Consent Request Timing Using Probability-Based Consumer Availability
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Solution Overview
Problem
Existing methods for obtaining consumer consent for actions such as transactions, data exchange, or updates to terms and conditions are inefficient, often requiring multiple requests due to consumer unavailability, leading to increased computational and network resource usage and inconvenience.
Innovation Solution
A computer-implemented method determines a time interval where the probability of consumer consent exceeds non-consent, using AI and Boolean decision trees to optimize when consent requests are sent, minimizing unnecessary requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple consent requests are sent to consumers, then the merchant can ensure obtaining consent, but the number of requests increases and resource consumption increases
Solution Approach 1:
The system performs preliminary actions by analyzing historical data and consumer behavior patterns to predict the optimal time to request consent. By determining the time interval when the probability of consumer providing consent exceeds the probability of not providing consent, the system prepares and schedules consent requests at the most favorable moment, reducing the need for multiple retry requests and thereby decreasing resource consumption while maintaining reliable consent acquisition.
2Ease of operation
If consent requests are sent at arbitrary times, then the system can simplify the request process, but consumers are more likely to be unavailable or unprepared
Solution Approach 1:
The system utilizes feedback from historical data about consumer behavior, availability patterns, and response rates to dynamically determine the optimal time interval for requesting consent. This feedback mechanism allows the system to adapt to real-world consumer patterns, scheduling requests when consumers are most likely to be available and prepared, thereby maintaining simplicity while significantly improving consent availability and response rates.
3Reliability
If the system waits for consumer availability, then consent quality improves, but the time to complete the action increases
Solution Approach 1:
The system performs preliminary analysis of historical data to pre-determine the optimal time interval for requesting consent. By calculating and scheduling the request at the predicted optimal moment rather than waiting passively for consumer availability, the system reduces the time delay while ensuring high-quality consent acquisition, as the timing is based on predictive models of consumer behavior rather than reactive waiting.
Data Source
AI summary
The present invention relates to a method (10) of requesting consent from a consumer to complete an action. The method (10) comprises: determining (1) a time interval during which a probability of a consumer providing consent to complete the action exceeds a probability of the consumer not providing consent to complete the action; and requesting (2) consent from the consumer to complete the action during the time interval. Also disclosed is a system (30) for requesting consent from a consumer to complete an action. The system (30) comprises a probability processor (31) and a request processor (32). The probability processor (31) is configured to determine a time interval during which a probability of a consumer providing consent to complete the action exceeds a probability of the consumer not providing consent to complete the action. The request processor (32) is configured to request consent from the consumer to complete the action during the time interval. The action may comprise: a payment transaction, an exchange of data, and/or an update to terms and conditions of use or a service agreement. The method (10) and/or system (30) may be used in the completion of a merchant-initiated transaction.