Patent Publication Number: US-2023164270-A1

Title: Systems and methods of providing automated resolutions

Description:
BACKGROUND 
     Customers call customer service centers in order to attempt to solve problems with their service. Generally, the provider of the service hires customer service representatives to answer the calls from the customers. Hiring this staff is expensive. Long wait times due to insufficient staff often causes dissatisfaction for the customer while waiting a long time to talk to a customer service representative. While these call centers sometimes have digital solutions that give the customer certain options from to select, the options are rigid, and the digital solutions are limited in an ability to discern details regarding the subject of the inquiry. This often results in the customer wanting to talk to the customer service representative. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Aspects of the present disclosure are best understood from the following detailed description when read with the accompanying figures. It is noted that, in accordance with the standard practice in the industry, various features are not drawn to scale. In fact, the dimensions of the various features may be arbitrarily increased or reduced for clarity of discussion. 
         FIG.  1    is a block diagram of an automated customer resolution system, in accordance with some embodiments. 
         FIG.  2    is a block diagram of automated customer resolution software, in accordance with some embodiments. 
         FIG.  3    is a block diagram of automated customer resolution software, in accordance with some embodiments. 
         FIG.  4    is a call flow diagram of an embodiment of implementing customer service procedures, in accordance with some embodiments. 
         FIG.  5    is a visual representation of an automated decision tree, in accordance with some embodiments. 
         FIG.  6    is a flowchart related to a customer service method, in accordance with some embodiments. 
         FIG.  7   - FIG.  9    are flowcharts that are implemented after the flowchart in  FIG.  6    in accordance with some embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     The following disclosure provides many different embodiments, or examples, for implementing different features of the provided subject matter. Specific examples of components, values, operations, materials, arrangements, or the like, are described below to simplify the present disclosure. These are, of course, merely examples and are not intended to be limiting. Other components, values, operations, materials, arrangements, or the like, are contemplated. For example, the formation of a first feature over or on a second feature in the description that follows may include embodiments in which the first and second features are formed in direct contact and may also include embodiments in which additional features may be formed between the first and second features, such that the first and second features may not be in direct contact. In addition, the present disclosure may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. 
     (Optional, use when applicable) Further, spatially relative terms, such as “beneath,” “below,” “lower,” “above,” “upper” and the like, may be used herein for ease of description to describe one element or feature&#39;s relationship to another element(s) or feature(s) as illustrated in the figures. The spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. The apparatus may be otherwise oriented (rotated    90   degrees or at other orientations) and the spatially relative descriptors used herein may likewise be interpreted accordingly. 
     Systems and methods of implementing automated solutions to inquiries are disclosed in this description. In some embodiments, the systems and methods are used to provide answers or solutions to customer service inquiries. In some embodiments, a computer device is configured to convert audio data of speech with the inquiry into textual data. Rule based systems or artificial intelligence systems then search through resolution data structures that describe automated resolutions. In some embodiments, the automated resolutions are based on solutions used to solve past inquiries. Rule based systems or artificial intelligence systems are configured to select a target automated resolution from the various automated resolution based on the textual data with the customer inquiry. In some embodiments, the automated resolution selected is the one most likely to solve the inquiry in the textual data. In this manner, the system and methods are capable of deciphering how to solve the inquiry in an automated manner. 
       FIG.  1    is a block diagram of an automated customer resolution system  100 , in accordance with some embodiments. 
     Automated customer resolution system  100  includes an automated customer resolution device  120  (which is a server(s)  120 , in some embodiments), a database  127 , and a user device  130 . The automated customer resolution device  120  is a computer device that is operably connected to the database  127 . Automated customer resolution device  120  is connected to a network  103  and is configured to manage the processing (e.g., writing and storing) of data  125 ,  126  (referred to generically or collectively as data) stored in non-transitory computer readable medium  119  in the database  127 . In some embodiments, the network  103  includes a wide area network (WAN) (i.e., the internet), a wireless WAN (WWAN) (i.e., a cellular network), a local area network (LAN), and/or the like. 
     Data includes automated customer service resolutions (ACSR in  FIG.  1   )  126 . Each of the automated customer service resolutions  126  includes executable instructions for implementing a set of automated procedures that helps to resolves a customer inquiry. A customer inquiry is a problem or request from a customer that use service procedures for resolution. Each of the automated customer service resolutions  126  includes executable instructions for implementing the service procedures in an automated manner to help resolve different customer inquiries. Data further includes customer service resolution data structures (CSRDS in  FIG.  1   )  125 . Each of the customer service resolution data structures  125  relates to a different automated customer service resolution  126  of the automated customer service resolutions  126 . In some embodiments, each of the customer service resolution data structures  125  describes the automated procedures implemented by one of the automated customer service resolutions  126 . In some embodiments, each of the customer service resolution data structures  125  links each of the automated customer service resolutions  126  with one or more historical customer service inquires. In other words, previously received historical customer service inquiries are linked to the automated customer service resolutions  126  by the customer service resolution data structures  125 , in accordance with some embodiments. In this manner, automated customer service resolutions  126  used to resolve previous customer service inquiries are linked by the customer service resolution data structures  125 , in accordance with some embodiments. 
