What is the point of big data if you can’t show a commercial benefit to the business?
It has been a huge buzzword for years; big data will transform your business and major investments have been made to collect, store and attempt to interpret / analyse the data for useful information to gain competitive advantage. One of the major problems is that big data just keeps on getting bigger!!
According to a recent survey conducted by OnePoll in May 2015 for Rosslyn Analytics only 11% of corporate leaders have been able to generate real financial value from the data they collect. 56% of senior IT managers believe key data remains inaccessible to business decision-makers. These worrying findings from the survey get worse when priorities for the next 2 years are to push headlong into investment in analytics capability without putting strategy first. Alignment of IT and business within these companies appears to be out of kilter, due to the lack of a strategic approach.
Yet again it appears that the worlds of online advertising and marketing are taking a lead on working out how to make data useful and commercially viable; that is because they need to in order to survive and thrive. They focus on making money from their data
because they have to; the simple business case states if we can’t monetise the data we go out of business! They can’t afford to be
collecting vast amounts of data and then being unable to interpret it for commercial advantage.
Twitter’s recent acquisition of startup, WhetLab (www.whetlab.com) is interesting as it is another validation in the market of the need to cut through the noise and get to the money in real-time. Machine Learning applies contemporary science to the understanding of data beyond the current model of rules and taxonomies used by analytics firms globally. The speed of change is immense and as big data gets bigger the limitations in these solutions have become more apparent, perhaps explaining some of the findings in the survey for Rosslyn Analytics. The drive for large global technology players is how can they deliver insight for their customers from the vast array of data they help collect for them. Machine Learning is the way forward; only this method can process the scale of data fast enough to ultimately provide the right information at the right time.
At Chatterbox Labs we have been working on this problem for 6 years through applying scientific rigour to create Machine Learning products utilising our NLP Framework. Our CTO, Stuart foresaw the problems big data would cause and the opportunity for us to resolve this. Our first product, Path 2 Purchase, is a showcase solution to pinpoint, in real-time, purchase intent in short form social data; we can do this in English through to Mandarin. Our patent-pending decision tree and smart algorithms are taught what to look for and can then classify (present benchmark is 146k messages a second) data turning it into actionable information for our partners to monetise. In short at Chatterbox Labs we have the solution to show you the money!!
For more information please contact Andrew Watson VP Strategic Alliances, Andrew@chatterbox.co or visit our website www.chatterbox.co