Patent Publication Number: US-2021192373-A1

Title: Determining and executing proactive delivery actions using artificial intelligence

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit of and priority to U.S. Provisional Patent Application 62/949,860, which was filed on Dec. 18, 2019, and is incorporated herein by reference in its entirety. 
    
    
     BACKGROUND 
     Package delivery service providers, (such as the United States Postal Service (USPS), United Parcel Service company (UPS), Federal Express company (FedEX), and the like), maintain customer service systems to provide information and services to package delivery customers (e.g., senders and recipients). Example customer service systems may include web-based tracking information systems, and call centers whereby customers may speak with live customer service representatives for obtaining information and other package delivery related services. For example, a customer may speak with a live customer service representative to receive tracking information for a package (i.e., any item that is being delivered), re-route a package to a different delivery destination, reschedule delivery, modify shipment speed, or modify a service associated with package delivery. 
     SUMMARY 
     In one example aspect a computer-implemented method includes monitoring analytics data for a delivery item; accessing a user profile for a user associated with the delivery item; detecting the occurrence of an event trigger based on the analytics data and the user profile; and executing a proactive mitigating action based on detecting the occurrence of the event trigger. Associated systems and computer program products are also described. 
     In another example aspect, a computer program product includes a computer readable storage medium having program instructions embodied therewith. The program instructions are executable by a computing device to cause the computing device to perform operations including: building a user profile linking a delivery-related action that a user has taken for a delivery item with a set of values from analytics data associated with the delivery item; detecting an occurrence of an event trigger based on values from analytics data of an in-transit delivery item matching the set of values from the user profile, and executing a proactive mitigating action after detecting the occurrence of the event trigger. 
     In another example aspect, a system includes a computer readable memory device including program instructions; a processor, operably connected to the computer readable memory device, that executes the program instructions to perform operations comprising: building a user profile linking a delivery-related action that a user has taken for a delivery item with a set of values from analytics data associated with the delivery item; monitoring analytics data for a delivery item in transit; detecting an occurrence of an event trigger based on values from analytics data of an in-transit delivery item matching the set of values from the user profile; and executing a proactive mitigating action after detecting the occurrence of the event trigger. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  shows an overview of an example implementation and an example network for determining and executing delivery actions using artificial intelligence in accordance with aspects of the present disclosure. 
         FIG. 2  shows an example flowchart of a process for executing a proactive mitigating action based on the occurrence of an event trigger. 
         FIG. 3  illustrates an example implementation for generating and executing a proactive mitigating instruction based on user profile data and package analytics data. 
         FIG. 4  illustrates example components of a device that may be used within environment of  FIG. 1 . 
     
    
    
     DETAILED DESCRIPTION 
     Certain embodiments of the disclosure will hereafter be described with reference to the accompanying drawings, wherein like reference numerals denote like elements. It should be understood, however, that the accompanying drawings illustrate only the various implementations described herein and are not meant to limit the scope of various technologies described herein. The drawings show and describe various embodiments of the current disclosure. 
     Item or package delivery service providers may host customer service call centers whereby customers may speak with live customer service representatives for obtaining information and other package delivery related services, such as rescheduling the delivery of an item or package. The use of live customer service representatives is costly, and may require an extended period of wait time for a customer to reach a live customer service representative, depending on the call volume and number of representatives. This causes inefficient use of resources, including the resources used for missed package deliveries that the recipient customers fail to timely reschedule via live customer service representatives, whether due to wait times or other causes associated with customer service call centers. 
     As noted, redelivery efforts for missed package deliveries are inefficient, burdensome, and costly for a package delivery service provider, including the technical inefficiencies and costs associated with increased sorting machinery usage, increased computer and memory usage, increased delivery vehicle usage, increased call center bandwidth usage, and the like. Accordingly, aspects of the present disclosure may include embodiments that may automatically generate a proactive action(s) that reduces the volume of live customer service activity, including the activity associated with scheduling redeliveries. Additionally, or alternatively, the embodiments described herein may reduce missed delivery attempts and redeliveries by proactively modifying a delivery based on conditions and/or analytics data associated with the delivery. 
