Real-Time Offer Evaluation via Preference Data Integration
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Solution Overview
Problem
Current systems fail to capture a comprehensive, real-time view of consumer preferences across multiple channels, leading to ineffective creation and delivery of targeted offers and discounts, as they are not automatically integrated with loyalty systems, relying on historical data and manual research.
Innovation Solution
Integration of enterprise preference data into loyalty systems using a real-time offer evaluation method that dynamically consults a preference distributor to evaluate offer rules based on customer preferences, enabling immediate decision-making for offers such as coupons, discounts, and loyalty points across various communication channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If historical data from CRM and transaction history systems are used to create offers, then offers can be generated with available data, but the offers cannot be created or updated in real-time and do not reflect current consumer preferences
Solution Approach 1:
The system pre-establishes integration pathways and data flow mechanisms between the centralized preference database and loyalty systems before real-time offer creation is needed. This preliminary setup enables immediate access to current preference data when offers need to be created, eliminating the time delay of traditional historical data retrieval while ensuring comprehensive preference information is available.
Solution Approach 2:
The patent introduces an intermediary integration layer that connects the centralized enterprise preference database with loyalty systems. This intermediary component facilitates real-time data exchange and synchronization, allowing preference information to flow seamlessly between systems without manual intervention, thus resolving both the time delay and information completeness issues.
2Loss of information
If preference information from multiple channels is captured in a centralized database, then a comprehensive view of consumer preferences is available, but the information is not automatically integrated with loyalty systems for real-time offer evaluation
Solution Approach 1:
The patent implements a universal integration interface that serves multiple functions: data synchronization, real-time evaluation, and offer delivery. This multi-functional component handles all interactions between the centralized preference database and various loyalty systems through a single standardized mechanism, reducing overall system complexity while maintaining comprehensive preference information integration.
Solution Approach 2:
The system dynamically adjusts data synchronization parameters and integration depth based on specific loyalty system requirements and real-time needs. By changing parameters such as data refresh frequency, evaluation criteria weights, and integration scope, the system achieves comprehensive preference integration without requiring complex customizations for each loyalty system connection.
3Productivity
If real-time preference data is integrated with loyalty systems, then offers can be evaluated and delivered immediately, but the system complexity and integration requirements increase
Solution Approach 1:
The patent extracts the real-time evaluation logic and preference data access mechanisms from the core loyalty system into a separate, dedicated real-time offer evaluation module. This extraction allows the loyalty system to maintain its existing complexity level while the specialized module handles real-time operations, achieving fast offer evaluation without proportionally increasing overall system complexity.
Solution Approach 2:
The system segments the offer creation and evaluation process into distinct modular components: preference data retrieval, real-time evaluation, offer generation, and delivery. Each segment operates independently with well-defined interfaces, enabling real-time processing while keeping individual component complexity manageable and allowing parallel development and maintenance.
Data Source
AI summary
Techniques for real-time offer evaluations are presented. An enterprise system detects and interaction with a customer. Metrics for the interaction are acquired and a centralized preference server delivers real time preference values known for the customer. The metrics and the preference values are used to dynamically and in real-time evaluate conditions for an enterprise offer and when met the offer is delivered to the customer in real time.