Network analytics systems and methods

• US 8,781,874 B2
• Filed: 02/29/2012
• Issued: 07/15/2014
• Est. Priority Date: 04/12/2010
• Status: Active Grant

• Current Assignee: First Data Corporation (Fiserv Incorporated)
• Original Assignee: First Data Corporation (Fiserv Incorporated)
• Inventors: Tavares, Silvio, Fahy, Susan, Carlson, Dennis
• Primary Examiner(s): Singh, Gurkanwaljit
• Application Number:
  US13/408,482
• Publication Number:
  US 20120215589A1
• Time in Patent Office: 867 Days
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 20/20 Point-of-sale [POS] network systems
• CPC Class Codes: G06Q 20/202 Interconnection or interaction of plural electronic cash registers [ECR] or to host computer, e.g. network details, transfer of information from host to ECR or from ECR to ECR
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities

Abstract

In one method, a request is received for a market trend report corresponding to a designated payment type over a designated timeframe. A payment type dataset is identified from aggregated POS data. The payment type dataset comprises POS datasets corresponding to the timeframe and to transactions categorized by payment type. Market trend data is generated as a function of the payment type dataset and is output as a report. The method may produce a variety of reports. For example, a report may display the percentage of transactions for each payment type in terms of numbers of transactions. A report may further show whether each payment type is increasing or decreasing in numbers of transactions over the timeframe.

Claims

1. A system for market reporting according to point-of-sale (POS) data, the system comprising:

an aggregation subsystem, communicatively coupled with a POS network comprising a plurality of POS terminals, and configured to aggregate POS datasets from the plurality of POS terminals in the POS network, each POS terminal being disposed at a merchant associated with terminal data indicating at least one merchant classifier, and each POS terminal being configured to collect transaction data as a function of transactions effectuated via the POS terminal, wherein the transaction data comprises a time of the transaction, an amount of the transaction and an account identifier used to pay for the transaction, and each transaction being routed over one of a plurality of payment networks, each payment network being associated with payment network data, the POS dataset for each of the POS terminals comprising the terminal data, the payment network data and the transaction data;

a data storage subsystem, communicatively coupled with the aggregation subsystem and configured to store the aggregated POS data from the plurality of POS terminals in the POS network;

a trend processing subsystem, communicatively coupled with the POS data store, and configured to generate a market trend for a designated payment type over a timeframe by;

identifying a payment type dataset from the aggregated POS data, the payment type dataset comprising the POS datasets corresponding to the timeframe and to transactions categorized by payment type; and

generating the market trend as a function of the payment type dataset; and

a reporting subsystem, communicatively coupled with the trend processing subsystem, and configured to output graphical report data as a function of the market trend generated by the trend processing system, the graphical report data configured to be displayed on a user device.

2. A system as in claim 1, wherein the reporting subsystem further configures the graphical report data to permit the display of the percentage of transactions for each payment type in terms of numbers of transactions.

3. A system as in claim 2, wherein the reporting subsystem further configures the graphical report data to permit the display of whether each payment type is increasing or decreasing in numbers of transactions over the timeframe.

4. A system as in claim 1, wherein the reporting subsystem further configures the graphical report data to permit the display of the percentage of transactions for each payment type in terms of dollar volumes over the timeframe.

5. A system as in claim 4, wherein the reporting subsystem further configures the graphical report data to permit the display of whether each payment type is increasing or decreasing in dollar volumes over the timeframe.

6. A system as in claim 1, wherein the payment type dataset comprises PIN debit transactions, and wherein the reporting subsystem further configures the graphical report data to permit the display of the percentage of the number of PIN debit transactions that occurred with each payment network.

7. A system as in claim 6, wherein the reporting subsystem further configures the graphical report data to permit the display of whether each payment network is increasing or decreasing in numbers of transactions over the timeframe.

8. A system as in claim 1, wherein the payment type dataset comprises PIN debit transactions, and wherein the reporting subsystem further configures the graphical report data to permit the display of transaction growth and dollar volume growth for each payment network over the time frame.

9. A system as in claim 1, wherein the payment type dataset comprises PIN debit transactions, wherein the given market comprises one or more geographical regions, and wherein the reporting subsystem further configures the graphical report data to permit the display of the percentage of transactions in different geographical regions where the POS terminals are located.

10. A system as in claim 1, wherein the payment type dataset comprises PIN debit transactions, wherein the given market comprises one or more industry classifications based on the merchant classifiers, and wherein the reporting subsystem further configures the graphical report data to permit the display of the percentage of transactions in different industry classifications according to payment network.

11. A system as in claim 1, wherein the payment type dataset comprises PIN debit transactions, and wherein the reporting subsystem further configures the graphical report data to permit the display of the percentage of the dollar volume of PIN debit transactions that occurred with each payment network.

12. A system as in claim 11, wherein the reporting subsystem further configures the graphical report data to permit the display of whether each payment network is increasing or decreasing in dollar volumes of transactions over the timeframe.

13. A system as in claim 1, wherein the payment type dataset comprises signature debit transactions, and wherein the reporting subsystem further configures the graphical report data to permit the display of the percentage of the number of signature debit transactions that occurred with each payment network.

14. A system as in claim 13, wherein the reporting subsystem further configures the graphical report data to permit the display of whether each payment network is increasing or decreasing in numbers of transactions over the timeframe.

15. A system as in claim 1, wherein the payment type dataset comprises signature debit transactions, and wherein the reporting subsystem further configures the graphical report data to permit the display of transaction growth and dollar volume growth for each payment network over the time frame.

16. A system as in claim 1, wherein the payment type dataset comprises signature debit transactions, and wherein the reporting subsystem further configures the graphical report data to permit the display of the percentage of the dollar volume of signature debit transactions that occurred with each payment network.

