Channel Event Incentives for Predictive Demand Surge Response

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Solution Overview

Problem

Conventional demand surge detection methods are reactionary and fail to incorporate diverse data sources, primarily relying on request increases without considering alternative strategies to manage demand surges effectively.

Innovation Solution

A system that processes channel events, including user-sourced data, to generate channel analysis data for predicting demand surges and dynamically adjust incentives, pricing, and inventory management based on real-time and predictive analytics.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional approaches rely solely on detecting increases in requests to identify demand surges, then the detection method is simple and easy to implement, but the accuracy and comprehensiveness of demand prediction deteriorates

Engineering Contradiction:

Improvedemand prediction accuracyVSAvoiddata processing system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent combines multiple data sources including user-sourced data, channel events, and traditional request data into a unified demand prediction model. This merging of diverse data streams enhances prediction accuracy by providing a more comprehensive view of demand patterns while using integrated processing to manage system complexity.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The system processes multiple types of data (user-sourced data, channel events, request data) through a unified demand prediction model that serves multiple functions: detecting demand surges, predicting future demand, and generating incentives. This multi-functional approach improves accuracy without proportionally increasing complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Reliability

If the system incorporates multiple data sources and factors for demand detection, then the holistic determination of demand surge improves, but the complexity of the detection system increases

Engineering Contradiction:

Improvedemand surge detection reliabilityVSAvoiddetection system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system pre-processes and structures multiple data sources (user-sourced data, channel events) before feeding them into the demand prediction model. This preliminary organization of data improves detection reliability by ensuring consistent data quality while reducing the computational complexity during the actual demand detection process.

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If the system only increases prices to address demand surges, then the response mechanism is simple, but the versatility of demand management strategies deteriorates

Engineering Contradiction:

Improvedemand management strategy versatilityVSAvoidincentive system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system dynamically generates diverse incentive types (coupons, discounts, credits, rewards) based on real-time demand conditions, user preferences, and business objectives. This dynamic incentive generation enhances strategy versatility by adapting to different scenarios while using automated rules and algorithms to manage system complexity.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes multiple parameters simultaneously including incentive type, magnitude, timing, and target user segments to create versatile demand management strategies. By adjusting these parameters based on demand prediction outcomes, the system achieves high adaptability without requiring complex manual configuration.

Inventive Principle:

Principle #35Parameter changes

4Speed

If real-time processing of channel events is implemented, then the responsiveness to demand changes improves, but the computational resource consumption increases

Engineering Contradiction:

Improvedemand detection speedVSAvoidcomputational resource consumption

Core Design Contradiction:

SpeedVSUse of energy by moving object

Solution Approach 1:

The system processes channel events with selective intensity based on demand conditions. During normal operations, it uses streamlined processing for common event types, while activating more intensive analysis only when demand surges are detected or predicted. This partial action approach maintains high responsiveness while reducing overall computational resource consumption.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS20260073421A1Computing networks, architectures and techniques for processing incentives based on channel events

Publication Date: 2026.03.12 MARROW IP LLC

AI summary

A computerized method comprising: tracking user behavior data of users each using a respective mobile device within a channel; detecting a demand surge in the channel based on channel analysis data for the channel, wherein the channel analysis data for the channel are based channel events for the channel; and generating one or more first incentives for one or more first users of the users based on the demand surge and incentive metrics, wherein the one or more first incentives are configured to change user behavior of the one or more first users. Other embodiments are disclosed herein.