Abstract: The present disclosure provides a detailed description of techniques used in systems, methods, and computer program products for marketing touchpoint attribution bias correction. More specifically, the herein disclosed techniques enable identifying a collection of marketing touchpoints (e.g., associated with a desired conversion) and receiving touchpoint data and/or conversion data associated with those touchpoints. The received data is used to determine contribution values for each of the respective touchpoints that indicate the probability of conversion generated by the respective touchpoints. Some contribution values can have attribution biases. Such biases are addressed by identifying a low contribution value associated with the collection of touchpoints and reducing or eliminating the low contribution value from the remaining contribution values to generate corrected contribution values for the remaining touchpoints.

Abstract: A method, system, and computer program product for media spend management using real-time marketing campaign stimuli selection based on user response predictions. Embodiments commence upon identifying one or more users comprising an audience for one or more marketing campaigns. Observed touchpoint data records are collected based on audience responses to campaign stimuli. A collection of historical touchpoint data records are used to form a predictive model that captures relationships between the stimuli and the responses. At any moment in time, such as when a particular user is online, the predictive model is used to predict one or more next desired touchpoints based on a particular user's then-current online interactions. Marketing campaign stimuli that has a known historical effectiveness with respect to the desired touchpoints is reported. A marketing manager can increase the prevalence of such effective stimuli so as to increase the likelihood of desired responses by the particular user.

Abstract: The present disclosure provides a detailed description of techniques used in systems, methods, and computer program products for determining marketing touchpoint attributions in a segmented media campaign. Embodiments commence by forming a touchpoint attribution predictive model based on stimulus data records and Internet-collected touchpoint data records. A set of media campaign segments can be received or derived and then used for selecting corresponding segment touchpoint data records. Segmented touchpoint contribution values for the media campaign segments are generated by applying the segment touchpoint data records to the touchpoint attribution predictive model. The segmented touchpoint contribution values serve to relate a segment of users with varying engagement states experienced by that segment of users.

Abstract: A method, system, and computer program product for forming and validating a predictive model. The predictive model is based on empirically-determined data taken from one or more user encounters. A first portion of a set of user data corresponds to a first set of respective users that have performed at least some first conversion activity after experiencing a touchpoint encounter. A second set of user data corresponds to second respective users that have experienced at least one of the touchpoint encounters. The user data from the first portion are parsed to identify characteristics that are used for calculating propensity to convert scores. The cookies and scores are used to generate a predictive model that forms a prediction for a given user to convert. The predictive model is validated by comparing the predictions to empirically-determined conversion data (e.g., taken from the second set of user data).

Abstract: A method, system, and computer program product for managing Internet advertising campaigns. Embodiments commence upon receiving (e.g., over a network) advertisement touchpoint data pertaining to a plurality of touchpoints. The advertisement touchpoint data comprises measured stimulation data (e.g., impressions) and measured response data (e.g., conversions). The stimulation data and response data is formatted into an initial succession of candidate touchpoint contribution values where each of the individual touchpoints contributes its respective portion of the total contribution from the total set of measured responses. A non-linear model is applied over the succession of candidate touchpoint contribution values to form a non-linear succession of candidate touchpoint contributions. Individual touchpoints receive an apportionment based on the non-linear succession of candidate touchpoint contributions.

Abstract: A system and method for allocating credit for an advertising conversion among various advertising touchpoints encounter by the consumer is provided. The system and method comprise receiving data pertaining to touchpoints and conversions of an advertising campaign across multiple channels. Users are correlated across the channels and the various conversions, touchpoints, and touchpoint attributes are identified. Each touchpoint attribute and touchpoint attribute value is assigned a weight. An attribution algorithm is selected, and coefficients are calculated using the assigned weights. The algorithm is executed and true scores corresponding to the touchpoints encountered by each converting user are computed.

Abstract: The present disclosure provides a detailed description of techniques used in systems, methods, and in computer program products for real-time marketing portfolio optimization and reapportioning. The claimed embodiments enable calculating and saving a maximum efficiency response curve of a media portfolio, the maximum efficiency response curve comprising a range of response values resulting from a set of media portfolio input characteristics. A user interacts with an interactive graphical user interface which accepts an input characteristic change to alter a spending apportionment in the media portfolio, relative to the calculated and saved a maximum efficiency response curve. Using the stored maximum efficiency response curve as a baseline, results of the reapportionment(s) are generated and displayed.

Abstract: A computer-implemented method, simulation and prediction system, and computer program product for advertising portfolio management. Embodiments commence upon receiving data comprising a plurality of marketing stimulations and respective measured responses, both pertaining to a first time period. A computer is used to form a multi-channel simulation model, where the simulation model accepts the marketing stimulations then outputs simulated responses. The simulation model is used for determining cross-channel weights to apply to the respective measured responses pertaining to the first time period. The simulation model is updated to reflect updated marketing stimulations pertaining to a second time period. The updated marketing stimulations overwrite some of the plurality of marketing stimulations captured in the first time period.

Abstract: A method, system, and computer program product for advertising portfolio management. The method form processes steps for determining effectiveness of marketing stimulations in a plurality of marketing channels included in a marketing campaign. The method commences upon receiving data comprising a plurality of marketing stimulations and respective measured responses, then determining from the marketing stimulations and the respective measured responses, a set of cross-channel weights to apply to the respective measured responses, where the cross-channel weights are indicative of the influence that a particular stimulation applied to a first channel has on the measure responses of other channels. The cross-channel weights are used in calculating the effectiveness of a particular marketing stimulation over an entire marketing campaign.