     In some embodiments, customer service resolution data structures  125  and automated customer service resolutions  126  have database formats written in one or more database languages. The database formats define the structure of the customer service resolution data structures  125 , automated customer service resolutions  126 . Exemplary database languages include JSON, ASCII, XML, and CSV. One of ordinary skill in the art would understand that JSON, ASCII, XML, and CSV are exemplary database languages and are not in any way limiting on the current disclosure. In some embodiments, the customer service resolution data structures  125  and automated customer service resolutions  126  are in database formats written in other suitable database languages. In some embodiments, the customer service resolution data structures  125  and automated customer service resolutions  126  are in database formats written in the same database language JSON, ASCII, XML, and CSV. In some embodiments, the customer service resolution data structures  125  and automated customer service resolutions  126  are in database formats written different database languages JSON, ASCII, XML, and CSV. For example, in some embodiments, some of the customer service resolution data structures  125  are in JSON and some of the automated customer service resolutions  126  are in XML. 
     The automated customer resolution device  120  is configured to manage the writing and storing of the customer service resolution data structures  125  and automated customer service resolutions  126  in the databases  127  and to perform other functionality including the automated procedures described herein. The automated customer resolution device  120  includes computer executable instructions  129  that are executable by one or more processors  121 . The computer executable instructions  129  are stored on a non-transitory computer readable medium  128 . In some embodiments, non-transitory computer readable medium  128  include a random-access memory (RAM), a read-only memory (ROM), an electrically erasable programmable ROM (EEPROM), optical disk storage, magnetic disk storage, other magnetic storage devices, combinations of the aforementioned types of computer-readable mediums, or any other medium that can be used to store computer executable code in the form of instructions or data structures that can be accessed by a computer device. When the one or more processors  121  of the automated customer resolution device  120  implement the computer executable instructions  129 , the one or more processors  121  execute automated customer resolution software  122 . 
     The automated customer resolution software  122  is configured to convert auditory data  123  into textual data  124 . The auditory data  123  is of a captured voice with speech related to a customer service inquiry. In some embodiments, the textual data  124  includes a textual transcript of the customer service inquiry, which was originally captured as the auditory data  123 . In some embodiments, the textual data  124  is ASCII data of the textual transcript. Thus, textual data  124  includes a textual representation of the customer service inquiry that was originally captured related to the customer service inquiry. In  FIG.  1   , the auditory data  123  and the textual data  124  are stored in the non-transitory computer readable medium  128 . 
     In  FIG.  1   , the auditory data  123  originates from a user device  140  where a user  142  speaks into the user device  140  to describe the customer service inquiry. The speech from the user  142  is captured by the user device  140 . The captured speech is converted into the auditory data  123  by the automated customer resolution software  122  in the automated customer resolution device  120 . The user device  140  includes one or more processors  146  and computer executable instructions  144  that are stored on a non-transitory computer readable medium  145 . In some embodiments, non-transitory computer-readable medium  145  include a random-access memory (RAM), a read-only memory (ROM), an electrically erasable programmable ROM (EEPROM), optical disk storage, magnetic disk storage, other magnetic storage devices, combinations of the aforementioned types of computer-readable mediums, or any other medium that can be used to store computer executable code in the form of instructions or data structures that can be accessed by a computer device. Examples of a user devices  140  include a cellular phone, a smart phone, a session initiation protocol (SIP) phone, a laptop, a smart watch, a personal digital assistant (PDA), a satellite radio, a global positioning system, a multimedia device, a video device, a digital audio player (e.g., MP3 player), a camera, a game console, a tablet, a smart device, and a wearable communication device. 
     In some embodiments, a call is established with the user device  140  associated with the user  142  (also referred to as the customer  142 , in some embodiments). In some embodiments, the customer  142  calls a customer service center  131 . The customer service center  131  is a location where customer service representatives, such as user  132 , receive calls from a customer, such as customer  142 . In some embodiments, customer service representatives operate in a geographically distributed manner such that there is no customer service center  131 . A call is established between the user device  140 , a user device  130  and the automated customer resolution device  120 . In some embodiments, the call is a telephone call or other audible communication, such as voice of internet provider (VOIP). The user device  130  includes one or more processors  136  and computer executable instructions  134  that are stored on a non-transitory computer readable medium  135 . In some embodiments, non-transitory computer-readable medium  135  include a random-access memory (RAM), a read-only memory (ROM), an electrically erasable programmable ROM (EEPROM), optical disk storage, magnetic disk storage, other magnetic storage devices, combinations of the aforementioned types of computer-readable mediums, or any other medium that can be used to store computer executable code in the form of instructions or data structures that can be accessed by a computer device. Examples of a user devices  130  include a cellular phone, a smart phone, a session initiation protocol (SIP) phone, a laptop, a smart watch, a personal digital assistant (PDA), a satellite radio, a global positioning system, a multimedia device, a video device, a digital audio player (e.g., MP3 player), a camera, a game console, a tablet, a smart device, and a wearable communication device. In some embodiments, the user device  130  is operated by a user  132  (also referred to as a customer service representative  132 , in some embodiments). 
     However, prior to speaking to the customer service representative  132 , the automated customer resolution device  120  is configured to transmit an audible inquiry request to the user device  140  during the call, wherein the audible inquiry request is playable through the user device  140  and asks for the customer  142  to describe a service problem. In response, the customer  142  speaks into the user device  140  with the customer service inquiry. The user device  140  is transmits the speech of the customer service inquiry to the automated customer resolution device  120  via network  103 . The automated customer resolution software  122  is configured to convert the captured speech into the auditory data  123 . The captured speech is transmitted from the user device  140  to the automated customer resolution device  120  as a response to transmitting the audible inquiry request. The automated customer resolution software  122  is configured to convert the auditory data  123  into textual data  124 . 
