Systems and methods to recommend price of benefit items offered through a membership platform

Abstract

Systems and methods are provided for recommending price of benefit items offered through a membership platform. Exemplary implementations may: obtain benefit information for content creators of a membership platform; obtain consumption information, the consumption information describing acceptance of offers for the benefit items at the requested amounts by the subscribers of the content creators; train a machine learning model on input/output pairs to generate a trained machine learning model, the individual input/output pairs including training input information and training output information; store the trained machine learning model; determine, using the trained machine learning model, recommended amounts of consideration for the benefit items that correspond to greater acceptance; generate recommendations for individual content creators conveying the recommended amounts for the benefit items offered by the individual content creators; and/or perform other operations.

What is claimed is: 
     
         1 . A system configured to recommend price of benefits obtained by consumers through an online membership platform, the system comprising:
 one or more physical processors configured by machine-readable instructions to:
 train a machine learning model to generate a trained machine learning model, the machine learning model being trained based on information characterizing benefit items obtained by consumers through an online membership platform, the online membership platform hosting content creators of the benefit items, the information further characterizing consumption of the benefit items at requested amounts of consideration by a set of the consumers, the trained machine learning model being configured to output a recommended amount of consideration for a first benefit item of a content creator, the recommended amount of consideration corresponding to greater consumption by the set of the consumers and being different from a requested amount of consideration associated with the first benefit item initially requested by the content creator; 
 store the trained machine learning model; and 
 responsive to obtaining input by the content creator into a user interface conveying acceptance of the recommended amount of consideration:
 update the information characterizing the first benefit item to show that the requested amount of consideration associated with the first benefit item has been changed to the recommended amount of consideration; and 
 provide the trained machine learning model the information characterizing the first benefit item as updated to refine the trained machine learning model. 
 
   
     
     
         2 . The system of  claim 1 , wherein the one or more physical processors are further configured by the machine-readable instructions to:
 generate a recommendation for the recommended amount of consideration; and   effectuate presentation of the recommendation on the user interface displayed on a computing platform associated with the content creator, the user interface being configured to receive the input conveying the acceptance of the recommended amount of consideration for the first benefit item.   
     
     
         3 . The system of  claim 2 , wherein a change from the requested amount of consideration to the recommended amount of consideration is performed automatically in response to obtaining the input. 
     
     
         4 . The system of  claim 1 , wherein the consumption of the benefit items at the requested amounts of consideration by the set of the consumers is characterized based on quantity of consumers who have consumed the benefit items at the requested amounts of consideration. 
     
     
         5 . The system of  claim 4 , wherein the recommended amount of consideration is an amount associated with having a largest quantity of consumers who have consumed the benefit items. 
     
     
         6 . The system of  claim 1 , wherein the benefit items are characterized by benefit type. 
     
     
         7 . The system of  claim 6 , wherein the recommended amount of consideration is for the benefit items of a first benefit type, the first benefit item being of the first benefit type. 
     
     
         8 . The system of  claim 7 , wherein the first benefit type corresponds to a medium of creation. 
     
     
         9 . A system configured to recommend price of benefits obtained by consumers through an online membership platform, the system comprising:
 one or more physical processors configured by machine-readable instructions to:
 provide a trained machine learning model with information characterizing a first benefit item associated with a content creator hosted by an online membership platform, the trained machine learning model having been trained based on consumption of benefit items at requested amounts of consideration by a set of consumers through the online membership platform; 
 generate, using output of the trained machine learning model, a recommendation conveying a recommended amount of consideration for the first benefit item that corresponds to greater consumption by the set of consumers; 
 responsive to acceptance of the recommendation by the content creator via input into a user interface:
 automatically set an offered amount of consideration associated with the first benefit item to the recommended amount of consideration; and 
 provide the trained machine learning model with information indicating that the offered amount of consideration associated with the first benefit item has been automatically set to the recommended amount of consideration to refine the trained machine learning model. 
 
   
     
     
         10 . The system of  claim 9 , wherein the one or more physical processors are further configured by the machine-readable instructions to:
 effectuate presentation of the recommendation on the user interface displayed on a computing platform associated with the content creator during a registration of a user account of the content creator with the online membership platform; and   wherein the user interface is configured to obtain first input by the content creator to accept the recommendation.   
     
     
         11 . A method to recommend price of benefits obtained by consumers through an online membership platform, the method comprising:
 training a machine learning model to generate a trained machine learning model, the machine learning model being trained based on information characterizing benefit items obtained by consumers through an online membership platform, the online membership platform hosting content creators of the benefit items, the information further characterizing consumption of the benefit items at requested amounts of consideration by a set of the consumers, the trained machine learning model being configured to output a recommended amount of consideration for a first benefit item of a content creator, the recommended amount of consideration corresponding to greater consumption by the set of the consumers and being different from a requested amount of consideration associated with the first benefit item initially requested by the content creator;   storing the trained machine learning model; and   responsive to obtaining input by the content creator into a user interface conveying acceptance of the recommended amount of consideration:
 updating the information characterizing the first benefit item to show that the requested amount of consideration associated with the first benefit item has been changed to the recommended amount of consideration; and 
 providing the trained machine learning model the information characterizing the first benefit item as updated to refine the trained machine learning model. 
   
     
     
         12 . The method of  claim 11 , further comprising:
 generating a recommendation for the recommended amount of consideration; and   effectuating presentation of the recommendation on the user interface displayed on a computing platform associated with the content creator, the user interface being configured to receive the input conveying the acceptance of the recommended amount of consideration for the first benefit item.   
     
     
         13 . The method of  claim 12 , wherein a change from the requested amount of consideration to the recommended amount of consideration is performed automatically in response to obtaining the input. 
     
     
         14 . The method of  claim 11 , wherein the consumption of the benefit items at the requested amounts of consideration by the set of the consumers is characterized based on quantity of consumers who have consumed the benefit items at the requested amounts of consideration. 
     
     
         15 . The method of  claim 14 , wherein the recommended amount of consideration is an amount associated with having a largest quantity of consumers who have consumed the benefit items. 
     
     
         16 . The method of  claim 11 , wherein the benefit items are characterized by benefit type. 
     
     
         17 . The method of  claim 16 , wherein the recommended amount of consideration is for the benefit items of a first benefit type, the first benefit item being of the first benefit type. 
     
     
         18 . The method of  claim 17 , wherein the first benefit type corresponds to a medium of creation. 
     
     
         19 . A method to recommend price of benefits obtained by consumers through an online membership platform, the method comprising:
 providing a trained machine learning model with information characterizing a first benefit item associated with a content creator hosted by an online membership platform, the trained machine learning model having been trained based on consumption of benefit items at requested amounts of consideration by a set of consumers through the online membership platform;   generating, using output of the trained machine learning model, a recommendation conveying a recommended amount of consideration for the first benefit item that corresponds to greater consumption by the set of consumers;   responsive to acceptance of the recommendation by the content creator via input into a user interface:
 automatically setting an offered amount of consideration associated with the first benefit item to the recommended amount of consideration; and 
 providing the trained machine learning model with information indicating that the offered amount of consideration associated with the first benefit item has been automatically set to the recommended amount of consideration to refine the trained machine learning model. 
   
     
     
         20 . The method of  claim 19 , further comprising:
 effectuating presentation of the recommendation on the user interface displayed on a computing platform associated with the content creator during a registration of a user account of the content creator with the online membership platform; and   wherein the user interface is configured to obtain first input by the content creator to accept the recommendation.