Metrics - Based Filtering of Commissions Parameters

Abstract

The present disclosure is directed to a system and method to allow sellers of products to establish individual products in a multilevel marketing (MLM) commission system, where the product is offered and sold to a first purchaser—who then actively by requesting a code, or passively, through the purchase of the product, becomes a user of the commission system. This user is provided a code such that the code may be passed onto followers of the registered user. The registered user will be allowed to advertise the product to a second purchaser and the second purchaser will be allowed to purchase the product and provide advertisements to other purchasers. Commissions paid to respective downline purchasers for a single product may be limited by a preset number of defined levels. After a product is purchased, commissions are paid out to each respective purchaser according to the commission plan assigned to the user. Users may be assigned or may be able to select their own commission plan. The system may assign or suggest commission plans to the used to optimize metric such as sales or profit. The user may elect to donate an amount of their commission to entities such as charities.

1 . (canceled) 
     
     
         2 . A method for metrics-based filtering and optimization of commission parameters, the method comprising:
 determining one or more correlations between each of a plurality of commission plans and different metrics, wherein the correlations indicate that each of the commission plans are optimized for one or more of the metrics;   receiving information sent over a communication network regarding a use of a first embedded link that includes a first code associated with a first user and a first commission plan, wherein the original embedded link is used by a user device of a second user to generate an online request;   generating a second embedded link that includes a second code associated with the second user, wherein tile second code is based on information associated with the first user and indicative of one or more upline users that include at least the first user;   filtering the commission plans based on information regarding the second user;   selecting a second commission plan for the second user from the filtered set of commission plans based on optimization of a metric selected for the second user; and   identifying a set of upline users associated with one or more uses of the second embedded link, wherein the set of upline users includes the first user associated with the first commission plan and the second user associated with the second commission plan.   
     
     
         3 . The method of  claim 2 , wherein each of the plurality of commission plans are associated with a respective set of parameters, and wherein filtering the commission plans is further based on the set of parameters. 
     
     
         4 . The method of  claim 3 , further comprising identifying one or more correlations between the optimized metric and at least one of the parameters. 
     
     
         5 . The method of  claim 4 , further comprising assigning a correlation coefficient to one or more of the correlations, and identifying that at least one of the correlations is significant based on the assigned correlation coefficient. 
     
     
         6 . The method of  claim 3 , wherein the parameters specify at least one of user location, user demographic, product, product category, and date. 
     
     
         7 . The method of  claim 2 , wherein the optimized metric includes at least one of rating, returns, page visitors, downloads, user retention rate, user satisfaction, sales volume, sales per unit time, revenue, and profit. 
     
     
         8 . The method of  claim 2 , further comprising generating one or more new commission plans, wherein the filtered set of commission plans includes one or more of the new commission plans. 
     
     
         9 . The method of  claim 2 , wherein the metric is selected from a list of metrics each associated with a priority, and further comprising selecting a metric from the list until the metric is significantly correlated with at least one parameter of the commission plans. 
     
     
         10 . A non-transitory, computer-readable storage medium, having embodied thereon a program executable by a processor to perform a method for metrics-based filtering and optimization of commission parameters, the method comprising:
 determining one or more correlations between each of a plurality of commission plans and different metrics, wherein the correlations indicate that each of the commission plans are optimized for one or more of the metrics;   receiving information sent over a communication network regarding a use of a first embedded link that includes a first code associated with a first user and a first commission plan, wherein the original embedded link is used by a user device of a second user to generate an online request;   generating a second embedded link that includes a second code associated with the second user, wherein the second code is based on information associated with the first user and indicative of one or more upline users that include at least the first user;   filtering the commission plans based on information regarding the second user;   selecting a second commission plan for the second user from the filtered set of commission plans based on optimization of a metric selected for the second user; and   identifying a set of upline users associated with one or more uses of the second embedded link, wherein the set of upline users includes the first user associated with the first commission plan and the second user associated with the second commission plan.   
     
     
         11 . The non-transitory, computer-readable storage medium of  claim 10 , wherein each of the plurality of commission plans are associated with a respective set of parameters, and wherein filtering the commission plans is further based on the set of parameters. 
     
     
         12 . The non-transitory, computer-readable storage medium of  claim 11 , further comprising identifying one or more correlations between the optimized metric and at least one of the parameters. 
     
     
         13 . The non-transitory, computer-readable storage medium of  claim 12 , further comprising assigning a correlation coefficient to one or more of the correlations, and identifying that at least one of the correlations is significant based on the assigned correlation coefficient. 
     
     
         14 . The non-transitory, computer-readable storage medium of  claim 11 , wherein the parameters specify at least one of user location, user demographic, product, product category, and date. 
     
     
         15 . The non-transitory, computer-readable storage medium of  claim 10 , wherein the optimized metric includes at least one of rating, returns, page visitors, downloads, user retention rate, user satisfaction, sales volume, sales per unit time, revenue, and profit. 
     
     
         16 . The non-transitory, computer-readable storage medium of  claim 10 , further comprising generating one or more new commission plans, wherein the filtered set of commission plans includes one or more of the new commission plans. 
     
     
         17 . The non-transitory, computer-readable storage medium of  claim 10 , wherein the metric is selected from a list of metrics each associated with a priority, and further comprising selecting a metric from the list until the metric is significantly correlated with at least one parameter of the commission plans.