‘The time has come, the Walrus said, to talk of many things . . . ‘
But instead of ‘shoes and ships and sealing wax’, let’s talk about something that is new, different and exciting: the emergence of Natural Language as the next logical step in the evolution of search and business intelligence.
When you think of search, you probably think first of Google, and with good reason. They’ve done a masterful job of establishing themselves as the pre-eminent force in the field of ‘search’. Google taught us all how to search. But, the problem is, they taught us all how to search . . . WRONG.
With Google you don’t search for exactly what you want. You search for ‘kind of what you want’ and hope that what you’re really looking for will be on the first few pages of the 10,000 they return.
‘The time has come . . . ‘ to talk about NLP – Natural Language Processing and how computers can now understand, not only the content, but also the INTENT of what it is that you are looking for.
Our mission, at EasyAsk, has been to expand beyond the traditional ‘key word’ search bottleneck and provide the next generation of NLP-based search for both ecommerce search and merchandising, and business intelligence solutions. We’re proud to claim a leadership role in helping advance both the adoption and functionality of Natural Language search.
EasyAsk powers the ecommerce search within the GAP, Lands End and others on the high end, Shuler Shoes, Travers Tools and others in the SMB space. Our partnership with NetSuite provides EasyAsk solutions to their SMB/SaaS markets.
As I’m sure you know Microsoft’s search engine, Bing, is also an NLP-based solution. I, like many of you, use Google, but also use Bing. The results are different. In my experience Bing understands my ‘intent’ and provides a more accurate response to my question. It should. It’s a pretty good NLP engine that crawls the web.
Now we are watching the launch of IBM’s Watson project. The Jeopardy challenge is an excellent test of what an NLP-based solution can do when the right resources are applied. We applaud IBM for this incredibly, successful project and for furthering the cause for NLP-based computing.
But how does this impact you? You’re in business. Maybe you’re a small business looking for an accurate ecommerce solution. You have lots of choices. All of the search engines you’ll look at are pretty good. Almost all of them are ‘key word’ based, some provide navigation. Only one provides an NLP-based engine that will give your customers the item they are searching for on the very first page, every time. Only one allows you to search for products ‘less than $50’, for example.
Only one leads the industry in converting browsers to buyers. EasyAsk.
Maybe you’re part of a larger company and just can’t find answers to the questions you’d like to ask of your Business Intelligence solution. Frustrating. Especially after a team of engineers labored for months, spent millions of dollars trying to build the right BI solution. Possibly you’re one of the thousands of business users desperately trying to get analysis and reports out of your CRM system so you know what marketing campaigns are driving closed deals, what your sales pipeline looks like and which customers are ready for renewal, but have outstanding support issues…
Now imagine similar NLP technology that powered IBM’s Watson, optimized for your corporate information. Watson was able to compete and win at Jeopardy because it understood the questions. You communicate to Watson exactly the way you’d speak to another person.
With EasyAsk Business Edition, you ask questions of EasyAsk exactly the way you’d ask of your VP Sales or your CFO. For example: ‘show me customers who bought products last year, but not last quarter’. It’s easy, just ask. EasyAsk.
So, we welcome both IBM and Microsoft to the next step in the evolution of search. It’s just a better way to search. But . . . and I just can’t resist this . . . we were here first!
Next time, let’s discuss the perfect front end for CRM! Thanks for listening.