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Call for Paper - August 2020 Edition
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Trail for Unearthing Latent Consumer Behavior through Big Data Analytics

Subuddhi Asara Senaratne, Leelanga Dananjaya Seneviratne

About The Authors


Subuddhi Asara Senaratne
99X Technology
Sri Lanka

Subuddhi Asara Senaratne,

Software Engineer,

Research and Development,

99X Technology.

Leelanga Dananjaya Seneviratne
University of Moratuwa
Sri Lanka

Dr. B. L. D. Seneviratne,

Senior Lecturer and Researcher,

Department of Interdisciplinary Studies,

Faculty of Information Technology,

University of Moratuwa,

Sri Lanka.


Abstract


With the increasing trend in market competition, the key to success shifts from products to the customers. Customer Relationship Management has become an emerging topic for enterprises which encourages relationship enhancement and focus on strengthening bonds with the customers. Being customer focus, helps an organization to better serve their customers thus leading to increased customer retention. In understanding customers, availability of vast amount of data is an advantage. With the advancement of technology, data is gathered from different places associated with different consumption contexts and therefore, big data has become one of the most vibrant technologies to obtain insights about the consumers. The increasing need for consumer behaviour analysis reforms the use of Big Data. Unique volume, velocity, and variety of primary data available from individual consumers provide behavioural insights about consumers, where marketers could translate those in gaining competitive advantage. But at present, big data analytics interprets the result to exhibit the effect rather than exploiting the cause behind. Consumers on the other hand are complex beings exhibiting results based on hidden constructs leading to different decisions. These hidden drivers are the latent behaviours of consumers and this paper proposes possible ways that technology can be utilized to unearth such hidden constructs.


bisnis

Keywords


Big Data; Consumer Behavior; Personalities; Personality Identification; Data Analytics; Marketing Intelligence; Big Data Analytics;

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IJRBT introduces peer-review from its first Edition onwards. The researchers submitting their papers for publication should review atleast one technical paper from their domain. The manuscript also undergoes mandatory procedural review with IJRBT review and scholar panel.