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Engineering and Technology OPEN ACCESS

Visual Analytics in U.S. Retail: A Data-driven Business Intelligence Framework for Mapping the Retail KPI Matrix

Kazi Obaidur Rahman
MBA (Business Analytics), Gannon University, Erie, Pennsylvania, USA.
Achhia Khanam
MBA in Accounting & Business Analytics, Maharishi International University, Fairfield, Iowa
Songeta Dhar
DBA (Doctor of Business Administration), Westcliff University, Los Angeles, California, USA.
Mehedi Hasan
MBA(Accounting), American International University, Bangladesh.
Amir Hamza Akash
MSc. (Statistics & Analytics), University of Arkansas, Fayetteville, Arkansas, USA.
Md Ashiqur Rahman Khan
Executive MBA (Management), University of Dhaka, Dhaka, Bangladesh.
Shamina Sharmin Jishan
MBS (Accounting), National University, Dhaka, Bangladesh.
Fairuz Sadaf Aishwarya
MBA in MIS, International American University, Los Angeles, California, USA.
DOI Crossref DOI 10.37547/tajet/Volume08Issue02-15
tajet 2026
VOL. 8 / NO. 2 FEBRUARY
FULL TEXT PP. 153-161
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VOLUME 8
ISSUE 2
YEAR 2026
PAGES 153-161
RESEARCH OVERVIEW

Abstract

Visual analytics approach in mapping the KPIs (Key Performance Indicators) of US retail landscape has become indispensable. Since the US retail has become more dynamic and competitive, intensified by rapidly evolving e-commerce and changing consumer behaviors, retailers tend to rely on this real-time data-driven decision-making approach to remain competitive. Business Intelligence (BI) applications play significant roles in optimizing retail KPI mapping with visual analytics through interactive dashboards, charts, graphs, and KPI matrix.

This research paper proposes a robust framework for visual analytics in optimizing the U.S. retail KPI matrix by integrating the Business Intelligence (BI) tools. This framework supports stakeholders with valuable insights from high-velocity data streams for taking data-driven strategic decisions to stay competitive. In this article, we demonstrate how visual analytics supports stakeholders in decision-making process, enhances interpretability, and maximize outcomes by applying BI application.  

The key findings include a set of KPI matrix for a typical U.S. retail entity, interactive dashboards based on this KPIs for visualizing the entity’s operational, financial, and other business performance for taking strategic decision. Here, we integrated business intelligence tools like power BI in developing interactive dashboards, analyzing and visualizing KPIs for enhancing operational efficiency. We believe, this paper will contribute to the growing needs of academic literature on business intelligence applications in U.S. retail analytics. Besides, it enables retail investors and stakeholders to visualize the key business insights, business performance, prospects and opportunities.

RESEARCH TOPICS

Keywords

Retail KPI metrics Business Intelligence Visual Analytics Retail Analytics U.S. Retail.

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References

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