A Streamlit app for a Customer Segmentation Project using K-means Clustering, RFM (Recency, Frequency, Monetary) analysis, and Association Rule Mining.
Welcome to our Customer Segmentation app , a dynamic tool developed by utilizing Streamlit, the renowned open-source Python framework. This application facilitates the detailed analysis and segmentation of customer data, allowing businesses to fine-tune their strategies and grasp the nuances of various market segments more effectively.In today's business landscape, understanding customers is crucial for targeted marketing efforts. However, businesses face challenges in segmenting their diverse customer base effectively. The right criteria for segmentation must be meaningful, actionable, and easy to understand. Accurate and up-to-date data is needed to accurately reflect the dynamic nature of the customer base. To overcome this, businesses can use a comprehensive methodology that includes data collection, cleaning, transformation, visualization, and clustering algorithms like k-means and RFM analysis. The Apriori algorithm can uncover associations within customer behaviors. Data summarization techniques can be used to deploy insights into marketing strategies. A streamlined web application with Streamlit can visually present these insights, enabling businesses to adapt dynamically to market demands.
Highlight Features Explore the comprehensive sections of our application:
1.Upload Data: Upload fresh data or option for a sample file to delveop into data exploration.
2.Data Understanding: Use handy tools to cleanse the data and delve into exploratory data analysis with our visualization tools.
3.Data Visualization: Visualize all necessary visualizations to understand your customers
4.Modeling and Prediction: Engage with the RFM analysis and KMeans algorithm to identify the best clustering strategy and Input new data and get predictions on the potential cluster for new customers while having the facility to download the results.
5.Summary: Simplify the visualizations for understanding customer segmentation using K-means Clustering, RFM analysis, and Association Rule Mining. Additionally, explore dashboard ideas for a streamlined presentation of insights
6.Feedback: Share your valuable feedback for the continual enhancement of the application.
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