Abstract: Systems, computer-implemented methods, and non-transitory computer-readable media are provided for on-boarding client data received from multiple information sources. Consistent with the disclosed embodiments, a computer system may receive metadata concerning information received from one or more information sources. The computer system may receive instructions for mapping the information onto a schema of a trait-based modeling system. Based on these received instructions, the computer system may generate a script for on-boarding the client data. The computer system may provide the script to a server, which may execute the script, causing the resulting information to be provided to a trait-based modeling system to optimize a field in the schema of the trait-based modeling system.

Abstract: In one embodiment, the present disclosure is directed to a method of identifying baselines for relationships. The method include obtaining, at a computer, a first set of relationships between information atoms, identifying baselines for the first set of relationships, and obtaining a second set of relationships between the information atoms. The method further includes determining differences between the baselines and the second set of relationships, and identifying how the differences relate to at least one information atom. A result is determined and output based on how the differences relate to the at least one information atom.

Abstract: In one embodiment, the present disclosure is directed to a method of identifying baselines for relationships. The method include obtaining, at a computer, a first set of relationships between information atoms, identifying baselines for the first set of relationships, and obtaining a second set of relationships between the information atoms. The method further includes determining differences between the baselines and the second set of relationships, and identifying how the differences relate to at least one information atom. A result is determined and output based on how the differences relate to the at least one information atom.

Abstract: Systems, apparatus, and methods for correlating two items of interest, based on a plurality of data items and characteristics. The data items may include objective and quantitative data, as well as subjective and qualitative data. In one implementation, the relationship of an individual to a metric is determined. The system, apparatus, and methods may store characteristics describing individuals generally, along with metrics relevant to an organization; receive a plurality of data items; extract information associated with the individual from the data items; determine a number of relationships between the data items, individuals, metric, and characteristics; and use the relationships to determine an overall relationship between the individual and the metric, based on the data and characteristics. In addition, related groups of characteristics may be identified.

Abstract: The present disclosure generally relates to systems and methods for analyzing and displaying data. In accordance with one implementation, a computer-implemented method is provided that comprises displaying one or more personas. The method also includes displaying information associated with individuals within the persona and assigning and displaying a score to the persona which represents the persona's propensity to become a customer of a business. The displayed interface also may display characteristics associated with personas, relationships between personas, and geographical regions associated with personas. It may also display a communication display and provide a means for communicating with individuals and personas by way of a communication preference.

Abstract: Systems, apparatus, and methods for correlating two items of interest, based on a plurality of data items and characteristics. The data items may include objective and quantitative data, as well as subjective and qualitative data. In one implementation, the relationship of an individual to a metric is determined. The system, apparatus, and methods may store characteristics describing individuals generally, along with metrics relevant to an organization; receive a plurality of data items; extract information associated with the individual from the data items; determine a number of relationships between the data items, individuals, metric, and characteristics; and use the relationships to determine an overall relationship between the individual and the metric, based on the data and characteristics. In addition, related groups of characteristics may be identified.

Abstract: The present disclosure generally relates to providing an interface for visualization of data. In accordance with one implementation, a computer-implemented method is provided that comprises displaying one or more metrics and detecting a selection of the one or more metrics. The method also includes displaying one or more objects representing persona groups and one or more corresponding gravity wells for each selected one of the one or more metrics. The displayed interface visually represents correlation between each of the one or more objects, each of the one or more objects representing one of a corresponding persona group from persona groups, and the corresponding gravity well.

Abstract: Systems, apparatus, and methods for correlating two items of interest, based on a plurality of data items and characteristics. The data items may include objective and quantitative data, as well as subjective and qualitative data. In one implementation, the relationship of an individual to a metric is determined. The system, apparatus, and methods may store characteristics describing individuals generally, along with metrics relevant to an organization; receive a plurality of data items; extract information associated with the individual from the data items; determine a number of relationships between the data items, individuals, metric, and characteristics; and use the relationships to determine an overall relationship between the individual and the metric, based on the data and characteristics. In addition, related groups of characteristics may be identified.

Abstract: Systems, apparatuses, and methods for determining an individual's sentimental baseline, based on a plurality of data items and characteristics. The data items may include objective and quantitative data, as well as subjective and qualitative data. The system, apparatus, or method may obtain a number of relationships between information atoms, identify sentiments associated with the relationships, and calculate sentimental baselines for those relationships. Differences from any baseline may also be calculated, to determine true changes in sentiment. Relationships between those differences and other data or relationships may also be calculated, to determine how a change in sentiment is related to other changes in behavior. For example, relationships between a particular difference and changes in any metric, sub-metric, group of characteristics, data item, data source, characteristic, sentiment, or groups thereof may be determined. These relationships may also be used to predict future behavior or sentiment.

Abstract: Systems, apparatus, and methods for correlating two items of interest, based on a plurality of data items and characteristics. The data items may include objective and quantitative data, as well as subjective and qualitative data. In one implementation, the relationship of an individual to a metric is determined. The system, apparatus, and methods may store characteristics describing individuals generally, along with metrics relevant to an organization; receive a plurality of data items; extract information associated with the individual from the data items; determine a number of relationships between the data items, individuals, metric, and characteristics; and use the relationships to determine an overall relationship between the individual and the metric, based on the data and characteristics. In addition, related groups of characteristics may be identified.

Abstract: System, apparatus, and methods for profiling constituents of an organization. These constituents may include donors, volunteers, supporters, advocates, stakeholders, affiliates, customers, employees, managers, executives, advisors, regulators, vendors, suppliers, partners, contractors, beneficiaries, friends, followers, or fans of any organization. In one implementation, the relationship of constituents to an organization is determined. The system, apparatus, and methods may store characteristics describing constituents generally, along with metrics relevant to an organization; receive a plurality of data items; extract information associated with the constituents from the data items; determine a number of relationships between the data items, constituents, metric, and characteristics; and use the relationships to determine an overall relationship between the constituents and the organization, based on the data and characteristics. In addition, related groups of characteristics may be identified.

Abstract: Systems, apparatuses, and methods for determining an individual's sentimental baseline, based on a plurality of data items and characteristics. The data items may include objective and quantitative data, as well as subjective and qualitative data. The system, apparatus, or method may obtain a number of relationships between information atoms, identify sentiments associated with the relationships, and calculate sentimental baselines for those relationships. Differences from any baseline may also be calculated, to determine true changes in sentiment. Relationships between those differences and other data or relationships may also be calculated, to determine how a change in sentiment is related to other changes in behavior. For example, relationships between a particular difference and changes in any metric, sub-metric, group of characteristics, data item, data source, characteristic, sentiment, or groups thereof may be determined. These relationships may also be used to predict future behavior or sentiment.

Abstract: Systems, apparatus, and methods for correlating two items of interest, based on a plurality of data items and characteristics. The data items may include objective and quantitative data, as well as subjective and qualitative data. In one implementation, the relationship of an individual to a metric is determined. The system, apparatus, and methods may store characteristics describing individuals generally, along with metrics relevant to an organization; receive a plurality of data items; extract information associated with the individual from the data items; determine a number of relationships between the data items, individuals, metric, and characteristics; and use the relationships to determine an overall relationship between the individual and the metric, based on the data and characteristics. In addition, related groups of characteristics may be identified.