Cloud Platform for Projected Location Customer Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current location-based services primarily focus on a mobile device owner's current location, failing to determine future positions, which leads to missed marketing opportunities and sales, and hinder the development of enhanced cloud-based mobile applications.
Innovation Solution
A cloud-based platform that stores customer preferences and geolocation data, matches customer interests with nearby products and retailers, and provides navigation and special offers, enabling retailers to target customers with personalized discounts and promotions based on projected locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If location-based services focus only on current location, then system simplicity is maintained, but marketing opportunities and sales are lost
Solution Approach 1:
The system performs preliminary actions by determining projected future locations of mobile device owners before they actually arrive at those locations. The server calculates anticipated positions based on current location data and movement patterns, then proactively pushes marketing content and notifications to devices in advance, enabling retailers to capture customer attention and drive sales before the customer physically arrives at the store.
Solution Approach 2:
The system transitions from static current-location-based services to dynamic future-location-based services. The server continuously updates projected locations based on real-time movement data, adjusting marketing content delivery dynamically as customers move through different geographic zones, enabling adaptive marketing strategies that respond to changing customer positions and behaviors.
2Productivity
If future position determination is implemented, then marketing opportunities increase, but technical implementation complexity increases
Solution Approach 1:
The server acts as an intermediary between mobile devices and retailers, centralizing the complex computational tasks of projecting future locations and matching customers with relevant products. Rather than requiring complex processing in each mobile device, the server performs location analysis, calculates projected positions, and delivers processed marketing content, simplifying the technical implementation while enabling sophisticated marketing capabilities.
Solution Approach 2:
The system enables self-service by automatically determining projected locations and generating appropriate marketing content without requiring manual intervention. The server autonomously processes location data, predicts future positions, identifies relevant products from retailer databases, and pushes notifications to customers, reducing the need for complex manual configuration and ongoing technical management.
3Measurement precision
If cloud-based platform is deployed, then customer matching capability improves, but infrastructure requirements increase
Solution Approach 1:
The cloud-based server platform performs multiple functions: receiving and processing location data from mobile devices, calculating projected future positions, querying retailer product databases, generating matching recommendations, and pushing notifications to customers. This multi-functional platform consolidates what would otherwise require separate systems, reducing overall infrastructure complexity while maintaining high matching accuracy through centralized intelligent processing.
Data Source
AI summary
The present disclosure describes methods, systems, and computer program products for providing an on-demand, cloud-based platform exposing a geolocation service. One computer-implemented method includes storing, in a persistence, customer master data received as part of a customer registration process, storing, in the persistence, customer preferences received in a customer-created product preferences list, receiving geolocation updates from a customer mobile device, determining if there is a match between a particular customer preference and a product in a product catalog based on received customer preferences and the customer location based on the received geolocation updates, transmitting generated determined matches to display on a map to the customer mobile device, and transmitting online navigation data to the customer mobile device.