     As one illustrative example, the embodiments of systems and/or methods, described herein, may proactively reschedule the delivery of a delivery item (e.g., a package) based on analytics information indicating that a recipient of the package is unavailable to receive the delivery. Additionally, or alternatively, the systems and/or methods may proactively reschedule or redirect a delivery based on historical user profile information indicating that the recipient has a previous pattern of rescheduling or redirecting delivery under certain conditions (e.g., weather conditions on a day of delivery, day of the week of the delivery, time of day of the delivery, based on the recipient&#39;s work schedule, etc.). In some embodiments, changes in delivery estimates (e.g., a delay in delivery or an early delivery) may trigger a proactive mitigating action. In various implementations, rescheduling the delivery of an item may include cancelling the originally scheduled delivery attempt before the attempt occurs, and replacing it with a different, newly scheduled delivery attempt based on attributes such as the various data as described herein. 
     In general, the embodiments of systems and/or methods, described herein, may utilize advanced analytics systems henceforth summarized in the term “artificial intelligence”, leveraging historical data stored in a user profile, and/or rules engines to automatically generate and execute mitigating actions based on package analytics data. As described herein, the proactive mitigating actions may reduce call volume to a call center and the associated usage of call center technical resources, reduce missed deliveries and the associated usage of delivery-related technical resources, and/or improve customer satisfaction. In some embodiments, aspects of the present disclosure may provide a user (e.g., a sender and/or recipient) with an automated system to confirm, deny, or modify an auto-generated proactive action (e.g., confirm, deny, or modify a redelivery instruction, etc.). One who is skilled in the art of artificial intelligence systems will be able to identify other relevant techniques, but these systems could include but are not limited to web-based systems, chatbots, text messaging services. These may be used to notify a user about an auto-generated mitigating action to be proactively taken (e.g., the rescheduling of a delivery). Such systems may also be used to allow the user to confirm, deny, or modify the auto-generated mitigating action. In some embodiments, there may also be partial or fully automated help desk processes in place to support customers. 
     In some embodiments, a user profile may be generated, updated, and maintained over time. The user profile may include information that may be used to calculate, predict, or determine proactive actions that can be taken in response to package analytics data relating to a package delivery. As described herein, the building of a user profile for a user may involve tracking and storing information regarding the user&#39;s calling activity into a call center, the details of calls made to the call center, missed delivery activity, package delivery rescheduling activity, package delivery rerouting activity, the conditions under which package delivery has been missed, rescheduled, and/or rerouted, and the like. In some embodiments, artificial intelligence may be implemented to estimate, interpolate, or determine one or more portions of the user profile based on the user profiles of other similar users. 
     In some embodiments, a proactive mitigation system may access a user profile, monitor package analytics data, and implement artificial intelligence to detect an event that triggers the generation of a proactive action based on the package analytics data and the user profile. Example package analytics data may include information identifying the sender, the recipient, weather conditions along a delivery route of the package, estimated delivery day of the week, estimated delivery time of day, declared value of the package, contents of the package (if shared by the sender), delays or changes in expected delivery, or the like. The user profile may identify the package analytics data or the conditions under which a package delivery has been missed, rescheduled, and/or rerouted. In various implementations, proactive measures and mitigating actions may be taken (e.g., to reschedule a delivery, reroute a delivery, notify the recipient, etc.) based on the package analytics data. Further, the best-suited proactive mitigating action may be taken for the specific user based on the user&#39;s user profile indicating the delivery actions the user has taken previously under certain conditions. 
     Embodiments of the disclosure may include a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure. 
       FIG. 1  shows an overview of an example implementation and an example network  100  for determining and executing delivery actions using artificial intelligence in accordance with aspects of the present disclosure. As shown in  FIG. 1 , environment  100  may include a user analytics data system  110 , a user profile system  120 , a package analytics system  130 , a proactive mitigation system  140 , and a network  150 . 
