Systems for generating customized datasets

A system, comprising:

• one or more processors;
• and
• non-transitory computer memory storing instructions that, when executed via the one or more processors, cause the one or more processors to determine contact-customized actions by performing operations comprising:
• executing a data mining engine at an attribute aggregator to acquire a first attribute;
• and
• in response to acquiring the first attribute:
• mining contacts from contact datasets;
• applying a pattern recognition process to determine a second attribute of the contacts;
• determining, by executing a first machine learning process, that the first attribute correlates to the second attribute;
• associating, based at least in part on determining that the first attribute correlates to the second attribute, a third attribute with the contacts;
• storing the contacts and associated attributes in a first relational data structure;
• receiving a user request;
• and
• generating, by executing a second machine learning process:
• a customized contact dataset of the contacts associated with the third attribute, and
• a customized action steps dataset comprising one or more action steps determined based at least in part on historical actions taken by the contacts prior to generating the customized action steps dataset.

One or more non-transitory computer-readable media storing instructions for determining contact-customized actions that, when executed via one or more processors, cause the one or more processors to perform operations comprising:

• executing a data mining engine at an attribute aggregator to acquire a first attribute;
• and
• in response to acquiring the first attribute:
• mining contacts from contact datasets;
• applying a pattern recognition process to determine a second attribute of the contacts;
• executing a first correlation process to determine that the first attribute correlates to the second attribute;
• associating, based at least in part on determining that the first attribute correlates to the second attribute, a third attribute with the contacts;
• storing the contacts and associated attributes in a first relational data structure;
• receiving a user request;
• and
• executing a dataset generator to determine:
• a customized contact dataset of the contacts associated with the third attribute, and
• a customized action steps dataset comprising one or more action steps determined based at least in part on historical actions taken by the contacts prior to generating the customized action steps dataset.

A system for determining contact-customized actions, the system comprising:

• means for executing a data mining engine at an attribute aggregator to acquire a first attribute;
• and
• in response to acquiring the first attribute, means for:
• mining contacts from contact datasets;
• applying a pattern recognition process to determine a second attribute of the contacts;
• determining, by executing a first machine learning process, that the first attribute correlates to the second attribute;
• associating, based at least in part on determining that the first attribute correlates to the second attribute, a third attribute with the contacts;
• storing the contacts and associated attributes in a first relational data structure;
• receiving a user request;
• and
• generating, by executing a second machine learning process:
• a customized contact dataset of the contacts associated with the third attribute, and
• a customized action steps dataset comprising one or more action steps determined based at least in part on historical actions taken by the contacts prior to generating the customized action steps dataset.