Systems and methods for data analytics and electronic displays thereof to payment facilitators and sub-merchants

1. A computer-implemented method, comprising:

receiving, at an acquirer processor computing system, aggregated transaction data from one or more point of sale terminals operated by the sub-merchant or other sub-merchants associated with the payment facilitator;

sorting the aggregated transaction data using a transaction module of the acquirer processor computing system;

applying, using the transaction module, a weight to each article of sorted aggregated transaction data;

storing, at the acquirer processor computing system, the sorted and weighted aggregated transaction data in a transaction database;

determining, using the acquirer processor computing system, to transmit analytics data associated with the sorted and weighted aggregated transaction data to the sub-merchant, wherein the determining comprises:

providing, at the acquirer processor computing system, the sorted and weighted aggregated transaction data from the transaction database as an input to a machine learning model that is trained to predict whether the sorted and weighted aggregated transaction data is relevant to the sub-merchant based on geographical data associated with the sub-merchant; and

receiving, as an output from the machine learning model, an indication to transmit the analytics data associated with at least a subset of the sorted and weighted aggregated transaction data to the sub-merchant;

transmitting the analytics data from the acquirer processor computing system to a sub-merchant computing system associated with the sub-merchant;

determining, by the acquirer processing computing system, whether the analytics data is capable of being displayed on an electronic dashboard of a screen of the sub-merchant computing system, wherein the determining comprises:

identifying, by analyzing blocks of data received from the sub-merchant computing system, a first percentage of regions of the electronic dashboard occupied by existing content; and

identifying that at least a subset of the analytics data is capable of being displayed in a region associated with a second percentage of regions of the electronic dashboard unoccupied by any content; and

presenting, responsive to determining that the analytics data is capable of being displayed on the electronic dashboard, at least the subset of the analytics data in the region on the electronic dashboard.

2. The computer-implemented method of claim 1 , wherein the aggregated transaction data received at the one or more point of sale terminals includes at least one of: personally identifiable information, payment vehicle data, customer data, geographic location data, product data, service data, merchant data, and sub-merchant data.

3. The computer-implemented method of claim 1 , wherein the analytics data includes a unique sub-merchant identifier and a unique payment facilitator identifier.

4. The computer-implemented method of claim 1 , wherein the analytics data is provided by the acquirer processing computer system dynamically.

5. The computer-implemented method of claim, wherein the analytics data presented on the electronic dashboard further includes at least one of: a demographics report and a notification or a financial report.

6. A computer system, comprising:

a memory having processor-readable instructions stored therein; and

a processor configured to access the memory and execute the processor-readable instructions, which when executed by the processor configures the processor to perform plurality of functions, including functions for:

receiving, at the computer system, aggregated transaction data from one or more point of sale terminals operated by the sub-merchant or other sub-merchants associated with the payment facilitator;

sorting the aggregated transaction data using a transaction module of the acquirer processor computing system;

applying, using the transaction module, a weight to each article of sorted aggregated transaction data;

storing, at the computer system, the sorted and weighted aggregated transaction data in a transaction database;

determining, using the computer system, to transmit analytics data associated with the sorted and weighted aggregated transaction data to the sub-merchant, wherein the determining comprises:

providing, at the computer system, the sorted and weighted aggregated transaction data from the transaction database as an input to a machine learning model that is trained to predict whether the sorted and weighted aggregated transaction data is relevant to the sub-merchant based on geographical data associated with the sub-merchant; and

receiving, as an output from the machine learning model, an indication to transmit the analytics data associated with at least a subset of the sorted and weighted aggregated transaction data to the sub-merchant;

transmitting the analytics data from the acquirer processor computing system to a sub-merchant computing system associated with the sub-merchant;

determining, by the computer system, whether the analytics data is capable of being displayed on an electronic dashboard of a screen of the sub-merchant computing system, wherein the determining comprises:

identifying, by analyzing blocks of data received from the sub-merchant computing system, a first percentage of regions of the electronic dashboard occupied by existing content; and

identifying that at least a subset of the analytics data is capable of being displayed in a region associated with a second percentage of regions of the electronic dashboard unoccupied by any content; and

presenting, responsive to determining that the analytics data is capable of being displayed on the electronic dashboard, at least the subset of the analytics data in the region on the electronic dashboard.

7. The computer system of claim 6 , wherein the aggregated transaction data received at the one or more point of sale terminals includes at least one of: personally identifiable information, payment vehicle data, customer data, geographic location data, product data, service data, merchant data, and sub-merchant data.

8. The computer system of claim 6 , wherein the analytics data includes a unique sub-merchant identifier and a unique payment facilitator identifier.

9. The computer system of claim 6 , wherein the analytics data presented on the electronic dashboard further includes at least one of: a demographics report and a notification or a financial report.

10. A non-transitory computer-readable medium, comprising:

a memory having processor-readable instructions stored therein, to direct a processor for:

receiving, at an acquirer processor computing system, aggregated transaction data from one or more point of sale terminals operated by the sub-merchant or other sub-merchants associated with the payment facilitator;

sorting the aggregated transaction data using a transaction module of the acquirer processor computing system;

applying, using the transaction module, a weight to each article of sorted aggregated transaction data;

storing, at the acquirer processor computing system, the sorted and weighted aggregated transaction data in a transaction database;

determining, using the acquirer processor computing system, to transmit analytics data associated with the sorted and weighted aggregated transaction data to the sub-merchant, wherein the determining comprises:

providing, at the acquirer processor computing system, the sorted and weighted aggregated transaction data from the transaction database as an input to a machine learning model that is trained to predict whether the sorted and weighted aggregated transaction data is relevant to the sub-merchant based on geographical data associated with the sub-merchant; and

receiving, as an output from the machine learning model, an indication to transmit the analytics data associated with at least a subset of the sorted and weighted aggregated transaction data to the sub-merchant;

transmitting the analytics data from the acquirer processor computing system to a sub-merchant computing system associated with the sub-merchant;

determining, by the acquirer processing computing system, whether the analytics data is capable of being displayed on an electronic dashboard of a screen of the sub-merchant computing system, wherein the determining comprises:

identifying, by analyzing blocks of data received from the sub-merchant computing system, a first percentage of regions of the electronic dashboard occupied by existing content; and

identifying that at least a subset of the analytics data is capable of being displayed in a region associated with a second percentage of regions of the electronic dashboard unoccupied by any content; and

presenting, responsive to determining that the analytics data is capable of being displayed on the electronic dashboard, the analytics data in the region on the electronic dashboard.

11. The non-transitory computer-readable medium of claim 10 , wherein the aggregated transaction data received at the one or more point of sale terminals includes at least one of: personally identifiable information, payment vehicle data, customer data, geographic location data, product data, service data, merchant data, and sub-merchant data.