Abstract: Provided herein are systems, methods and computer readable media for forecasting demand. An example method comprises generating a virtual offer for one or more combinations of a category or sub-category, location, and price range, accessing consumer data comprising one or more users and user data related to each of the one or more users, calculating a probability that a particular user would buy a particular offer in a particular time frame for at least a portion of the plurality of users and for each of the virtual offers, and determining an estimated number of units of 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.

Abstract: Provided herein are systems, methods and computer readable media for forecasting demand. An example method comprises generating a virtual offer for one or more combinations of a category or sub-category, location, and price range, accessing consumer data comprising one or more users and user data related to each of the one or more users, calculating a probability that a particular user would buy a particular offer in a particular time frame for at least a portion of the plurality of users and for each of the virtual offers, and determining an estimated number of units of 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.

Abstract: Provided herein are systems, methods and computer readable media for forecasting demand. An example method comprises generating a virtual offer for one or more combinations of a category or sub-category, location, and price range, accessing consumer data comprising one or more users and user data related to each of the one or more users, calculating a probability that a particular user would buy a particular offer in a particular time frame for at least a portion of the plurality of users and for each of the virtual offers, and determining an estimated number of units of 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.

Abstract: Provided herein are systems, methods and computer readable media for identifying supply. An example for identifying merchants for fulfilling demand comprises receiving one or more virtual offers and an associated quantity of at least a portion of the one or more virtual offers, wherein the one or more virtual offers are representative of a residual demand for a geographic area, assigning a virtual offer of the one or more of the virtual offers to one or more merchants in an instance in which a supply source of the one or more merchants is identified as able to supply at least a portion of the associated quantity of the virtual offer, and determining a priority score for the one or more merchants, wherein the one or more merchants are rankable based on the priority score.

Abstract: Provided herein are systems, methods and computer readable media for forecasting demand. An example method comprises generating a virtual offer for one or more combinations of a category or sub-category, location, and price range, accessing consumer data comprising one or more users and user data related to each of the one or more users, calculating a probability that a particular user would buy a particular offer in a particular time frame for at least a portion of the plurality of users and for each of the virtual offers, and determining an estimated number of units of 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.

Abstract: Provided herein are systems, methods and computer readable media for providing sales pipeline automation. An example method comprises calculating a forecasted demand, the forecasted demand comprising at least one or more virtual offers and a demanded quantity of at least a portion of the one or more virtual offers, identifying one or more merchants, wherein the one or more merchants are identified as able to supply at least a portion of the residual demand, assigning the one or more merchants to one or more sales resources in accordance with at least a calculated sales value of the one or more merchants.

Abstract: Provided herein are systems, methods and computer readable media for forecasting demand. An example method comprises generating a virtual offer for one or more combinations of a category or sub-category, location, and price range, accessing consumer data comprising one or more users and user data related to each of the one or more users, calculating a probability that a particular user would buy a particular offer in a particular time frame for at least a portion of the plurality of users and for each of the virtual offers, and determining an estimated number of units of 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.

Abstract: Provided herein are systems, methods and computer readable media for assigning, calculating or determining a provider quality score. An example method comprises capturing metric information from a web source, the metric information indicative of a product, service, or experience performance of a provider. For example each of a number of reviews and the total number of reviews may be captured. The method may further comprise assigning a provider quality score.

Abstract: Provided herein are systems, methods and computer readable media for assigning, calculating or determining a provider quality score. An example method comprises capturing metric information from a web source, the metric information indicative of a product, service, or experience performance of a provider. For example each of a number of reviews and the total number of reviews may be captured. The method may further comprise assigning a provider quality score.

Abstract: Provided herein are systems, methods and computer readable media for forecasting demand. An example method comprises generating a virtual offer for one or more combinations of a category or sub-category, location, and price range, accessing consumer data comprising one or more users and user data related to each of the one or more users, calculating a probability that a particular user would buy a particular offer in a particular time frame for at least a portion of the plurality of users and for each of the virtual offers, and determining an estimated number of units of 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.

Abstract: Provided herein are systems, methods and computer readable media for forecasting demand. An example method comprises generating a virtual offer for one or more combinations of a category or sub-category, location, and price range, accessing consumer data comprising one or more users and user data related to each of the one or more users, calculating a probability that a particular user would buy a particular offer in a particular time frame for at least a portion of the plurality of users and for each of the virtual offers, and determining an estimated number of units of 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.