Context-Based Notification System for Mobile Merchants
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Solution Overview
Problem
Conventional solutions burden customers with the need to actively search for mobile merchants, leading to wasted effort and missed sales opportunities due to unavailability of products or excessive distance, while merchants face challenges in anticipating customer locations and product demand.
Innovation Solution
A system that dynamically determines and notifies customers of nearby merchants based on proximity and interest, allowing for automatic recommendations and fulfillment options such as pickup or delivery, using a network of merchant and customer devices with location-determination capabilities and a fulfillment server to optimize merchant routes and inventory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If customers actively search for mobile merchants, then they can find merchants, but it burdens customers with wasted effort and time
Solution Approach 1:
The system performs preliminary actions by proactively determining customer locations, identifying nearby merchants, and sending notifications before customers need to make purchases. The fulfillment server continuously monitors customer positions and pre-notifies customers of nearby merchants, eliminating the need for customers to actively search.
Solution Approach 2:
The system enables self-service by automatically performing the search and notification functions without requiring customer intervention. The fulfillment server autonomously determines customer locations, identifies relevant merchants, and sends notifications automatically, making the system serve itself rather than requiring active customer participation.
2Productivity
If merchants travel to anticipated customer locations, then sales opportunities increase, but merchants face challenges in anticipating customer locations and product demand
Solution Approach 1:
The system implements feedback mechanisms where customer location data, purchase history, and merchant performance information are continuously collected and analyzed. This feedback loop enables the system to improve its predictions of customer locations and product demand over time, allowing merchants to make more accurate anticipations.
Solution Approach 2:
The system performs preliminary analysis of customer data and merchant patterns to predict future customer locations and product demands before merchants arrive. By analyzing historical data and current trends, the system can anticipate where customers will be and what they will want, enabling merchants to prepare accordingly.
3Ease of operation
If the system provides dynamic notifications and fulfillment options, then customer satisfaction increases, but system complexity increases
Solution Approach 1:
The fulfillment server is designed as a universal platform that handles multiple functions including location determination, customer identification, merchant matching, notification sending, and fulfillment coordination. By consolidating these diverse functions into a single multi-functional system, the patent reduces overall system complexity while maintaining enhanced customer service capabilities.
Data Source
AI summary
In some examples, a location of a merchant is updated as the merchant moves. A server receives the location of the merchant, and compares that location to the location of a user, so as to determine whether the merchant is located within a first threshold distance or a second, smaller threshold distance from the location of the user. If the user is within the first threshold distance, the server presents a first point of sale (POS) interface to initiate an order from the merchant and present the user with an option to fulfill that order through delivery. If the merchant is located within the second, smaller threshold distance from the user, the server presents the user with a second POS interface that gives the user an option to fulfill the order through pickup instead of delivery.