Location-Aware Retail Service for Proximity-Based Offer Filtering
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Solution Overview
Problem
Retailers lack effective means to determine consumer interest in specific products and offer personalized, location-based deals that meet consumers' criteria, leading to inefficient marketing and potential showrooming, while consumers face unclear inventory availability and varying prices between online and in-store purchases.
Innovation Solution
A location-aware retail service that uses big data to provide real-time, proximity-sensitive notifications to consumers based on their declared interests, allowing them to specify preferences and criteria for purchases, ensuring that only relevant offers are presented when the consumer is near a store capable of fulfilling those criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If proximity notifications are sent to consumers when near a store, then consumer engagement increases, but retailers cannot determine if consumers are interested in specific products or willing to shop
Solution Approach 1:
The system performs preliminary actions by having consumers pre-register their product interests, shopping criteria, and preferences before they arrive at the store. This advance preparation enables the system to send targeted notifications only when relevant conditions are met, rather than sending generic proximity alerts to all consumers.
Solution Approach 2:
The system establishes a feedback loop where consumers provide information about their interests and criteria, receive targeted notifications, and can update their preferences based on what they receive. This continuous feedback mechanism ensures the system learns and adapts to consumer preferences, improving notification relevance over time.
2Adaptability or versatility
If consumers check online inventory and prices, then they can compare options, but online prices vary from in-store prices and the experience is not conducive to shopping trips
Solution Approach 1:
The system acts as an intermediary between online and offline shopping experiences. It bridges the gap by providing consumers with real-time information about in-store inventory and pricing through mobile notifications, eliminating the need to separately check online while maintaining the convenience of mobile-based shopping assistance during physical store visits.
3Adaptability or versatility
If promotional systems gather information from consumers to infer offers, then personalized marketing can be provided, but consumers have little control over the conclusions drawn
Solution Approach 1:
The system inverts the traditional approach by having consumers explicitly state their preferences and criteria rather than having the system infer them. Instead of the system making assumptions about what consumers want, consumers directly input their shopping criteria, giving them full control over the personalization parameters while still receiving tailored notifications.
Data Source
AI summary
Techniques for retail location-aware services are provided. A consumer defines parameters in which it is acceptable to the consumer to receive an offer for a good or service. When the parameters are achievable for an enterprise and when the consumer is in a configured proximity to the desired good or service, the mobile device of the consumer is notified of the offer.