Detecting trends is provided. The method comprises receiving, from a number of data sources, data regarding choices of people at a number of specified events and public places and determining, according to a number of clustering algorithms, trend clusters according to data received from the data sources cross-referenced to defined event types and place types. Customer profile data and preferences are received from a number of registered customers through user interfaces, and a number of customer clusters according to the customer profile data and preferences are determined according to clustering algorithms. Correlation rules are calculated between the trend clusters and the customer clusters. A number of trend predictions and recommendations are then sent to a user regarding a number of specified events or time frames according to the correlation rules.

Provided are various mechanisms and processes for generating delivery associate incentive values. In some implementations, predicted demand can be generated based on a first set of historical data and predicted supply can be generated based on a second set of historical data. Delivery quality values can be generated based on the predicted demand and the predicted supply. The delivery quality values can be used to determine incentive values that are provided to delivery associates of an on-demand delivery platform.

A method is disclosed. A data set including: (a) identifiers of a set of incidents occurring within a defined geographic region to which at least one service provider responded during a first time period and (b) address data identifying a location within the geographic region of each said incident of the set is retrieved over a network. An instruction to generate a heat map of the incidents occurring within the geographic region during the first time period is received from a user via a user interface generated to a display device. In response to the instruction to generate the heat map, the address data is converted to GPS data. A heat map of an aerial view of the geographic region based on the GPS data is generated. The heat map is displayed to the display device in a user interface.

A computer-implemented method is disclosed. The method includes using reverse geo-coding to determine user transaction locations for a user, determining a number of user transactions for the user that correspond to each of a plurality of statistical area levels, determining a subdivision of each of the plurality of statistical area levels that has the highest number of domestic card present transactions for the user, identifying an effective area of influence (EAI) for the user, based on a determination of a statistical area level that has the highest number of domestic card present transactions for the user, and accessing geographically classified statistics from public data sources related to one or more of the plurality of the statistical area levels. A location based market recommendation is generated based on the geographically classified statistics and the effective area of influence.

A method, according to some implementations, includes obtaining a criteria for a trial design study, determining permutations for designs in response to the criteria, and determining permutations for scenarios in response to the criteria. The method may further include generating combinations of the permutations for the designs and the permutations for the scenarios, simulating designs corresponding to the generated combinations, and determining performance of the simulated designs.

A method, according to some implementations, includes obtaining trial design simulation results for a set of trial designs and determining a score for each trial design based on a performance criteria. The method may further include evaluating the designs in the set of trial designs to determine a convex hull for the set of trial designs, filtering designs based on the convex hull, and communicating the convex hull designs.

A method for trial design with pareto techniques is provided. The method includes obtaining trial design simulation results for a set of trial designs and determining a score for each trial design based on a performance criteria. The method further includes evaluating Pareto optimality for each design in the set of trial designs to determine a Pareto frontier, filtering designs that are not on the Pareto frontier, and communicating the Pareto frontier designs.

A method, according to some implementations, includes displaying an interface structured to evaluate design data by a group of users and identifying user parameters for each user in the group. The method ma further include configuring the interface for each user in the group based at least in part on the user parameters, receiving, via the interface, user input data from one or more users in the group, and scoring designs based on the user input and user parameters.

A method, according to some implementations, includes obtaining trial design simulation results for a set of trial designs and determining a set of Pareto designs in the set of trial designs based at least in part on the trial design simulation results and one or more performance parameters. The method further includes determining a set of convex hull designs in the set of trial designs, determining a set of recommended designs based at least in part on the set of Pareto designs and the set of convex hull designs, and transmitting the set of recommended designs.

A method for determining trial designs is provided. The method includes obtaining simulation data for a set of trial designs. The simulation data includes performance parameters and performance parameter values associated with each design in the set of designs for a set of criteria; determining an optimality criteria for evaluating the trial designs; searching, within the set of trial designs, for globally optimum designs based on the optimality criteria; and recommending globally optimum designs.