Natural Language, a Solution Who’s Time Has Come

September 29, 2011

Editor’s Note: The Beyond Search team invited Craig Bassin, president of EasyAsk, a natural language processing specialist and search solution provider to provide his view of the market for next generation search systems. For more information about EasyAsk, navigate to

This past February I watched, along with millions of others, IBM’s spectacular launch of Watson on Jeopardy!  Watson was IBM’s crowning achievement in developing a Natural Language based solution finely tuned to compete, and win, on Jeopardy.

By IBM’s own estimates they invested between $1 and $2 billion to develop Watson.  IBM ranks Watson as one of the 3 most difficult challenges in their long and successful history, along with spectacular accomplishments such as the Deep Blue chess program and the Blue Gene, Human Genome mapping program.  Rarified air, indeed.

While many were watching to see if a computer could defeat human players my interests were different.  Watson was about to introduce natural language solutions to the broader public and show the world that such solutions are truly the wave of the future.

The results were historic.  Watson soundly defeated the human competitors.  On the marketing side, IBM continues to spend hundreds of millions of dollars to tell the world that the time for natural language is now.

IBM is not the only firm to bring natural language processing (NLP) into the application mainstream:

  • Microsoft acquired Powerset, a small company with strong NLP technology, to create Bing and compete head-on with Google,
  • Yahoo, one of the original Internet search companies, found Bing compelling enough to strike an OEM agreement with Microsoft and make Bing Yahoo’s search solution,
  • Apple acquired a linguistic natural language interface tool called Siri, which is now being incorporated into the Mac and iPhone operating systems,
  • Oracle Corporation bought Inquira for its NLP-based customer support solution,
  • RightNow Technologies similarly acquired Q-Go, a Dutch company also providing NLP-based customer support solutions.

Many companies are now positioning themselves as natural language tools and have expanded the once tight definition of NLP to include things such as analyzing text to understand intent or sentiment.  This is the impact of Watson – it has put natural language into the mainstream and many organizations want to ride the marketing current driven by Watson regardless of closely aligned their technology is with Watson.

But let’s also look at Watson for what it really is – one of the most expensive custom solutions every built.  Watson required an extremely large (and expensive) cluster of computers to run – 90 Power Server 750 systems, totaling 2,880 processor cores.  It also required substantial R&D staff to build the analytics, content and natural language processing software stack.  In fact, IBM didn’t come to Jeopardy, Jeopardy came to IBM.  They replicated the Jeopardy set at IBM labs, placing a a great deal of horsepower underneath that stage.

The first foray of Watson into the real world will be in healthcare  and the possibilities are exciting.  Clearly IBM intends to focus Watson on some of the largest, most difficult challenges.  But how does that help you run your business?  You’re not going to see Watson running in your IT environment or on your preferred SaaS cloud anytime soon.

If Watson is focused on big problems, how can I  use natural language solutions to better my business today?  Perhaps you want to increase website customer conversion and user experience, better manage sales processes, deliver superior customer support, or in general, make it easier for your workers to find the right information to do their job. So where do you go?

That’s where EasyAsk comes in.

I mentioned a few interesting solutions above, but let’s talk about four specific areas: e-commerce, CRM, HRIS and healthcare.


One of the biggest surprises to me is how often companies will settle for terribly inadequate search.  When we first meet with customers, our first challenge is to find problems with their search.  Most of the time, it is not too hard.  When the value of better search is so well documented, why would you settle for bad search?  It feels like most companies have given up on the search box as a real customer conversion tool.

EasyAsk natural language search delivers the best results in the industry.  EasyAsk natural language makes the search box work!  First time, every time.  It allows customers to find products in a single click and virtually eliminates no results pages.  This is called customer conversion – and it is the easiest way to increase e-commerce revenue.  E-Commerce leaders such as the Lands End, Lamps Plus, Coldwater Creek, Harbor Freight, Dollar Days and others use natural language e-commerce search today to deliver tangible results every day.


Companies are often challenged to get their sales, marketing and support teams to use the CRM systems they buy.  Why?  Because it is difficult for these non-technical business users to find and analyze the myriad of information about leads, accounts, opportunities, sales and more.  While CRM systems are good at capturing customer and sales information, the built in tools and interfaces are often difficult or inflexible to use by the average CRM user.

EasyAsk has implemented a natural language search and analysis interface for sales on top of SugarCRM and NetSuite.  It is now easier than ever for sales reps, managers and executives to get visibility into their sales processes and execution to increase revenue.  So, EasyAsk enables users to ask questions of their CRM system in plain English.  A sales VP can ask three questions in 30 seconds to get visibility into the sales pipeline:

“Show sales last quarter by sales rep”

“Show open opportunities forecasted to close this quarter by sales rep”

“Show new qualified leads from last quarter”

The end result is greater visibility into the sales process and the ability for everyone to finally get maximum productivity from the CRM system without complex training programs.  There’s no need to displace or replace your existing CRM solution, we’ll enhance it.  Now, could this be any easier?  Truthfully, I can’t imagine how.


Natural language has the potential to help dramatically increase the quality of healthcare.  While IBM recently announced a relationship with Wellpoint to create such solutions on Watson, other firms are using EasyAsk today to make that potential a reality today.

Hartford Hospital uses EasyAsk natural language tools to find patient information and analyze healthcare delivery processes to increase the quality of care.  Siemens has incorporated EasyAsk natural language in their healthcare solutions and is bringing such benefits to customers worldwide.

Human Resources

Application ISVs such as Personnel Data Systems, Gensource and Ceridien have revolutionized Human Resource applications with natural language interfaces driven by EasyAsk, allowing managers and HR reps to more effectively manage the skills the company has, and ensure employees are utilized effectively.

This Is Not Just the Beginning

The applications for natural language are limitless.  Natural language tools to identify the right investments, analyze pharmaceutical trial information, select the right communications services, find flights, hotels or other travel services, and even tools that help children better study history.

While Watson holds great promise for the future, EasyAsk provides proven solutions that can improve your business today.  What is your idea for a natural language solution?  I’d love to hear.  Contact us at and let us know your ideas.

Craig Bassin, September 29, 2011





3 Responses to “Natural Language, a Solution Who’s Time Has Come”

  1. Lucie Battaini on September 29th, 2011 4:20 am

    Cool way of writing. Kudos 🙂

  2. Language Matters and Computational Linguistics | maplemuse on September 29th, 2011 9:38 am

    […] Natural Language, a Solution Who’s Time Has Come ( […]

  3. Jordi Torras on September 29th, 2011 1:09 pm

    Great article! and Natural Language Processing can also help at SEO too!

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