17. A system as in claim 16, wherein the reporting subsystem further configures the graphical report data to permit the display of whether each payment network is increasing or decreasing in dollar volumes of transactions over the timeframe.

18. A system as in claim 1, wherein the payment type dataset comprises credit transactions, and wherein the reporting subsystem further configures the graphical report data to permit the display of the percentage of the number of credit transactions that occurred with each payment network.

19. A system as in claim 18, wherein the reporting subsystem further configures the graphical report data to permit the display of whether each payment network is increasing or decreasing in numbers of transactions over the timeframe.

20. A system as in claim 1, wherein the payment type dataset comprises credit transactions, and wherein the reporting subsystem further configures the graphical report data to permit the display of transaction growth and dollar volume growth for each payment network over the time frame.

21. A system as in claim 1, wherein the payment type dataset comprises credit transactions, and wherein the reporting subsystem further configures the graphical report data to permit the display of the percentage of the dollar volume of credit transactions that occurred with each payment network.

22. A system as in claim 21, wherein the reporting subsystem further configures the graphical report data to permit the display of whether each payment network is increasing or decreasing in dollar volumes of transactions over the timeframe.

23. A method for market reporting according to point-of-sale (POS) data, the method comprising:

aggregating POS datasets from a plurality of POS terminals in a POS network, each POS terminal being disposed at a merchant associated with terminal data indicating at least one merchant identifier and at least one merchant classifier, and each POS terminal being configured to collect transaction data as a function of transactions effectuated via the POS terminal, wherein the transaction data comprises a time of the transaction, an amount of the transaction and an account identifier used to pay for the transaction, and each transaction being routed over one of a plurality of payment networks, each payment network being associated with payment network data, the POS dataset for each of the POS terminals comprising the terminal data, the payment network data and the transaction data

receiving a reporting request for a market trend report corresponding to a designated payment type over a designated timeframe;

identifying a payment type dataset from the aggregated POS data, the payment type dataset comprising the POS datasets corresponding to the timeframe and to transactions categorized by payment type;

generating market trend data as a function of the payment type dataset; and

outputting graphical report data as a function of the market trend data in response to the reporting request.

24. A method as in claim 23, wherein the graphical report data permits the display of the percentage of transactions for each payment type in terms of numbers of transactions.

25. A method as in claim 24, wherein the graphical report data permits the display of whether each payment type is increasing or decreasing in numbers of transactions over the timeframe.

26. A method as in claim 23, wherein the graphical report data permits the display of the percentage of transactions for each payment type in terms of dollar volumes over the timeframe.

27. A method as in claim 26, wherein the graphical report data permits the display of whether each payment type is increasing or decreasing in dollar volumes over the timeframe.

28. A method as in claim 23, wherein the payment type dataset comprises PIN debit transactions, and wherein the graphical report data permits the display of the percentage of the number of PIN debit transactions that occurred with each payment network.

29. A method as in claim 28, wherein the graphical report data permits the display of whether each payment network is increasing or decreasing in numbers of transactions over the timeframe.

30. A method as in claim 23, wherein the payment type dataset comprises PIN debit transactions, and wherein the graphical report data permits the display of transaction growth and dollar volume growth for each payment network over the time frame.

31. A method as in claim 23, wherein the payment type dataset comprises PIN debit transactions, wherein the given market comprises one or more geographical regions, and wherein the graphical report data permits the display of the percentage of transactions in different geographical regions where the POS terminals are located.

32. A method as in claim 23, wherein the payment type dataset comprises PIN debit transactions, wherein the given market comprises one or more industry classifications based on the merchant classifiers, and wherein the graphical report data permits the display of the percentage of transactions in different industry classifications according to payment network.

33. A method as in claim 23, wherein the payment type dataset comprises PIN debit transactions, and wherein the graphical report data permits the display of the percentage of the dollar volume of PIN debit transactions that occurred with each payment network.

34. A method as in claim 33, wherein the graphical report data permits the display of whether each payment network is increasing or decreasing in dollar volumes of transactions over the timeframe.

35. A method as in claim 23, wherein the payment type dataset comprises signature debit transactions, and wherein the graphical report data permits the display of the percentage of the number of signature debit transactions that occurred with each payment network.

36. A method as in claim 35, wherein the graphical report data permits the display of whether each payment network is increasing or decreasing in numbers of transactions over the timeframe.

37. A method as in claim 23, wherein the payment type dataset comprises signature debit transactions, and wherein the graphical report data permits the display of transaction growth and dollar volume growth for each payment network over the time frame.

38. A method as in claim 23, wherein the payment type dataset comprises signature debit transactions, and wherein the graphical report data permits the display of the percentage of the dollar volume of signature debit transactions that occurred with each payment network.

39. A method as in claim 38, wherein the graphical report data permits the display of whether each payment network is increasing or decreasing in dollar volumes of transactions over the timeframe.

40. A method as in claim 23, wherein the payment type dataset comprises credit transactions, and wherein the graphical report data permits the display of the percentage of the number of credit transactions that occurred with each payment network.

41. A method as in claim 40, wherein the graphical report data permits the display of whether each payment network is increasing or decreasing in numbers of transactions over the timeframe.

42. A method as in claim 23, wherein the payment type dataset comprises credit transactions, and wherein the graphical report data permits the display of transaction growth and dollar volume growth for each payment network over the time frame.

43. A method as in claim 23, wherein the payment type dataset comprises credit transactions, and wherein the graphical report data permits the display of the percentage of the dollar volume of credit transactions that occurred with each payment network.

44. A method as in claim 43, wherein the graphical report data permits the display of whether each payment network is increasing or decreasing in dollar volumes of transactions over the timeframe.