Abstract: A weather intelligence system retrieves weather forecast data for a number of geographic regions. The weather intelligence system determines, using the weather forecast data for each of the geographic regions, a set of geographic regions predicted to experience a weather anomaly, or unusual weather condition, during a particular time interval. The weather intelligence system determines, through a machine-learning process, whether the weather forecast data indicates conditions that people would generally consider to be unusually hot or cold. The weather intelligence system can then programmatically enable a trigger to transmit a service-related offer associated with the weather anomaly to user devices located within one of the geographic regions where that weather anomaly is determined.

Abstract: Examples described herein include methods, techniques, and systems for optimizing appointment scheduling of an establishment. The establishment may be part of any industry that provides goods and/or services to a plurality of persons. To optimize appointment scheduling, the methods, techniques, and systems described herein may analyze appointment data of a past time period to predict whether the persons will keep their respective pre-scheduled appointments in a future time period. To do so, the establishment may utilize a two-tier predictive module to perform a first predictive categorization followed by a second predictive categorization. The first predictive categorization may aid the establishment to determine whether the pre-scheduled appointments for the future time period are predicted to be kept appointments or missed appointments.

Abstract: A weather intelligence system retrieves weather forecast data for a number of geographic regions. The weather intelligence system determines, using the weather forecast data for each of the geographic regions, a set of geographic regions predicted to experience a weather anomaly, or unusual weather condition, during a particular time interval. The weather intelligence system determines, through a machine-learning process, whether the weather forecast data indicates conditions that people would generally consider to be unusually hot or cold. The weather intelligence system can then programmatically enable a trigger to transmit a service-related offer associated with the weather anomaly to user devices located within one of the geographic regions where that weather anomaly is determined.