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Big Data, Multimedia, Sentiment Analysis & Monetization

Posted by Abhishek Singh (View Profile | View All Posts) | February 20, 2013 1:12 PM

As I mentioned in my previous post, Big Data must create value - real and tangible economic value for it to be meaningful. And it must do more than just what a traditional Datawarehouse could achieve. Taking structured transactional data, putting it in a Datawarehouse and mining it for statistical analysis to obtain customer insights is nothing new or revolutionary for all of us to spend so much time talking about. The maximum amount of data (and one with largest growth rate) that is being generated nowadays is unstructured and with cameras in every phone, a lot of this data consists of multimedia like video and pictures. Tagging these videos with metadata and annotations tries to put some structure around these large files. For example, when you watch a video on Youtube, how does it know what else to "recommend", what to "feature" and what to "suggest"? Youtube's search ranking algorithm tries to constantly stay ahead of the game by delivering the most relevant and engaging content, so as to optimise the return-on-investment for its advertisers. Similarly, TripAdvisor's ability to put structure around the large volume of its unstructured data (namely hotel reviews, pictures, ratings, etc.) is proving to be financially successful for both itself and its partners. One reality of all this large volume of data being created rapidly is how do you stay ahead of the game and continuously innovate to make more money than your competitors?

 

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For purposes of illustration, we can look at Hotel industry, its adoption of Sentiment Analysis and how it has used the technology to positively influence its room pricing abilities. Hotel industry is abuzz with something called Online Reputation Management. Companies like Radian6 (SalesForce Subsidiary in Canada), ReviewPro (Spain), Brand Karma (US) Hootsuite (US), ViralHeat (US) and SocialNuggests (US), ClaraBridge, SentiRate and TrustYou(with US based subsidiary called Review Analyst) along with the field's largest player TripAdvisor are all trying to tame the large volume of data consisting of hotel reviews in meaningful manner. Additionally, it is creating substantial all-round economic value. For hotels it's creating the ability for them to charge higher premiums compared to their competitors. For customers it is giving them the ability to get maximum value for their money. For technology providers, it is creating ability to offer a host of new age services both to the businesses like hotels as well as directly to customers. Larger technology players like Tripadvisor are minting money multiple ways. From offering value added services to customers by becoming the default site for hotel value comparisons (both price and reputation comparisons), they are able to sell digital real estate to the highest bidder for ad space as well as charging commissions to hotels for bookings generated from their website. In the end both the customer and the hotels get exactly what they are looking for -increased value for their money....

Monetization of Big Data is one of biggest challenge that the technology players are constantly working to solve and when done right, it unlocks tremendous economic potential for everyone...

Next imagine a world of video reviews (like Youtube) and picture reviews (hint: Pinterest) all getting organised and sorted to provide meaningful analysis for customers shopping the market for their ideal honeymoon destination or their dream vacation or just a weekend getaway... Tremendous opportunity with lots of money for everyone to make...

Comments

Interesting thoughts, Abhishek. To extend this further, going fwd, I see an amalgamation of intelligence gathered through these 2-channels I.e. structured data available fm a customer-profile residing in a Data Warehouse/CRM & the intelligence being gathered thru BigData for that customer. The 'Whole' will be bigger than the sum of the 2 parts & will create a much bigger ROI case to support more investment in BigData.

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