     The user analytics data system  110  may include one or more computing device and/or database system that gathers, processes and/or stores a variety of user analytics data pertaining to users and their behaviors relating to item delivery or package delivery activity. In some embodiments, example user analytics data may include a user&#39;s calling activity into a call center, the details of calls made to the call center (e.g., the length of the call, purpose of the call, actions taken as a result of the call, etc.), missed delivery activity, package delivery rescheduling activity, package delivery rerouting activity, conditions under which package delivery has been missed, rescheduled, and/or rerouted, etc. Additionally, or alternatively, the user analytics data may include the user&#39;s work schedule, shopping history, location history, and/or any other data that may pertain to package delivery services or behaviors associated with package delivery services. As shown in  FIG. 1 , the user analytics data system  110  may provide user analytics data to a user profile system  120 . In some embodiments, the user analytics data system  110  may append a user identifier to a set of user analytics data provided to the user profile system  120 . 
     The user profile system  120  may include one or more computing device that receives user analytics data from the user analytics data system  110 , and builds and maintains user profiles for different users over a period of time. For example, the user profile system  120  may build, maintain, and update a user profile for a particular user by obtaining, tracking, and storing user analytics data associated with the user. In various embodiments, the user profile may store information that identifies delivery actions that the user has historically or previously taken under a certain set of conditions. That is, the user profile may store information linking delivery-related actions with a set of values associated with the package analytics data under which those delivery-related actions were taken by that user. For example, the user profile may store (e.g., in a data structure) a set of values relating to the user analytics information that identifies calls to a call center that the user previously made, the purpose of the calls, the conditions under which the calls were made, and delivery actions (e.g., the user&#39;s instructions regarding how and when to deliver or redeliver a package) that were taken via the call, or via a web-based system (e.g., delivery actions to reroute/redeliver/reschedule package delivery, track package information, change package delivery speed, etc.). Additionally, or alternatively, the user profile may store information relating to missed deliveries for the user, and the conditions of the missed delivery (e.g., time of day of the missed delivery, day of the week, weather conditions, etc.). 
     As one illustrative example, the user profile may store information indicating or identifying that the user has historically or previously rescheduled delivery under a set of conditions (e.g., on a certain day of the week or at a certain time of day, when the package is delayed, when the package has a declared value exceeding a certain threshold, when the package is being delivered in inclement weather, etc.). As another illustrative example, the user profile may store information indicating or identifying that the user has historically called in to a customer service center to reroute delivery, e.g., to a different address, under a certain set of conditions (e.g., when the package delivery estimate is updated to a sooner than originally expected date or time, when the declared value exceeds a threshold, etc.). As another example, the user profile may store information indicating or identifying that the user has historically changed delivery options for outgoing packages (e.g., to require a signature of the recipient) under a certain set of conditions (e.g., when the declared value of the package exceeds a threshold, when the package is sent to a particular recipient, when the package has a particular contents, etc.). In some embodiments, the user profile may store any other combination of delivery actions and conditions associated with delivery actions. As shown in  FIG. 1 , the user profile system  120  may provide user profiles or data from user profiles to the proactive mitigation system  140 . 
     The package analytics system  130  may include one or more computing device that stores, processes, and tracks package analytics data, such as package tracking information, estimated delivery dates/times for a package, package delivery speed, package delivery services (e.g., express service, priority service, first-class service, etc.), package delivery options, declared package values, declared package contents, sender information, recipient information, etc. Additionally, or alternatively, the package analytics system  130  may gather, determine, process, and track other package analytics data, such as weather information along a delivery route, package delivery estimate updates (e.g., early or delayed deliveries), etc. As shown in  FIG. 1 , the package analytics system  130  may provide the package analytics data to the proactive mitigation system  140 . 
