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The market basket analysis provides an affinity analysis of Sales Pattern for product categories, subcategories, and items.
Market Basket Analysis in R for leading supermarket chain. This Predictive Analytics Dashboard represents data in a visual and interactive way which helps to Identify customer buying pattern such as which items are purchased together, or how the purchase of one item influence the customer to buy another item being purchased or one item to avoid the customer to buy another item. It eventually helps the supermarket to explore the ample opportunity which includes but is not limited to Optimize Promotion, Items Multipack, Store planograms, Store Segmentations, Inventory, cross-selling, and many more.
It also provides the association rules for the category, sub-category, and items using cutting-edge machine learning algorithms which helps to optimize marketing strategy in near real-time.
Disclaimer: The data, characters and brand names depicted in the visualizations are for demo purposes only. Any resemblance to actual data, or to brand names, is purely coincidental.
Product Association Insights
Frequent Itemset Identification
Customer Purchase Behavior Prediction
Sales Trend Forecasting
Cross-Selling and Upselling Suggestions
Customer Segmentation Based on Buying Patterns
Transaction Analysis and Reporting
Personalized Product Recommendations
Product Affinity Scores
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Submit RequestThe purpose of this dashboard was to aid the store in its awareness of customer behavior towards the products that are being sold. It also addressed inventory issues to ensure that there is sufficient stock for customers to purchase and to avoid excessive stock that will not be sold. Additionally the dashboard also helps them in improving customer service and strategic planning.
Customer buying behaviour was examined in detail to enhance inventory control because it was observed that certain products were off the shelves way too often, or there were times when many did not sell at all.
We also found out how some products are consumed together in order to establish how they can be sold together to increase the sale.
Lastly, we provided clear insights into how different product categories are performing. This helped them plan better and use smart cross-selling strategies to increase revenue.
Supermarket Chain Managers
Marketing Teams
Inventory Managers
Product Managers
Retail Consultants
Supply Chain Managers
Business Analysts
Category Managers
Top Categories Associated with the selected Category and their supported vs Confidence values.
Correlation analysis of the items.
Items that can be cross merchandise with the selected category.
Association Rules analysis to determine how purchase of one item influence the other item's purchase.
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