One of the biggest challenge faced by brands implementing social media listening is that there is too much unstructured information and data. It is like what some of the folks in the industry call it, information puke. Absence of data is a worry and too much data is also a concern.
As written in one of our presentations earlier on Big data, One of the biggest challenge with so much data on social media is; deriving a meaningful contextual information.
Social media data is highly unstructured. Unlike other customer data from retail, banking etc. which is structured, data on social media is very unstructured.
Case Study: Attempt to derive meaningful contextual information on conversation around Satya Nadella
There were more than 110 thousand mentions of the newly appointed Satya Nadella in last few days. In our attempt to analyze what were people talking about him, we were faced with information overload. There were more than 50 thousand tweets/posts per day.
That being said,here is how poople are talking about Satya Nadella on social media. You can view the interactive version here: http://bit.ly/1jvzudm
Most organizations want to capture contextual conversations and other widely available sources of unstructured data from social media, blog commentaries and other sources in real time, and put them side by side with structured data in their information ecosystem for a much clearer picture of what is going on.