Booking Availability Engine

A method of generating a predicted booking limit for a promotion and marketing service relating to a service associated with a merchant for selective booking by a consumer via the promotion and marketing service and at least one external booking service, the method comprising:

• determining, by a promotional server of the promotion and marketing service, an initial predicted booking limit for one or more time slots relating to a service associated with a merchant, the one or more time slots defining a time duration during which a promotion offered by the promotion and marketing service for the service associated with the merchant can be redeemed for performance of the service associated with the merchant, wherein the initial predicted booking limit is defined by a predicted total number of bookings for the service associated with the merchant, the predicted total number of bookings including a first portion of predicted bookings corresponding to promotion and marketing service bookings made through the promotion and marketing service, and a second portion of predicted bookings corresponding to external bookings that are made outside of the promotion and marketing service;
• querying, by the promotional server, a promotion system database associated with the promotional server to retrieve promotional historical data associated with the promotion and marketing service;
• calculating, by the promotional server, based at least in part on the promotional historical data retrieved from the promotion system database, a predicted external bookings value defined by the second portion of predicted bookings corresponding to external bookings that are made outside of the promotion and marketing service for each time slot in the set of time slots using an iterative reinforcement learning technique and based on an empirical cumulative density function;
• and
• determining, by the promotional server, using the iterative reinforcement learning technique, a predicted booking limit defined by the first portion of predicted bookings corresponding to promotion and marketing service bookings made through the promotion and marketing service for each time slot in the set of time slots based on the calculated predicted external bookings value for the time slot and the initial predicted booking limit for the time slot.

An apparatus for generating a predicted booking limit for a promotion and marketing service relating to a service associated with a merchant for selective booking by a consumer via the promotion and marketing service and at least one external booking service, the apparatus comprising a processor and a memory, the memory storing computer program code that, when executed by the processor, causes the apparatus to:

• determine, by a promotional server of the promotion and marketing service, an initial predicted booking limit for one or more time slots relating to a service associated with a merchant, the one or more time slots defining a time duration during which a promotion offered by the promotion and marketing service for the service associated with the merchant can be redeemed for performance of the service associated with the merchant, wherein the initial predicted booking limit is defined by a predicted total number of bookings for the service associated with the merchant, the predicted total number of bookings including a first portion of predicted bookings corresponding to promotion and marketing service bookings made through the promotion and marketing service, and a second portion of predicted bookings corresponding to external bookings that are made outside of the promotion and marketing service;
• querying, by a booking optimization module of the promotional server, a promotion system database associated with the promotional server to retrieve promotional historical data associated with the promotion and marketing service;
• calculate, by the promotional server, based at least in part on the promotional historical data retrieved from the promotion system database, a predicted external bookings value defined by the second portion of predicted bookings corresponding to external bookings that are made outside of the promotion and marketing service for each time slot in the set of time slots using an iterative reinforcement learning technique and based on an empirical cumulative density function;
• and
• determine, by the promotional server, using the iterative reinforcement learning technique, a predicted booking limit defined by the first portion of predicted bookings corresponding to promotion and marketing service bookings made through the promotion and marketing service for each time slot in the set of time slots based on the calculated predicted external bookings value for the time slot and the initial predicted booking limit for the time slot.

A computer program product for generating a predicted booking limit for a promotion and marketing service relating to a service associated with a merchant for selective booking by a consumer via the promotion and marketing service and at least one external booking service comprising a non-transitory computer-readable storage medium storing computer program code that, when executed by a processor of an apparatus, causes the apparatus to:

• determine, by a promotional server of the promotion and marketing service, an initial predicted booking limit for one or more time slots relating to a service associated with a merchant, the one or more time slots defining a time duration during which a promotion offered by the promotion and marketing service for the service associated with the merchant can be redeemed for performance of the service associated with the merchant, wherein the initial predicted booking limit is defined by a predicted total number of bookings for the service associated with the merchant, the predicted total number of bookings including a first portion of predicted bookings corresponding to promotion and marketing service bookings made through the promotion and marketing service, and a second portion of predicted bookings corresponding to external bookings that are made outside of the promotion and marketing service;
• querying, by a booking optimization module of the promotional server, a promotion system database associated with the promotional server to retrieve promotional historical data associated with the promotion and marketing service;
• calculate, by the promotional server, based at least in part on the promotional historical data retrieved from the promotion system database, a predicted external bookings value defined by the second portion of predicted bookings corresponding to external bookings that are made outside of the promotion and marketing service for each time slot in the set of time slots using an iterative reinforcement learning technique and based on an empirical cumulative density function;
• and
• determine, by the promotional server, using the iterative reinforcement learning technique, a predicted booking limit defined by the first portion of predicted bookings corresponding to promotion and marketing service bookings made through the promotion and marketing service for each time slot in the set of time slots based on the calculated predicted external bookings value for the time slot and the initial predicted booking limit for the time slot.