     The proactive mitigation system  140  may include one or more computing device that receives or obtains user profiles from the user profile system  120  and package analytics data from the package analytics system  130 . In some embodiments, the proactive mitigation system  140  may monitor or process the package analytics data, and automatically generate a proactive mitigating action when it detects or determines the occurrence of a triggering event. As described herein, the determination of the triggering event and the proactive mitigating action may be based on the user profile information and the package analytics data. As one illustrative example, the proactive mitigation system  140  may detect or determine that a triggering event has occurred when the delivery of the package is delayed or will be delayed (e.g., as determined or indicated by the package analytics data). Based on user profile information indicating that the recipient calls a customer service call center when package delivery is delayed, the proactive mitigation system  140  may automatically select, initiate, determine, or generate an appropriate mitigating action, and may proactively execute the mitigating action. In this example, the mitigating action may be to send the recipient a message (e.g., an e-mail, text message, automated phone call, etc.) advising the recipient of the delay in delivery. Because he or she has been proactively notified of the delayed delivery, the recipient is less likely to call the call center, thus reducing resource usage, call volume, and the like. As noted previously, the proactive mitigation system  140  may determine the appropriate mitigating action to be action that is the same or similar to an action that has been taken in the past by the user while in the same or a similar situation, as indicated or connoted in the user&#39;s user profile information. 
     As another example, the proactive mitigation system  140  may analyze the package analytics data and determine that an event trigger has occurred because the package analytics information/data indicates that the package is scheduled to be delivered early (e.g., at 2:00 pm) to the user&#39;s home address, and user profile information indicates that the recipient typically is at work, rather than at home, at the early delivery time. The proactive mitigation system  140  may then analyze the user profile data and determine that, in the past, the user has typically rerouted packages to the user&#39;s work location when the packages are scheduled to be delivered before 5:30 pm. Based on the delivery time information and the user&#39;s past actions, the proactive mitigation system  140  may then generate or initiate a mitigating instruction to proactively reroute the package delivery to a different location (i.e., to the recipient&#39;s work location in this example). In this way, the likelihood of a missed delivery is decreased, which decreases the usage of sorting resources, computer resources, vehicle resources, bandwidth resources, and the like on missed deliveries. 
     As another example, the proactive mitigation system  140  may generate a proactive mitigating instruction to change a delivery option to require a signature based on the package analytics data indicating a declared value exceeding a threshold, and user profile information indicating that the sender typically requires a signature when the declared value exceeds the threshold. In this way, a call to a customer service call center that would have otherwise been placed to change the delivery option may be avoided. As another example, the proactive mitigation system  140  may generate a proactive mitigating instruction to reschedule delivery, or reroute delivery to a different location during inclement weather and when the user profile indicates that the recipient or sender has previously rescheduled or rerouted delivery during inclement weather. As another example, the proactive mitigation system  140  may generate a proactive mitigating instruction to reroute a delivery based on the recipient rerouting a different delivery. Additionally, or alternatively, the proactive mitigating instruction may be based on any combination or variety of rules and criteria based on information stored in the user profile and the package analytics data. 
     In some embodiments, the proactive mitigating instruction may extend beyond delivery-related actions. For example, the processes performed by the proactive mitigation system  140  may be applied to other types of systems as well, such as ordering and/or shopping systems. As an illustrative example, the proactive mitigation system  140  may generate a proactive mitigating instruction to place an order for an item for a user based on the user&#39;s shopping history indicating that the user has historically placed an order for the item at regular intervals. 
     As shown in  FIG. 1 , the proactive mitigation system  140  may output the proactive mitigating action for execution (e.g., to a package delivery system). In some embodiments, the proactive mitigation system  140  may provide a confirmation message to the user (e.g., via text message, e-mail message, web-based application, chatbot, etc.), and the user may confirm, modify, or cancel the proactive mitigating action. By predicting a user&#39;s actions in the context of package delivery and by proactively executing predicted mitigating actions, technical resources are used more efficiently with reduced waste, the level of call center volume may be reduced, and the number of missed delivery attempts may be reduced. Further, customer satisfaction and other advantages may be realized as a result of proactively executing mitigating actions as described herein. 
