Method, apparatus, and computer program product for facilitating dynamic pricing

An apparatus for programmatically facilitating dynamic pricing of a promotion, in real-time, based on one or more factors by adjusting a first promotion price of a price adjustable promotion to a second promotion price, the apparatus comprising at least a processor, and a memory associated with the processor having computer coded instructions therein, with the computer instructions configured to, when executed by the processor, cause the apparatus to:

• electronically provide, via a communication interface, a plurality of promotions, configured for display on a user interface of a consumer device, the plurality of promotion including the price adjustable promotion at a first promotion price, the price adjustable promotion comprising a plurality of redemption parameters;
• execute an iterative learning model configured to receive, as input, market reaction data, and output an updated promotion price,
• wherein the execution of the iterative learning model comprises:
• collect market reaction data, indicating a volume and a velocity at which the price adjustable promotion sells;
• identify the price adjustable promotion from the plurality of promotions by determining eligibility for a price adjustment, the price adjustable promotion having (i) the first promotion price, (ii) a forecasted demand that provides an indication of a promotion inventory exhaustion period and a plurality of redemption parameters that comprise at least a promotional period, (iii) a promotional value, and (iv) a redemption expiration;
• wherein the determination of the eligibility for the price adjustment comprises:
• determining a probability that the price adjustable promotion will sell out based on the market reaction data, utilizing the iterative learning model;
• comparing a confidence value indicative of the strength of the determined probability that the price adjustable promotion will sell out;
• outputting the forecasted demand for the price adjustable promotion in an instance in which the confidence value satisfies the predetermined revenue threshold;
• and
• determining that the promotion inventory exhaustion period overlaps a next price change time demonstrating that the first promotional price is adjustable prior to an expiration of the promotion inventory exhaustion period, wherein the next price change time defines a next time that the first promotional price can be adjusted and is calculated based on consumer behavior that is tracked in real time;
• utilize the market reaction data to generate, using a processor of a dynamic price calculator module executing on a pricing apparatus, the updated promotion price for the price adjustable promotion by adjusting a previous promotion price based on (i) the forecasted demand, (ii) a remaining inventory of the promotion, and (iii) an estimated revenue;
• electronically provide, via the communication interface, configured for display at the user interface of the consumer device, the price adjustable promotion at the updated promotion price while at least one of the plurality of redemption parameters for the price adjustable promotion remain constant,
• wherein, during a first iteration, the previous promotion price is the first promotion price;
• determine if the price adjustable promotion is sold out;
• and
• in an instance in which the price adjustable promotion is not sold, continue with the execution of the iterative learning model.

A computer program product for programmatically facilitating dynamic pricing of a promotion, in real-time, based on one or more factors by adjusting a first promotion price of a price adjustable promotion to a second promotion price, the computer program product comprising a non-transitory computer readable medium having computer program instructions stored therein, said instructions when executed by a processor:

• electronically providing, via a communication interface, a plurality of promotions, configured for display on a user interface of a consumer device, the plurality of promotion including the price adjustable promotion at a first promotion price, the price adjustable promotion comprising a plurality of redemption parameters;
• executing an iterative learning model configured to receive, as input, market reaction data, and output an updated promotion price,
• wherein the execution of the iterative learning model comprises:
• collecting market reaction data, indicating a volume and a velocity at which the price adjustable promotion sells;
• identifying the price adjustable promotion from the plurality of promotions by determining eligibility for a price adjustment, the price adjustable promotion having (i) the first promotion price, (ii) a forecasted demand that provides an indication of a promotion inventory exhaustion period and a plurality of redemption parameters that comprise at least a promotional period, (iii) a promotional value, and (iv) a redemption expiration;
• wherein the determination of the eligibility for the price adjustment comprises:
• determining a probability that the price adjustable promotion will sell out based on the market reaction data, utilizing the iterative learning model;
• comparing a confidence value indicative of the strength of the determined probability that the price adjustable promotion will sell out;
• outputting the forecasted demand for the price adjustable promotion in an instance in which the confidence value satisfies the predetermined revenue threshold;
• and
• determining that the promotion inventory exhaustion period overlaps a next price change time demonstrating that the first promotional price is adjustable prior to an expiration of the promotion inventory exhaustion period, wherein the next price change time defines a next time that the first promotional price can be adjusted and is calculated based on consumer behavior that is tracked in real time;
• utilizing the market reaction data to generate, using a processor of a dynamic price calculator module executing on a pricing apparatus, the updated promotion price for the price adjustable promotion by adjusting a previous promotion price based on (i) the forecasted demand, (ii) a remaining inventory of the promotion, and (iii) an estimated revenue;
• electronically providing, via the communication interface, configured for display at the user interface of the consumer device, the price adjustable promotion at the updated promotion price while at least one of the plurality of redemption parameters for the price adjustable promotion remain constant,
• wherein, during a first iteration, the previous promotion price is the first promotion price;
• determining if the price adjustable promotion is sold out;
• and
• in an instance in which the price adjustable promotion is not sold, continuing with the execution of the iterative learning model.