Google Analytics gives web site owners good information about what’s clicking with visitors to their site, how those users got there, and more. But, attaining that insight can be somewhat laborious for those not well-versed in the tool and its interface, says Nick Cassimatis, associate professor in the Department of Cognitive Science at Rensselaer Polytechnic Institute. He’s the founder of natural language processing technology startup SkyPhrase. His take: Apply SkyPhrase to the task, and things get a lot easier.

The startup in February began private beta testing of its NLP interface to Google Analytics. “Google Analytics lets you ask things like how many people from California visited the site last month, or which of your pages were most visited on mobile devices,” says Cassimatis. “Our system lets you ask these questions in natural language and get answers to them” more seamlessly than using Google Analytics alone.

Previous to bringing its NLP help to Google Analytics, SkyPhrase had a public site that let users run natural language searches of their Gmail or Twitter accounts, as well as flights and music.

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Online publishers and other content providers have a new analytics tool to help them understand what their readers care about and use that information to better connect them to their sites’ relevant and compelling content. Launching today is Dash, based on the predictive content analytics platform Parse.ly. The technology crawls every article page for Parse.ly’s publisher-partners, and analyzes, in real time and at scale, the text to identify relevant topics to group related content together. Behind this lies natural language processing technology, which uses language queues hidden inside the text to determine its affiliated topics. To date Dash has extracted over 350,000 unique topics through all the URLs is has crawled during private beta for a healthy taxonomy of topics across the web being consumed by users.

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