Abstract: The present disclosure describes systems and methods for providing enhanced location analysis and consumer insights using mobile sightings data. An approximate geographic location is useful to mobile service providers and advertisers who wish to provide targeted content to consumers based on their location. The location analysis described herein provides more depth and detail about the detected geographic location of the consumer and also insights into business locations visited by the user of the device, consumer/market segments and patterns of behavior (for an individual consumer and/or for aggregated group of consumers), retail trends and patterns, and other profile information. For example, a location profile analytics system as described herein can determine a probability that an approximate geographic location actually corresponds to a specific geographic location, such as a business location.

Abstract: The present disclosure describes systems and methods for providing enhanced location analysis and consumer insights using mobile sightings data. An approximate geographic location is useful to mobile service providers and advertisers who wish to provide targeted content to consumers based on their location. The location analysis described herein provides more depth and detail about the detected geographic location of the consumer and also insights into business locations visited by the user of the device, consumer/market segments and patterns of behavior (for an individual consumer and/or for aggregated group of consumers), retail trends and patterns, and other profile information. For example, a location profile analytics system as described herein can determine a probability that an approximate geographic location actually corresponds to a specific geographic location, such as a business location.

Abstract: The present disclosure describes systems and methods for automatically rolling-up data associated with one or more geographic units, such as ZIP+4 codes, such that the rollup comprises a minimum number of households to protect anonymity and ensure compliance with privacy regulations, while preserving variance of the underlying data associated with the geographic regions. Data attributes may include demographic data, socio-economic data, lifestyle segmentation, psychographic data, behavioral data, credit data, and other data. The rollup process may involve identifying one or more geographic units with a number of households below a minimum or threshold amount, applying filters to find candidate geographic units for rollup, scoring candidate geographic units to select best pairings for rollup, and repeating until the rollup group has at least the minimum number of households. The process may make trades off between granularity (e.g.

Abstract: Various systems and methods are disclosed for accessing and traversing disparate, complex, and multi-dimensional data structures to dynamically and interactively generate reports based on automated modeling of complex and non-uniformly formatted data. Automated analysis of probabilistic functions and temporal-based data records enable non-technical users to quickly and dynamically act on time-sensitive information. In response to various user inputs, the system automatically accesses and traverses complex data structures (including, for example, frequency distribution models) calculates complex data based on the traversals, displays the calculated complex data to the user, and enters the calculated complex data into the reports.

Abstract: The present disclosure describes systems and methods for automatically rolling-up data associated with one or more geographic units, such as ZIP+4 codes, such that the rollup comprises a minimum number of households to protect anonymity and ensure compliance with privacy regulations, while preserving variance of the underlying data associated with the geographic regions. Data attributes may include demographic data, socio-economic data, lifestyle segmentation, psychographic data, behavioral data, credit data, and other data. The rollup process may involve identifying one or more geographic units with a number of households below a minimum or threshold amount, applying filters to find candidate geographic units for rollup, scoring candidate geographic units to select best pairings for rollup, and repeating until the rollup group has at least the minimum number of households. The process may make trades off between granularity (e.g.

Abstract: The present disclosure describes systems and methods for automatically rolling-up data associated with one or more geographic units, such as ZIP+4 codes, such that the rollup comprises a minimum number of households to protect anonymity and ensure compliance with privacy regulations, while preserving variance of the underlying data associated with the geographic regions. Data attributes may include demographic data, socio-economic data, lifestyle segmentation, psychographic data, behavioral data, credit data, and other data. The rollup process may involve identifying one or more geographic units with a number of households below a minimum or threshold amount, applying filters to find candidate geographic units for rollup, scoring candidate geographic units to select best pairings for rollup, and repeating until the rollup group has at least the minimum number of households. The process may make trades off between granularity (e.g.