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US 2021/0201241 A1Published application
Methodology and system for optimizing communications in dynamic lightweight personalized analytics
OwnerSandra K. JOHNSONinventor
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Abstract
An embodiment of the present invention is directed to a feedback-based system and methodology for dynamically selecting communication messages, social media data, support data, etc. (denoted data) in evaluating dynamic lightweight personalized analytics (DLPA). Disclosed embodiments include a process for optimizing the key performance indicators (KPIs) used in measuring success by dynamically selecting the type, size, etc. of data leveraged by DLPA. This facilitates a small memory footprint and optimal computation when making smart, customized suggestions to users.
Claims20
A system for dynamically optimizing communication data relating to dynamic lightweight personalized analytics (DLPA), the system comprising:
- an interface that receives one or more inputs via an enterprise payments services bus;
- a data store that stores and manages arrays of data structures comprising key performance indicators (KPIs), DLPA metrics and support data;
- and
- a dynamic lightweight personalized analytics engine comprising a computer processor and coupled to the data store and the interface, the computer processor configured to perform the steps of:
- receiving one or more customer parameters and remittance trends, wherein the one or more customer parameters comprise social media data, support data and communications data;
- accessing, via a customer account database, one or more key performance indicators (KPIs);
- accessing one or more DLPA metrics;
- wherein the DLPA metrics are impacted by one or more responses to a customer remittance suggestion;
- responsive to the KPI and DLPA metrics, adjusting a size of a data array for a predetermined time window for an individual customer;
- the step of adjusting comprising:
- comparing an initial test period with a count trigger;
- calculating a new set of values for KPIs and one or more impact metrics for the initial test period;
- determining whether an impact metric is greater than or equal to a metric threshold;
- if the impact metric is greater than or equal to the metric threshold, then increasing a priority of recommendation acceptance rate (RAR) or recommendation impact (RI) and increasing the size of the data array;
- if the impact metric is less than the metric threshold, then decreasing a metric count and decreasing a priority of recommendation acceptance rate (RAR) or recommendation impact (RI) and decreasing the size of the data array;
- dynamically processing a plurality of transaction data based on the one or more adjusted at least one array to achieve memory conservation and optimal computation;
- based on the adjusting step, generating a set of remittance suggestions and financial suggestions;
- and
- communicating the set of remittance suggestions and financial suggestions.
16 more elements
A method for dynamically optimizing communication data relating to dynamic lightweight personalized analytics (DLPA), the method comprising the steps of:
- receiving one or more customer parameters and remittance trends, wherein the one or more customer parameters comprise social media data, support data and communications data;
- accessing, via a customer account database, one or more key performance indicators (KPIs);
- accessing one or more DLPA metrics;
- wherein the DLPA metrics are impacted by one or more responses to a customer remittance suggestion;
- responsive to the KPI and DLPA metrics, adjusting a size of a data array for a predetermined time window for an individual customer;
- the step of adjusting comprising:
- comparing an initial test period with a count trigger;
- calculating a new set of values for KPIs and one or more impact metrics for the initial test period;
- determining whether an impact metric is greater than or equal to a metric threshold;
- if the impact metric is greater than or equal to the metric threshold, then increasing a priority of recommendation acceptance rate (RAR) or recommendation impact (RI) and increasing the size of the data array;
- if the impact metric is less than the metric threshold, then decreasing a metric count and decreasing a priority of recommendation acceptance rate (RAR) or recommendation impact (RI) and decreasing the size of the data array;
- dynamically processing a plurality of transaction data based on the one or more adjusted at least one array to achieve memory conservation and optimal computation;
- based on the adjusting step, generating a set of remittance suggestions and financial suggestions;
- and
- communicating the set of remittance suggestions and financial suggestions.
12 more elements
A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out steps of:
- receiving one or more customer parameters and remittance trends, wherein the one or more customer parameters comprise social media data, support data and communications data;
- accessing, via a customer account database, one or more key performance indicators (KPIs);
- accessing one or more DLPA metrics;
- wherein the DLPA metrics are impacted by one or more responses to a customer remittance suggestion;
- responsive to the KPI and DLPA metrics, adjusting a size of a data array for a predetermined time window for an individual customer;
- the step of adjusting comprising:
- comparing an initial test period with a count trigger;
- calculating a new set of values for KPIs and one or more impact metrics for the initial test period;
- determining whether an impact metric is greater than or equal to a metric threshold;
- if the impact metric is greater than or equal to the metric threshold, then increasing a priority of recommendation acceptance rate (RAR) or recommendation impact (RI) and increasing the size of the data array;
- if the impact metric is less than the metric threshold, then decreasing a metric count and decreasing a priority of recommendation acceptance rate (RAR) or recommendation impact (RI) and decreasing the size of the data array;
- dynamically processing a plurality of transaction data based on the one or more adjusted at least one array to achieve memory conservation and optimal computation;
- based on the adjusting step, generating a set of remittance suggestions and financial suggestions;
- and
- communicating the set of remittance suggestions and financial suggestions.
12 more elements
Dependencies are inferred from the claim text.