     The automated customer resolution software  122  implemented by the automated customer resolution device  120  is configured to select a target automated customer service resolution  126  for the customer service inquiry from a plurality of automated customer service resolutions  126  based on the textual data  124  and a customer service resolution data structure  125  of a plurality of the customer service resolution data structures  125 . In some embodiments, the automated customer resolution software  122  is configured to search through the customer service resolution data structures  125  and find the customer service resolution data structures  125  related to an automated customer service resolution  126  (i.e., the target automated customer service resolution  126 ) associated with a previous customer service inquiry that most closely matches the customer service inquiry from the textual data  124 . Thus, unlike automated systems that simply request that a customer enter or speak a number related to a fixed solution, the automated customer resolution software  122  implemented by the automated customer resolution device  120  is configured to analyze the customer service inquiry in textual form and select the target automated customer service resolution  126  based on the customer service resolution data structures  125  that describe the automated customer service resolutions  126 . 
     In some embodiments, the automated customer resolution software  122  implemented by the automated customer resolution device  120  simply executes the target automated customer service resolution  126  in response to selecting the target automated customer service resolution  126  for the customer service inquiry and without any further action. In some embodiments, the automated customer resolution software  122  implemented by the automated customer resolution device  120  sends an audible request to the user device  140  asking the customer  142  whether the customer  142  wants to implement the target automated customer service resolution  126 . In some embodiments, customer input data is received by the automated customer resolution software  122  from the user device  140 . The customer input data is a selection by the customer  142  of the target automated customer service resolution  126 : In response, the target automated customer service resolution  126  is executed in response to receiving the customer input data. In still other embodiments, the automated customer resolution software  122  sends an audible request regarding whether the customer  142  would like to transfer the call to an customer service representative, such as the customer service representative  132 . In some embodiments, the automated customer resolution software  122  is configured to receive customer input data, wherein the customer input data is from the user device  140  and is a selection by the customer  142  to transfer the call related to the customer service inquiry to the user device  130  associated with the customer service representative  132 . In some embodiments, the automated customer resolution software  122  presents the customer service representative  132  in the customer service center  131  with an option through the user device  130  to execute the target automated customer service resolution  126  for the customer inquiry. In some embodiments, the target automated customer service resolution  126  for the customer service inquiry is executed in response to receiving customer service representative input data that the option has been selected by the customer service representative  132  through the user device  130 . 
       FIG.  2    is a block diagram of automated customer resolution software  200 , in accordance with some embodiments. 
     The automated customer resolution software  200  corresponds to the automated customer resolution software  122  in  FIG.  1    in accordance with some embodiments. The automated customer resolution software  200  includes an interactive voice response (IVR) module  202 , a processing engine  204 , a customer service engine  206 , a playbook engine  208 , and an artificial intelligence (AI) engine  210 . 
     The IVR module  202  is configured to answer a customer service call from a customer  212 . The IVR module  202  then plays a welcome message and request that the customer  212  provide auditory input identifying the language that the customer  212  prefers for the call. After the customer  212  provides the auditory input, the IVR module  202  sets the language preferences for the customer service call in accordance with the auditory input from the customer  212 . The IVR module  202  receives the auditory inputs from the customer  212  and converts the auditory inputs into auditory data (e.g., auditory data  123  in  FIG.  1   ). 
     The processing engine  204  is configured to convert the auditory data into textual data (e.g., textual data  124  in  FIG.  1   ). In some embodiments, once the IVR module  202  obtains and sets the language preferences, the processing engine  204  is configured to transmit an auditory request for some basic identifying information from the customer  212  such as personal phone number, name, address etc. The customer  212  provides this information as an auditory input, which the IVR module  202  converts into auditory data. The processing engine  204  then converts the auditory data into textual data. In some embodiments, the processing engine  204  uses the textual data with the customer&#39;s identifying information to find a customer page  214 . In some embodiments, the customer page  214  includes account data for the particular customer  212 . 
     The processing engine  204  is then configured to transmit an auditory request that asks the customer  212  to audibly provide the customer inquiry. For example, the customer  212  is allowed to freely ask a question and/or state a problem. The auditory input with the customer inquiry is converted into auditory data by the IVR module  202 . The processing engine  204  then converts the auditory data with the speech that includes the customer inquiry into textual data. 
     The customer service engine  206  then creates a digital customer service ticket  216 . The digital customer service ticket  216  links the textual data with the customer inquiry to a service list. The service list is used to establish priority for the customer inquiries of different customers  212 . For example, if ultimately it is established that the customer  212  is to speak with a customer service representative, the digital customer service ticket establishes the customer&#39;s place in line. 
     Once the AI engine  210  receives the digital customer service ticket  216  from the customer service engine  206 , the AI engine  210  is configured to select a target automated customer service resolution (e.g., a target automated customer service resolution  126  in  FIG.  1   ) for the customer service inquiry from a plurality of automated customer service resolutions (e.g., a plurality of automated customer service resolutions  126  in  FIG.  1   ) based on the textual data (e.g., the textual data  124  in  FIG.  1   ) and a customer service resolution data structure (e.g., a customer service resolution data structure  125  in  FIG.  1   ) of a plurality of customer service resolution data structures (e.g., a plurality of customer service resolution data structures  125  in  FIG.  1   ). In  FIG.  2   , the automated customer service resolutions are playbooks  220 . Thus, a target playbook  220  is selected by the AI engine  210  based on a customer service resolution data structure that most closely matches the customer service inquiry in the textual data linked to the digital customer service ticket  216 . 
