Metrics and Benchmarks for Empirical and Comprehension Focused Visualization Research in the Sales Domain

Loo Yew Jie, Doris Hooi-Ten Wong, Zarina Mat Zain, Nilam Nur Amir Sjarif, Roslina Ibrahim, Nurazean Maarop

Abstract


Data visualization is an effort which aims to communicate data effectively and clearly to the audience through graphical
representation. Data visualization efforts must be coordinated with an understanding into the Cognitive Learning Theory (CLT). In the sales domain, sales data visualization are made possible with the available Business Intelligence (BI) tools such as Microsoft Power BI, Tableau, Plotly, and others. These tools allow seamless interaction for the top management as well as the sales force with regard to the data. Sales data visualization comes with an array of advantages such as self-service analysis by business users, rapidly adapt to changing business conditions, and enable continuous on-demand reporting among others. The advantages of sales data visualization also comes with the challenges such as difficulty in identifying visual noise, high rate of image change, and high performance requirements. In an effort to reduce cognitive activity that does not enhance learning, sales visualization dashboard must be designed in a way that is neither
too simplistic nor too complex to ensure that the Intrinsic Cognitive Load (ICL), Extrinsic Cognitive Load (ECL), and Germane Cognitive Load (GCL) are in sync with the audience. With the combination of sales data visualization and CLT, understanding complex sales details quickly is made possible by not only the top management of the organization, but also the sales force of the organization.


Keywords


Data Visualization, Sales, Cognitive Load Theory, Metrics, Benchmark

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DOI: http://doi.org/10.11591/ijeecs.v12.i3.pp1340-1348

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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