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

A system configured to recommend price of subscription levels offered by content creators through an online membership platform, the system comprising:

• one or more physical processors configured by machine-readable instructions to
• obtain benefit information for content creators of an online membership platform, the content creators offering different levels of ongoing subscribership to consumers, the benefit information characterizing benefit items received by subscribers of the content creators in accordance with the different levels of the ongoing subscribership, the benefit information characterizing a first benefit item received by the consumers who become the subscribers of a first content creator in accordance with a first level of subscribership;
• provide a trained machine learning model the benefit information, the trained machine learning model having been trained based on acceptance of offers for the different levels of ongoing subscribership at different requested amounts;
• generate, using output of the trained machine learning model, recommendations conveying recommended amounts of recurring consideration for the different levels of ongoing subscribership that correspond to greater acceptance, such that a first recommendation conveying a first recommended amount is determined for the first level of subscribership, wherein a user interface is configured to obtain user entry and/or selection by the content creators to accept the recommendations;
• responsive to acceptance of the recommendations by the content creators:
• automatically set offered amounts of recurring consideration for the different levels of ongoing subscribership to the recommended amounts of recurring consideration;
• and
• provide the trained machine learning model with information indicating the offered amounts of recurring consideration have been automatically set to the recommended amounts of recurring consideration to refine the trained machine learning model.

A method to recommend price of subscription levels offered by content creators through an online membership platform, the method comprising:

• obtaining benefit information for content creators of an online membership platform, the content creators offering different levels of ongoing subscribership to consumers in exchange for different requested amounts of recurring consideration, the benefit information characterizing benefit items received by subscribers of the content creators in accordance with the different levels of the ongoing subscribership, the benefit information characterizing a first benefit item received by the consumers who become the subscribers of a first content creator in exchange for a first requested amount of recurring consideration in accordance with a first level of subscribership;
• obtaining consumption information for the content creators, the consumption information describing acceptance of offers for the different levels of ongoing subscribership at the different requested amounts by sets of the subscribers subscribing to the content creators;
• training 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, the training input information including the benefit information, and the training output information including the consumption information;
• storing the trained machine learning model;
• determining, using the trained machine learning model, recommended amounts of recurring consideration for the different levels of ongoing subscribership that correspond to greater acceptance, including determining a first recommended amount for the first level of subscribership, the first recommended amount being different from the first requested amount;
• generating recommendations for individual ones of the content creators conveying the recommended amounts for the different levels of ongoing subscribership, including generating a first recommendation conveying the first recommended amount for the first level of subscribership for the first content creator, wherein a user interface is configured to obtain user entry and/or selection by the content creators to accept the recommendations;
• responsive to acceptance of the recommendations by the content creators:
• updating the benefit information to reflect the different levels of ongoing subscribership being offered in exchange for the recommended amounts of recurring consideration conveyed in accepted ones of the recommendations;
• and
• providing the trained machine learning model the benefit information reflecting the different levels of ongoing subscribership being offered in exchange for the recommended amounts of recurring consideration to refine the trained machine learning model.