POINT-OF-SALE-BASED MARKET TRACKING AND REPORTING

• US 20110251870A1
• Filed: 04/12/2010
• Published: 10/13/2011
• Est. Priority Date: 04/12/2010
• Status: Active Grant

• Current Assignee: First Data Corporation (Fiserv Incorporated)
• Original Assignee: First Data Corporation (Fiserv Incorporated)
• Inventors: Homler, Karen, Tavares, Silvio
• Granted Patent: US 8,195,500 B2
• Time in Patent Office: Days
• US Class Current: 705/7.29
• 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 30/02 Marketing; Price estimation or determination; Fundraising
• 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

Systems and methods are described for transforming actual aggregated data (e.g., transaction and terminal data) from a large number of POS terminals into market trend reports that include macro-level trend data and analyses. For example, POS datasets are aggregated from POS terminals distributed across many merchant outlet locations, each POS dataset including location data and transaction data for its respective POS terminal. A reporting request is received for a market trend report corresponding to a designated market over a designated timeframe. A market dataset is identified from the portion of the aggregated POS data corresponding to the designated timeframe and market. Unreliable portions of the data may be discarded. Market trend data is then calculated as a function of the reliable portion of the market dataset, and graphical report data is output as a function of the market trend data in response to the reporting request.

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 of a plurality of merchant identifiers and at least one of a plurality of merchant classifiers, and each POS terminal being configured to collect transaction data as a function of transactions effectuated via the POS terminal, the POS dataset for each of the POS terminals comprising the terminal 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 market over a timeframe by;

identifying a market dataset from the aggregated POS data, the market dataset comprising the POS datasets corresponding to the timeframe and to POS terminals having terminal data indicating a merchant classifier corresponding to the market;

calculating a reliable portion of the market dataset as a function of the POS datasets in the market dataset; and

generating the market trend as a function of the reliable portion of the market 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. The system of claim 1, wherein:

the trend processing subsystem is further configured to analyze the market trend as a function of the reliable portion of the market dataset to identify a trend event indicating a statistically significant feature of the market trend; and

the reporting subsystem is further configured to output the graphical report data to graphically indicate the trend event.

3. The system of claim 2, wherein:

the trend processing subsystem is further configured to receive supplemental reporting data from an analyst in response to identifying the trend event; and

the reporting subsystem is further configured to output the graphical report data to include the supplemental reporting data.

4. The system of claim 2, wherein the trend processing subsystem is further configured to:

for each merchant identifier associated with at least one of the POS datasets from the reliable portion of the market dataset, calculate a merchant contribution representing a contributing effect on the trend event attributable to the POS datasets associated with the merchant identifier; and

generating a merchant driver by identifying at least one merchant contribution as indicating a statistically significant contributing effect on the trend event attributable to the corresponding merchant identifier.

5. The system of claim 4, wherein the reporting subsystem is further configured to:

output the graphical report data to indicate the merchant driver.

6. The system of claim 2, further comprising:

a macroeconomic data store configured to store macroeconomic data corresponding to at least a portion of the timeframe,

wherein the trend processing subsystem is further communicatively coupled with the macroeconomic data store and is further configured to determine a correlation between the trend event and the macroeconomic data, and

wherein the reporting subsystem is further configured to output the graphical report data to indicate the correlation.

7. The system of claim 6, further comprising:

the macroeconomic data store is further configured to store the macroeconomic data in association to geographic data corresponding to geographic regions associated with at least one of the POS datasets from the reliable portion of the market dataset, such that the correlation between the trend event and the seasonality data indicates a further correlation between the trend event and the macroeconomic data associated with at least one geographic region.

8. The system of claim 6, further comprising:

the macroeconomic data store is further configured to store the macroeconomic data in association to merchant identifiers associated with at least one of the POS datasets from the reliable portion of the market dataset, such that the correlation between the trend event and the seasonality data indicates a further correlation between the trend event and the macroeconomic data associated with at least one of the merchant identifiers.

9. The system of claim 6, wherein the macroeconomic data is selected from a group consisting of:

gross domestic product data;

unemployment data;

personal bankruptcy data; and

consumer debt data.

10. The system of claim 2, further comprising:

a seasonality data store configured to store seasonality data corresponding to at least a portion of the timeframe,

wherein the trend processing subsystem is further communicatively coupled with the seasonality data store and is further configured to determine a correlation between the trend event and the seasonality data, and

wherein the reporting subsystem is further configured to output the graphical report data to indicate the correlation.

