Database Reference
In-Depth Information
answers to such questions as “What are the precursors to failure?” or “How
are these systems related?” These are the types of questions that conventional
monitoring doesn't answer; a Big Data solution finally offers the opportunity
to get new and better insights into the problems at hand
What, Why, and Who? Social Media Analytics
Perhaps the most talked-about Big Data use pattern involves social media
and customer sentiment analysis—it's also perhaps the most overhyped and
misunderstood. Although Big Data can help you to figure out what customers
are saying about your brand (or your competitor's brand), we think that the
current focus needs to expand.
Social media analytics is a pretty hot topic, but we're already starting to see
“buyer fatigue,” because the realities of current practice don't live up to the
constant hype around this use case. Simply put, there's a big difference between
what
people are saying or thinking and
why
they said or thought it. Your social
media Big Data analytics project should attempt to answer both the “what”
and the “why” to provide you with the analytics payoff that you seek.
We were recently able to identify some negative buzz that was specifically
targeted to a financial company that we were helping. We wanted to find out
why the negative buzz was there in the first place—why were people in a
such a state that they used technology to spread this negative sentiment?
More importantly, was this impacting sales, what could be done about it, and
how would we know if a particular response made things better? We call this
closed loop analytics
. If you simply listen to what people are saying, but don't
have the ability to analyze the information and respond accordingly, you're
still flying largely blind.
Understanding why people are saying something about your organiza-
tion involves cross-correlating everything: promotions, product mixes, pric-
ing changes, policy changes, marketing, corporate responsibility, and a whole
host of other activities that contribute to consumers' opinions in the first
place. There's a fundamental requirement that too few companies are talking
about: you need to combine external and internal information flows in the
same analytics pipeline. That's where you'll start to gain real insight and re-
alize an uplift; as it turns out, there are few (if any) external services that
provide social media offerings to do this since they can't handle the internal
structured sources, or they lack the analytics to combine the two—the IBM
Big Data platform can do this.
