Abstract: The foregoing are among the objects attained by the invention, which provides, in some aspects, digital data processing methods for generation of customized user interfaces that present links, images or other components representing items of interest to a user in an order that is prioritized as a function of (a) representations in a multidimensional factor space of characteristics of the respective items, and (b) representations in that same multidimensional space of characteristics of “context-indicative items”—e.g., items in which the user has previously shown an interest, as indicated by clicks or other interactions with those items respective components in the user interface.

Abstract: The invention provides, in some aspects, digital data processing methods of generating digital content pieces (e.g., email messages or portions thereof) that are customized in accord with individual recipient behaviors. Such methods include the step of generating and digitally transmitting to a digital data devices of a recipient a digital content piece that (i) has a call to action to which the recipient can respond and (ii) that has a plurality of features selected so as to maximize a probability, P(b1, b2, . . . , bM, x1, x2, . . . , xM), that the recipient will respond to that call to action, where that probability is defined by the relation P(b1,b2, . . . , bM,x1,x2, . . . , xM)=exp(?j=1, . . . , Mbjxj)/(1+exp(?j=1, . . . , Mbjxj)) where x1, x2, . . . , xM are values for each of a plurality, M, of features characterizing the digital content piece and/or the recipient, b1, b2, . . . , bM are respective coefficients for each of the values x1, x2, . . . , xM.

Abstract: The invention provides, in some aspects, digital data processing methods of generating digital content pieces (e.g., email messages or portions thereof) that are customized in accord with individual recipient behaviors. Such methods include the step of generating and digitally transmitting to a digital data devices of a recipient a digital content piece that (i) has a call to action to which the recipient can respond and (ii) that has a plurality of features selected so as to maximize a probability, P(b1, b2, . . . , bM, x1, x2, . . . , xM) , that the recipient will respond to that call to action, where that probability is defined by the relation P(b1,b2, . . . , bM, x1, x2, . . . , xM)=exp(?j=1, . . . , Mbjxj)/(1+exp(?j=1, . . . , Mbjxl)) where x1, x2, . . . , xM are values for each of a plurality, M, of features characterizing the digital content piece and/or the recipient, b1, b2, . . . , bM are respective coefficients for each of the values x1, x2, . . .

Abstract: The invention provides, in some aspects, digital data processing methods of generating digital content pieces (e.g., email messages or portions thereof) that are customized in accord with individual recipient behaviors. Such methods include the step of generating and digitally transmitting to a digital data devices of a recipient a digital content piece that (i) has a call to action to which the recipient can respond and (ii) that has a plurality of features selected so as to maximize a probability, P(b1,b2, . . . ,bM,x1,x2, . . . ,xM), that the recipient will respond to that call to action, where that probability is defined by the relation P(b1,b2, . . . ,bM,x1,x2, . . . ,xM)=exp(?j=1, . . . ,Mbjxj)/(1+exp(?j=1, . . . ,Mbjxj)) where x1,x2, . . . ,xM are values for each of a plurality, M, of features characterizing the digital content piece and/or the recipient, b1,b2, . . . ,bM are respective coefficients for each of the values x1,x2, . . . ,xM.

Abstract: The invention provides in some aspects methods of digital data processor-based analysis of digital data that represent interactions to identify distinct individuals and/or the entities with which they are affiliated (e.g., households, businesses, social or other groups) involved in those interactions. The methods can be employed, for example, to analyze digital data representing retail purchase, marketing and visitor interactions for tracking and/or reporting purposes.

Abstract: The invention provides in some aspects methods of digital data processor-based analysis of digital data that represent interactions to identify distinct individuals and/or the entities with which they are affiliated (e.g., households, businesses, social or other groups) involved in those interactions. The methods can be employed, for example, to analyze digital data representing retail purchase, marketing and visitor interactions for tracking and/or reporting purposes.

Abstract: The invention provides methods and apparatus for optimizing markdown scheduling that group multiple retail sites into bins (or buckets) for purposes of scheduling markdown pricing on an item (or group of related items) sold by those sites. The groupings can be based, for example, on a metric that is a function of the current inventory of the item (or items) and its expected sales at each site. A markdown schedule is generated for the combined grouping of stores in each bucket, rather than for the individual stores that make up that bucket, thereby speeding price optimization determination. A report of those schedules can be used, for example, by pricing managers or other personnel to set prices at the sites. Alternatively, or in an addition, the schedules can be used in conjunction with an inventory control system to set prices for the items and/or on RFID or other electronic shelf displays.

Abstract: In one such aspect, the invention provides a method for optimizing merchandise profitability that includes the step of modeling gross margin as a function of product breadth and depth for each of at least one class of goods retailed by each of at least one retail site in a group of sites of the retail enterprise, and as a function of the expected discount price for each such class of goods at each such retail site. The method further includes maximizing the gross margin so modeled to the enterprise and, from that maximization, determining for at least one such retail site an optimal breadth, depth, and/or discount price, for at least one such class of goods retailed by it.

Abstract: The invention provides methods of, and systems for, optimizing the allocation of inventory to, and pricing of, goods sold by multiple retail sites, e.g., in a store, chain or other retail enterprise. Such a method includes generating a plurality of possible or “candidate” allocations of a given inventory among the multiple retail sites. That inventory can be, for example, a supply of the same or like goods at a distribution center that serves the retail sites. Each candidate allocation comprises an assignment of a respective share of that inventory to each of the sites. For each of the candidate allocations, an optimal price of the goods at each of the retail sites is estimated. The optimal price is one that will return an optimal gross margin to the respective site, given its assignment of the respective share of the inventory for the particular candidate allocation. For each of the candidate allocations, a sum is determined of the optimal gross margins across all the retail sites.

Abstract: Systems, methods and computer program products are provided for assigning at least one task to at least one shift. Typically, the method begins by receiving task assignment data, where the task assignment data includes at least one task, at least one shift and at least one priority associated with the at least one task. After receiving the task assignment data, at least one set of task/shift assignments is generated based upon the task assignment data, where each set of task/shift assignments has an associated solution value. After generating the task/shift assignments, an optimum set of task/shift assignments is selected based upon the generated sets of task/shift assignments and a quantitative measure of quality associated with the optimum set of shift schedules, where the quantitative measure of quality is based upon a threshold value and a solution value associated with the optimum set of task/shift assignments.

Abstract: Systems, methods and computer program products are provided for generating at least one shift schedule. A method of generating at least one shift schedule includes receiving scheduling data. Then, a plurality of candidate shift schedules can be generated based upon the scheduling data. Thereafter, an optimum set of shift schedules can be selected based upon the plurality of candidate shift schedules and a quantitative measure of quality associated with the optimum set of shift schedules. The quantitative measure of quality is based upon a threshold cost and a cost associated with the optimum set of shift schedules. The method can also include processing the candidate shift schedules in accordance with one or more business rules. In such instances, the optimum set of shift schedules can be selected based upon the processed candidate shift schedules and the quantitative measure of quality.