Narrowcasting Engine for Targeted Merchant Offer Delivery
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional communication systems face inefficiencies in reaching target audiences, with high marketing spend resulting in low response rates due to irrelevant advertisements and cumbersome redemption processes in rewards/loyalty programs, leading to wasted resources and consumer dissatisfaction.
Innovation Solution
A communication system that utilizes active data gathering and active learning to create user profiles based on demographic, behavioral, and preference data, dynamically selecting and delivering relevant offers to users through a narrowcasting engine, integrated with a rewards/loyalty program for efficient incentive redemption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional broadcasting model is used to reach target audiences, then coverage area is maximized, but response rate deteriorates to only about 1%
Solution Approach 1:
The patent segments the broad audience into specific target groups based on demographic, behavioral, and preference data. The narrowcasting engine divides the population into distinct segments and delivers customized offers to each segment, transforming the undifferentiated broadcasting approach into targeted communications that achieve high response rates while maintaining efficient resource utilization.
Solution Approach 2:
The patent applies local quality by providing different offers and communications to different user segments based on their specific characteristics. Each user receives customized content tailored to their demographics, behavior patterns, and preferences, rather than a uniform broadcast message, thereby maximizing relevance and response rate for each local segment.
2Loss of information
If targeted marketing based on demographic data is implemented, then relevance of offers is improved, but effectiveness deteriorates because demographic information is insufficient
Solution Approach 1:
The patent merges multiple data sources including demographic data, behavioral data from user activities, and preference data from user inputs to create comprehensive user profiles. This combination of diverse data types provides a complete picture of user characteristics, enabling highly relevant and effective targeted marketing that overcomes the limitations of using demographic information alone.
Solution Approach 2:
The patent performs preliminary data gathering and user profiling before delivering marketing offers. By collecting and analyzing demographic, behavioral, and preference data in advance, the system prepares detailed user profiles that enable subsequent offers to be highly relevant and effective, rather than relying on insufficient demographic information at the time of marketing.
3Productivity
If rewards/loyalty programs with traditional redemption processes are used, then customer engagement is improved, but administrative complexity deteriorates and waste increases
Solution Approach 1:
The patent implements self-service mechanisms where users can automatically redeem rewards through the system without complex administrative processing. The automated narrowcasting engine and integrated rewards system enable users to receive and redeem offers through streamlined digital processes, reducing administrative complexity while maintaining high customer engagement through convenient self-service redemption.
Data Source
AI summary
A system includes an offer datastores including one or more offers from one or more merchants, a registered card module to register one or more payment cards to be used for a purchase transaction, a transaction matching module to identify the one or more merchants from a collection of purchase transaction data and to match the purchase transaction of the identified one or more merchants with one or more offers in the offer datastore from the identified one or more merchants, and a rewards module to determine an incentive to be applied to the one or more payment cards based on any offer associated with the matched merchant and generate a qualified transaction data to be transmitted to an issuer of the one or more payment cards.