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1. (US20190012677) SERVICE CONTRACT RENEWAL LEARNING SYSTEM
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Claims

1. A computer-implemented method comprising:
generating a service contract renewal propensity model for an asset based on historical service contract information associated with the asset;
determining a propensity of a consumer of the asset to renew a service contract between the consumer and a service provider, wherein the determining comprises processing the service contract renewal propensity model based on input asset information and input consumer information associated with the service contract;
determining at least one reminder operation to be performed, from among a plurality of reminder operations, based on the determined propensity of the consumer to renew the service contract; and
outputting information about the determined at least one reminder operation to be performed for display on a display device.
2. The method of claim 1, wherein the input asset information used by the service contract renewal propensity model comprises a geographic location of the asset and features intrinsic to a type of the asset.
3. The method of claim 1, wherein the input consumer information used by the service contract renewal propensity model comprises at least one of a financial status of the consumer, previous renewal history of the consumer, and a number of historical service requests made by the consumer within a predetermined period of time.
4. The method of claim 1, wherein the determined at least one reminder operation to be performed includes dynamically adjusting a period of time between sending reminders for renewing the service contract to the consumer.
5. The method of claim 1, wherein the determined at least one reminder operation to be performed includes generating one or more offers in association with the service contract renewal, and transmitting the one or more offers to the consumer.
6. The method of claim 1, wherein the determined at least one reminder operation to be performed includes determining a period of time before an end of the service contract at which to begin sending reminders to the consumer for renewing the service contract.
7. The method of claim 1, wherein the outputting further comprises outputting a listing of assets associated with the consumer and a point in time at which respective service agreements associated with the assets will be in default, for display on the display device.
8. The method of claim 1, wherein the determining the propensity of the consumer to renew the service contract further comprises determining a propensity of the consumer to be late in renewing the service contract based on the executed service contract renewal propensity model.
9. A computing system comprising:
a processor configured to
generate a service contract renewal propensity model for an asset based on historical service contract information associated with the asset,
determine a propensity of a consumer of the asset to renew a service contract between the consumer and a service provider, wherein the determining comprises processing the service contract renewal propensity model based on input asset information and input consumer information associated with the service contract, and
determine at least one reminder operation to be performed, from among a plurality of reminder operations, based on the determined propensity of the consumer to renew the service contract; and
an output configured to output information about the determined at least one reminder operation to be performed for display on a display device.
10. The computing system of claim 9, wherein the input asset information used by the service contract renewal propensity model comprises a geographic location of the asset and features intrinsic to a type of the asset.
11. The computing system of claim 9, wherein the input consumer information used by the service contract renewal propensity model comprises at least one of a financial status of the consumer, previous renewal history of the consumer, and a number of historical service requests made by the consumer within a predetermined period of time.
12. The computing system of claim 9, wherein the determined at least one reminder operation to be performed by the processor includes dynamically adjusting a period of time between sending reminders for renewing the service contract to the consumer.
13. The computing system of claim 9, wherein the determined at least one reminder operation to be performed by the processor includes generating one or more offers in association with the service contract renewal, and transmitting the one or more offers to the consumer.
14. The computing system of claim 9, wherein the determined at least one reminder operation to be performed by the processor includes determining a period of time before an end of the service contract at which to begin sending reminders to the consumer for renewing the service contract.
15. The computing system of claim 9, wherein the output is further configured to output a listing of assets associated with the consumer and a point in time at which respective service agreements associated with the assets will be in default, for display on the display device.
16. The computing system of claim 9, wherein the processor is further configured to determine a propensity of the consumer to be late in renewing the service contract based on the executed service contract renewal propensity model.
17. A non-transitory computer readable medium having stored therein instructions that when executed cause a computer to perform a method comprising:
generating a service contract renewal propensity model for an asset based on historical service contract information associated with the asset;
determining a propensity of a consumer of the asset to renew a service contract between the consumer and a service provider, wherein the determining comprises processing the service contract renewal propensity model based on input asset information and input consumer information associated with the service contract;
determining at least one reminder operation to be performed, from among a plurality of reminder operations, based on the determined propensity of the consumer to renew the service contract; and
outputting information about the determined at least one reminder operation to be performed for display on a display device.
18. The non-transitory computer readable medium of claim 17, wherein the input asset information used by the service contract renewal propensity model comprises a geographic location of the asset and features intrinsic to a type of the asset.
19. The non-transitory computer readable medium of claim 17, wherein the input consumer information used by the service contract renewal propensity model comprises at least one of a financial status of the consumer, previous renewal history of the consumer, and a number of historical service requests made by the consumer within a predetermined period of time.
20. The non-transitory computer readable medium of claim 17, wherein the determining the propensity of the consumer to renew the service contract further comprises determining a propensity of the consumer to be late in renewing the service contract based on the executed service contract renewal propensity model.