     In some embodiments, the AI engine  210  is configured to search through the customer service resolution data structures and find the customer service resolution data structures related to a playbook  220  (i.e., the target automated customer service resolution  126 ) associated with a previous customer service inquiry that most closely matches the customer service inquiry from the textual data. Furthermore, if a selection is made that confirms that the selected playbook  220  implements the desired actions for the customer service inquiry, the AI engine  210  reinforces the link between the customer service inquiry and the target playbook  220  so that similar customer inquiries are resolved in a similar manner. If on the other hand, the target playbook  220  did not resolve the customer service inquiry, the AI engine  210  is configured to associate the actions of the customer service representative used to resolve the customer service inquiry (possibly in a new playbook  220 ) so that these actions are used to resolve similar customer service inquiries in the future. 
     Once the target playbook  220  is selected by the AI engine  210 , the target playbook  220  is provided to the playbook engine  208 . The playbook engine  208  is configured to implement the target playbook  220  so that the actions that solve the customer service inquiry are taken by the automated customer resolution software  200 . In some embodiments, the playbook engine  208  lists the possible actions that the customer  212  can take, every service/action that can be taken to assist the customer  212 , and provides a platform for knowledge-articles. In some embodiments, the playbook engine  208  implements the actions defined by the target playbook  220 . 
     In some embodiments, at the end of customer service call, the AI engine  210  requests that the customer  212  state a satisfaction index. The satisfaction index is used as an indicator to train the AI engine  210  and continuously improve the AI engine&#39;s ability to appropriately select a target playbook  220  for customer service inquiries. In some embodiments, the customer/caller will still have option to be redirected to a customer service representative and get human assistance. This function will still be available in-case the AI engine  210  still is not yet trained to assist the customer  212  regarding a customer service inquiry. 
       FIG.  3    is a block diagram of automated customer resolution software  300 , in accordance with some embodiments. 
     The automated customer resolution software  300  corresponds to the automated customer resolution software  122  in  FIG.  1    in accordance with some embodiments. The automated customer resolution software  300  includes an IVR module  302 , a processing engine  304 , a business service (BBS) engine  306 , a playbook engine  308 , an (OSS)  309 , and other applications  310 . In some embodiments, the BBS engine  306  is one example of the customer service engine  206  in  FIG.  1   . 
     The IVR module  302  is configured to answer a customer service call from a customer  312 . The IVR module  302  then plays a welcome message and request that the customer  312  provide auditory input identifying the language that the customer  312  prefers for the call. After the customer  312  provides the auditory input, the IVR module  302  sets the language preferences for the customer service call in accordance with the auditory input from the customer  312 . The IVR module  302  receives the auditory inputs from the customer  312  and converts the auditory inputs into auditory data (e.g., auditory data  123  in  FIG.  1   ). 
     In  FIG.  3   , the welcome message states various options that a customer  312  can select from including, receiving product information, receiving billing information, reporting service issues, using a free inquiry option (i.e., Tell me what you want), and talking to a customer service representative  330  (also referred to as a customer service agent  330 ). In some embodiments, playbooks  320  are directly linked to particular options such as receiving product information, receiving billing information, report service issues. If the customer  312  selects these options, then the playbooks  320  are simply implemented by the playbook engine  308 . Additionally, if the customer  312  selects to talk to the customer service representative  330 , the BSS engine  306  takes over to connect the call to the user device of the customer service representative  330 . However, if the customer  312  selects to talk to a customer service representative  330 , the processing engine  304  is configured to transmit an auditory request that the customer  312  freely and audibly state their customer service inquiry. The IVR module  302  is configured to convert the audibly stated customer service inquiry into auditory data of the customer&#39;s speech of the customer service inquiry. 
     The processing engine  304  is configured to convert the auditory data into textual data (e.g., textual data  124  in  FIG.  1   ). In some embodiments, once the IVR module  202  obtains and sets the language preferences, the processing engine  304  is configured to transmit an auditory request for some basic identifying information from the customer  312  such as personal phone number, name, address etc. The customer  312  provides this information as an auditory input, which the IVR module  302  converts into auditory data, in which then the processing engine  304  converts into textual data. In some embodiments, the processing engine  304  uses the textual data with the customer&#39;s identifying information to find a customer page  314 . In some embodiments, the customer page  314  includes account data for the particular customer  312 . 
     The processing engine  304  is configured to select a target automated customer service resolution (e.g., a target automated customer service resolution  126  in  FIG.  1   ) for the customer service inquiry from a plurality of automated customer service resolutions (e.g., a plurality of automated customer service resolutions  126  in  FIG.  1   ) based on the textual data (e.g., the textual data  124  in  FIG.  1   ) and a customer service resolution data structure (e.g., a customer service resolution data structure  125  in  FIG.  1   ) of a plurality of customer service resolution data structures (e.g., a plurality of customer service resolution data structures  125  in  FIG.  1   ). In  FIG.  1   , the automated customer service resolutions are playbooks  320 . Thus, a target playbook  320  is selected by the processing engine  304  based on a customer service resolution data structure that most closely matches the customer service inquiry in the textual data. 
