Systems and methods for use in forecasting changes in sales

Abstract

In some embodiments, apparatuses and methods are provided to forecast expected sales and/or demand for one or more products at one or more retail shopping facilities. Some embodiments include systems to forecast retail sales, comprising: a network transceiver; a forecast control circuit; and a memory storing computer instructions executed by the control circuit that receives, via the network transceiver from at least one third party service unassociated with retail shopping facilities and accessed over a distributed computer network, reservation data corresponding with people traveling during a future period of time to a geographic region that is within a threshold distance from a first retail shopping facility; and forecasts expected sales, during the future period of time associated with the reservation data, of at least a first set of products at the first retail shopping facility as a function of the reservation data.

What is claimed is: 
     
         1 . A system to forecast retail sales, comprising:
 a network transceiver coupled to communicate over a distributed computer network;   a forecast control circuit; and   a memory coupled to the forecast control circuit and storing computer instructions that when executed by the forecast control circuit cause the forecast control circuit to:   access reservation data corresponding with people traveling during a future period of time via the network transceiver;   access, by the forecast control circuit via the distributed computer network, additional data from multiple different and geographically distributed Internet of Things;   access a first set of rules to be applied to the reservation data;   apply the first set of rules to the reservation data to identify a first retail shopping facility corresponding to a forecasted geographic region corresponding to a subset of the reservation data;   access a second set of rules and apply the second set of rules to identify a portion of the additional data obtained from the Internet of Things that are associated with the geographic region;   access a third set of rules applied in forecasting sales;   apply the third set of rules to identify historic actual sales of at least a first set of products during historic periods of time having historic reservation data that corresponds to the subset of the reservation data, and forecast expected sales, during the future period of time associated with the reservation data, of at least the first set of products, including at least expected sales of a first product, at the first retail shopping facility as a function of the subset of the reservation data, the portion of the additional data and the historic actual sales; and   an inventory system communicatively coupled over the distributed computer network to access the forecasted expected sales during the future period of time and comprising memory storing inventory information of available inventory of the first retail shopping facility, wherein the inventory system receives the forecasted expected sales, accesses an inventory set of rules, applies the inventory set of rules and causes an adjustment to an order of the first product of the first set of products as a function of the expected sales and an adjustment of inventory of the first product at the first retail shopping facility corresponding to the future period of time.   
     
     
         2 . The system of  claim 1 , wherein the forecast control circuit is further configured to define a cluster of multiple retail shopping facilities that are within a threshold distance of the geographic region, and forecasts expected sales of at least the first product at each of the multiple retail shopping facilities of the cluster as a function of the subset of the reservation data. 
     
     
         3 . The system of  claim 1 , wherein the forecast control circuit is further configured to predict an end to a season as a function of the reservation data and causes a change in inventory ordering relative to at least the first retail shopping facility based on the predicted end to the season. 
     
     
         4 . The system of  claim 1 , wherein the inventory system is configured to adjust the inventory of each product of the first set of products during the future period of time as a function of the corresponding forecasted expected sales of a corresponding one of the first set of products. 
     
     
         5 . The system of  claim 4 , wherein the inventory system is configured to modify a sales strategy of at least the first product of the first set of products based on the expected sales of the first product and the inventory information corresponding to at least the first product. 
     
     
         6 . The system of  claim 1 , further comprising:
 a worker scheduling circuit coupled with the forecast control circuit to receive the expected sales, wherein the worker scheduling circuit is configured to adjust numbers of workers scheduled during at least a portion of the future period associated with the forecasted expected sales.   
     
     
         7 . The system of  claim 1 , wherein the reservation data comprises cancellation data of previous reservations, and the forecast control circuit in forecasting the expected sales reduces previously forecasted expected sales as a function of the cancellation data. 
     
     
         8 . The system of  claim 7 , wherein the forecast control circuit in receiving the reservation data is configured to receive, via the network transceiver from at least one third party service unassociated with retail shopping facilities and accessed over the distributed computer network, reservation data corresponding with the people traveling during the future period of time to the geographic region. 
     
     
         9 . The system of  claim 1 , wherein the forecast control circuit is further configured to determine based on the reservation data a date of an expected event, and incorporate the event into an events schedule. 
     
