Personalized Reward Offers via Machine Learning
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Solution Overview
Problem
Existing reward programs and promotional offers are not customized to individual customer preferences, leading to irrelevant information and difficulties in integrating merchant offers with payment methods, making it hard for customers to effectively utilize these offers.
Innovation Solution
A payment service system that uses machine-learning models to personalize reward offers based on user data, automatically connecting them to payment cards and redeeming them at the point of sale, enhancing user experience and efficiency through seamless integration with merchant systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional communication methods are used to communicate reward programs and promotional offers, then information can be delivered to customers, but the information is not customized to individual customer preferences leading to irrelevant promotional information
Solution Approach 1:
The system personalizes promotional offers by analyzing individual customer data including purchase history, preferences, and behavior patterns. Each customer receives customized reward offers tailored to their specific interests and spending habits, transforming generic promotional information into locally relevant content for each user segment.
Solution Approach 2:
The system continuously monitors customer responses to promotional offers and uses this feedback to refine future personalization. By tracking which offers are viewed, accepted, and redeemed, the system adjusts the relevance and customization of subsequent promotional information to better match individual customer preferences.
2Ease of operation
If manual processes are used for viewing, accepting, and redeeming promotional offers, then customers can control their participation, but the process requires good memory and affirmative activities involving delay
Solution Approach 1:
The system automatically enrolls customers in relevant reward programs based on their purchase history and preferences without requiring manual acceptance. Promotional offers are pre-configured and automatically applied at the point of sale, eliminating the need for customers to remember or manually redeem offers.
Solution Approach 2:
The system autonomously manages the entire reward lifecycle including offer selection, customer enrollment, tracking, and redemption. The payment card system automatically identifies applicable rewards and applies them without customer intervention, making the process self-service oriented and eliminating manual steps.
3Adaptability or versatility
If payment cards are issued with reward programs, then financial-service providers can provide promotional offers, but it is difficult to integrate offers for particular products or services with particular payment methods
Solution Approach 1:
The payment card system is designed with multi-functional capabilities to handle various types of reward programs and promotional offers from multiple merchants. The system provides a universal platform that can integrate different payment methods, reward structures, and merchant systems through standardized interfaces while maintaining flexibility for customization.
Solution Approach 2:
The financial-service provider acts as an intermediary between merchants and customers, managing the integration of promotional offers with payment methods. The system mediates the complex interactions by centralizing offer management, handling compatibility checks, and coordinating between different merchant systems and payment processors.
Data Source
AI summary
In one embodiment, a method includes, by one or more computing devices associated with a payment service, receiving, by the payment service and from a first client device associated with a sender, a request for a digital gift to be added to a payment account of a recipient, identifying, one or more recommended digital gifts for the recipient based on transaction history of the recipient on the payment service, where the one or more digital gifts are identified using a machine-learning model trained using a transaction history of one or more users of the payment service, providing, in response to receiving a selection of one of the recommended digital gifts from the first client device, and sending, by the payment service to a second client device associated with the recipient, a notification that the sender has provided the recipient with the identified digital gift.