     In some embodiments, the processing engine  304  is configured to search through the customer service resolution data structures and find the customer service resolution data structures related to a target playbook  320  (i.e., the target automated customer service resolution  126 ) associated with a previous customer service inquiry that most closely matches the customer service inquiry from the textual data. In some embodiments, the processing engine  304  is configured to recognize the category of the customer service inquiry by keyword recognition. A search is then performed of the customer service resolution data structures to find the closest match between the category and the previous customer service inquiries. 
     Once the target playbook  320  is selected by the processing engine  304 , the target playbook  320  is provided to the playbook engine  308 . The playbook engine  308  is configured to implement the target playbook  320  so that the actions that solve the customer service inquiry are taken by the automated customer resolution software  300 . In some embodiments, the playbook engine  308  lists the possible actions that the customer  312  can take, every service/action that can be taken to help the customer  312 , and provides a platform for knowledge articles. In some embodiments, the playbook engine  308  implements the actions defined by the target playbook  320 . 
     In some embodiments, at the end of customer service call, the OSS  309  requests that the customer  312  state a satisfaction index. The satisfaction index is used as an indicator to the OSS  309  with respect to keyword and category selection. This helps the processing engine  304  to continuously improve the ability to appropriately select a playbook  320  for customer service inquiries. 
       FIG.  4    is a call flow diagram  400  of an embodiment of implementing customer service procedures, in accordance with some embodiments. 
     The call flow diagram  400  includes 3 sets of procedures  402 ,  404 ,  406 . Procedures  402  relate to procedures for a contract customer that has a customer account. Procedures  404  relate to non-contract customer that does not have a customer account. Procedures  406  relate to procedures where no query is found. The Communication Platform (CP) application  210  is an example of the AI engine  210  in  FIG.  2    and the BSS  206  is one embodiment of the customer service engine  206  in  FIG.  2   . 
     Prior to procedures  402 ,  404 ,  406 , the customer  142  makes a call to the customer service center (e.g., the customer service center  131  in  FIG.  1   ) and the automated customer resolution software  200  is configured to answer and establish the call at procedure  408 . At procedure  410 , the automated customer resolution software  200  is configured to transmit an audible request that ask whether the customer  142  has a contract or other equivalent question. 
     Within procedures  402  are procedures  412 ,  414 ,  416 ,  418 ,  420 ,  422 ,  424 ,  426 ,  428 ,  430 ,  432 ,  434 ,  436 ,  438 ,  440 . Flow beings at procedure  412 . At procedure  412 , a customer provides and the IVR module  202  receives an audible of answer of Yes to procedure  410 . At procedure  414 , the IVR module  202  responds with an audible query to the user device  140  of the customer  142  that asks for the customer&#39;s identification information (e.g., mobile number, name, address). At procedure  416 , the customer  142  sends an audible answer with the customer&#39;s identification information. The IVR module  202  then transfers the audible data with the audible answer to the CP application  210 , which is an example of the AI engine  210 . 
     The CP application  210  is configured to convert the audible data into textual data at procedure  418 . The CP application  210  sends the textual data to the BSS  206  where the BSS  206  looks up the customer information at procedure  420 . At procedure  422 , the BSS  206  sends the customer information to the CP application  210 . The IVR module  202  then sends an audible query that asks for the customer service inquiry, at procedure  424 . At procedure  426 , the user device  140  sends audio to the IVR module  202  with the customer inquiry, where the IVR module  202  converts the audio into auditory data and the auditory data into textual data. The textual data is sent to the CP application  210 , where the CP application  210  identifies a category of the customer inquiry and identifies a search query from the textual data at procedure  428 . At procedure  430 , the CP application  210  is configured to search through customer service resolution data structures based on the search query and find the customer service resolution data structures related to a target automated customer service resolution associated with a previous customer service inquiry that most closely matches the search inquiry. The target automated customer service resolution is also implemented at procedure  430 . A response is provided to the customer service inquiry, which is sent by the IVR module  202  to the user device  140  at procedure  432 . 
     In some embodiments, a call is made to a customer service representative by the BSS  206  at procedure  434 . An input from the customer service representative is received by the AI engine  210  at procedure  436 . In some embodiments, this occurs when the customer  142  selects to talk to a customer service representative. The AI engine  210  is configured to search through customer service resolution data structures based on the search query and find the customer service resolution data structures related to a target automated customer service resolution associated with a previous customer service inquiry that most closely matches the search inquiry at procedure  438 . At procedure  440 , the target automated customer service resolution is implemented and an answer to the customer service inquiry is transmitted by the IVR module  202  to the user device  140 . 
     Within procedures  404  are procedures  442 ,  443 ,  444 ,  445 ,  446 ,  447 . Procedures  404  relate to procedures that occur when the customer  142  is a non-contract customer and the customer service inquiry has a target automated customer service resolution. Flow begins at procedures  442 . At procedure  442 , a customer  142  provides and the IVR module  302  receives an audible of answer of No to procedure  410 . The IVR module  202  then sends an audible query that asks for the customer  142  to provide the customer service inquiry as speech into the user device  140  at procedure  443 . At procedure  444 , the user device  140  sends audio to the IVR module  202  with the customer service inquiry, where the IVR module  202  converts the audio into auditory data and the auditory data into textual data. The textual data is sent to the CP application  210 , where the CP application  210  identifies a category of the customer service inquiry and identifies a search query from the textual data at procedure  445 . At procedure  446 , the CP application  210  is configured to search through customer service resolution data structures based on the search query and find the customer service resolution data structures related to a target automated customer service resolution associated with a previous customer service inquiry that most closely matches the search inquiry. The target automated customer service resolution is also implemented at procedure  446 . A response is provided to the customer service inquiry, which is sent by the IVR module  202  to the user device  140  at procedure  447 . 