     As further shown in  FIG. 1 , the user analytics data system  110 , the user profile system  120 , the package analytics system  130 , and the proactive mitigation system  140  may communicate via a network  150 . The network  150  may include network nodes and one or more wired and/or wireless networks. For example, the network  150  may include a cellular network (e.g., a second generation (2G) network, a third generation (3G) network, a fourth generation (4G) network, a fifth generation (5G) network, a long-term evolution (LTE) network, a global system for mobile (GSM) network, a code division multiple access (CDMA) network, an evolution-data optimized (EVDO) network, or the like), a public land mobile network (PLMN), and/or another network. Additionally, or alternatively, the network  150  may include a local area network (LAN), a wide area network (WAN), a metropolitan network (MAN), the Public Switched Telephone Network (PSTN), an ad hoc network, a managed Internet Protocol (IP) network, a virtual private network (VPN), an intranet, the Internet, a fiber optic-based network, and/or a combination of these or other types of networks. In embodiments, the network  140  may include copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. 
     The quantity of devices and/or networks in the environment  100  is not limited to what is shown in  FIG. 1 . In practice, the environment  100  may include additional devices and/or networks; fewer devices and/or networks; different devices and/or networks; or differently arranged devices and/or networks than illustrated in  FIG. 1 . Also, in some implementations, one or more of the devices of the environment  100  may perform one or more functions described as being performed by another one or more of the devices of the environment  100 ; e.g., the functions may all be performed by a single device. Devices of the environment  100  may interconnect via wired connections, wireless connections, or a combination of wired and wireless connections. 
       FIG. 2  shows a flowchart of an example of a process  200  for executing a proactive mitigating action based on the occurrence of an event trigger. The operations of  FIG. 2  may be implemented in the environment of  FIG. 1 , for example, and are described using reference numbers of elements depicted in  FIG. 1 . As noted above, the flowchart illustrates the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. 
     As shown in  FIG. 2 , process  200  may include monitoring and/or analyzing the package analytics data for a delivery item (block  210 ). For example, the proactive mitigation system  140  may monitor package analytics data (e.g., received or obtained from the package analytics system  130 ) for a delivery item (e.g., package) currently in transit to a destination. As described above, the package analytics data for a delivery item may include information/data indicating the sender, the recipient, the location of the package (e.g., arrived at Post Office, Fairfax, Va.) at a specific time, the current status of the package (e.g., in transit), weather conditions along a delivery route of the package, estimated delivery day of the week, estimated delivery time of day, declared value of the package, contents of the package (if shared by the sender), delays or changes in expected delivery, or the like. 
     Process  200  may also include accessing a user profile (e.g., obtaining information from a user profile) associated with the delivery item (block  220 ). For example, the proactive mitigation system  140  may access a user profile received or obtained from the user profile system  120 . In some embodiments, the proactive mitigation system  140  may access a user profile associated with the sender, recipient, or other party associated with the delivery item, where one or more of these parties may be specified in the package analytics data. As described herein, the user profile may identify or specify one or more conditions under which a package delivery previously has been missed, rescheduled, and/or rerouted by the user associated with the user profile. Additionally, or alternatively, the user profile may identify delivery-related actions the user has taken previously under certain conditions. That is, the user profile may store information linking delivery-related actions with the package analytics data under which those delivery-related actions were taken. 
     Process  200  may further include detecting the occurrence of an event trigger (block  230 ). For example, the proactive mitigation system  140  may detect or determine the occurrence of an event trigger that indicates that a proactive mitigating action should be taken. In various implementations, in general, the proactive mitigation system  140  may detect or determine that an event trigger has occurred by: 1) processing and/or analyzing the information for a specific package from the package analytics data that it is monitoring (from block  210 ), for example, to extract or form a candidate set of data values that may (or may not) warrant or be a reason for taking a mitigating action, 2) comparing the candidate set of data values to corresponding set of data values from the user profile (from block  220 ) to see if the data value(s) match, and 3) if the trigger value do match, what, if any, action the user took in the past when the trigger conditions occurred. 
