Method, apparatus, and computer program product for auto-replenishing an inventory of promotions

1. A computer-implemented method for improving consumer traffic attributed to an inventory of promotions offered for sale at a given time via an inventory module of a promotional system, wherein the method is implemented by an auto-replenishment engine for auto-replenishing the inventory of promotions, the method comprising:

with at least a processor of the promotional system, accessing scheduling data relating to scheduled services and availability of a provider;

with the processor, generating target data from the accessed scheduling data by applying the scheduled services and the availability to calculate a target number of consumers to redeem a promotion at the provider within a predetermined period of time;

accessing the inventory module, configured to maintain and provide, in a database, a current inventory of promotions and outstanding promotions available via the promotional system for redemption at the provider, wherein the promotions and the outstanding promotions have associated promotional value and cost, and the outstanding promotions have been purchased by consumers and have associated service types;

accessing a redemption analytics module of the promotional system, wherein the redemption analytics module is configured to generate, with the processor, a redemption curve of historical redemptions by identifying a promotion category, inputting data relating to historical promotions having a similar promotion category, and calculating a redemption ratio;

fitting the redemption curve of the historical redemptions by multiplying the redemption ratio for each time period by the sum of the current inventory and the outstanding promotions such that the fitted redemption curve reflects expected redemptions during respective time periods between the respective purchase dates and expiration dates;

calculating, with an auto-replenish calculator module implemented by at least the processor, a number of promotions to be made available for purchase and redeemable at the provider for particular associated services types, with which to replenishment the inventory, and respective replenishment dates of the number of promotions by incorporating the target number into the fit redemption curve of the historical redemptions reflecting the redemption rates and the redemption ratios input from the redemption analytics module; and

transmitting data to the inventory module such that the inventory module causes an increase in the current inventory of promotions in the database redeemable at the provider and for sale via the promotional system on the respective replenishment dates.

2. The method of claim 1 , wherein generating the redemption curve of historical redemptions further comprises:

identifying the promotion category based on service types, the associated promotional value and the cost for the current inventory of promotions;

inputting data relating to outstanding historical promotions in an instance in which the historical promotions have a similar promotion category to the identified promotion category; and

calculating the redemption ratio and a redemption rate for the provider for a plurality of time periods, such that the redemption ratio is a percentage of historical redemptions relative to outstanding historical promotions and the respective historical expiration dates, and the redemption rate is as a rate per unit of time at which purchased promotions are redeemed.

3. The method of claim 1 , further comprising:

generating predicted future redemption rates by processing the scheduling data, the scheduled services, and the associated service types.

4. The method of claim 1 , further comprising:

determining seasonality of associated service types and incorporating the seasonality of the associated services types into the fit redemption curve.

5. The method of claim 1 , further comprising:

calculating an estimate of repeat consumers to the provider following redemption of promotions, wherein the number of promotions and the respective replenishment dates are calculated further based on the calculated estimate of repeat consumers.

6. The method of claim 1 , further comprising:

processing historical data relating to the associated service types to fit the redemption curve for promotions having similar service types.

7. An apparatus for improving consumer traffic attributed to an inventory of promotions offered for sale at a given time via an inventory module of a promotional system, wherein the apparatus is configured for auto-replenishing the inventory of promotions, the apparatus comprising an auto-replenishment engine configure to:

with at least a processor, access scheduling data relating to scheduled services and availability of a provider;

with the processor, generate target data from the accessed scheduling data by applying the scheduled services and the availability to calculate a target number of consumers to redeem a promotion at the provider within a predetermined period of time;

access the inventory module, configured to maintain and provide, in a database, a current inventory of promotions and outstanding promotions available via the promotional system for redemption at the provider, wherein the promotions and the outstanding promotions have associated promotional value and cost, and the outstanding promotions have been purchased by consumers and have associated service types;

access a redemption analytics module of the promotional system, wherein the redemption analytics module is configured to generate, with the processor, a redemption curve of historical redemptions by identifying a promotion category, inputting data relating to historical promotions having a similar promotion category, and calculating a redemption ratio;

fit the redemption curve of the historical redemptions by multiplying the redemption ratio for each time period by the sum of the current inventory and the outstanding promotions such that the fitted redemption curve reflects expected redemptions during respective time periods between the respective purchase dates and expiration dates;

calculate, with an auto-replenish calculator module implemented by at least the processor, a number of promotions to be made available for purchase and redeemable at the provider for particular associated services types, with which to replenishment the inventory and respective replenishment dates of the number of promotions by incorporating the target number into the fit redemption curve of the historical redemptions reflecting the redemption rates and the redemption ratios input from the redemption analytics module; and

transmit data to the inventory module such that the inventory module causes an increase in the current inventory of promotions in the database redeemable at the provider and for sale via the promotional system on the respective replenishment dates.

