The need to understand social media has been around for a few years now. Companies are increasingly realizing that the discussion of their products and services has gone viral. For some companies this means the conversation has moved into an environment that they just don’t understand. Viralheat seeks to bring understanding to large enterprises and small businesses alike through their shockingly affordable social media analytics services. Adoption is it’s goal with a new free sentiment analysis API released one year after their free social trends API.
Now that Twitter has created a machine readable transcript of human conversations, we’re seeing a new application for analytics: how do you understand 1,000 simultaneous conversations? This is a impossible task for even a team of humans but it is the perfect project for high powered computer systems. Until now, the cost of such a service has been prohibitively high, with analytics for the “Twitter firehose” running into the $1,000s.
I had the opportunity to chat with Viralheat’s CEO Raj Kadam and CTO Vishal Sankhla last week. They told me the story of the organic development of their social media analytics platform. Initially, Viralheat was focused on tracking viral videos. Over time their customers began to ask for insight into the social networks. One request led to another until the gap in the marketplace became clear. Where was the affordable provider of social media analytics? Viralheat’s leadership would like to see social media analytics adopted as widely as google analytics. In their eyes, it should be a utility that anyone building a website can harness.
What we’re witnessing here is a fundamental shift in the mode of communication between companies and consumers. In the old model, consumers had to go to companies through their store, website, or hot line in order to provide feedback. With the advent of social media, the conversations that used to happen person to person are now machine readable and highly shareable. In this new scenario, it is the companies that must seek out the conversations that their customers are having publicly on other platforms.
Viralheat has a pretty powerful distinguishing factor at the heart of its sentiment analysis API: it has been training on data from 1,300+ customers. Add that to the fact that calls to the sentiment API are free up to 5,000 per day or 150,000 per month and you have a compelling offer. Another unique component is that the sentiment API from Viralheat continues to train as you use it. Application developers can use a feedback API call to tell Viralheat if they think it has made a mistake, thereby continually improving the quality of the sentiment engine.
Kadam and Sankhla laid out an interesting scenario related to financial markets. Suppose you have a publicly traded manufacturer that produces nine products. You can track the sentiment ratings on those products over time. What will it mean for the stock if sentiment is trending downward? This kind of information seems ripe for inclusion in company-specific or industry-focused investment research reports. Of course, individual stocks, or collections of stocks can be tracked as well, but that application is elementary.
The Viralheat API returns responses in both XML and JSON. Viralheat is one of 13 social analytics APIs.