Systems and methods for generating aggregated merchant analytics for a sector location

Abstract

A method for generating and providing aggregated merchant analytics for a sector location is provided. The method includes defining a plurality of sectors of a geographic region and receiving transaction data for financial transactions occurring within a period of time, the transaction data associated with a plurality of merchants. The plurality of merchants are located in the geographic region. The method also includes identifying, for each merchant, one sector of the plurality of sectors in which the merchant is located. The method further includes generating aggregated merchant analytics for each sector based on the transaction data associated with all merchants located in the sector, wherein the aggregated merchant analytics represent a ranking of each sector relative to all other sectors, and displaying on a user interface of the user computing device the aggregated merchant analytics, wherein the aggregated merchant analytics are graphically represented on a map of the defined sectors.

What is claimed is: 
     
         1 . A method for generating aggregated merchant analytics for a sector, said method implemented by a merchant analytics computing device including at least one processor in communication with a memory, the merchant analytics computing device in communication with a user computing device, said method comprising:
 defining a plurality of sectors of a geographic region;   receiving, by the merchant analytics computing device, transaction data for financial transactions occurring within a period of time, the transaction data associated with a plurality of merchants, the plurality of merchants located in the geographic region;   identifying, for each merchant of the plurality of merchants, one sector of the plurality of sectors in which the merchant is located;   generating, by the merchant analytics computing device, aggregated merchant analytics for each sector based on the transaction data associated with all merchants of the plurality of merchants located in the sector, wherein the aggregated merchant analytics represent a ranking of each sector relative to all other sectors of the plurality of sectors; and   displaying, by the merchant analytics computing device, on a user interface of the user computing device the aggregated merchant analytics, wherein the aggregated merchant analytics are graphically represented on a map of the defined sectors.   
     
     
         2 . The method of  claim 1 , wherein the merchant analytics include a growth score, said method further comprising:
 calculating a growth of each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the growth represents a difference in total sales revenue in each sector from a beginning of the period of time to an end of the period of time;   determining a relative ranking for each sector by comparing the growth of each sector of the plurality of sectors; and   generating the growth score for each sector based on the relative ranking.   
     
     
         3 . The method of  claim 1 , wherein the merchant analytics include a stability score, said method further comprising:
 calculating a stability of each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the stability represents maintenance of total sales revenue within a range of values around an average value of the total sales revenue in each sector during the period of time;   determining a relative ranking for each sector by comparing the stability of each sector of the plurality of sectors; and   generating the stability score for each sector based on the relative ranking.   
     
     
         4 . The method of  claim 1 , wherein the merchant analytics include a size score, said method further comprising:
 calculating a size of each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the size represents a total sales revenue in each sector during the period of time;   determining a relative ranking for each sector by comparing the size of each sector of the plurality of sectors; and   generating the size score for each sector based on the relative ranking.   
     
     
         5 . The method of  claim 1 , wherein the merchant analytics include a traffic score, said method further comprising:
 calculating a traffic of each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the traffic represents a number of transactions initiated in each sector during the period of time;   determining a relative ranking for each sector by comparing the traffic of each sector of the plurality of sectors; and   generating the traffic score for each sector based on the relative ranking.   
     
     
         6 . The method of  claim 1 , wherein the merchant analytics include a ticket size score, said method further comprising:
 calculating an average ticket size for each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the average ticket size represents an average transaction amount in each sector during the period of time, and wherein the average ticket size is calculated by dividing a total sales revenue for a sector by a number of transactions initiated in the sector during the period of time;   determining a relative ranking for each sector by comparing the average ticket size of each sector of the plurality of sectors; and   generating the ticket size score for each sector based on the relative ranking.   
     
     
         7 . The method of  claim 1 , wherein the merchant analytics include a composite score, said method further comprising:
 generating a growth score for each sector, wherein the growth score represents a first relative ranking of the plurality of sectors based on a difference in total sales revenue in each sector from a beginning of the period of time to an end of the period of time;   generating a stability score for each sector, wherein the stability score represents a second relative ranking of the plurality of sectors based on a maintenance of a total sales revenue within a range of values around an average value of the total sales revenue in each sector during the period of time;   generating a size score for each sector, wherein the size score represents a third relative ranking of the plurality of sectors based on the total sales revenue in each sector during the period of time;   generating a traffic score each sector, wherein the traffic score represents a fourth relative ranking of the plurality of sectors based on a number of transactions initiated in each sector during the period of time;   generating a ticket size score for each sector, wherein the ticket size score represents a fifth relative ranking of the plurality of sectors based on an average transaction amount in each sector during the period of time; and   generating the composite score for each sector, wherein the composite score represents a sixth relative ranking of the plurality of sectors based on an aggregation of the growth score, the stability score, the size score, the traffic score, and the ticket size score of each sector.   
     
