Systems and methods for developing convertible term products

• US 10,489,860 B1
• Filed: 12/19/2014
• Issued: 11/26/2019
• Est. Priority Date: 12/23/2013
• Status: Active Grant

• Current Assignee: Massachusetts Mutual Life Insurance Company
• Original Assignee: Massachusetts Mutual Life Insurance Company
• Inventors: Ross, Gareth, Walker, Tricia
• Primary Examiner(s): Brindley, Benjamin S
• Application Number:
  US14/576,704
• Time in Patent Office: 1,803 Days
• Field of Search: 705 4
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

Methods and systems for developing profitable convertible term products are disclosed. The methods include the disaggregation of the pricing of existing term products and the use of big data analytics to identify opportunities to improve the acceptance of the product within a particular share of the market. Then, a pricing model and a selling model are built to test the product.

Claims

1. A computer-implemented method comprising:

upon displaying a user interface on a computing device associated with a first user, receiving, by an analytics engine manager module of a server, a selection of an existing term product dataset for modification;

retrieving, by a product analysis module of the server, from a product database, the existing term product dataset;

retrieving, by the product analysis module of the server, from the product database, a second term product dataset, wherein the second term product dataset shares at least one characteristic value with the existing term product dataset;

evaluating, by the product analysis module of the server, performance of the existing term product dataset against the second term product dataset by comparing a performance value associated with each of the existing term product dataset and the second term product dataset;

dividing, by a pricing modeling module of the server, the existing term product dataset into constituent parts based on a price of each constituent part;

executing, by the pricing module of the server, a computer-generated model configured to;

iteratively analyze impact of proposed changes to the constituent parts by comparing the proposed changes to historical data in a database to determine any modification of each constituent to achieve a result by determining at least one constituent part to be modified;

analyze a second user'"'"'s needs based on user profile comprising user information provided by the user and previously purchased products using natural language processing;

generate a third term product dataset from the constituent parts based on the second user'"'"'s needs, and assign a new price value to the constituent parts based on the analysis of the impact of proposed changes to the constituent parts and any modification of each constituent;

executing, by a product dataset reconstitution module of the server, a simulation protocol to analyze a capability of the third term product dataset to address market needs by assessing product pricing for the third term product dataset and determine if the third term product dataset satisfies market needs;

when the third term product satisfies the market needs;

updating, by the product dataset reconstitution module of the server, the product database by inserting a record corresponding to the third term product dataset as a new convertible term product satisfying market needs.

2. The method according to claim 1, wherein analyzing the capability comprises assessing product positioning for the third term product dataset.

3. The method according to claim 1, wherein analyzing the capability comprises assessing product promotion for the third term product dataset.

4. The method according to claim 1, wherein analyzing the capability comprises assessing advertising for the third term product dataset.

5. The method according to claim 1, wherein analyzing the capability comprises assessing customer satisfaction for the third term product dataset.

6. The method according to claim 1, further comprising generating, by a sales modeling module of the server, a selling model for the third term product dataset.

7. The method according to claim 1, further comprising testing, by a testing module of the server, the third term product in the selling model dataset.

8. The method according to claim 1, wherein the product dataset database comprises records of previous, existing, and future products.

9. The method according to claim 1, wherein the characteristics include at least one of resources available for the project, target market share, desired impact on target market share, and expected return on investment.

10. The method according to claim 1, wherein the at least one other term product dataset is selected by identifying at least one product in the product dataset database having the same parameter or characteristic as the third term product.

11. The method according to claim 1, wherein the at least one other term product dataset is selected by identifying at least one product in the product database having the same parameter or characteristic as the first product dataset.

12. A system comprising:

a server comprising;

an analytics engine manager module of the server configured to;

upon displaying a user interface on a computing device associated with a first user, receive a selection of an existing term product for modification;

a product definition module of the server configured to;

retrieve, from a product database, the existing term product dataset;

retrieve, from the product database, a second term product dataset, wherein the second term product dataset shares at least one characteristic value with the existing term product dataset;

a product analysis module of the server configured to;

evaluate performance of the existing term product dataset against the second term product dataset by comparing a performance value associated with each of the existing term product dataset and the second term product dataset;

a pricing modeling module of the server configured to;

divide the existing term product dataset into constituent parts based on a price of each constituent part;

execute a computer-generated model configured to;

iteratively analyze impact of proposed changes to the constituent parts by comparing the proposed changes to historical data in a database to determine any modification of each constituent to achieve a result by determining at least one constituent part to be modified;

analyze a second user'"'"'s needs based on user profile comprising user information provided by the user and previously purchased products using natural language processing; and

generate a third term product dataset from the constituent parts based on the second user'"'"'s needs and assign a new price value to the constituent parts based on the analysis of the impact of proposed changes to the constituent parts and any modification of each constituent; and

a product dataset reconstitution module of the server configured to;

trigger a simulation protocol to analyze a capability of the third term product dataset to address market needs by assessing product pricing for the third term product dataset and determine if the third term product dataset satisfies market needs;

when the third term product satisfies the market needs;

update the product database by inserting a record corresponding to the third term product dataset as a new convertible term product satisfying market needs.

13. The system according to claim 12, further comprising a sales modeling module of the server configured to generate a selling model for the third term product dataset.

14. The system according to claim 12, further comprising a testing module of the server configured to test the new term product dataset in the selling model.