Offer Aggregation System for Personalized Reward Delivery
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Solution Overview
Problem
Existing systems for delivering targeted offers to customers are limited by the lack of visibility into spending habits across multiple merchants and offer vendors, and they fail to effectively utilize customer behavior and financial information for personalized offer generation.
Innovation Solution
A provider computing system that aggregates and filters pre-filtered offers from multiple sources based on customer account information, generating a prioritized offer list for timely and personalized delivery to customers, thereby enhancing the relevance and usability of reward offers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If offer vendors provide targeted offers based on limited customer spending data from single merchants, then offer delivery is simple and direct, but the personalization and relevance of offers deteriorates due to lack of comprehensive customer behavior visibility
Solution Approach 1:
The patent combines offer aggregation functionality into a single centralized system that consolidates offers from multiple vendors and merchants. This merging approach enables comprehensive customer behavior analysis across all partnered merchants while maintaining a unified offer delivery mechanism, thus improving personalization without proportionally increasing overall system complexity.
Solution Approach 2:
The offer aggregation system acts as an intermediary layer between multiple offer vendors/merchants and the customer. This mediator consolidates offers from various sources, applies comprehensive filtering based on aggregated customer spending data, and delivers personalized offers, thereby enhancing offer relevance while managing complexity through a single points of contact.
2Ease of operation
If customers receive offers from multiple offer vendors separately, then each vendor can manage their offers independently, but customers must sift through numerous offers from different sources which increases time and reduces ease of operation
Solution Approach 1:
The offer aggregation system performs preliminary filtering and consolidation of offers from multiple vendors before presenting them to customers. By pre-processing offers and applying filters based on customer spending habits across all partnered merchants, the system eliminates the need for customers to manually sift through numerous offers, thus saving time and improving ease of operation.
3Adaptability or versatility
If merchants and offer vendors use only local customer spending data, then data privacy is maintained locally, but the ability to generate relevant targeted offers deteriorates due to limited visibility across multiple merchants
Solution Approach 1:
The system merges customer spending data from multiple partnered merchants into a unified view within the offer aggregation system. This consolidation enables comprehensive analysis of customer spending habits across all merchants while maintaining data security through controlled access, thereby improving targeted offer relevance without permanent loss of information privacy.
Data Source
AI summary
Systems, methods, and apparatuses for aggregating merchant offers include a network interface structured to facilitate data communication via a network, an accounts database structured to store account information associated with accounts held by the provider, including a payment account associated with a customer, and a processing circuit comprising a processor and memory. The processing circuit is structured to receive a pre-filtered offer from an offer vendor, aggregate the pre-filtered offer with other received pre-filtered offers from multiple offer vendors to create an aggregated offer list, filter the aggregated offer list based on the account information for the customer to create a filtered offer list, generate a prioritized offer list based on the account information for the customer, and transmit the prioritized offer list to a customer device of the customer.