Retail Shopper Route Analytics System
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Solution Overview
Problem
Current asset tracking systems in retail operations are unable to generate fine-grained location coordinate information, limiting their ability to determine detailed routes of travel and analyze shopper behavior effectively.
Innovation Solution
A system architecture that integrates location information, map information, and transaction data to determine detailed shopping routes and generate various metrics and visualizations, enabling improved retail operations and customer flow management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current asset tracking systems are used, then basic location tracking is achieved, but fine-grained location coordinate information and detailed route determination are not achieved
Solution Approach 1:
The patent segments the retail environment into multiple zones with unique identifiers and divides the tracking process into discrete steps: receiving zone identification signals, determining locations based on these signals, and processing location data through categorized steps. This segmentation enables fine-grained location tracking without requiring complex continuous monitoring systems throughout the entire retail space.
Solution Approach 2:
The patent introduces an intermediary processing system that receives zone identification signals from transmitters and endpoint devices, processes these signals through multiple processing steps, and generates detailed route information. This intermediary layer transforms basic signal data into fine-grained location coordinates and detailed route determinations without requiring direct complex interactions between all system components.
2Loss of information
If detailed route determination is implemented, then shopper behavior analysis capability is improved, but data processing complexity increases
Solution Approach 1:
The patent performs preliminary actions by categorizing location data into multiple processing steps before final analysis. Location information is processed through sequential steps that organize data by zone, time, and shopper journey stages. This preliminary organization enables effective shopper behavior analysis without requiring complex real-time processing of all raw location data simultaneously.
Solution Approach 2:
The patent adds dimensional organization to location data by processing information across multiple dimensions: spatial zones, temporal sequences, and behavioral categories. This multi-dimensional processing transforms simple location coordinates into rich shopper behavior insights by analyzing patterns across different dimensions rather than treating all data points uniformly.
3Adaptability or versatility
If multiple data sources are integrated, then analytics capability is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal processing framework that handles multiple data sources (location signals, transaction data, shopper profiles) through a single integrated system. This multi-functional system processes diverse data types using common processing steps and unified data structures, enabling versatile analytics capabilities without requiring separate specialized systems for each data source.
Solution Approach 2:
The patent merges multiple data sources and processing functions into a unified analytics system. Location information, transaction data, and shopper behavior patterns are combined and processed together through integrated processing steps, creating comprehensive analytics capabilities. This merging reduces the need for multiple separate systems and their associated complexities while maintaining high analytics versatility.
Data Source
AI summary
The present disclosure provides methods and systems for tracking a shopper route at a retail enterprise. Location information associated with assets can be collected at a retail location, from which a detailed route through the retail location may be recreated and overlaid on map data reflecting a retail location layout. Further analysis may be performed on the route. Additionally, the route may be overlaid on a map, including business context information and point-of-sale transaction information, allowing for various metrics and metric visualizations to be generated that can be further analyzed to achieve various objectives.