Shopping Optimization Engine for Real-Time Multi-Store Price Comparison
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Solution Overview
Problem
Consumers face challenges in efficiently comparing prices, sales, and discounts across different grocery and retail stores, leading to time-consuming shopping processes and potential overspending, especially for those with restricted mobility or busy schedules, without integrated solutions for real-time pricing aggregation and personalized shopping strategies.
Innovation Solution
A price comparison and shopping optimization system with a software application and server system that aggregates real-time pricing, discounts, and coupons across multiple stores, provides personalized shopping strategies, and supports in-person purchases, online orders, and delivery, using an optimization engine to calculate the most cost-effective shopping strategies based on user preferences and delivery time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If consumers manually search through store advertisements, brochures, and online resources to compare prices, then they may find cost-effective options, but the process becomes time-consuming and tedious
Solution Approach 1:
The system merges data from multiple stores, advertisements, brochures, and online resources into a single centralized platform. The price comparison system aggregates pricing information, sales, and discounts from numerous sources simultaneously, allowing consumers to view all relevant information in one place without manually visiting each source separately.
Solution Approach 2:
The system acts as an intermediary between consumers and multiple retail stores. It automatically collects, processes, and presents price comparison data from various stores through user-friendly interfaces including mobile applications and websites, eliminating the need for consumers to directly search through each store's separate channels.
2Ease of operation
If consumers shop at a single store without considering alternatives, then the shopping process is simplified, but they risk overspending and missing out on better deals
Solution Approach 1:
The system performs preliminary price comparisons and identifies the most cost-effective shopping options before the consumer makes purchasing decisions. By pre-calculating savings, highlighting best deals, and organizing price data in advance, the system enables consumers to make informed decisions quickly without having to manually evaluate multiple stores during the shopping process.
Solution Approach 2:
The system provides immediate feedback to consumers about potential savings and cost-effective options. Through features such as savings calculations, deal highlights, and store recommendations, the system continuously informs consumers about better pricing alternatives, enabling them to adjust their shopping choices to minimize spending while maintaining simplicity.
3Adaptability or versatility
If not all grocery stores offer online ordering or shipping options, then in-store shopping remains necessary for some items, but this limits convenience for individuals with restricted mobility or busy schedules
Solution Approach 1:
The system provides universal access to multiple shopping methods through a single platform. It integrates information about in-store shopping, online ordering, and shipping options across different stores, allowing consumers to choose the most convenient method for each item or store based on their specific needs and the store's capabilities.
Solution Approach 2:
The system dynamically adapts to different shopping scenarios and consumer needs. It provides real-time information about which stores offer online ordering or shipping, allowing consumers to flexibly switch between in-store and online shopping methods based on availability, urgency, and personal convenience requirements.
4Loss of energy
If consumers track and utilize coupons or time-sensitive sales from multiple stores, then they can maximize savings, but managing such offers becomes an overwhelming task
Solution Approach 1:
The system performs automatic tracking and management of coupons and time-sensitive sales offers. It proactively identifies available discounts, monitors expiration dates, and notifies consumers about relevant deals without requiring manual tracking. The system handles the complexity of managing multiple coupons and sales across different stores automatically.
Solution Approach 2:
The system replaces manual coupon management with automated digital processes. Instead of consumers physically collecting, organizing, and tracking paper or digital coupons across multiple stores, the system uses automated data collection, storage, and analysis to manage all coupon information centrally, presenting relevant offers through digital interfaces.
Data Source
AI summary
The present invention is a price comparison and shopping system and associated method to optimize the shopping experience by enabling users to locate specials and discounts across multiple grocery and retail stores (i.e., stores). The system comprises a software application installed on a user device and a server system communicatively coupled via a network. The server includes a store data repository for storing prices and discounts, a coupon repository for active deals, and an optimization engine for determining cost-effective shopping strategies based on user inputs, preferences, and real-time data aggregated from multiple sources. The system provides recommendations for cost-effective stores and displays estimated savings to users, enabling informed decision-making. Additionally, the system facilitates online orders, pickups, deliveries, and in-person shopping by linking with store systems and providing navigation guides.