Abstract: A system and method for a process performed on a computer for constructing recommendation-based predictive models is disclosed. The system and methods access a collection of data records comprising a composite numerical representation of a primary performance indicator or PPI. The PPI comprises an ordinal data point having a calculated ordinal data level. A set of key drivers are determined having an influence on the PPI. Each of the key drivers comprises an ordinal data point having a calculated ordinal data level. An ordinal logistical regression is utilized to calculate the probability of increasing the PPI if each of the members of the set of key drivers are independently increased by a single ordinal data level. A recommended action from a user customizable candidate set of recommendations corresponding to the key driver having the highest probability of increasing the PPI is provided.

Abstract: Systems, methods, and apparatus for providing tee time prices are disclosed herein. A pricing module may receive price and demand values of tee times; determine elasticity; and provide prices for a selected purchasing channel of a plurality of purchasing channels. Other embodiments may be described and claimed.

Abstract: A system and method for a process performed on a computer for constructing recommendation-based predictive models is disclosed. The system and methods access a collection of data records comprising a composite numerical representation of a primary performance indicator or PPI. The PPI comprises an ordinal data point having a calculated ordinal data level. A set of key drivers are determined having an influence on the PPI. Each of the key drivers comprises an ordinal data point having a calculated ordinal data level. An ordinal logistical regression is utilized to calculate the probability of increasing the PPI if each of the members of the set of key drivers are independently increased by a single ordinal data level. A recommended action from a user customizable candidate set of recommendations corresponding to the key driver having the highest probability of increasing the PPI is provided.

Abstract: A system and method for determining an expected profit obtained through financing or selling a commodity is disclosed. Financial information from a selected customer is obtained and entered into a computer. Historical data from a remote database is requested. The requested data is a subset of the historical data in the database, with data selected based on the financial information. A plurality of curve fitting models are applied to the historical data subset to form a plurality of historical data subset fitted curves. A likelihood probability value of each fitted curve is calculated and a best fitted curve is selected. A profit function curve and the best fitted curve are combined to form an expected profit curve. Information from the expected profit curve is displayed to enable a finance offer or offer for sale to be made based on the information.

Abstract: A method of progressively advancing an internet customer, as well as any type of retail customer in a retail setting, through a series of customer interest level stages towards a highest stage is disclosed. The ultimate highest stage typically is represented by the purchase or acquisitions of goods or services from the internet website provider or retail provider. Initially, the method includes generating a website of interest accessible by one or more internet customers and then within that website, providing an initial webpage of interest for the internet customer. The first webpage includes a display of segregated content representing a choice of multiple stages of progressively higher interest level found on a separate webpage of interest associated with each stage of higher interest level, where the initial webpage includes a link to each webpage of interest.