COVID-19 is the perfect time for enterprises to bring in thick data along with existing big data

Major enterprises have turned to big data for better management of data. In the customer support industry, big data analytics have been used to harvest insights regarding shopping trends and patterns. These insights are then used to create an improved and more attractive environment and also increase sales.

The drawback in this method  is that enterprises often fail to utilize thick data- qualitative, non-numerical insights into the clients’ emotions, behavior, and goals- derived form first hand interactions.  When this happens, especially during a situation like the current pandemic, it puts the already stressed clients under more stress, which is not suitable for the organization.

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Many companies  rely entirely on the big data insights, and miss the actual client interactions and information, often in person. they also miss the obvious opportunities and threats. Depending entirely on  quantitative data alone  for evaluating the clients’ preferences and expectations means disregarding the rich qualitative data that personal connect delivers. While analytics is a huge help, the best information is generally collated from direct interaction with business owners and clients, common sense, and intuition.

The observation was true even before the pandemic and is doubly-important now, as traditional business models have been disrupted. Enterprises had to come up with an alternate method for meaningful interaction with clients. CIOs feel that companies that address the client requirements and include empathy as part of their business process, are the ones that will strengthen their client relationships.

There is no doubt that Big data has helped enterprises trawl through the ever-increasing digital exhaust routes and evaluate the patterns accurately and quickly. The tech has a long list of advances under its belt- personalized marketing, faster fraud identification, improved healthcare research, etc.

Despite all these advantages, big data ends up giving only half the story. The text is not equipped to capture context or the nuance relevant to client experience possible only via direct interaction with clients and observing their behavior. Big data is flawless when enterprises require when, where, how, and what of interactions, but fails miserably when asked to report the why.

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Thick data is a vital element at this juncture. Enterprises can build a solid foundation with a complete view of the client when combining both big and thick data. This is possible due to the perfect blend of numbers from both ends and the human insights that adds context to the data.

CIOs believe that thick data is good for revealing the emotions regarding cold data. This can be collected from various sources like facial expressions from a video, body language, or even quotes. Industry  leaders opine that emotions should be the most significant stakeholder while making decisions related to qualitative data.

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Data scientists will detect that leads are not converting, or a recently launched service’s critical element is not being fully utilized. This analysis is quantitative as they can explain what has happened but not why it happened so. Thick data will be instrumental in uncovering the why as well.

Enterprise leaders feel that the current situation is the most opportune moment to understand the client’s requirements and make the changes accordingly. Enterprises should quickly learn to derive thick data as well, and add the much needed layer to their analytics strategies.