppers have traditionally been a hallmark of the in-store experience, but savvy retailers are finding ways around this online. Consider Nordstrom’s clothing-less storefront Nordstrom Local, where customers can try clothes and accessories with the assistance of a virtual stylist, but are directed online to make purchases. In the online realm, search is the closest equivalent to a personal assistant, and ecommerce sites must leverage it to its fullest — not just to delight shoppers, but to maximize their own conversion and profit potential.