Cashback Notification via Email and Screen Analysis
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Solution Overview
Problem
Shopping portals face a delay in notifying users of cashback rewards, which reduces user incentivization, as they rely on periodic merchant reports rather than real-time purchase data.
Innovation Solution
A system and method that analyzes user emails and online screen content to identify order-confirmation data, allowing for immediate calculation and notification of cashback rewards by parsing data values such as date, time, order number, and purchase amount, and determining reward eligibility based on valid terms and merchant records.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If shopping portals wait for periodic merchant reports to calculate cashback rewards, then they can ensure accurate reward calculation based on verified purchase data, but users experience delayed notification of rewards which reduces user incentivization
Solution Approach 1:
The system performs preliminary detection of order confirmation emails and screens immediately after user purchases, extracting purchase data before the periodic merchant report arrives. This allows the system to calculate and notify users of cashback rewards instantly while still verifying eligibility against the merchant report later, thus resolving the contradiction between immediate notification and accurate calculation.
2Productivity
If shopping portals implement real-time analysis of user emails and screens to detect purchases, then users receive instant cashback notifications which increases user engagement, but the system complexity increases due to additional monitoring and parsing requirements
Solution Approach 1:
The system leverages existing user applications (email clients and browser extensions) that users already have installed and are actively using. These applications self-monitor for order confirmation content and automatically report detected purchases to the shopping portal, eliminating the need for complex dedicated monitoring hardware or invasive system-level access while achieving real-time detection.
3Loss of time
If the system monitors and parses user emails and screen content in real-time, then it can identify order confirmations immediately for instant cashback notification, but user privacy concerns increase due to access to personal communication and browsing data
Solution Approach 1:
The system uses an intermediary approach by leveraging existing trusted applications (email clients and browser extensions) that users already grant permission to access their data for legitimate purposes. These intermediaries detect order confirmation content and share relevant purchase data with the shopping portal without requiring the portal to directly access or monitor all user communications, thus reducing privacy intrusion while maintaining real-time detection capability.
Data Source
AI summary
The present disclosure relates to a system, method, and computer program for providing users with notifications of a cashback rewards from a shopping portal using screen and email analysis. A shopping portal system analyzes the content and characteristics of user emails, as well as screens viewed by the user through a client application (e.g., webpages and mobile application screens), to identify probable order-confirmation emails and screens. In response to identifying an order-confirmation email or an order-confirmation screen, the system determines whether a cashback reward should be credited to the user for the order corresponding to the order-confirmation email/screen. In response to an order-confirmation email or screen satisfying the criteria for a cashback reward, the system credits a user account with the cashback reward and notifies the user of the reward.