Is your site search producing relevant, personalized results? Are you getting the conversion rates you want?

If you’re in the e-commerce space, these statistics may not be new to you: while only 30% e-commerce visitors use site search, conversion rates through site search can be up to 50% higher than the average. But even the top-tiered e-commerce sites fail to provide the most optimized search experience for online shoppers - 70% don’t have product synonyms enabled and 65% don’t support spelling corrections.

Being so accustomed to Google and Amazon, online users have come to expect similar e-commerce site search quality. If your e-commerce search is lagged behind, your conversion and retention rates may suffer.

We’ve learned from first-hand experience that e-commerce site search performance does have a measurable impact to the bottom line. A modification or improvement to a particular search functionality can produce a correlated increase in conversion rate, and thus overall e-commerce revenue.

Although the same set of search functionalities is used across the e-commerce industry, the challenges and ease of implementing them are drastically differed for every search engine and every unique e-commerce website.

Having an actionable search strategy roadmap can help you better understand your e-commerce search engine – its strengths, weaknesses, and a clear view of what’s needed to be done for short- and long-term improvements. An example roadmap that's worked well for our customers is the e-commerce search optimization scorecard.

E-commerce site search optimization scorecard

The search functionalities in the scorecard are organized based on basic vs. leading-edge functionalities on one spectrum, and difficult to achieve vs. easy to achieve functionalities on another spectrum.

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e-commerce search scorecard

E-commerce site search optimization scorecard

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You can use the scorecard to thoroughly assess each of your e-commerce search functionalities – which functionalities does your website already have? Which ones are doing well or not so well? Which ones can be implemented quickly and have an impact on the bottom line? Remember, where each functionality is placed on the scorecard depends on the specific e-commerce website and search engine.

Take a large e-commerce client of ours for example.

The company has successfully implemented some basic functionalities, such as Stock Position Information, Price Ranges, Language Support, etc. However, three other basic functionalities - Query Completion, Spell Correction, and “Did You Mean” - were missing. These fundamental features, once implemented, resulted in an increase of 2% in conversion rate and a drop of 50% in failed queries.

Having an actionable strategy can help you better understand your e-commerce search engine. Built on proven e-commerce site search best practices, your strategy can identify your site search's strengths and weaknesses and provide a clear view of what’s needed to be done for short- and long-term improvements. 

E-commerce site search features defined

Below are the definitions for some of the functionalities mentioned in our e-commerce search optimization scorecard. By implementing these site search features following best practices, you can boost your e-commerce site's effectiveness and increase revenue.

  • Breadcrumb negation - allows a customer to remove previous selections from the query without going back to the start. For example, a user searches for "Plasma TV," then selects "Sony," then selects price range "$400-$600." At this point, they realize they can’t get a Sony TV within this price range. So if they negate the "Sony" selection (which is midway in this query), then it will keep the price range filter ($400-$600), but open up to brands like LG, Toshiba, Panasonic, etc.
  • Category facets - faceted classification gives the users the ability to find items based on more than one dimension, such as product facets, special feature facets, etc.
  • Category snapping - allows the search engine to understand the query better, resulting in a more satisfying user journey. For example, "Nike Sneaker red 12" probably means Brand:Nike ShoeType:Sneaker Color:Red Size:12.
  • “Did you mean?” - provides relevant alternative suggestions when the user may have misspelled a search term.
  • Facet negation – when a user clicks on the “negation” icon next to an option, the option will be removed from search results.
  • Intelligent query parsing - translates a search string into specific instructions for the search engine. Intelligent query parsing can take the context of the search query into account and produce more relevant search results.
  • Personalization – uses big data and log analytics to provide relevant product recommendations based on online users’ search queries and click activities.
  • Phrase search - allows users to search for content containing an exact sentence or phrase rather than containing a set of keywords in random order.
  • Query completion - predicts the rest of a word or phrase that the user is typing into the search box, based on popular search queries or queries selected by the retailer.
  • Query fall backs - allows a search engine to "step back" when it knows some combination of terms won’t find good results. For example, "little black summer dress" may produce good results, but falling back to "black summer dress" will.
  • Query redirection - redirects a user's search query to relevant results when that specific query produces no results.
  • Relevancy ranking – uses predictive analytics to predict and place the items the user will most likely to buy at the top of the search results page. See how search engine scoring works to enhance search relevancy.
  • Results pagination – splits search results into multiple pages.
  • Social navigation - a user's navigation through the website is guided and structured by the behavior of other users.
  • Spell correction - uses dictionary documents to find possible misspellings for words entered by a user and suggests the correct spellings.

Contact us to learn more about how we leverage our search quality analysis and the optimization scorecard to help your company improve site search.

Phil Lewis

Functional & Industry Analytics Sr. Manager – Accenture Applied Intelligence

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