8. The apparatus of claim 7 , wherein generating the redemption curve of historical redemptions further comprises:

identifying the promotion category based on service types, the associated promotional value and the cost for the current inventory of promotions;

inputting data relating to outstanding historical promotions in an instance in which the historical promotions have a similar promotion category to the identified promotion category; and

calculating the redemption ratio and a redemption rate for the provider for a plurality of time periods, such that the redemption ratio is a percentage of historical redemptions relative to outstanding historical promotions and the respective historical expiration dates, and the redemption rate is as a rate per unit of time at which purchased promotions are redeemed.

9. The apparatus of claim 7 , wherein the auto-replenishment engine is further configured to:

generate predicted future redemption rates by processing the scheduling data, the scheduled services, and the associated service types.

10. The apparatus of claim 7 , wherein the auto-replenishment engine is further configured to:

determine seasonality of associated service types and incorporating the seasonality of the associated services types into the fit redemption curve.

11. The apparatus of claim 7 , wherein the auto-replenishment engine is further configured to:

calculate an estimate of repeat consumers to the provider following redemption of promotions, wherein the number of promotions and the respective replenishment dates are calculated further based on the calculated estimate of repeat consumers.

12. The apparatus of claim 7 , wherein the auto-replenishment engine is further configured to:

process historical data relating to the associated service types to fit the redemption curve for promotions having similar service types.

13. A computer program product for improving consumer traffic attributed to an inventory of promotions offered for sale at a given time via an inventory module of a promotional system by auto-replenishing the inventory of promotions, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instructions are configured for:

with at least a processor, accessing scheduling data relating to scheduled services and availability of a provider;

with the processor, generating target data from the accessed scheduling data by applying the scheduled services and the availability to calculate a target number of consumers to redeem a promotion at the provider within a predetermined period of time;

accessing the inventory module, configured to maintain and provide, in a database, a current inventory of promotions and outstanding promotions available via the promotional system for redemption at the provider, wherein the promotions and the outstanding promotions have associated promotional value and cost, and the outstanding promotions have been purchased by consumers and have associated service types;

accessing a redemption analytics module the promotional system, wherein the redemption analytics module is configured to generate, with the processor, a redemption curve of historical redemptions by identifying a promotion category, inputting data relating to historical promotions having a similar promotion category, and calculating a redemption ratio;

fitting the redemption curve of the historical redemptions by multiplying the redemption ratio for each time period by the sum of the current inventory and the outstanding promotions such that the fitted redemption curve reflects expected redemptions during respective time periods between the respective purchase dates and expiration dates;

calculating, with an auto-replenish calculator module implemented by at least the processor, a number of promotions to be made available for purchase and redeemable at the provider for particular associated services types, with which to replenishment the inventory and respective replenishment dates of the number of promotions by incorporating the target number into the fit redemption curve of the historical redemptions reflecting the redemption rates and the redemption ratios input from the redemption analytics module; and

transmitting data to the inventory module such that the inventory module causes an increase in the current inventory of promotions in the database redeemable at the provider and for sale via the promotional system on the respective replenishment dates.

14. The computer program product of claim 13 , wherein generating the redemption curve of historical redemptions further comprises:

identifying the promotion category based on service types, the associated promotional value and the cost for the current inventory of promotions;

inputting the data relating to outstanding historical promotions in an instance in which the historical promotions have a similar promotion category to the identified promotion category; and

calculating the redemption ratio and a redemption rate for the provider for a plurality of time periods, such that the redemption ratio is a percentage of historical redemptions relative to outstanding historical promotions and the respective historical expiration dates, and the redemption rate is as a rate per unit of time at which purchased promotions are redeemed.

15. The computer program product of claim 13 , where the computer-executable program code instructions are further configured for:

generating predicted future redemption rates by processing the scheduling data, the scheduled services, and the associated service types.

16. The computer program product of claim 13 , where the computer-executable program code instructions are further configured for:

determining seasonality of associated service types and incorporating the seasonality of the associated services types into the fit redemption curve.

17. The computer program product of claim 13 , where the computer-executable program code instructions are further configured for:

calculating an estimate of repeat consumers to the provider following redemption of promotions, wherein the number of promotions and the respective replenishment dates are calculated further based on the calculated estimate of repeat consumers.

18. The computer program product of claim 13 , where the computer-executable program code instructions are further configured for:

processing historical data relating to the associated service types to fit the redemption curve for promotions having similar service types.