     
         8 . The method of  claim 1  further comprising:
 generating a merchant record for each merchant of the plurality of merchants; 
 receiving an investment goal associated with the plurality of merchants; 
 sorting the plurality of merchant records according to the investment goal and the merchant analytics for each sector in which each merchant of the plurality of merchants is located; and 
 displaying the sorted merchant records in an optimized merchant management portfolio. 
 
     
     
         9 . A merchant analytics computing device comprising at least one processor in communication with a memory, said merchant analytics computing device in communication with a user computing device, said at least one processor programmed to:
 define a plurality of sectors of a geographic region;   receive transaction data for financial transactions occurring within a period of time, the transaction data associated with a plurality of merchants, the plurality of merchants located in the geographic region;   identify, for each merchant of the plurality of merchants, one sector of the plurality of sectors in which the merchant is located;   generate aggregated merchant analytics for each sector based on the transaction data associated with all merchants of the plurality of merchants located in the sector, wherein the aggregated merchant analytics represent a ranking of each sector relative to all other sectors of the plurality of sectors; and   display on a user interface of the user computing device the aggregated merchant analytics, wherein the aggregated merchant analytics are graphically represented on a map of the defined sectors.   
     
     
         10 . The merchant analytics computing device of  claim 9 , wherein said at least one processor is further programmed to:
 calculate a growth of each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the growth represents a difference in total sales revenue in each sector from a beginning of the period of time to an end of the period of time;   determine a relative ranking for each sector by comparing the growth of each sector of the plurality of sectors; and   generate the growth score for each sector based on the relative ranking.   
     
     
         11 . The merchant analytics computing device of  claim 9 , wherein said at least one processor is further programmed to:
 calculate a stability of each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the stability represents maintenance of total sales revenue within a range of values around an average value of the total sales revenue in each sector during the period of time;   determine a relative ranking for each sector by comparing the stability of each sector of the plurality of sectors; and   generate the stability score for each sector based on the relative ranking.   
     
     
         12 . The merchant analytics computing device of  claim 9 , wherein said at least one processor is further programmed to:
 calculate a size of each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the size represents a total sales revenue in each sector during the period of time;   determine a relative ranking for each sector by comparing the size of each sector of the plurality of sectors; and   generate the size score for each sector based on the relative ranking.   
     
     
         13 . The merchant analytics computing device of  claim 9 , wherein said at least one processor is further programmed to:
 calculate a traffic of each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the traffic represents a number of transactions initiated in each sector during the period of time;   determine a relative ranking for each sector by comparing the traffic of each sector of the plurality of sectors; and   generate the traffic score for each sector based on the relative ranking.   
     
     
         14 . The merchant analytics computing device of  claim 9 , wherein said at least one processor is further programmed to:
 calculate an average ticket size for each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the average ticket size represents an average transaction amount in each sector during the period of time, and wherein the average ticket size is calculated by dividing a total sales revenue for a sector by a number of transactions initiated in the sector during the period of time;   determine a relative ranking for each sector by comparing the average ticket size of each sector of the plurality of sectors; and   generate the ticket size score for each sector based on the relative ranking.   
     
     
         15 . The merchant analytics computing device of  claim 9 , wherein said at least one processor is further programmed to:
 generate a growth score for each sector, wherein the growth score represents a first relative ranking of the plurality of sectors based on a difference in total sales revenue in each sector from a beginning of the period of time to an end of the period of time;   generate a stability score for each sector, wherein the stability score represents a second relative ranking of the plurality of sectors based on a maintenance of a total sales revenue within a range of values around an average value of the total sales revenue in each sector during the period of time;   generate a size score for each sector, wherein the size score represents a third relative ranking of the plurality of sectors based on the total sales revenue in each sector during the period of time;   generate a traffic score each sector, wherein the traffic score represents a fourth relative ranking of the plurality of sectors based on a number of transactions initiated in each sector during the period of time;   generate a ticket size score for each sector, wherein the ticket size score represents a fifth relative ranking of the plurality of sectors based on an average transaction amount in each sector during the period of time; and   generate the composite score for each sector, wherein the composite score represents a sixth relative ranking of the plurality of sectors based on an aggregation of the growth score, the stability score, the size score, the traffic score, and the ticket size score of each sector.   
     
