Internal site search is one of the formative components of an ecommerce site. Every retailer has it, but not every site it using search to its greatest capacity.
With the sometimes overwhelming amount of product choices available to consumers, search, done effectively, can expertly narrow down the list of choices and deliver products that are likely to convert. Done with efficiency, speed and relevance, search will be a tool that keeps customers coming back.
With all of the innovations in ecommerce marketing, tried-and-true site search still remains one of retailers’ most effective marketing tools. In fact, more than 40% of shoppers will use site search as their primary method of finding products on an ecommerce site.
The problem is, while other innovations, like the “quick view,” have been developed to get shoppers to the product page more quickly, site search has lagged behind. A typical site search experience goes more like this: User types in a long-tail keyword like “running shoes” and receives thousands of search results. If filters are available, the users must choose the right filters, wait for the page to load (maybe multiple times if different filters are chosen), then click the right product.
This process requires several clicks, form transmissions and page loads, each of which consumes far too much of the precious little time a retailer has to capture and maintain customers’ interest.
Every retailer knows that the more time it takes customers to accomplish their goals, the less chance of conversion. It could even mean losing a customer for good. A Jupiter Research study found that 80% of customers will abandon a site after a poor search experience.
There are three pillars of effective site search:
· Efficiency: The highest converting ecommerce sites require fewer steps to sales conversion. While many retailers have invested time to streamline the checkout process, too few have given this same focus to search.
· Speed: Research says that more than 50% of users will abandon a site after waiting only three seconds for a page to load. Three seconds! If a site is asking customers to wait while search results load in a new page, and wait even longer for the results to be filtered, they will leave the site.
· Relevance: Consumers expect internal search engines to know what they’re looking for, regardless of the quality of their search time. Unfortunately, 85% of site searches don’t return what the user sought.
In short, effective search is achieved by helping customers find exactly what they’re looking for, in the shortest amount of time possible. By implementing some innovative and best practices in search, retailers can begin to achieve this, resulting in a more positive user experience and higher conversions.
Provide “quick view” functionality from the search box
Display search results as a pop-out menu directly from the search box. Functionality should be “smart” and show results as the user is typing, based on the search term.
Go beyond product listing
Rather than only displaying products from this box, go a step further and let the customer filter directly from that box to reduce the number of clicks. Products should change dynamically based on the filtering, without substantial load time (remember the three second threshold).
Retailers should provide substantial product information in terms of price, a high-level description and review data. All of these components will help customers make quick decisions and encourage clicks.
Personalize the results
If a retailer is already collecting customer browsing and buying behavior data, the data should be used to influence search results. For instance, customer data may indicate that one shopper on your site is male and another is female. If each of those customers types “black dress shoes” into the search box, the results should be dramatically different. Results based on identified customer information and preferences will increase clicks and even further product discovery.
Collect the data
Retailers should utilize analytics tools to not only log “most searched” terms, but also make connections between the efficacy of certain terms with displayed products. The data should answer the question, “What products are more likely to convert on which search terms?”
Once the question is answered, search results should be refined to display those high-converting products.