MLM Commission Structure Merging via Machine Learning

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Solution Overview

Problem

Merging multi-level marketing (MLM) companies with different commission structures poses challenges in maintaining member income stability, as existing methods either keep companies separate or disrupt existing commission structures, leading to member disorientation and income loss.

Innovation Solution

Implementing a system that uses machine learning algorithms to simulate sales and commissions, adjusting commission rules based on historical data to maintain member income stability by merging MLMs into a multi-line system, allowing each member to retain their downlines and access a multi-line commission structure.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If MLM companies with different commission structures are merged, then the merged company can offer a multi-line commission structure, but members experience disorientation and income loss due to changes in commission positions

Engineering Contradiction:

Improvemulti-line commission structureVSAvoidmember income stability

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system performs preliminary actions by simulating commission calculations multiple times before implementing the merged structure. The simulation module runs commission calculations iteratively to predict income changes, allowing the system to prepare appropriate compensation rules in advance to mitigate member income loss.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback by comparing simulated commission results with historical commission data. The comparison module analyzes differences between predicted and actual commissions, using this feedback to adjust compensation rules and minimize income disruption for members during the transition.

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If MLM companies with different commission structures are merged, then a unified multi-line system can be created, but existing commission structures are disrupted causing member disorientation

Engineering Contradiction:

Improveunified multi-line systemVSAvoidmember understanding of commission structure

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system introduces an intermediary compensation rule that bridges different commission structures. The rule module generates transitional compensation rules that act as intermediaries between the old binary/unilevel structures and the new multi-line structure, helping members understand and adapt to the unified system without complete disruption.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system applies parameter changes by dynamically adjusting commission rates and calculation parameters based on simulation results. The rule module modifies commission parameters iteratively to maintain member income levels while transitioning to the unified multi-line structure, making the change less perceptible and less disruptive to members.

Inventive Principle:

Principle #35Parameter changes

3Adaptability or versatility

If company A with binary commission structure merges with company B with unilevel commission structure, then both companies can operate under one entity, but members must continue building their original structure types

Engineering Contradiction:

Improvemerged company structureVSAvoidcommission structure complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system merges different commission structures by integrating binary and unilevel structures into a unified multi-line commission structure. The merger module combines the downline structures of both companies while the rule module generates compensation rules that honor both original structures, allowing members to maintain their existing downlines without forcing them to rebuild in a different structure type.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS20230281550A1Ai-generated plans within merged user structures

Publication Date: 2023.09.07 KWIKCLICK LLC

AI summary

Disclosed herein is a system and method to any two or more MLMs to be merged into a multiline MLM system despite having different commission structures. Each member of the original MLMs is able to maintain their existing downlines without any changes. Existing MLM members may have full access to the multi-line MLM commission structure. Each type of commission may be calculated using a corresponding commission rule, which may begin in an initial state but may be changed using historical data as a guide for a learning algorithm so that the commissions generated by the rules are close to the commissions members were making in their original MLMs. Simulations of sales and commissions generated from those sales can be run a number of times on a loop, and over time the commission rules will change to bring the simulated commissions closer to expected future commissions based on historical commissions.