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Krish Krishnan

"If we knew what it was we were doing, it would not be called research, would it?" - Albert Einstein.

Hello, and welcome to my blog.

I would like to use this blog to have constructive communication and exchanges of ideas in the business intelligence community on topics from data warehousing to SOA to governance, and all the topics in the umbrella of these subjects.

To maximize this blog's value, it must be an interactive venue. This means your input is vital to the blog's success. All that I ask from this audience is to treat everybody in this blog community and the blog itself with respect.

So let's start blogging and share our ideas, opinions, perspectives and keep the creative juices flowing!

About the author >

Krish Krishnan is a worldwide-recognized expert in the strategy, architecture, and implementation of high-performance data warehousing solutions and big data. He is a visionary data warehouse thought leader and is ranked as one of the top data warehouse consultants in the world. As an independent analyst, Krish regularly speaks at leading industry conferences and user groups. He has written prolifically in trade publications and eBooks, contributing over 150 articles, viewpoints, and case studies on big data, business intelligence, data warehousing, data warehouse appliances, and high-performance architectures. He co-authored Building the Unstructured Data Warehouse with Bill Inmon in 2011, and Morgan Kaufmann will publish his first independent writing project, Data Warehousing in the Age of Big Data, in August 2013.

With over 21 years of professional experience, Krish has solved complex solution architecture problems for global Fortune 1000 clients, and has designed and tuned some of the world’s largest data warehouses and business intelligence platforms. He is currently promoting the next generation of data warehousing, focusing on big data, semantic technologies, crowdsourcing, analytics, and platform engineering.

Krish is the president of Sixth Sense Advisors Inc., a Chicago-based company providing independent analyst, management consulting, strategy and innovation advisory and technology consulting services in big data, data warehousing, and business intelligence. He serves as a technology advisor to several companies, and is actively sought after by investors to assess startup companies in data management and associated emerging technology areas. He publishes with the BeyeNETWORK.com where he leads the Data Warehouse Appliances and Architecture Expert Channel.

Editor's Note: More articles and resources are available in Krish's BeyeNETWORK Expert Channel. Be sure to visit today!

It is clearly a sign of the times. Companies are now seriously looking at Social Analytics as part of their mainstream BI portfolio. Why? why the sudden importance one might wonder. Consider the following situation

Customer A purchases a product from Company XYZ at Store123. They are very happy about the product and the associated service. Chances are this customer will market the product by word of mouth to their immediate contacts. This was the situation till Twitter, MySpace and Facebook became the voice of the customer. Today the same customer almost immediately uses their social network site and blogs about the company, store, product and all the good stuff they experienced. What this does is a very powerful marketing channel for the company and its product, creating a market demand across the globe.

IF the Customer had a negative experience and was very upset, the message from this customer will evoke more similar reactions, and this will end up as a negative branding and marketing for the said company and its product/service.
      
Companies today have realized the fact that they are selling, servicing and marketing to customers known and unknown. The customer experience that they provide to these customers, can swing into a positive marketing and branding exercise or can cause a negative impact.

How do companies measure this? how will they hear the voice of the customer?. This is where the emerging field of  Sentiment analysis and Opinion mining plays a large role. There are software products available to enable the processing of customer sentiments in the internet and in the media, by analyzing these sentiments, companies can train their CRM, Call Center and Marketing departments to enhance the quality of service and can reap rich rewards.

Marketing will be the biggest beneficiary of this exercise. Today if you cannot market to the individual, your chances of getting their attention to the product / service that you intend to sell will simply not be there.

We are seeing the increase of target marketing on the internet and especially on Social Networking sites, why? the answer to that lies in the fact that you might be able to get the attention of hundreds of customers in one swoop, and reapply the same ad multiple times across areas of the world. Companies have been able to do this based on three items

1. Clickstream data analysis
2. Sentiment analysis
3. Market basket analysis.

Most of us know 1 and 3 and its importance. Item number 2 is the new kid on the block that will impact the success of exercises that are being done from analyzing the data from items 1 and 3.

Sentiment Analytics help us understand the sentiments of customers and the associated audience feedback. Companies have started tapping into the internet and there are very successful case studies of how companies have reaped rich rewards from just this one exercise
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IF we can expand this to go beyond just sentiment analysis to other areas such as buying experience, product experience and even look at wishlists etc, we will be able to leverage the voice of the customer beyond just corrective course and target marketing.

If we are to look at the next big thing, Social Analytics is one of them.

Posted August 27, 2009 9:33 AM
Permalink | 1 Comment |

1 Comment

Interesting concept - but it seems like maybe this "sentiment analysis" would be limited in its usefulness. for one thing, you're limited to those who use twitter and the like. For another, it seems it would be difficult to determine how widespread any given sentiment would be since it seems like it would be hard, if not impossible, to have the kind of sample control you need for analysis. Please elaborate...

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