     Within procedures  406  are procedures  448 ,  449 ,  450 ,  451 ,  452 ,  453 ,  454 ,  455 ,  456 . Procedures  406  relate to procedures that occur when the customer  142  is a non-contract customer and the customer inquiry does not initially find a target automated customer service resolution. These procedures assume that at procedure  442 , a customer  142  provides and the IVR module  302  receives an audible of answer of No to procedure  410 . 
     The IVR module  202  sends an audible query to the user device  140  of the customer  142  that asks for speech from the customer  142  that states the customer service inquiry, at procedure  448 . At procedure  449 , the user device  140  sends audio to the IVR module  202  with the customer service inquiry, where the IVR module  202  converts the audio into auditory data and the auditory data into textual data. The textual data is sent to the CP application  210 , where the CP application  210  identifies a category of the customer service inquiry and identifies a search query from the textual data at procedure  450 . At procedure  451 , the CP application  210  is configured to search through customer service resolution data structures based on the search query. However, none of the customer service resolution data structures identify a target automated customer service resolution that matches the search inquiry. Thus, the CP application  210  suggest a similar customer service inquiry (also referred to as query or suggested query) from the previous customer inquiry in the customer service resolution data structures at procedure  451 . At procedure  452 , the IVR module  202  transmits an audible message to the user device  140  stating the suggested query and asking that the customer  142  confirm that the suggested customer service inquiry is applicable. At procedure  453 , the customer  142  sends a response of yes through the user device  140  to the IVR module  202 . At procedure  454 , the IVR module  202  converts indicates that the suggested customer service inquiry is applicable so that a search is performed based on the suggested customer service inquiry. At procedure  455 , the CP application  210  is configured to search through customer service resolution data structures based on the suggested search query and find the customer service resolution data structures related to a target automated customer service resolution associated with a previous customer service inquiry that most closely matches the suggested search query. The target automated customer service resolution is also implemented at procedure  455 . A response is provided to the suggested query, which is sent by the IVR module  202  to the user device  140  at procedure  456 . 
     Procedures  457 ,  458 ,  459 ,  460   461 ,  462 ,  463  are implemented after procedures  402 ,  404 , and/or  406 , in accordance with some embodiments. At procedure  457 , the IVR module  202  sends audio to the user device  140  asking the customer  142  if the customer service inquiry was solved. If the customer  142  sends audio with an answer of no to the IVR module  202 , flow proceeds to procedure  424  where procedures  424 - 440  are implemented, in accordance with some embodiments. If the customer  142  sends audio with an answer of no to the IVR module  202 , flow proceeds to procedure  444  where procedures  444 - 447  are implemented, in accordance with some embodiments. If the customer  142  sends audio with an answer of no to the IVR module  202  flow proceeds to procedure  449  where procedures  449 - 456  are implemented, in accordance with some embodiments. Otherwise, the customer  142  sends audio with an answer of yes to the IVR module  202  at procedure  458 . At procedure  459 , the IVR module  202  sends audio or text to the user device  140  with a survey. At procedure  460 , the IVR module  202  receives an audio or textual response to the survey from the user device  140  of the customer  142 . At procedure  461 , the CP application  210  stores the survey and applies a machine learning process based on the answers to the survey so that the CP application  210  learns how to select the target automated customer service resolutions (e.g., target playbooks) from the plurality of automated customer service resolutions. Furthermore, at procedure  462 , a log of the procedures that were implemented is created, which creates a new automated customer service resolution in some embodiments. Finally, at procedure  463 , the IVR module  202  closes the conversation and ends the call with the user device  140 . 
       FIG.  5    is a visual representation of an automated decision tree  500 , in accordance with some embodiments. 
     The automated decision tree  500  corresponds with the automated customer service resolutions  126  of  FIG.  1   , the playbooks  220  of  FIG.  2   , and the playbooks  320  in  FIG.  3   . 
     The automated decision tree  500  includes a set of automated procedures  502 - 520  that are implemented by the automated customer resolution software  122  (See  FIG.  1   ) in an automated manner. The automated decision tree  500  relates to automated procedures  502 - 520  when a customer loses their mobile user device. However, this particular customer inquiry is simply exemplary. In other embodiments, the customer service inquiry is related to any type of problem, request or question related to customer service that is implementable in an automated manner or at least in a partially automated manner by the automated customer resolution software  122 . 
     Flow begins at automated procedure  502 . At automated procedure  502 , the automated customer resolution software  122  requests that the customer enter their mobile number. If the mobile number is received, the automated customer resolution software  122  looks up the customer details regarding their mobile user device. If the customer details are not found, a set of procedures  506  are followed. If the customer details are found, the automated customer resolution software  122  is configured to obtain the customer details at procedure  508 . At automated procedure  510 , the automated customer resolution software  122  determines that information related to the mobile device&#39;s subscriber identity module (SIM) is not included in the customer details. Alternatively, at automated procedure  512 , the information related to the mobile device&#39;s SIM is found. At procedure  514 , the automated customer resolution software  122  is unable to connect to the SIM. Alternatively, at procedure  516 , the automated customer resolution software  122  is configured to connect to the SIM. At automated procedure  518 , the automated customer resolution software  122  continues suspending the operation of the SIM since a suspension operation was already started. Alternatively, at automated procedure  520 , a suspension operation is initiated for the SIM. 
