https://github.com/abhroroy365/market_analysis

This project explores customer segmentation and market analysis in the context of online retail using an online retail dataset. By applying advanced analytics, we aim to uncover insights that can drive strategic decisions and enhance business performance.
https://github.com/abhroroy365/market_analysis

clustering data data-analysis data-visualization kmeans-clustering machine-learning market-analysis python silhouette-analysis

Last synced: 7 days ago
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This project explores customer segmentation and market analysis in the context of online retail using an online retail dataset. By applying advanced analytics, we aim to uncover insights that can drive strategic decisions and enhance business performance.

• Host: GitHub
• URL: https://github.com/abhroroy365/market_analysis
• Owner: abhroroy365
• Created: 2024-04-15T14:37:22.000Z (7 months ago)
• Default Branch: master
• Last Pushed: 2024-04-15T14:41:25.000Z (7 months ago)
• Last Synced: 2024-04-19T19:28:32.059Z (7 months ago)
• Topics: clustering, data, data-analysis, data-visualization, kmeans-clustering, machine-learning, market-analysis, python, silhouette-analysis
• Language: Jupyter Notebook
• Homepage:
• Size: 16.4 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# Description

This project explores customer segmentation and market analysis in the context of online retail using an online retail dataset. By applying advanced analytics, we aim to uncover insights that can drive strategic decisions and enhance business performance. Through a combination of statistical analysis and machine learning techniques, we extract customer behavior and market dynamics to inform actionable strategies for maximizing profitability and improving customer engagement.

- Market Analysis : Extracting insights about the demographic customer behavior,market sales, along top selling products, both with respect to count and sales amount.

- Customer segmentation: Segmenting customers into clusters using KMeans, with respect to RFM (Recency, Frequency and Monetary Value). Using the clusters, an idea of variety of customer using the platform can be analyzed, along with targeted marketing and promotions.

## Acknowledgements

Dataset is available at kaggle

 - [Kaggle Dataset Link](https://www.kaggle.com/datasets/ulrikthygepedersen/online-retail-dataset)