     Thus, in various embodiments, the proactive mitigation system  140  may detect or determine whether or not a trigger event has occurred based on information stored within a data structure that identifies the actions a user has previously or historically taken (e.g., as shown in the user profile) based on a set of package analytics data values that define or are associated with the event trigger. That is, an event trigger occurrence may be detected when a set of package analytics data values match the data values from the user profile (e.g., package analytics data values that were previously stored in the user profile) that define the event trigger; i.e., the data values from the user profile that have caused the user to take an action in the past. 
     As one illustrative example, the proactive mitigation system  140  may detect or determine that an event trigger has occurred based on: 1) the package analytics data indicating that the delivery of a package is expected to be delayed, and 2) the user profile data indicating that the intended recipient of the package has a history of calling in to a customer call center when package deliveries have been delayed. 
     As another illustrative example, the proactive mitigation system  140  may detect that an event trigger has occurred based on: 1) the package analytics data indicating that both: a) the delivery of a package is scheduled during inclement weather, and b) the declared value of the package exceeds a threshold; and 2) the user profile data indicating that the recipient of the package has historically called the customer call center to modify delivery actions when both a) and b) have occurred in the past—for example, the recipient may have historically called the customer call center to modify the delivery actions to require a signature upon delivery and to reroute the delivery of a package to an alternate location (e.g., the recipients place of employment). 
     As another illustrative example, the proactive mitigation system  140  may detect or determine that an event trigger has occurred based on: 1) the package analytics data indicating that a package is in route to be delivered to the user at their home address, and 2) the user profile indicating that both: a) the user&#39;s location is away from a home location (e.g., when the user is on vacation), and b) that the user has historically had packages held by the delivery system until the user&#39;s location is once again the home location (e.g., when the user returns from vacation). 
     The proactive mitigation system  140  may detect the occurrence of other event triggers based on any variety of package analytics data and user profile data, and the event triggers may be different for each user, depending in part on how they have acted in the past under certain delivery conditions, as reflected in the package analytics data. Thus, for different users, each having different user profile data, the same set of package analytics data values may be a trigger event for some users, but not be a trigger event for other users. Thus, in various implementations, the set of conditions or circumstances (e.g., the trigger event as represented by the information in the package analytics data) that results in a mitigating action for one user may result in no trigger, and no mitigating action for a different user. Similarly, the set of circumstances (e.g., the trigger event) that cause the system  140  to execute a certain mitigating action for one user can cause the system  140  to execute a different mitigating action for another user, even though set of circumstances is the same (e.g., the trigger event). 
     Process  200  may also include executing a proactive mitigating action based on the event trigger (block  240 ). For example, if the proactive mitigation system  140  detects or identifies an event trigger in the package analytics data (e.g., at block  230 ), then the system  140  may identify, lookup, or otherwise determine a proactive mitigating action(s) corresponding to the event trigger that was detected, and then proactively initiate or execute those mitigating action(s). As described herein for some implementations, the proactive mitigation system  140  may identify, select, or determine a particular proactive mitigating action(s) from among a group of proactive mitigating actions based on information stored in a data structure that maps the proactive mitigating action to the event trigger and the package analytics data. In various such implementations, the detected event trigger and the package analytics data for that specific package may be used to look up the appropriate mitigating action(s), where the mitigating action(s) are modeled on what the associated user (e.g., the recipient) has done in the past under the same or similar conditions per the user&#39;s analytics data. 
     That is, different package analytics data values may define or correspond to different types of event triggers and different proactive mitigating actions to be taken. Also, for different users, each having different user profile data, the same set of analytics data values may map to a different proactive mitigating action. That is, the mitigating action taken for one user under a certain set of conditions or circumstances (e.g., a certain trigger event) can be different from the mitigating action taken for another user under the same set of circumstances (e.g., in response to the same trigger event). In this way, the proactive mitigation system  140  may select the best-suited or appropriate proactive mitigating action for each specific user based on that user&#39;s user profile, which identifies actions the user has previously taken under a certain set of conditions. 
