Archive for month: July, 2012


Gartner E-Commerce Search Best Practices Part 2

In my last blog post, I discussed the recent Gartner report “Best Practices in Strategically Combining Search, Content Analytics and E-Commerce.” One of the most important e-commerce search best practices that analysts Whit Andrews and Gene Alvarez emphasize is the ability to “Offer effective definition-matching and handling of ambiguity in Query terms.” Let’s take a closer look at what this means, and how it applies to your search environment.

Effective Definition Matching

The Gartner reports talks about how a truly effective e-commerce search environment must understand the “language variations that are specific to what’s being sold and the audience to whom it’s being sold.” This really boils down to two items a search engine must be able to do:

  1. For each term in a search string, understand what that value represents – an attribute, product name, product category, etc. – and allow each column to have different relevancies.
  2. The ability to process search strings of different complexities as entire entities and understand how the individual terms relate in order to return the most accurate results.

This is the essence of natural language.  A natural language engine will process a complete search phrase, break it down linguistically and understand the full meaning of the request – NOT just what individual terms mean.  In this way, a natural language engine such as EasyAsk can fully support the specific “language of the site” and allow visitors to “speak” to the site in that language via the search engine.

With natural language processing, you can be assured that not only will simple searches – “blue shirts” – be processed effective, but so will complex ones – “women’s blue short sleeve shirts under $50.”  You can fulfill this e-commerce search best practice with the most effective definition matching possible.


Ambiguity can come in many different forms.  It can come from mistakes or typos.  It can come from simple language variations such as different tenses.  Or it can come from a visitor’s lack of knowledge of the products – asking for “purple blouses” when none are available on the site.  To help you fulfill this aspect of the Gartner best practices, your search engine needs to give you the following:

  • Spell correction – your search engine needs to provide automatic spell correction.  Anticipating and pre-coding every potential misspelling of each term on your Website is a time consuming task. Who wants to do that?
  • Stemming – Your search engine needs to automatically support the different tenses, plurals and other variances of terms.  Once again, why should you need to have the time consuming task of entering every potential variance of each term?
  • Relaxation – this concept allows the search engine to drop part of a search term if no specific products exist in order to make sure some products are returned.  Seeing some products is always better than seeing NO products.  With relaxation, a search for “black levi jeans” will still return Levi jeans, even if there are none in black.  You search engine needs to have automatic support for this capability.

All of these characteristics will help you virtually eliminate the dreaded “no results” page and dramatically enhance the customer experience by always returning products to the visitor, even when there is some degree of ambiguity.

Further Flexibility

What if your “site language” is more complex than standard terms?  What if your site has a number of acronyms and industry terms?  What if you have cryptic model numbers that customers need to use to find parts or products?

To fulfill this last requirement, your search engine needs to make it easy to add synonyms, custom search terms and rules.  Once again this is where natural language engines help you implement best practices.

With natural language, you easily specify additional search terms and rules in – well, natural language.  You simply type in terms of any level of complexity and associate those with the existing terms or products in your catalog by simply pointing and clicking.

Learn More

To read more on these capabilities, please download our white paper, “The ABCs of E-Commerce Search: A Guide to Essential E-Commerce Search Features.”  In Part 3 of our blog post series, we’ll look at best practices in Search Analytics and Merchandising.


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Free chapter of Greg Nundelman’s Book, “Designing Search: UX Strategies for eCommerce Success”


EasyAsk Best Practices White Paper, “The ABCs of E-Commerce Search.”



Gartner Best Practices in E-Commerce Search – Part 1

July is “Best Practices” month here at EasyAsk – where we describe good search, navigation and merchandising techniques that can help you convert more customers.  As you and your teams ramp up for busy back-to-school and holiday seasons, we want to help you convert more visitors into sales.  Over the course of this month, our team will show different best practices in search, navigation and merchandising and how they can impact customer experience.

While EasyAsk has many lessons to share, we always like to recognize best practices from independent firms, especially when they align with our vision. Gartner, a preeminent research firm, recently released a report called “Best Practices in Strategically Combining Search, Content Analytics and E-Commerce“, written by Whit Andrews and Gene Alvarez – two of the brightest minds in e-commerce and search.

Among the findings in this report, the Gartner analysts clearly stated the value of search, navigation and merchandising to an e-commerce environment:

  • Search is the means by which shoppers most nakedly reveal their needs and wants (as they themselves perceive them) to sellers.
  • Search is, therefore, a particularly powerful way to promote, relate and reveal products in a shopping experience.

The analysts went on from there to lay out two very important best practices in e-commerce search:

  1. Offer Effective Definition-Matching and Handling of Ambiguity in Query Terms
  2. Use Search and Content Analytics to Fulfill Shoppers’ Desires Through Merchandise, Related and Suggested Offers, and Advertising

These two best practices highlight the unique advantages natural language technology delivers in an e-commerce search environment.  Since natural language understands both the intent of the search and the content being searched, visitor searches are more accurately matched and the search engine seamlessly deals with ambiguity – misspellings, tenses, stemming and when to relax terms.  Natural language also understands the relationship between terms in a search to derive contextual meaning and further eliminates ambiguity.

In addition, the actionable analytics and natural language business rules in EasyAsk make it easy for your business people to better merchandise your site with context-driven offers, promotions and ads.

In the next two blog posts of this series, I will drill down into each of the two Gartner best practices we discussed above.  I will examine the best practices, detail how natural language fulfills the promise of these best practices and show customer sites where these practices are applied.

The most valuable best practices typically come from experts that have visibility into the widest spectrum of implementations – learning how smart people across the industry approach problems differently.  We’re always happy to confirm when EasyAsk best practices match those of top-tier research firms, such as Gartner.

Ready to see how EasyAsk's eCommerce solution can help you? Request a demo!