Methodology Behind Product Recommendations

The recommendations are based on frequency and similarity, which are divided into three levels: customer specific, product specific, and customer segment specific.

Customer Specific Recommendations

Customer-specific recommendations, such as "Frequently Purchased," are calculated based on how often a customer bought a specific product. The frequency rate is determined using the count of baskets of the specific customer as the denominator and the basket count of customer-product purchases as the numerator. This frequency rate is then multiplied by the product's historical profitability metric to generate a recommendation score.

Product Specific Recommendations

Product-specific recommendations, like "Bought Together," are based on how often two products were purchased together. The frequency rate is calculated using the count of baskets with the quoted product as the denominator and the basket count with product and co-product purchases as the numerator. The recommendation score is determined by multiplying the frequency rate by the co-product's historical profitability metric.

Customer Segment Specific Recommendations

For customer segment-specific recommendations, such as "Others Buy," the frequency rate is calculated using the count of baskets of the customer segment as the denominator and the basket count of customer segment - product purchases as the numerator. The frequency rate is then multiplied by the product's historical profitability metric to generate a recommendation score. These outputs are stored in the Model Table "Customer Segment Recommendations."

How To Generate Recommendations for Similar Products

There are several methodologies for generating recommendations for similar products, similar products from a specific brand, up-sell products, and down-sell products. The outputs from these are stored in respective model tables for further analysis and implementation.

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In addition to transactional data, product-to-product similarity is also considered in generating these recommendations.