5. An apparatus configured for improved demand forecasting utilizing searched attributes derived from a consumer's browsing activity including icon selection, navigation of a hierarchal structure presented as a website or app, and location, the apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least: generate a virtual offer for one or more combinations of a category or sub-category, location, and price range; derive a first portion of searched attributes from data that is received as input upon icon selection at a consumer facing user interface; access and pre-populating a second portion of the searched attributes upon receiving global positioning system (GPS) data indicative of a location from a consumer device; implicitly infer a third portion of the searched attributes as a function of user browsing activity, the user browsing activity being navigation of a hierarchical data structure, the data structure organized by location and hyper-location or category and sub-category; storing, for each of one or more consumers, each of the first portion, the second portion, and third portion of the searched attributes; access, for each of one or more consumers, consumer data accessed from a consumer profile of the consumer, wherein the consumer data comprises searched attributes associated with the consumer, wherein each portion of the searched attributes derived from the data received as input upon icon selection is associated with at least one second portion indicative of a GPS location, and wherein each third portion of searched attributes implicitly inferred as a function of user browser activity also is associated with at least one second portion indicative of a GPS location; calculate a probability that a particular consumer would buy a particular offer in a particular time frame for at least a portion of the plurality of consumers and for each of the virtual offers; determine an estimated number of units to be sold for at least a portion of the one or more virtual offers as a function of at least the probability associated with each of the one or more virtual offers; and generate promotions, each representative of an offer for sale of an actual product or service from an actual merchant, comprised of attributes configured to be matched to the searched attributes, from among the one or more virtual offers having an estimated number of units to be sold that meets a predetermined threshold; and cause display of a particular page layout on a user interface of a consumer device associated with the consumer, the particular page layout comprised of the promotions matching the searched attributes associated with the consumer and the consumer device, the particular page layout configured as a function of specifications of the consumer device, a detected specific location, and consumer preferences.
5. An apparatus configured for improved demand forecasting utilizing searched attributes derived from a consumer's browsing activity including icon selection, navigation of a hierarchal structure presented as a website or app, and location, the apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least: generate a virtual offer for one or more combinations of a category or sub-category, location, and price range; derive a first portion of searched attributes from data that is received as input upon icon selection at a consumer facing user interface; access and pre-populating a second portion of the searched attributes upon receiving global positioning system (GPS) data indicative of a location from a consumer device; implicitly infer a third portion of the searched attributes as a function of user browsing activity, the user browsing activity being navigation of a hierarchical data structure, the data structure organized by location and hyper-location or category and sub-category; storing, for each of one or more consumers, each of the first portion, the second portion, and third portion of the searched attributes; access, for each of one or more consumers, consumer data accessed from a consumer profile of the consumer, wherein the consumer data comprises searched attributes associated with the consumer, wherein each portion of the searched attributes derived from the data received as input upon icon selection is associated with at least one second portion indicative of a GPS location, and wherein each third portion of searched attributes implicitly inferred as a function of user browser activity also is associated with at least one second portion indicative of a GPS location; calculate a probability that a particular consumer would buy a particular offer in a particular time frame for at least a portion of the plurality of consumers and for each of the virtual offers; determine an estimated number of units to be sold for at least a portion of the one or more virtual offers as a function of at least the probability associated with each of the one or more virtual offers; and generate promotions, each representative of an offer for sale of an actual product or service from an actual merchant, comprised of attributes configured to be matched to the searched attributes, from among the one or more virtual offers having an estimated number of units to be sold that meets a predetermined threshold; and cause display of a particular page layout on a user interface of a consumer device associated with the consumer, the particular page layout comprised of the promotions matching the searched attributes associated with the consumer and the consumer device, the particular page layout configured as a function of specifications of the consumer device, a detected specific location, and consumer preferences. 7. The device of claim 5 , the device further comprising processing circuitry configured to: subsequent to calculating the probability, generate a ranking of the calculated probability calculations; and compare the ranking to a relevancy threshold; and determine the estimated number of units to be sold for a portion meeting or exceeding the relevancy threshold.