       FIG.  6    is a flowchart  600  related to a customer service method, in accordance with some embodiments. 
     Flowchart  600  is implemented by the automated customer resolution software  122  in  FIG.  1   , the automated customer resolution software  200  in  FIG.  2   , or the automated customer resolution software  300  in  FIG.  3   , in accordance with some embodiments. Flowchart  600  includes blocks  602 - 610 . Flow begins at block  602 . 
     At block  602 , a call with a user device associated with a customer. An example of block  602  is procedure  408  in  FIG.  4   . An example of a user device is user device  140  in  FIG.  1   . An example of a customer is customer  142  in  FIG.  1    and  FIG.  4   , customer  212  in  FIG.  2   , and customer  312  in  FIG.  3   . Flow then proceeds to block  604 . 
     At block  604 , an audible inquiry request is transmitted to the user device during the call, wherein the audible inquiry request is playable through the user device and asks for the customer to describe an inquiry. An example of block  604  is shown in procedure  424 , procedure  443 , and procedure  448  in  FIG.  4   . Flow then proceeds to block  606 . 
     At block  606 , auditory data is obtained from the user device in response to transmitting the audible inquiry request, wherein the auditory data is of a voice with speech related to the inquiry. An example of block  606  is shown as procedure  426 , procedure  444 , and procedure  449  in  FIG.  4   . An example of auditory data is shown as auditory data  123  in  FIG.  1   . Flow then proceeds to block  608 . 
     At block  608 , the auditory data is converted into textual data. Examples of block  608  include portions of procedure  428 , procedure  450 , and procedure  451  in  FIG.  4   . An example of the textual data includes textual data  124  in  FIG.  1   . Flow then proceeds to block  610 . 
     At block  610 , a target automated resolution is selected for the inquiry from a plurality of automated resolutions based on the textual data and a resolution data structure of a plurality of resolution data structures, wherein each of the resolution data structures relates to an automated resolution of the plurality of automated resolutions. Examples of block  610  include procedure  430 , procedure  446 , and procedure  455 . Examples of automated resolutions includes automated customer service resolutions  126 , playbooks  220  in  FIG.  2   , playbooks  320  in  FIG.  3   , and the automated decision tree  500  in  FIG.  5   . Example of resolution data structures include customer service resolution data structures  125  in  FIG.  1   . 
       FIG.  7   - FIG.  9    include different flowcharts  700 ,  800 ,  900  that are implemented after the flowchart  600 . 
     In some embodiments, flowchart  700  is implemented after flowchart  600  while flowcharts  800 ,  900  are not implemented. 
     In some embodiments, flowchart  800  is implemented after flowchart  600  while flowcharts  700 ,  900  are not implemented. 
     In some embodiments, flowchart  900  is implemented after flowchart  600  while flowcharts  700 ,  800  are not implemented. 
     Flowchart  700  includes block  702 . At block  702 , the target automated resolution is executed in response to selecting the target automated resolution for the inquiry. In some embodiments, no additional procedures or blocks are executed between block  610  and block  702 . In some embodiments, examples of block  702  are included in procedure  430 , procedure  446 , and procedure  455   
     In  FIG.  8   , flowchart  800  includes block  802 - 804 . In some embodiments, block  802  begins after block  610 . At block  802 , customer input data is received, wherein the customer input data is a selection by a customer of the target automated resolution. In some embodiments, the automated customer resolution software  122  first ask the customer whether the customer  142  would like to implement the target automated customer service resolution  126  resulting from the search of the customer service resolution data structures  125 . Flow then proceeds to block  804 . 
     At block  804 , the target automated resolution is executed in response to receiving the customer input data. In some embodiments, if the customer  142  answers that yes, the customer would like to implement the target automated customer service resolution  126 . In response, the automated customer resolution software  122  implements the target automated customer service resolution  126 . 
     In  FIG.  9   , flowchart  900  includes block  902 - 906 . In some embodiments, block  902  begins after block  610 . At block  802 , customer input data is received, wherein the customer input data is a selection by a customer to transfer a call related to the inquiry to a user device related to an customer service representative. In some embodiments, the automated customer resolution software  122  first ask the customer whether the customer  142  would like to talk to an customer service representative. Examples of the user device include user device  130  in  FIG.  1   . Examples of the customer service representative are the customer service representative  132  shown in  FIG.  1    and the customer service representative  330  shown in  FIG.  3   . In some embodiments, the customer answers yes meaning that the customer would like to talk to the customer service representative. Flow then proceeds to block  904 . 
     At block  904 , the customer service representative is presented with an option through the user device to execute the target automated resolution for the inquiry. Flow then proceeds to block  906 . 
     At block  906 , the target automated resolution is executed in response to receiving customer service representative input data that the option has been selected by the customer service representative. In some embodiments, the customer service representative  132  decides after listening to the customer  142  that the target automated customer service resolution  126  is the best way to resolve the problem and selects the option through the user device  130 . In response, the automated customer resolution software  122  implements the target automated customer service resolution  126 . 
