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Human Analysts May Now be Expendable

Posted on 6.29.2014

The phrase “I’m only human” is often said after someone makes a mistake. We say this because humans are imperfect, we are forgetful and we are bound to make mistakes, some of us more than others.

On the other hand, computers do not make mistakes. They may give us the wrong answer from time to time but that is because we gave them the wrong variables. Since computers are not prone to the same vices that we are, they are the perfect tool for enterprises that are looking to maximize the amount of work being done all the while minimizing, if not completely eliminating, human error.

Bottlenose, a real-time cloud-based trend detection platform, has announced the release of their latest update to their analytics platform called Nerve Center 2.0. The update contains a slew of new features that could entice enterprises to start scaling back on the number of human analysts they employ.

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With Nerve Center 2.0, Bottlenose has enabled their platform to analyze high volumes of data in real-time, eliminating the need of constant human interaction. The update endows the Nerve Center with the ability to analyze social media content for demographic data as well as for emotions within content for advanced trend detection. When a new trend is detected, it alerts users to what’s trending, requiring human interaction only at the very end. To supplement trend alerts, the platform also generates detailed reports that are scheduled at set times throughout the day to keep users up-to-speed throughout the day. Bottlenose has also made Nerve Center 2.0 available to developers for the first time via API’s (Application Programming Interface).

"The automatic trend detection in Nerve Center 2.0 alleviates the need for constant attention from human analysts. Now, without having to monitor the platform 24/7, users can be alerted of any important trends such as breaking news, emerging influencers, viral content, bursting topics and hashtags, and spiking sentiment," said Bottlenose CEO and co-founder Nova Spivack. "This eliminates the choke point of humans in the process of real-time comprehension of patterns in vast amounts of data. And that's just the beginning. In the future, our platform will be able to spot a growing repertoire of complex patterns and trends in data streams. We are automating the analyst, one skill at a time."

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