     As noted, in various embodiments, the proactive mitigation system  140  may initiate, put into effect, or execute the appropriate proactive mitigating action(s) for the user (e.g., a package delivery related action which may correspond to an action that the user has previously taken in the same or a similar situation or under the same or similar conditions or circumstances, as represented by a given set of package analytics data). As described herein, examples of proactive mitigating actions may include rescheduling delivery of the package, redirecting or rerouting delivery of the package, modifying a delivery option of the package (e.g., signature confirmation, etc.), modifying a delivery or shipping speed of the package, providing the user with a message or notification, etc., or any combination of these. In some embodiments, the proactive mitigating action may also be or include sending a notification to the user indicating that a proactive action is being taken, or sending a notification or message having information that reduces the likelihood of the user calling in to a call center (e.g., a message notifying the user that a package delivery is delayed, which reduces the likelihood of the user calling in to a call center to inquire about the status of the delivery). Additionally, or alternatively, the proactive mitigation system  140  may output a confirmation or inquiry message to the user to provide the user with an opportunity to confirm, modify, or deny the proactive mitigating action that the system plans to implement. In this way, the user can control whether or not the system enacts the proactive mitigating action before the mitigating action occurs or is completed, as the user may prefer a different action than the action the system selects based on the user&#39;s user profile, which indicates the delivery actions the user has taken previously under certain conditions. 
       FIG. 3  illustrates an example implementation for generating and executing a proactive mitigating instruction based on user profile data and package analytics data. As shown  FIG. 3 , the proactive mitigation system  140  may receive a user profile (e.g., from the user profile system  120 ) and package analytics data (e.g., from the package analytics system  130 ). In some embodiments, the proactive mitigation system  140  may generate a proactive mitigating action based on the user profile and the package analytics data (e.g., in accordance with process  200  as described in  FIG. 2 ). As an illustrative example, the proactive mitigation system  140  may determine, based on the package analytics data, that a package is anticipated to be delivered earlier in the day than originally scheduled, and that the package requires a signature for release. The proactive mitigation system  140  may also determine, based on the user profile data, that a user (e.g., a recipient) of the package has previously rerouted delivery of the package to the user&#39;s office location (e.g., rather than the user&#39;s residence) when the package is delivered earlier in the day. Accordingly, the proactive mitigation system  140  may generate a proactive mitigating action to reroute the package to the user&#39;s office. As further shown in  FIG. 3 , the proactive mitigation system  140  may provide a notification of the proactive mitigating action to a user device  210  associated with the user (e.g., recipient). Based on receiving the proactive mitigating action notification, the user device  210  may display the proactive mitigating action whereby the user may confirm or deny or proactive mitigating action (e.g., by providing user input or a selection via the user device  210 ). That is, before executing a proactive mitigating action, the proactive mitigation system  140  may provide a notification of the proactive mitigating action to a user device  210 , and may not take action until receiving user input via the user device  210  to confirm or modify the proactive mitigating action. 
     In the example shown in  FIG. 3 , the user device  210  receives an input or selection to accept the proactive mitigating action (e.g., to reroute the package). Accordingly, the proactive mitigation system  140  outputs a rerouting instruction (e.g., to a package delivery system) to execute the package rerouting. In this way, the proactive mitigation system  140  may proactively modify delivery instructions based on the user&#39;s history and profile indicating actions the user has previously taken. As such, the chances of a missed delivery are reduced, and the likelihood that the user may call in to the call center (e.g., to reschedule a missed delivery) is reduced. 
       FIG. 4  illustrates example components of a device  400  that may be used within environment  100  of  FIG. 1 . Device  400  may correspond to the user analytics data system  110 , user profile system  120 , package analytics system  130 , proactive mitigation system  140 , and/or the user device  210 . Each of the user analytics data system  110 , user profile system  120 , package analytics system  130 , proactive mitigation system  140 , and/or the user device  210  may include one or more devices  400  and/or one or more components of device  400 . 
     As shown in  FIG. 4 , device  400  may include a bus  405 , a processor  410 , a main memory  415 , a read only memory (ROM)  420 , a storage device  425 , an input device  440 , an output device  445 , and a communication interface  450 . 
