Fashion Brand Zara's Sales Data Analysis to discover the Sales Trend in Future
Year: 2025
Type: article
Abstract: Completed a Data Analysis & Machine Learning project on Zara’s Sales Trends!In this project, I performed Exploratory Data Analysis (EDA) and built predictive models (using Random Forest and Linear Regression) to analyse how factors like price, season, section, material, and country of origin influence Zara’s sales performance.📊 Key Insights:Random Forest achieved better prediction accuracy (R² = 0.50)Sales peak during Autumn & Winter seasonsWOMAN section contributes the majority of total sales🔧 Tech Stack: Python, Pandas, Seaborn, Matplotlib, Scikit-Learn, Plotly📄 Check out my full PDF report below — feedback is always welcome!Access Project: https://lnkd.in/gKWfqRjvhashtag#DataScience hashtag#MachineLearning hashtag#EDA hashtag#Python hashtag#ZaraSalesAnalysis hashtag#RandomForest hashtag#LinearRegression hashtag#DataAnalytics hashtag#PredictiveModeling hashtag#LinkedInLearning hashtag#BusinessData hashtag#Analysis hashtag#Data hashtag#Kaggle
Author: Shariar, Arfin
Institution: University of Greater Manchester
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7104827634
FWCI:
Cites:
Cited by:
Related to: