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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63973
Volume:
10 |
5 |
May 2026
Pages:
1-7
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
MBA
Jeppiaar University
MBA
Jeppiaar University
In today's rapidly evolving digital economy, the demand for industry-oriented technical education and skill development has significantly increased. This study presents an analytical investigation of sales performance and future revenue growth at Trishana Technologies — a leading IT training institute in Bangalore, India. The research adopts a descriptive and analytical approach, collecting primary data through structured questionnaires from 100 respondents comprising students (52%), fresh graduates (28%), and working professionals (20%). The study evaluates key factors influencing student enrollment decisions including digital marketing effectiveness, trainer quality, placement assistance, course demand, and hybrid learning preferences. Business analytics tools — Microsoft Excel, SQL, and Power BI — were assessed for their role in monitoring and improving sales performance. Statistical methods including percentage analysis, chi-square test (χ² = 9.214, p = 0.027), and regression analysis (R = 0.872, R² = 0.760) were used to validate the hypotheses. Findings reveal that Data Science (30%) and Full Stack Development (25%) are the highest-demand courses; Google Ads (32%) is the most effective marketing channel; and placement assistance (34%) is the primary enrollment conversion factor. AI and Data Science (40%) emerged as the most anticipated future high-demand technology domain. The study concludes with strategic recommendations for strengthening sales growth and achieving sustainable organizational performance through data-driven decision-making.
KEYWORDS
This study demonstrates that Business Analytics plays a significant and measurable role in improving sales performance, customer engagement, and organizational growth at Trishana Technologies. By systematically analyzing sales trends, customer preferences, enrollment patterns, and marketing channel effectiveness, the research provides a data-driven framework that IT training institutions can immediately apply to strengthen their strategic decision-making. The statistical results are clear and robust: the chi-square test (χ² = 9.214, p = 0.027) confirms a significant relationship between analytics tool usage and sales performance outcomes, while regression analysis (R = 0.872, R² = 0.760) demonstrates that business analytics tools explain 76% of the variance in sales performance. Courses in Data Science, Artificial Intelligence, and Full Stack Development exhibit the strongest market demand, and Google Ads remains the most effective channel for student acquisition. Overall, the effective implementation of business analytics, modern marketing strategies, and continuous course innovation can improve future sales growth, student satisfaction, and long-term organizational competitiveness at Trishana Technologies. This study serves as a replicable, evidence-based analytical model for analytics-led growth in the IT training and EdTech sector.
Saravana Priya M. et al. (2024). Retail Store Sales Analysis: Unveiling Insights Through Power BI Business Analytics. SSRN Electronic Journal. https://ssrn.com/abstract=5039793 [2] Swathi S. (2024). Analysis of Sales Performance to Get Real Time Insights Using Business Intelligence Tools. MBA Project Report, Thangavelu Engineering College, Anna University, Chennai. [3] Umale, D. & Kolhatkar, V. (2024). Business Intelligence Approach for Sales Performance Analysis Using Power BI. Ajeenkya D Y Patil School of Engineering, Pune. [4] Mythili D. & Shrinithi P. (2026). An Analysis of Sales Performance in STAP Apparels Coimbatore. IJERME, 11(1), 16–19. DOI: 10.5281/zenodo.18709485 [5] Singh, S. & Jadhav, L. (2022). Data Analysis and Visualization of Sales Dataset using Power BI. IJRASET, 10(6), 1749–1759. DOI: 10.22214/ijraset.2022.44132 [6] Deevi Radha Rani et al. (2024). Performance Analysis of Sales Using Machine Learning. VFSTR Deemed University. https://ssrn.com/abstract=4493480 [7] Thongam Prity Devi, Sushmita Bharti & Raheel Hassan (2025). Enhancing Sales Performance Analysis Through Advanced Data Visualization Techniques. IJSREM, 09(11). DOI: 10.55041/IJSREM53646 [8] Lavanya Lokhande (2025). A Review on Sales Performance Analysis Using Power BI. IJARSCT. DOI: 10.48175/IJARSCT-29637 [9] Kothari, C.R. (2004). Research Methodology: Methods and Techniques. New Age International Publishers. [10] Powell, B. (2018). Microsoft Power BI: Complete Reference. Packt Publishing.
Publication Date
5/25/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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