     Bus  405  may include a path that permits communication among the components of device  400 . Processor  410  may include a processor, a microprocessor, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or another type of processor that interprets and executes instructions. Main memory  415  may include a random-access memory (RAM) or another type of dynamic storage device that stores information or instructions for execution by processor  410 . ROM  420  may include a ROM device or another type of static storage device that stores static information or instructions for use by processor  410 . Storage device  425  may include a magnetic storage medium, such as a hard disk drive, or a removable memory, such as a flash memory. 
     Input device  440  may include a component that permits an operator to input information to device  400 , such as a control button, a keyboard, a keypad, or another type of input device. Output device  445  may include a component that outputs information to the operator, such as a light emitting diode (LED), a display, or another type of output device. Communication interface  450  may include any transceiver-like component that enables device  400  to communicate with other devices or networks. In some implementations, communication interface  450  may include a wireless interface, a wired interface, or a combination of a wireless interface and a wired interface. In embodiments, communication interface  450  may receiver computer readable program instructions from a network and may forward the computer readable program instructions for storage in a computer readable storage medium (e.g., storage device  425 ). 
     Device  400  may perform certain operations, as described in detail below. Device  400  may perform these operations in response to processor  410  executing software instructions contained in a computer-readable medium, such as main memory  415 . A computer-readable medium may be defined as a non-transitory memory device and is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. A memory device may include memory space within a single physical storage device or memory space spread across multiple physical storage devices. 
     The software instructions may be read into main memory  415  from another computer-readable medium, such as storage device  425 , or from another device via communication interface  450 . The software instructions contained in main memory  415  may direct processor  410  to perform processes that will be described in greater detail herein. Alternatively, hardwired circuitry may be used in place of or in combination with software instructions to implement processes described herein. Thus, implementations described herein are not limited to any specific combination of hardware circuitry and software. 
     In some implementations, device  400  may include additional components, fewer components, different components, or differently arranged components than are shown in  FIG. 4 . 
     Aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions. 
     These computer readable program instructions may be provided to a processor of a general-purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks. 
     The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions. 
     Embodiments of the disclosure may include a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out or execute aspects and/or processes of the present disclosure. 
     In embodiments, the computer readable program instructions may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on a user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. 
     In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure. 
     The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     In embodiments, a service provider could offer to perform the processes described herein. In this case, the service provider can create, maintain, deploy, support, etc., the computer infrastructure that performs the process steps of the disclosure for one or more customers. These customers may be, for example, any business that uses technology. In return, the service provider can receive payment from the customer(s) under a subscription and/or fee agreement and/or the service provider can receive payment from the sale of advertising content to one or more third parties. 
     The foregoing description provides illustration and description, but is not intended to be exhaustive or to limit the possible implementations to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practice of the implementations. 
     It will be apparent that different examples of the description provided above may be implemented in many different forms of software, firmware, and hardware in the implementations illustrated in the figures. The actual software code or specialized control hardware used to implement these examples is not limiting of the implementations. Thus, the operation and behavior of these examples were described without reference to the specific software code—it being understood that software and control hardware can be designed to implement these examples based on the description herein. 
     Even though particular combinations of features are recited in the claims and/or disclosed in the specification, these combinations are not intended to limit the disclosure of the possible implementations. In fact, many of these features may be combined in ways not specifically recited in the claims and/or disclosed in the specification. Although each dependent claim listed below may directly depend on only one other claim, the disclosure of the possible implementations includes each dependent claim in combination with every other claim in the claim set. 
     While the present disclosure has been disclosed with respect to a limited number of embodiments, those skilled in the art, having the benefit of this disclosure, will appreciate numerous modifications and variations there from. It is intended that the appended claims cover such modifications and variations as fall within the true spirit and scope of the disclosure. 
     No element, act, or instruction used in the present application should be construed as critical or essential unless explicitly described as such. Also, as used herein, the article “a” is intended to include one or more items and may be used interchangeably with “one or more.” Where only one item is intended, the term “one” or similar language is used. Further, the phrase “based on” is intended to mean “based, at least in part, on” unless explicitly stated otherwise.