sentiments-architecture1Imagine you are responsible for ensuring quality and brand reputation of a auto vehicle and assuming the vehicle is connected to IBM Watson IoT Platform that monitors health as in mileage, oil levels, pollutants, electrical circuits, tire pressures and what not. Real time analytics in IBM Watson IoT Platform monitors events to detect alerts. Assuming a drastic loss in steering fluid on a brand new was detected and an alert was sent out for you to act upon. Well at this point, the first action would be to reach out to this particular customer, notify them about the problem and advice an immediate visit to a service station. Maybe even offer a free fix.

Asa followup, engineering will be engaged for root cause analysis. But you still need to fix out the deep of this problem across the several tens and thousands of sales of this particular make, model and year. As brand reputation is of core concern to your efforts, you would like to learn the social sentiments on this topic. This is where our work comes into play.

Visit our recipe on Social media integration with IBM Watson IoT platform where a topic to search the social world is derived from an insight captured by IBM Watson IoT Platform. The resulting comments or blogs on the related issue are analyzed with Watson APIs for Sentiments (positive and negative) that provides data required to identify the wide spread nature of the problem. If social sentiments go un-noticed, manufacturing companies risk reputation to the brand and millions to fix a recall.

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