Can Social Media be the next big lever for Business Intelligence? - Part 2
Guest post by
Karan Chadha, Associate Consultant - Business Intelligence, Oracle Practice, Enterprise Solutions, Infosys Technologies Ltd.
In Part 1 of this blog, I had discussed about social media data's immense potential for getting transformed into Business critical insights. I had also argued that the answer to the question about social media being the next big lever for business intelligence is a resounding Yes! However, having said that, it is imperative to understand various challenges encountered en route. In this part, I will focus on:
- Major challenges encountered by Social Media Intelligence (SMI) tools
- Some key features offered by Social Media Intelligence (SMI) tools
Challenges
All SMI tools have textual analytics as their underlying technology. Now, owing to the ambiguous and highly contextual nature of human conversations, textual analytics has always been an inexact science. To illustrate, let's say a statement like 'Ford was the greatest thing that has happened to the US' is encountered over the social space. This statement can have various interpretations. Either it can refer to the contributions of former US president Gerald Ford or it can allude to legendary Hollywood actor, Harrison Ford, or it could even be something else. So it has been a challenge for technology to understand these subtleties of human conversation and consequently, the effectiveness of SMI tools hasn't been more than 60%.
Another challenge has been in terms of positioning these tools to the organizations. Given the fact that many organizations are still struggling to manage even their structured organizational data, CIOs haven't been fully open to the idea of adding one more dimension to it. This apprehension isn't totally unjustified either considering that the fluid and noisy nature of social data makes it the most challenging to integrate into BI platforms. And the fact that the market still lacks mature and robust SMI tools has further resulted in lower penetration of these tools.
Key Features
Among a repertoire of features that SMI tools offer, three of them stand out for me:
- Geographic and Demographic Bucketing
An insight like half the people liked this new launch and half didn't is far less useful than an insights like most of the teens liked it and most of the middle aged haven't or most of the people in southern region appreciated it and most in the western region didn't. These kind of bucketed insights empower companies to prepare segment specific strategies. - Knowing the Influencers
Among millions of participants on the social space, there are a few who drive conversations and play a critical role in shaping opinions. For instance take the case of a few social activists who are frantically posting all over the social space about the environmental-friendliness of a new product and thus influencing the opinions of many. Several SMI tools provide this feature of identifying such opinion leaders giving companies a chance to foster relationships with them. - Red Flag Alerts
Several SMI tools provide red flag alerts when a situation demands an immediate action. Let me illustrate this with an example. Let's say a company comes up with a new version of its free-to-download music player software having a critical bug. An SMI tool, through the analysis of several customer comments over the social media space will raise a red flag thus alerting the company about the bug. This insight gives the company an option to immediately take off the product, fix the bug and put it back thus preventing a widespread loss of face. Now such a prompt response would be made possible only by the real time insights of an SMI tool. Nothing else would have sufficed in raising the red flag so early.
To conclude, I will say that Social Media is no longer an amusing world to be watched from the sidelines. Its challenges notwithstanding, it is time for companies to start integrating Social Media into their BI strategy and leverage its immense potential.
