Revenue Attribution for Embedded Software Modules
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Solution Overview
Problem
Attributing revenue in a multi-module embedded software environment is challenging, as it is difficult to determine which distributor should receive revenue when multiple modules are present on a client computer, leading to potential revenue loss and reduced investment in marketing programs.
Innovation Solution
A method that determines the presence of multiple embedded software types on a client system, assigns priority based on residency time and source, classifies each module, and applies a distribution factor to allocate revenue shares among partners, allowing for fair attribution and easy administration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple embedded software modules are installed on a client computer, then the user gains access to more functionality and features, but revenue attribution becomes difficult and revenue may be lost
Solution Approach 1:
The patent segments the client computer environment into distinct software modules, each with its own installation date and source information. By segmenting the revenue attribution process into separate evaluation steps for each module, the system can accurately determine which module generated the revenue stream even when multiple modules are present on the same client system.
Solution Approach 2:
The patent implements preliminary action by recording installation dates and source information at the time of module installation. This preliminary data collection enables accurate revenue attribution later, even when multiple modules are present on the client computer. The system prepares the necessary attribution data in advance, eliminating the need for complex real-time analysis when revenue needs to be allocated.
2Device complexity
If revenue is eliminated for second modules, then attribution is simplified, but distributor investment in marketing programs is reduced
Solution Approach 1:
The patent applies dynamics by making the revenue attribution flexible and adaptive rather than rigid. The system dynamically determines which module receives revenue based on real-time conditions (first module installed, second module installed, or both present), allowing the attribution process to adapt to different installation scenarios without requiring complex manual intervention or reducing distributor incentives.
Solution Approach 2:
The patent changes the parameters of revenue attribution based on installation timing and source information. Instead of using a fixed attribution rule, the system adjusts the attribution parameters dynamically - assigning 100% revenue to the first module in some cases, sharing revenue between modules in other cases, and eliminating revenue for second modules only when appropriate. This flexible parameter adjustment maintains simplicity while preserving distributor investment incentives.
3Measurement precision
If fair revenue attribution is implemented for multiple modules, then revenue distribution accuracy is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service by enabling each software module to self-identify and self-report its installation date and source information. The modules automatically provide the necessary attribution data without requiring manual configuration or complex system-wide coordination. This self-service approach achieves accurate revenue attribution while keeping the system relatively simple, as each module handles its own attribution information independently.
Data Source
AI summary
A method for attributing revenue for embedded software that displays advertising. The method includes the first step of determining the presence of more than one type of embedded software on a given client site. Then, the process assigns priority based on the length of time each type has resided on the client system and the source of each type, followed by classifying each software type, based on the history of present and predecessor copies of the software. A distribution factor is applied to each software type, based on the amount of advertising displayed by each software type and the length of time each software type has been installed. The partner revenue is distributed based on the distribution factor applied to each software type and a rate table.