     
         16 . A computer-readable storage medium having computer-executable instructions embodied thereon, wherein when executed by a merchant analytics computing device including at least one processor in communication with a memory, the computer-executable instructions cause the merchant analytics computing device to:
 define a plurality of sectors of a geographic region;   receive transaction data for financial transactions occurring within a period of time, the transaction data associated with a plurality of merchants, the plurality of merchants located in the geographic region;   identify, for each merchant of the plurality of merchants, one sector of the plurality of sectors in which the merchant is located;   generate aggregated merchant analytics for each sector based on the transaction data associated with all merchants of the plurality of merchants located in the sector, wherein the aggregated merchant analytics represent a ranking of each sector relative to all other sectors of the plurality of sectors; and   display on a user interface of a user computing device the aggregated merchant analytics, wherein the aggregated merchant analytics are graphically represented on a map of the defined sectors.   
     
     
         17 . The computer-readable storage medium of  claim 16 , wherein the computer-executable instructions further cause the merchant analytics computing device to:
 calculate a growth of each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the growth represents a difference in total sales revenue in each sector from a beginning of the period of time to an end of the period of time;   determine a relative ranking for each sector by comparing the growth of each sector of the plurality of sectors; and   generate the growth score for each sector based on the relative ranking.   
     
     
         18 . The computer-readable storage medium of  claim 16 , wherein the computer-executable instructions further cause the merchant analytics computing device to:
 calculate a stability of each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the stability represents maintenance of total sales revenue within a range of values around an average value of the total sales revenue in each sector during the period of time;   determine a relative ranking for each sector by comparing the stability of each sector of the plurality of sectors; and   generate the stability score for each sector based on the relative ranking.   
     
     
         19 . The computer-readable storage medium of  claim 16 , wherein the computer-executable instructions further cause the merchant analytics computing device to:
 calculate a size of each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the size represents a total sales revenue in each sector during the period of time;   determine a relative ranking for each sector by comparing the size of each sector of the plurality of sectors; and   generate the size score for each sector based on the relative ranking.   
     
     
         20 . The computer-readable storage medium of  claim 16 , wherein the computer-executable instructions further cause the merchant analytics computing device to:
 calculate a traffic of each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the traffic represents a number of transactions initiated in each sector during the period of time;   determine a relative ranking for each sector by comparing the traffic of each sector of the plurality of sectors; and   generate the traffic score for each sector based on the relative ranking.   
     
     
         21 . The computer-readable storage medium of  claim 16 , wherein the computer-executable instructions further cause the merchant analytics computing device to:
 calculate an average ticket size for each sector using received transaction data for a subset of the plurality of merchants located in each corresponding sector, wherein the average ticket size represents an average transaction amount in each sector during the period of time, and wherein the average ticket size is calculated by dividing a total sales revenue for a sector by a number of transactions initiated in the sector during the period of time;   determine a relative ranking for each sector by comparing the average ticket size of each sector of the plurality of sectors; and   generate the ticket size score for each sector based on the relative ranking.   
     
     
         22 . The computer-readable storage medium of  claim 16 , wherein the computer-executable instructions further cause the merchant analytics computing device to:
 generate a growth score for each sector, wherein the growth score represents a first relative ranking of the plurality of sectors based on a difference in total sales revenue in each sector from a beginning of the period of time to an end of the period of time;   generate a stability score for each sector, wherein the stability score represents a second relative ranking of the plurality of sectors based on a maintenance of a total sales revenue within a range of values around an average value of the total sales revenue in each sector during the period of time;   generate a size score for each sector, wherein the size score represents a third relative ranking of the plurality of sectors based on the total sales revenue in each sector during the period of time;   generate a traffic score each sector, wherein the traffic score represents a fourth relative ranking of the plurality of sectors based on a number of transactions initiated in each sector during the period of time;   generate a ticket size score for each sector, wherein the ticket size score represents a fifth relative ranking of the plurality of sectors based on an average transaction amount in each sector during the period of time; and   generate the composite score for each sector, wherein the composite score represents a sixth relative ranking of the plurality of sectors based on an aggregation of the growth score, the stability score, the size score, the traffic score, and the ticket size score of each sector.