Predictive and profile learning sales automation analytics system and method

Abstract

A sales automation system and method, namely a system and method for scoring sales representative performance and forecasting future sales representative performance. These scoring and forecasting techniques can apply to a sales representative monitoring his own performance, comparing himself to others within the organization (or even between organizations using methods described in application), contemplating which job duties are falling behind and which are ahead of schedule, and numerous other related activities. Similarly, with the sales representative providing a full set of performance data, the system is in a position to aid a sales manager identify which sales representatives are behind others and why, as well as help with resource planning should requirements, such as quotas or staffing, change.

What is claimed is: 
     
         1 . A sales automation system comprising:
 a central data repository included time stamped cached sales records, idealized and learned sales data, and performance metrics;   a repository of raw sales records including raw sales related data; and   a future planning and analysis module functionally communicable with said central data repository and said repository of raw sales records and functionally operable to retrieve data from said central repository and said repository of raw sales records and where said future planning and analysis module has functional analysis components operable to solve for variable based on an input scenario.   
     
     
         2 . The sales automation system as recited in  claim 1  further comprising:
 a machine learning and forecasting module functionally communicable with said central data repository and said repository of sales records and functionally operable to retrieve data from said central repository and said repository of raw sales records and where said machine learning a forecasting module has functional components operable to produce derived sales data outputs. 
 
     
     
         3 . The sales automation system as recited in  claim 2  further comprising:
 a data query module having functional algorithms to receive a user initiated query and produce conditional data and query the central data repository and said machine learning and forecasting module to transmit derived sales data to the date query module and produce analysis outputs loosed on conditional data; and 
 where said future planning and analysis module creates an input scenario based on the conditional data, derived sales data and analysis outputs and save for the variable using a scenario analysis engine. 
 
     
     
         4 . The sales automation system as recited in  claim 2  wherein the machine learning and forecasting module is further operable to use a learned profile of an individual or group of individuals to determine the effect on future revenue of an organization resulting from at least one change in the individual or group of individuals, wherein the at least one change is selected from the group: adding additional individuals to the group of individuals, replacing one individual for another individual, or eliminating an individual. 
     
     
         5 . A method for providing sales automation comprising:
 maintaining a central data repository included time stamped cached sales records, idealized and learned sales data, and performance metrics;   maintaining a repository of raw sales records including raw sales related data;   retrieving data from said central repository and said repository of raw sales records; and   solving for a variable based on an input scenario and the retrieved data from said central repository and said repository of raw sales records.   
     
     
         6 . The method as recited in  claim 5  further comprising:
 retrieving data from said central repository and said repository of raw sales records; and 
 producing derived sales data outputs based on the retrieved data from said central repository and said repository of raw sales records. 
 
     
     
         7 . The method as recited in  claim 6  further comprising:
 receiving a user initiated query; 
 producing conditional data; and 
 querying the central data repository; 
 producing analysis outputs based on the conditional data; and 
 creating the input scenario based on the conditional data, derived sales data and analysis outputs. 
 
     
     
         8 . The method as recited in  claim 6  further comprising using a learned profile of an individual or group of individuals to determine the effect on future revenue of an organization resulting from at least one change in the individual or group of individuals, wherein the at least one change is selected from the group: adding additional individuals to the group of individuals, replacing one individual for another individual, or eliminating an individual. 
     
     
         9 . A computer-readable memory comprising a set of instructions stored therein which, when executed by a processor, causes the processor to provide sales automation by:
 maintaining a central data repository included time stamped cached sales records, idealized and learned sales data, and performance metrics;   maintaining a repository of raw sales records including raw sales related data;   retrieving data from said central repository and said repository of raw sales records; and   solving for a variable based on an input scenario and the retrieved data from said central repository and said repository of raw sales records.   
     
     
         10 . The computer-readable memory as recited in  claim 9  further comprising:
 retrieving data from said central repository and said repository of raw sales records; and 
 producing derived sales data outputs based on the retrieved data from said central repository and said repository of raw sales records. 
 
     
     
         11 . The computer-readable memory as recited in  claim 10  further comprising:
 receiving a user initiated query; 
 producing conditional data; 
 querying the central data repository; 
 producing analysis outputs based on the conditional data; and 
 creating the input scenario based on the conditional data, derived sales data and analysis outputs. 
 
     
     
         12 . The computer-readable memory as recited in  claim 10  further comprising using a learned profile of an individual or group of individuals to determine the effect on future revenue of an organization resulting from at least one change in the individual or group of individuals, wherein the at least one change is selected from the group: adding additional individuals to the group of individuals, replacing one individual for another individual, or eliminating an individual.