Analytics Social

The Evolution of Social Business Intelligence – Guest Post

Guest Post

This mission of this blog is to share ideas about business analytics. One of the things I want to increasingly do this year is to feature more guest bloggers and do more interviews.

A few months ago, I came across Sanjay Shetty’s unique blog Communities R Us. His approach to blogging about social media topics is very visual. Sanjay and I ended up connecting via a recent blog post where we exchanged a few ideas. The idea of a guest post quickly developed. And here it is: Sanjay Shetty writes about his views on Social Business Intelligence.

Evolution of Social Business Intelligence: Human Business Intelligence

Social Media provides a fantastic opportunity for enterprises to gather enormous amount of business intelligence, whether it’s about their customers likes and dislikes, or whether it’s competitive intelligence. My earlier post and video covered quite a bit of ground. However, I’ve seen organizations limiting themselves and the power of the social opportunity in leveraging true human business intelligence.

Analytics Reading Social

Zarrella’s Hierarchy of Contagiousness – A review


A few days ago I bought and downloaded the ubiquitous eBook Zarrella’s Hierarchy of Contagiousness: The Science, Design, and Engineering of Contagious Ideas. There is a lot of stuff about social media out there but I find that many materials are fuzzy and hype-oriented. Dan Zarrella’s book is definitely different and I think that Business Analytics professionals like you will enjoy the book.


Social media have changed the way we market to our customers. But reaching the right people is not all that easy as you have probably experienced. The basic idea of Zarrella’s book is to look at why certain ideas are contagious and what you can do to make sure that your message is heard in the various social media channels. Zarrella introduces a useful model (Zarrella’s Hierarchy) that helps explain how messages get spread through social media. It is a hierarchy of three criteria:

  1. Exposure: People need to be exposed to a piece of content.
  2. Attention: Once people are exposed, will they actually notice the message?
  3. Motivation: Once an idea has been noticed, will people share it with others?
Analytics Social

Cognos Consumer Insight Helps Us Make Sense Of Social Media Discussions


Last week I decided to buy a new camera bag. Instead of heading out to one of the camera stores in Munich, I researched different styles and products on Google. The websites of most manufacturers were somewhat helpful. Once I had picked a few models, I starting drilling down by look at blogs, groups on Flickr and Twitter. And that was worth the effort – turned out that most people didn’t like the models I had initially picked. As a matter of fact, I ended up buying a bag that hadn’t caught my eye before. It got the best reviews. Long story short: Two blog entries along with a few comments in a Flickr group influenced my decision – not the manufacturer’s websites. Chances are that you have similar stories to tell.


Social MediaSocial Media are extremely influential. A Forrester report from 2009 stated that 78% of all consumers trust peer recommendations. Likewise, most consumers do not trust marketing messages any more. The implication for organizations is obvious: you have got to understand what customers are saying about you! But how do you best go about that? I remember sitting in my car ten years ago listening to a debate about the future of the internet. Somebody made the bold statement that companies would hire professional internet surfers in the future. These “analysts” were supposed to spend their days surfing the web and checking websites and forums for interesting things. Certainly an option. Hilarious.


Well, it doesn’t have to be manual. Earlier this year, IBM introduced a new solution called Cognos Consumer Insight and it allows organizations to analyze conversations in social media such as Twitter, Facebook, blogs etc.. To do that, the solution collects and processes data from the desired social media sites & categories. Text analytics are utilized to comb through the potentially massive amount of data and to identify sentiment and general trends. The output of all this can then be analyzed in the usual Cognos 10 environment.

Cognos Consumer Insight
Cognos Consumer Insight


The output of Cognos Consumer Insight is very powerful. The potential is huge:

  • Identify discussions about quality issues. Act on the information before the issues turn into a serious social media disaster.
  • Which product attributes are really important to customers? Is it the color, is it the look?
  • Which social media channels are the important ones for us? Is it Twitter, are they key blogs, discussion forums?
  • etc..

There are several different ways to look at the data. Apart from traditional reporting, you can perform a sentiment analysis, view evolving topic flows, identify affinities or simply look at specific tweets, statements and such (see the examples below).

Sentiment Analysis
Sentiment Analysis: Positive (green) vs negative (red)
Evolving Topics
Evolving Topics: Hot words


Understanding what people talk about and how they talk about your products and services is extremely important. IBM Cognos Consumer Insight helps you stay on top of this.

There is a lot more to discuss about this great solution. If you happen to attend BAForum and IoD, make sure to sign up for the relevant sessions about this topic. There is a highly interesting Social media & Customer Analytics track this year. Hope to see you there!

P.S.: Back to my camera bag: The discussion forums and blogs indicated that easy access to your camera is super important when selecting the right bag. A bunch of manufacturers had led me down a path of looking at maximum storage room. Their designs did not get any good reviews. Cognos Consumer Insight could help them improve their product design and messaging.


7 reasons to get social

Getting social at a Bavarian beergarden

This past month, I did something I haven’t done in a long time: I did not travel. Being home also opened up the opportunity to hang out in some of the famous beergardens in Munich. In case you haven’t been to a beergarden – it’s kind of like a social network: You connect with friends and strangers, you share, you chat, you collect and you sometimes get spammed (mostly by drunk people). One of those evenings I met a few people from a former job. The entire group basically consisted of pretty successful guys in their mid  30s and 40s. One of them raised the topic of social networking.