TipTop Technologies has just debuted two self-serve semantic data analytics services for small and medium-size businesses, to join its custom-service solutions directed at helping larger enterprises in the finance, marketing and publishing verticals engage in activities such as semantically classifying and categorizing unstructured information on the web, and track and influence company, product and topic buzz.
The two new solutions are Web Page Analyzer and Tweet Analyzer. “The notion here is that we want to make TipTop available very broadly, for deeper data analysis, and for anyone to leverage,” says Shyam Kapur, president and CEO of TipTop.
With Tweet Analyzer, users for a fee can upload .CSV files of tweets and in return receive a .CSV file that gives them back an understanding of those tweets’ contents, their main concepts and sentiment. “This is oriented clearly to those companies that don’t have in-house experience” of doing this, says Kapur. “It’s data analysis on tap.” Similarly, with Web Page Analyzer, users for a fee can submit any number of web pages for processing through the same semantic engine. The pages can be their own or anyone else’s content.
“I don’t think people really understand their own content, especially if they have a sizeable number of pages,” Kapur says. “But in other use cases you may want to understand your competitors’ pages, or others inside blogs or other public domain pages where the topics are of interest to you and your business. As long as the page is accessible without a user name and password, including public Facebook pages, you can process it.” In that way, SMBs can gain more insight into what’s being said about their products – good and bad; about their competitors’ offerings; or the space they serve in general.
TipTop actually began in the consumer space. Its products there include semantic information discovery system TipTop Insight Engine and TipTop Shopping, which uses its semantic engine to analyze user-generated product reviews from Amazon and highlight the best ones on a variety of features. Another recent launch by the company were iOS and Android versions of its Insight Engine to replace its mobile site. “The fundamental value proposition is similar to what is on our site, since they are conversions of our site for the app platform,” says Kapur.
“It will process news from hundreds of sources to find interesting and buzzy things. You can see what happening in the world updated every 5 minutes, explore whatever you like, and slice and dice it by sentiment to see positive and negative perspectives.”
Still in the works is PartyT, which is expected to be a paid consumer service, drawing on TipTop’s engine’s ability to read language as humans do, that Kapur says will be “something new – an evolution of service, ecommerce, of social networks, of the web as a whole.” Users will be called T Drinkers, and, as Kapur describes it, they can be humans or machines, each account participating in the network anonymously so that participants can express themselves freely. What he aims is for Party T to be “an instantiation in silicon of all human minds.”
Once logged in, a user is placed in the middle of all the conversations that are going on within TipTop at that time. Since anonymity is guaranteed, no one on the network can know exactly which identity or account – man or machine – is responsible for which contribution or interaction.
Users and TipTop will be in a continuous natural dialogue within TipTop, he says, and most of what will be shown to users as a result of that are tips processed via TipTop. Users, for example, who express in natural language a comment about what movie is worth watching, can get recommendations, show times and theatres showing movies that fit a certain description (those that show the human side of life, for instance); be given appropriate options once they’ve explained the timing that’s good for them; and upon the expressed thought about having a friend attend the event with, be shown the names of a few friends who are likely to enjoy watching that kind of show. It can even send an invite to them – not to mention booking the seats and suggesting a nearby restaurant.
“Enabling this kind of completely natural dialogue is quite within our reach now,” Kapur says. “By making TipTop a constant companion of the user, we also make the user feel comfortable revealing a lot about themselves and their preferences to TipTop. TipTop can thus provide highly personalized tips over a long period of time, not only one-time tips as a direct result of some single action that a user takes.”
Any thought that anyone shares will be valued more highly by TipTop only if it is supported by solid evidence, he adds. “In fact, one purpose of having data analyzed by TipTop is to generate the kind of solid evidence that could back a statement/thought/opinion someone wishes to make,” he says.