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You are viewing ARCHIVED CONTENT released online between 1 April 2010 and 24 August 2018 or content that has been selectively archived and is no longer active. Content in this archive is NOT UPDATED, and links may not function.By John Ginovsky
Move over, Big Data. Here comes Big Text.
Or, as it’s more commonly known, “text analytics.”
Or, sometimes, “text mining.”
Essentially, it’s the analysis of all the unstructured data a bank absorbs through email; social media posts; call center notes and transcripts; surveys and feedback forms—any information provided by or about customers not structured in some type of database.
More specifically, it could be a snarky comment on Facebook; the jottings of a call center representative; scribbled notes at the end of a survey; or a mobile text from a grateful customer to a helpful teller.
All those kinds of things produced by the combined population of current and potential customers provides usable insights—if they can be captured, sifted, sorted, digested, aggregated, and presented in some meaningful way.
Big Text is a growing area that’s generating quite a lot of literature by business and banking observers. Give credit, though, to Beyond the Arc with coming up with the catchier name of “Big Text.”
Read the complete article at: Is “Big Text” next big thing?