Social Media Analytics – Have we done it all ?

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Enter into a CMO’s office of a Bank with a pitch for sentiment analysis product or service, you probably would be thrown outta the window. The problem with sentiment analysis is,  its too old. Everyone has done it or has seen it working (if at all). Specially if you are in the retail industry (irrespective of what you sell), it makes a lot of sense to know how your products are doing in the market or in the mind of the consumer. People’s opinion and verbiage provides a direct feedback about what they feel while experiencing it. Its absolutely important to listen to your customer’s expression as it might snow ball into a negative larva ball killing your product or service even before the customer actually buys it.

Compare that to a banking parlance, the oddity are too many. But some of the most important attributes are

  1. There is no tangible product.
  2. There is no feeling associated with the product.
  3. There is no innovation in the primary product variance in the banking industry (a deposit account is a deposit account huh!!!)

So it would make a lot of sense to try and use the medium of social media to collect feedback loop around services rendered or in short “customer experience”. Various firms with digital aspirations have already established an arm of customer service through twitter handles. Almost all the banks have a Facebook page to like/dislike. There are dedicated fan/hate pages also for banks of various nature existing in Facebook and twitter without any involvement from the said bank/institutions. The thing about social media or the feedback through it is – You get a feedback only when its negative mostly. No one twits or posts a comment if they like anything without being prompted (paid) mostly. The best cases thus for the banks to use social media aanalytics would probably to

  • Gauge the customer experience – of an incident interfaced with a channel agent
  • Gauge the performance of the channel agent to turn the negative approach to a positive experience.
  • Mix up the blend of customer feedback from formalized channels like (survey) along with unstructured formats to establish like and dislike of customers.
  • Identify conversation threads which potentially could be a competitor intelligence (read it as Topic Modelling).
  • Compare products and services among competitors.

While all these things are technical and mathematical in nature, there is one area of it however is taken for granted. The social media related privacy, framework and rule sets are not formalized yet and is ever changing. So the above use cases are possible only with the assumptions of a free world.

P.S. – Facebook, Twitter or any other social media logos and brands are not associated with me apart from a pure “consumer” perspective. Each of the logos belong to their own registered brands respectively.