     
         10 . The system of  claim 1 , wherein the forecast control circuit is further configured to access a fourth set of rules and apply the fourth set of rules to the reservation data and the portion of the additional data, confirm one or more reservations of the reservation data based on the portion of the additional data received from one or more of the Internet of Things, and identify the historic periods of time having similar historic reservation data to the subset of the reservation data corresponding to the geographic region. 
     
     
         11 . The system of  claim 1 , wherein the forecast control circuit is further configured to continue to receive, prior to the future period of time, further reservation data and continue to track and evaluate the further reservation data over time to make adjustments to previous forecasted expected sales for the future period of time. 
     
     
         12 . The system of  claim 1 , wherein the forecast control circuit in forecasting the expected sales of at least the first product is configured to receive sales trend information for the first product proportionally adjust the historic actual sales of the first product to provide adjusted historic sales of the first product, and forecast the expected sales, during the future period of time, of at least the first product at the first retail shopping facility as a function of the adjusted historic sales of the first product. 
     
     
         13 . A method to forecast retail sales, comprising:
 by a forecast control circuit:   accessing reservation data corresponding with people traveling during a future period of time accessed over a distributed computer network;   accessing, by the forecast control circuit via the distributed computer network, additional data from multiple different and geographically distributed Internet of Things;   accessing a first set of rules to be applied to the reservation data;   applying the first set of rules to the reservation data to identify a first retail shopping facility corresponding to a forecasted geographic region corresponding to a subset of the reservation data;   accessing a second set of rules and applying the second set of rules to identify a portion of the additional data obtained from the Internet of Things that are associated with the geographic region;   accessing a third set of rules applied in forecasting sales;   applying the third set of rules to identify historic actual sales of at least a first set of products during historic periods of time having historic reservation data that corresponds to the subset of the reservation data, and forecasting expected sales, during the future period of time associated with the reservation data, of at least the first set of products, including at least expected sales of a first product, at the first retail shopping facility as a function of the subset of the reservation data, the portion of the additional data and the historic actual sales; and   accessing an inventory set of rules, applying the inventory set of rules and adjusting an order of the first product of the first set of products as a function of the expected sales and an adjustment of inventory of the first product at the first retail shopping facility corresponding to the future period of time.   
     
     
         14 . The method of  claim 13 , further comprises:
 defining a cluster of multiple retail shopping facilities that are within a threshold distance of the geographic region; and   wherein the forecasting, comprises forecasting expected sales of at least the first product at each of the multiple retail shopping facilities of the cluster as a function of the subset of the reservation data.   
     
     
         15 . The method of  claim 13 , further comprising:
 predicting an end to a season as a function of the reservation data; and   causing a change in inventory ordering relative to at least the first retail shopping facility based on the predicted end to the season.   
     
     
         16 . The method of  claim 13 , further comprising:
 maintaining the inventory information of available inventory of at least the first retail shopping facility; and   adjusting the inventory of each product of the first set of products during the future period of time as a function of the corresponding forecasted expected sales of a corresponding one of the first set of products.   
     
     
         17 . The method of  claim 16 , further comprising:
 maintaining inventory information of an inventory of products for sale at the first retail shopping facility; and   modifying a sales strategy of at least the first product of the first set of products based on the expected sales of the first product and the inventory information corresponding to at least the first product.   
     
     
         18 . The method of  claim 13 , further comprising:
 receiving, at a worker scheduling circuit, the expected sales; and   adjusting numbers of workers scheduled during a portion of the future period of time associated with the forecasted expected sales.   
     
     
         19 . The method of  claim 13 , wherein the receiving the reservation data comprises receiving cancellation data of previous reservations; and
 the forecasting the expected sales comprises reducing previously forecasted expected sales as a function of the cancellation data.   
     
     
         20 . The method of  claim 11 , further comprising:
 accessing a fourth set of rules and applying the fourth set of rules to the reservation data and the portion of the additional data, confirming one or more reservations of the reservation data based on the portion of the additional data received from one or more of the Internet of Things, and identifying the historic periods of time having similar historic reservation data to the subset of the reservation data corresponding to the geographic region.