11. The system of claim 10, wherein:

the seasonality data store is further configured to store the seasonality data in association to merchant identifiers associated with at least one of the POS datasets from the reliable portion of the market dataset, such that the correlation between the trend event and the seasonality data indicates a further correlation between the trend event and the seasonality data associated with at least one of the merchant identifiers.

12. The system of claim 2, further comprising:

a social data store configured to store social data indicating social trends or events occurring during at least a portion of the timeframe affecting at least one of the merchant identifiers associated with at least one of the POS datasets from the reliable portion of the market dataset,

wherein the trend processing subsystem is further communicatively coupled with the social data store and is further configured to determine a correlation between the trend event and the social data, such that the correlation between the trend event and the social data indicates an effect on the trend event attributable to the social trends or events affecting at least one of the merchant identifiers, and

wherein the reporting subsystem is further configured to output the graphical report data to indicate the correlation.

13. The system of claim 1, wherein the trend processing subsystem is configured to calculate the reliable portion of the market dataset by:

determining, for each of the POS datasets, transaction dates corresponding to the transaction data for the transactions effectuated via the respective POS terminal, such that the reliable portion of the market dataset includes only the POS datasets comprising transaction data for transactions having transaction dates occurring substantially over the entire timeframe.

14. The system of claim 1, wherein the trend processing subsystem is configured to calculate the reliable portion of the market dataset by:

identifying a POS baseline corresponding to a subset of the POS datasets in the market dataset; and

calculating a statistical variation between the POS baseline and the subset of the POS datasets, such that the subset of POS datasets is added to the reliable portion of the market dataset only when the statistical variation is less than a threshold level.

15. The system of claim 1, further comprising:

an interface subsystem communicatively coupled to a user device and the reporting system, and configured to;

receive a report request from the user device; and

communicate the graphical report data to the user device for display on the user device in response to the request.

16. The system of claim 1, wherein:

the trend processing subsystem is further configured to generate the market trend as a function of data from the POS datasets indicating at least one of;

a geographic location of the respective merchant;

an outlet identifier corresponding to an outlet of the respective merchant at which the respective POS terminal is disposed;

payment types corresponding to at least some of the transactions effectuated via the respective POS terminal;

a dollar volume corresponding to at least some of the transactions effectuated via the respective POS terminal;

an average ticket amount corresponding to at least some of the transactions effectuated via the respective POS terminal;

transaction types corresponding to at least some of the transactions effectuated via the respective POS terminal;

or

good-or-service classifications corresponding to at least some of the transactions effectuated via the respective POS terminal.

17. The system of claim 1, wherein the aggregation subsystem is configured to automatically and periodically aggregate the POS datasets from the plurality of POS terminals in the POS network.

18. The system of claim 1, wherein each of the merchant classifiers is selected from one of a set of Merchant Category Codes defined according to a government standard.

19. The system of claim 1, further comprising:

at least a portion of the POS network comprising at least some of the plurality of POS terminals.

20. A method for market reporting according to point-of-sale (POS) data, the system 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 of a plurality of merchant identifiers and at least one of a plurality of merchant classifiers, and each POS terminal being configured to collect transaction data as a function of transactions effectuated via the POS terminal, the POS dataset for each of the POS terminals comprising the terminal data and the transaction data;

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

identifying a market dataset from the aggregated POS data, the market dataset comprising the POS datasets corresponding to the timeframe and to POS terminals having terminal data indicating a merchant classifier corresponding to the market;

calculating a reliable portion of the market dataset as a function of the POS datasets in the market dataset;

generating market trend data as a function of the reliable portion of the market dataset; and

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

21. The method of claim 20, wherein:

the reporting request is received from a user device; and

outputting the graphical report data comprises configuring the graphical report data for display on the user device and communicating the graphical report data over a network to the user device.

22. The method of claim 20, further comprising:

analyzing the market trend as a function of the reliable portion of the market dataset to identify a trend event indicating a statistically significant features of the market trend; and

configuring the graphical report data to graphically indicate the trend event.

23. The method of claim 22, further comprising:

receiving supplemental reporting data from an analyst in response to identifying the trend event,

wherein the graphical report data comprises the supplemental reporting data.

24. The method of claim 22, further comprising:

calculating, for each merchant identifier associated with at least one of the POS datasets from the reliable portion of the market dataset, a merchant contribution representing a contributing effect on the trend event attributable to the POS datasets associated with the merchant identifier; and

generating a merchant driver by identifying at least one merchant contribution as indicating a statistically significant contributing effect on the trend event attributable to the corresponding merchant identifier.

25. The method of claim 24, wherein the graphical report data comprises an indication of the merchant driver.

26. The method of claim 22, further comprising:

retrieving macroeconomic data corresponding to at least a portion of the timeframe; and

determining a correlation between the trend event and the macroeconomic data,

wherein the graphical report data comprises an indication of the correlation.

