PeakPlanner: AI-Based Market Basket Insights for Demand Forecasting

PeakPlanner is an intelligent business analytics platform designed to assist organizations in sales trend forecasting and inventory optimization through data-driven insights. This system integrates data upload, preprocessing, and predictive modeling into a seamless pipeline using a PHP-based frontend and backend coupled with Python-based forecasting algorithms. It dynamically creates user-specific databases, organizes data month-wise, and utilizes Random Forest models for accurate demand prediction. Additionally, it generates insightful reports and visual dashboards that highlight business performance and growth opportunities. The platform offers an intuitive interface for uploading CSV data, automates model training and evaluation, and provides marketing strategy recommendations based on observed trends. This paper presents the architectural design, technical implementation, and practical implications of PeakPlanner in real-time business environments, demonstrating its potential to enhance decision-making through machine learning and data visualization.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-04-24
DOI
https://doi.org/10.22214/ijraset.2025.69258
Primary Topic
Forecasting Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

PeakPlanner: AI-Based Market Basket Insights for Demand Forecasting

Hasan Phudinawala
International Journal for Research in Applied Science and Engineering Technology
Forecasting Techniques and Applications
article

PeakPlanner: AI-Based Market Basket Insights for Demand Forecasting

Hasan Phudinawala
article en

Abstract

PeakPlanner is an intelligent business analytics platform designed to assist organizations in sales trend forecasting and inventory optimization through data-driven insights. This system integrates data upload, preprocessing, and predictive modeling into a seamless pipeline using a PHP-based frontend and backend coupled with Python-based forecasting algorithms. It dynamically creates user-specific databases, organizes data month-wise, and utilizes Random Forest models for accurate demand prediction. Additionally, it generates insightful reports and visual dashboards that highlight business performance and growth opportunities. The platform offers an intuitive interface for uploading CSV data, automates model training and evaluation, and provides marketing strategy recommendations based on observed trends. This paper presents the architectural design, technical implementation, and practical implications of PeakPlanner in real-time business environments, demonstrating its potential to enhance decision-making through machine learning and data visualization.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(4)
Openalex Percentile: Top 90%
Forecasting Techniques and Applications
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