Dynamic AR Shopping Route with Attention-Based Waypoints
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Solution Overview
Problem
Current augmented reality routing systems in shopping stores provide static route guidance and limited product information augmentation, failing to account for shopper profiles or attention dynamics, thus missing opportunities for personalized recommendations.
Innovation Solution
A method and system that uses an analytics engine and route calculator to identify recommended products based on sought items and shopper attention, calculating efficient routes through a store product map, incorporating waypoints for recommended products and dynamically updating recommendations based on attention sink product information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static route guidance is provided to shoppers, then navigation simplicity is improved, but personalization and sales opportunities are lost
Solution Approach 1:
The routing system transitions from static to dynamic by continuously monitoring shopper behavior through cameras and sensors, real-time analyzing shopping cart contents and dwell time, and dynamically adjusting route recommendations to balance navigation efficiency with personalized product discovery opportunities
Solution Approach 2:
The system implements feedback loops where shopper behavior data (dwell time, product interactions, cart additions) is continuously collected and fed back into the routing algorithm, enabling the system to learn from shopper responses and refine both route guidance and product recommendations adaptively
2Ease of operation
If comprehensive product information augmentation is provided, then shopping assistance is improved, but information overload and distraction increase
Solution Approach 1:
The system applies information augmentation selectively based on local shopper needs, providing detailed product information only when shoppers demonstrate interest through dwell time or repeated viewing, while keeping the interface clean and minimal for shoppers who prefer straightforward navigation
Solution Approach 2:
The system implements partial information presentation by showing only the most relevant product details initially, with the option to expand additional information on demand, rather than presenting all available information at once
3Productivity
If recommended products are added as waypoints in the route, then cross-selling opportunities are improved, but route efficiency may be reduced
Solution Approach 1:
The routing system dynamically adjusts the inclusion of recommended product waypoints based on real-time shopper behavior analysis, adding cross-selling opportunities when shoppers exhibit interest signals and maintaining direct routes when shoppers appear focused on specific shopping goals
Solution Approach 2:
The system changes routing parameters adaptively by adjusting the weight given to cross-selling opportunities versus route efficiency based on shopper profile, shopping context, and real-time behavior, allowing the optimization criteria to shift dynamically throughout the shopping journey
Data Source
AI summary
A store routing system for guiding a shopper in a store comprises a storage storing a store product map comprising location information for products available at the store. The system also comprises an analytics engine for identifying one or more recommended products for the shopper based on a set of one or more sought products. The system also comprises a route calculator for calculating a route through the store to a location of each of the sought products based on the store product map and for including a waypoint in the route corresponding to a location of each of the one or more recommended products.