System, method, and program product for generating and providing simulated user absorption information

1. A content optimization system providing simulated absorption information comprising:

a) a processor:

b) memory operably connected to the processor,

wherein the memory includes processor executable code that when executed by the processor performs the steps of:

i. generating, by a situation simulation module implemented via the processor executable code, a first simulation comprising a first target profile and a first target situation;

ii. obtaining, by a simulated content module implemented via the processor executable code, a first content selection from amongst a plurality of content selections, wherein the first content selection and first content selection information associated with the first content selection are stored in a content database;

iii. generating, by a training set module implemented via the processor executable code, a first simulated content training set, wherein the first simulated content training set is based on:

1. first lifestyle information associated with the first simulation from a lifestyle database;

2. first absorption information associated with one or more previously viewed content selections associated with the first simulation from an absorption database; and

3. first content information associated with the one or more previously viewed content selections from the content database;

iv. generating, using a first neural network, first simulated absorption information as an output based on the first content selection as an input and the first simulated content training set; and

v. transmitting, by an output module implemented via the processor executable code, the first simulated absorption information for display on a first user device via a user interface.

2. The content optimization system of claim 1 , wherein the generating step i. further comprises generating, by a target profile module implemented via the processor executable code, the first target profile based on first target profile information, wherein the first target profile information comprises a first plurality of specified parameters and a first plurality of tags associated with one or more features, and wherein generating the first target profile is performed by the steps of:

1. Displaying, by the output module, a target profile definition interface of the content optimization system on a first user device associated with a first user, wherein the target profile definition interface includes the one or more features;

2. Obtaining, by the target profile definition interface from the first user device:

i. a first selection of the one or more features associated with the first target profile;

ii. the first plurality of specified parameters associated with the one or more features; and

iii. the first plurality of tags associated with the one or more features;

3. Selecting, from a user profile database, a first subset of user profile information based on the first selection of the one or more features, the first plurality of specified parameters associated with the one or more features, and the first plurality of tags associated with the one or more features;

4. Storing, by the target profile module, the first target profile in the user profile database; and

5. Sending, by the target profile module, the first target profile to the training set module.

3. The content optimization system of claim 2 , wherein the target profile definition interface is generated by obtaining a first list of the one or more features and a first record count associated with each respective feature of the one or more features from a definitions database.

4. The content optimization system of claim 2 , wherein the one or more features comprise age, gender, lifetime system spending, and social media usage information.

5. The content optimization system of claim 2 , wherein the first plurality of specified parameters comprises one or more of a first plurality of relational operators and a first plurality of logical operators.

6. The content optimization system of claim 1 , wherein the generating step i. further comprises generating, by the target profile module, the first target situation based on first target situation information, wherein the first target situation information comprises a second plurality of specified parameters and a second plurality of tags associated with one or more situations, and wherein generating the first target situation is performed by the steps of:

1. Displaying, by the output module, a target situation definition interface of the content optimization system on a first user device, wherein the target situation definition interface includes the one or more situations;

2. Obtaining, by the target situation definition interface from the first user device:

(i) a second selection of the one or more situations associated with the first target situation;

(ii) the second plurality of specified parameters associated with the one or more situations; and

(iii) the second plurality of tags associated with the one or more situations;

3. Selecting from the lifestyle database a first subset of lifestyle information based on the second selection of the one or more situations, the second plurality of specified parameters associated with the one or more situations, and the second plurality of tags associated with the one or more situations;

4. Storing, by the target profile module, the first target situation in the lifestyle database; and

5. sending, by the target profile module, the first target situation to the training set module.

7. The content optimization system of claim 6 , wherein the target profile definition interface is generated by obtaining a second list of the one or more situations and a second record count associated with each respective situation of the one or more situations from the definitions database.

8. The content optimization system of claim 6 , wherein the one or more situations comprise a work situation.

9. The content optimization system of claim 6 , wherein the one or more situations comprise a commute situation.

10. The content optimization system of claim 6 , wherein the one or more situations comprise a home situation.

11. The content optimization system of claim 6 , wherein the second plurality of specified parameters comprises one or more of a second plurality of relational operators and a second plurality of logical operators.

12. The content optimization system of claim 1 , wherein the first content selection is obtained by selection by a first user of the first user device via the user interface.

13. The content optimization system of claim 1 , wherein the first content selection is obtained by generating, by the simulated content module, the first content selection based on the first simulation.

14. The content optimization system of claim 1 , wherein the first simulation is generated by the steps of:

1. Displaying, by the output module, a simulation definition interface of the content optimization system to the first user device, wherein the target situation definition interface includes the first target profile and the first target situation;

2. Obtaining, by the simulation definition interface from the first user device:

i. a third selection of first target profile and the first target situation; and

ii. a third plurality of tags associated with the first target profile and the first target situation;

3. Generating, by the situation simulation module, the first simulation based on the third selection of the first target profile, the first target situation, and the third plurality of tags;

4. Storing, by the situation simulation module, the first simulation in the lifestyle database; and

5. sending, from the situation simulation module to a simulation module of the content optimization system, the first simulation.

15. The content optimization system of claim 1 , wherein the first neural network implements a machine learning algorithm.

16. The system of claim 1 , wherein the first neural network is a deep neural network.

17. The system of claim 1 , wherein the first user device is a content provider device.

18. The system of claim 1 , wherein the user interface is a content provider user interface.