Abstract: A method, system, and computer program product for computer-aided management of marketing and advertising campaigns. Operations commence upon displaying a maximum efficiency response curve of a media portfolio, where the maximum efficiency response curve comprises a range of response values resulting from a given set of media portfolio input characteristics. A maximum efficiency ROI curve of the media portfolio is displayed, where the maximum efficiency ROI curve comprises a range of ROI values resulting from the set of media portfolio input characteristics. A user provides a prospective quantitative change to alter the media portfolio input characteristics in the media portfolio. The output response of the media portfolio to the prospective change is modeled, and suggested media plan reallocation values are displayed. An ROI value resulting from the prospective set of media portfolio input characteristics is displayed in juxtaposition to the maximum efficiency ROI curve.

Abstract: A system and method for allocating credit for an advertising conversion among various advertising touchpoints encounter by the consumer is provided. The system and method comprise receiving data pertaining to touchpoints and conversions of an advertising campaign across multiple channels. Users are correlated across the channels and the various conversions, touchpoints, and touchpoint attributes are identified. Each touchpoint attribute and touchpoint attribute value is assigned a weight. An attribution algorithm is selected, and coefficients are calculated using the assigned weights. The algorithm is executed and true scores corresponding to the touchpoints encountered by each converting user are computed.

Abstract: A system and method for allocating credit for an advertising conversion among various advertising touchpoints encounter by the consumer is provided. The system and method comprise receiving data pertaining to touchpoints and conversions of an advertising campaign across multiple channels. Users are correlated across the channels and the various conversions, touchpoints, and touchpoint attributes are identified. Each touchpoint attribute and touchpoint attribute value is assigned a weight. An attribution algorithm is selected, and coefficients are calculated using the assigned weights. The algorithm is executed and true scores corresponding to the touchpoints encountered by each converting user are computed.

Abstract: A method of determining a maneuver performed by an aircraft having sensors for monitoring motion data, the method including periodically sampling the sensors to electronically determine segments of motion data of the aircraft; aggregating sequences of the segments of the motion data; comparing the aggregated segments of motion data to models of particular maneuvers; and determining the maneuver performed by the aircraft.

Abstract: A system and method for allocating credit for an advertising conversion among various advertising touchpoints encounter by the consumer is provided. The system and method comprise receiving data pertaining to touchpoints and conversions of an advertising campaign across multiple channels. Users are correlated across the channels and the various conversions, touchpoints, and touchpoint attributes are identified. Each touchpoint attribute and touchpoint attribute value is assigned a weight. An attribution algorithm is selected, and coefficients are calculated using the assigned weights. The algorithm is executed and true scores corresponding to the touchpoints encountered by each converting user are computed.

Abstract: A software system provides a programming language for non-mathematical experts to define the business relations underlying the analytical problem combined with an interpretation engine, model build engine, and model simulation engine to process user information and produce the desired output. By integrating and streamlining model definition and data processing, operating directly at the level of business relations and attributes, the software of the present invention opens up the world of advanced analytics to non-mathematical experts.

Abstract: A method of determining a maneuver performed by an aircraft having sensors for monitoring motion data, the method including periodically sampling the sensors to electronically determine segments of motion data of the aircraft; aggregating sequences of the segments of the motion data; comparing the aggregated segments of motion data to models of particular maneuvers; and determining the maneuver performed by the aircraft.

Abstract: A bypass factor of an evaporator is used to indicate when an air filter of an HVAC is clogged. The bypass factor represents the amount of air that is bypassed without direct contact with the evaporator. As the air filter clogs, the bypass factor decreases. The bypass factor can also be used for early detection of clogging of the air filter. A first bypass factor is calculated by using the temperature measurements, and a second bypass factor is calculated by using the airflow rate of the air. The difference between the two bypass factors determines the error. An increase in the error indicates that the air filter is clogged. A coefficient of performance of the evaporator can also be calculated to detect if the air filter is clogged. A decrease in the coefficient of performance indicates that the air filter is clogged.

Abstract: A refrigerant system is provided with a method and a control programmed to perform the method, in which a low charge of refrigerant is identified. The mass flow of refrigerant through the system is calculated utilizing at least two different methods. The two calculated mass flow rates are compared, and if they differ by more than predetermined amount, a determination is made that there is a low charge of refrigerant within the system.

Abstract: A method and system for detecting and predicting air filter condition for an air handling system operates by determining a system resistance to air flow. The system resistance is utilized to determine a detection statistic indicative of current filter condition and to predict remaining life of the air filter. The system resistance is determined using models that approximate the expected operation of the air handling system. The approximation is then compared to actual values to obtain a difference. Once the difference between the approximated value exceeds a threshold value, an alarm is initiated that is indicative of system resistance. The remaining air filter life is then determined by using historically gathered data, or by using a known degradation rate of the air filter. Once the remaining life of the air filter is estimated, replacement can be scheduled that would coincide with other maintenance.

Abstract: The temperature of the air exiting an evaporator and the relative humidity of the air entering and exiting the evaporator can be calculated by using existing sensors in a vapor compression system. The temperature of the air exiting the evaporator is calculated by using the detected temperature of the air entering the evaporator, the saturation temperature of the air, and a bypass factor. The relative humidity of the air entering and exiting the evaporator are then estimated using a psychrometric chart. By using the existing sensors to determine the temperature of the air exiting the evaporator and the relative humidity of the air entering and exiting the evaporator, the load requirement of the vapor compression system can be calculated without employing additional sensors. The system capacity of the vapor compression system can be matched to the load requirement to allow the effective use of electric power.