Paper Title
PREDICTIVEMART ANALYTICS, A BIG MART SALES PREDICTION SYSTEM
Article Identifiers
Authors
Mansi Rao , Ishika Goel , Kshtiz Verma , Muskan Agrawal
Keywords
Abstract
PredictiveMart Analytics, which is a trailblazer in the field of retail sales forecasting, uses state-of-the-art machine learning to provide major marts with previously unheard-of levels of accuracy and insight. This ground-breaking research uses sophisticated algorithms to search through enormous datasets of past sales, consumer behavior, and outside variables in order to find hidden correlations and patterns. Regression models, time series analysis, and neural networks are some of the tools that PredictiveMart Analytics uses to produce incredibly accurate predictions of future sales trends. Big marts get a strategic edge in a number of important areas thanks to this all-encompassing approach to data analysis. Realizing precise inventory management allows for less waste and optimal stock levels. Real-time data-driven dynamic pricing strategies guarantee a competitive edge and optimize profit margins. A new level of reactivity and agility is added to overall business planning, enabling major marts to take advantage of every opportunity and adjust to market changes with ease
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How To Cite (APA)
Mansi Rao, Ishika Goel, Kshtiz Verma, & Muskan Agrawal (June-2024). PREDICTIVEMART ANALYTICS, A BIG MART SALES PREDICTION SYSTEM. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(6), a58-a65. https://ijnrd.org/papers/IJNRD2406005.pdf
Issue
Volume 9 Issue 6, June-2024
Pages : a58-a65
Other Publication Details
Paper Reg. ID: IJNRD_222471
Published Paper Id: IJNRD2406005
Downloads: 000121988
Research Area: Engineering
Country: ALIGARH, Uttar Pradesh, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2406005.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2406005
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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