27. The method of claim 22, further comprising:

retrieving seasonality data corresponding to at least a portion of the timeframe; and

determining a correlation between the trend event and the seasonality data,

wherein the graphical report data comprises an indication of the correlation.

28. The method of claim 22, further comprising:

retrieving social data indicating social trends or events occurring during at least a portion of the timeframe affecting at least one of the merchant identifiers associated with at least one of the POS datasets from the reliable portion of the market dataset; and

determining a correlation between the trend event and the social data, such that the correlation between the trend event and the social data indicates an effect on the trend event attributable to the social trends or events affecting at least one of the merchant identifiers,

wherein the graphical report data comprises an indication of the correlation.

29. The method of claim 20, wherein calculating the reliable portion of the market dataset comprises:

determining, for each of the POS datasets, transaction dates corresponding to the transaction data for the transactions effectuated via the respective POS terminal, such that the reliable portion of the market dataset includes only the POS datasets comprising transaction data for transactions having transaction dates occurring substantially over the entire timeframe.

30. The method of claim 20, wherein calculating the reliable portion of the market dataset comprises:

identifying a POS baseline corresponding to a subset of the POS datasets in the market dataset; and

calculating a statistical variation between the POS baseline and the subset of the POS datasets, such that the subset of POS datasets is added to the reliable portion of the market dataset only when the statistical variation is less than a threshold level.

31. A machine-readable medium for market reporting according to point-of-sale (POS) data, the machine-readable medium having instructions stored thereon which, when executed by a machine, cause the machine to perform steps comprising:

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

identifying a market dataset from POS datasets aggregated 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 of a plurality of merchant identifiers and at least one of a plurality of merchant classifiers, and each POS terminal being configured to collect transaction data as a function of transactions effectuated via the POS terminal, the POS dataset for each of the POS terminals comprising the terminal data and the transaction data, the market dataset comprising the POS datasets corresponding to the timeframe and to POS terminals having terminal data indicating a merchant classifier corresponding to the market;

calculating a reliable portion of the market dataset as a function of the POS datasets in the market dataset;

generating market trend data as a function of the reliable portion of the market dataset; and

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

32. The machine-readable medium of claim 31, the instructions stored thereon, when executed by the machine, causing the machine to perform steps further comprising:

analyzing the market trend as a function of the reliable portion of the market dataset to identify a trend event indicating a statistically significant feature of the market trend; and

configuring the graphical report data to graphically indicate the trend event.

33. The machine-readable medium of claim 32, the instructions stored thereon, when executed by the machine, causing the machine to perform steps further comprising:

calculating, for each merchant identifier associated with at least one of the POS datasets from the reliable portion of the market dataset, a merchant contribution representing a contributing effect on the trend event attributable to the POS datasets associated with the merchant identifier; and

generating a merchant driver by identifying at least one merchant contribution as indicating a statistically significant contributing effect on the trend event attributable to the corresponding merchant identifier.

34. The machine-readable medium of claim 32, the instructions stored thereon, when executed by the machine, causing the machine to perform steps further comprising:

retrieving macroeconomic data corresponding to at least a portion of the timeframe; and

determining a correlation between the trend event and the macroeconomic data,

wherein the graphical report data comprises an indication of the correlation.

35. The machine-readable medium of claim 32, the instructions stored thereon, when executed by the machine, causing the machine to perform steps further comprising:

retrieving seasonality data corresponding to at least a portion of the timeframe; and

determining a correlation between the trend event and the seasonality data,

wherein the graphical report data comprises an indication of the correlation.

36. The machine-readable medium of claim 32, the instructions stored thereon, when executed by the machine, causing the machine to perform steps further comprising:

retrieving social data indicating social trends or events occurring during at least a portion of the timeframe affecting at least one of the merchant identifiers associated with at least one of the POS datasets from the reliable portion of the market dataset; and

determining a correlation between the trend event and the social data, such that the correlation between the trend event and the social data indicates an effect on the trend event attributable to the social trends or events affecting at least one of the merchant identifiers,

wherein the graphical report data comprises an indication of the correlation.

37. The machine-readable medium of claim 31, the instructions stored thereon, when executed by the machine, causing the machine to perform steps further comprising:

determining, for each of the POS datasets, transaction dates corresponding to the transaction data for the transactions effectuated via the respective POS terminal, such that the reliable portion of the market dataset includes only the POS datasets comprising transaction data for transactions having transaction dates occurring substantially over the entire timeframe.