Supermarket Shelf Allocation Using Customer Shopping Paths
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Solution Overview
Problem
Conventional methods for commodity shelf management in supermarkets fail to account for differences in customer groups' preferences, leading to suboptimal placement of products and reduced sales benefits due to limitations in sale space variety and inability to place diverse commodities together.
Innovation Solution
A method and system that classify customers based on shopping paths and demographics, calculate the see-buy rate of commodities for each customer group, and determine optimal shelf placement to maximize expected benefits by considering frequent shopping paths and customer groups' preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If commodities are displayed by sector in limited sale spaces, then space organization is simplified, but the ability to place diverse and associated commodities together is reduced
Solution Approach 1:
The patent transitions from traditional two-dimensional shelf placement to three-dimensional spatial optimization by incorporating customer shopping paths. It uses spatial coordinates and path analysis to determine commodity placement in multiple dimensions (horizontal shelf positions, vertical stacking, and spatial relationships along customer trajectories), enabling associated commodities to be placed together even across different sectors while maintaining organized space utilization.
2Productivity
If popular commodities are placed at sites with greater customer traffic, then sales benefits are improved, but the specific preferences and shopping paths of different customer groups are not considered
Solution Approach 1:
The patent segments the customer base into distinct groups based on their shopping path characteristics and preferences. By analyzing customer behavior data, it identifies different customer segments (e.g., impulse buyers, planful shoppers, browsing customers) and tailors commodity placement strategies specifically for each segment's preferred shopping paths and decision-making patterns, rather than using a single uniform placement strategy for all customers.
Solution Approach 2:
The patent applies different commodity placement strategies to different locations along customer shopping paths based on the specific needs and behaviors of customers at each stage. It optimizes placement quality locally by considering which commodities should be positioned at specific points along different types of shopping paths, rather than applying a single global placement rule throughout the supermarket.
3Ease of operation
If associated commodities are placed together, then customer convenience is improved, but limitations on variety sectors in sale spaces prevent implementation
Solution Approach 1:
The patent resolves the space limitation by moving from conventional two-dimensional shelf assignment to three-dimensional spatial optimization that incorporates customer movement paths. It calculates optimal placement by considering the spatial relationships between commodities along customer trajectories, enabling associated commodities to be positioned in locations that maximize convenience while respecting the physical constraints of the supermarket layout and variety sector divisions.
Data Source
AI summary
A method of allocating shelves includes obtaining shopping paths of customers in a supermarket, classifying the plurality of customers into a plurality of customer classes based on the shopping paths of the plurality of customers, determining one or more shopping paths adopted by more customers in the plurality of customer classes as frequent shopping paths of a class of customers of the plurality of customer classes, calculating a see-buy rate of a commodity for each of the plurality of customer classes based on shopping lists and the frequent shopping paths of the plurality of customers, calculating a location for a set of commodities when total expected benefits for the set of commodities are maximized during a certain period of time. The total expected benefits include a sum of an expected benefit for each commodity in the set of commodities based on the see-buy rate and the frequent shopping paths.