     In some embodiments, a method, includes: converting auditory data into textual data, wherein the auditory data is of a voice with speech related to an inquiry; and selecting, using a computer device, a target automated resolution for the inquiry from a plurality of automated resolutions based on the textual data and a resolution data structure of a plurality of resolution data structures, wherein each of the resolution data structures relates to an automated resolution of the plurality of automated resolutions. In some embodiments, the method further includes executing the target automated resolution in response to selecting the target automated resolution for the inquiry. In some embodiments, the method further includes receiving customer input data, wherein the customer input data is a selection by a customer of the target automated resolution; and executing the target automated resolution in response to receiving the customer input data. In some embodiments, the method further includes: receiving customer input data, wherein the customer input data is a selection by a customer to transfer a call related to the inquiry to a user device related to an customer service representative; presenting the customer service representative with an option through the user device to execute the target automated resolution for the inquiry; and executing the target automated resolution for the inquiry in response to receiving customer service representative input data that the option has been selected by the customer service representative. In some embodiments, the target automated customer service resolution includes an automated decision tree. In some embodiments, the method of claim further includes establishing a call with a user device associated with a customer; transmitting audible inquiry request to the user device during the call, wherein the audible inquiry request is playable through the user device and asks for the customer to describe a customer service inquiry; obtaining the auditory data from the user device in response to transmitting the audible inquiry request. In some embodiments, selecting, using the computer device, the target automated resolution for the inquiry based on the textual data and the resolution data structures includes implementing an artificial intelligence (AI) engine that is configured to select the automated resolution for the inquiry based on the textual data and the resolution data structures. 
     In some embodiments, a computer system, includes: a non-transient computer readable medium that stores computer executable instructions; at least one processor operably associated with the non-transient computer readable medium, wherein when the at least one processor executes the computer executable instructions, the processor is configured to: convert auditory data into textual data, wherein the auditory data is of a voice with speech related to an inquiry; and select a target automated resolution for the inquiry from a plurality of automated solutions based on the textual data and the resolution data structures, wherein each of the resolution data structures relates to an automated resolution of the plurality of automated resolutions. In some embodiments, the at least one processor is further configured to execute the target automated resolution in response to selecting the target automated resolution for the inquiry. In some embodiments, the at least one processor is further configured to: receive customer input data, wherein the customer input data is a selection by a customer of the target automated resolution; and execute the target automated resolution in response to receiving the customer input data. In some embodiments, the at least one processor is further configured to: receive customer input data, wherein the customer input data is a selection by a customer to transfer a call related to the inquiry to a user device related to a customer service representative; present the customer service representative with an option through the user device to execute the target automated resolution for the inquiry; and execute the target automated resolution for the inquiry in response to receiving customer service representative input data that the option has been selected by the customer service representative. In some embodiments, the target automated resolution includes an automated decision tree. In some embodiments, the at least one processor is further configured to: establish a call with a user device associated with a customer; transmit audible inquiry request to the user device during the call, wherein the audible inquiry request is playable through the user device and asks for the customer to describe a customer service inquiry; obtain the auditory data from the user device in response to transmitting the audible inquiry request. In some embodiments, the at least one processor is configured to select, using the computer device, the target automated resolution for the inquiry based on the textual data and the resolution data structures by: implementing an artificial intelligence (AI) engine that is configured to select the automated resolution for the inquiry based on the textual data and the resolution data structures. 
     In some embodiments, a non-transient computer readable medium that stores computer executable instructions, wherein when at least one processor executes the computer executable instructions, the processor is configured to: convert auditory data into textual data, wherein the auditory data is of a voice with speech related to an inquiry; and select a target automated resolution for the inquiry from a plurality of automated solutions based on the textual data and the resolution data structures, wherein each of the resolution data structures relates to an automated resolution of the plurality of automated resolutions. In some embodiments, the at least one processor is further configured to execute the target automated resolution in response to selecting the target automated resolution for the inquiry. In some embodiments, the at least one processor is further configured to: receive customer input data, wherein the customer input data is a selection by a customer of the target automated resolution; and execute the target automated resolution in response to receiving the customer input data. In some embodiments, the at least one processor is further configured to: receive customer input data, wherein the customer input data is a selection by a customer to transfer a call related to the inquiry to a user device related to a customer service representative; present the customer service representative with an option through the user device to execute the target automated resolution for the inquiry; and execute the target automated resolution for the inquiry in response to receiving customer service representative input data that the option has been selected by the customer service representative. In some embodiments, the at least one processor is further configured to: establish a call with a user device associated with a customer; transmit audible inquiry request to the user device during the call, wherein the audible inquiry request is playable through the user device and asks for the customer to describe a customer service inquiry; obtain the auditory data from the user device in response to transmitting the audible inquiry request. In some embodiments, the at least one processor is configured to select, using the computer device, the target automated resolution for the inquiry based on the textual data and the resolution data structures by: implementing an artificial intelligence (AI) engine that is configured to select the automated resolution for the inquiry based on the textual data and the resolution data structures. 
     The foregoing outlines features of several embodiments so that those skilled in the art may better understand the aspects of the present disclosure. Those skilled in the art should appreciate that they may readily use the present disclosure as a basis for designing or modifying other processes and structures for carrying out the same purposes and/or achieving the same advantages of the embodiments introduced herein. Those skilled in the art should also realize that such equivalent constructions do not depart from the spirit and scope of the present disclosure, and that they may make various changes, substitutions, and alterations herein without departing from the spirit and scope of the present disclosure. 
     Aspects of the present disclosure are best understood from the following detailed description when read with the accompanying figures. It is noted that, in accordance with the standard practice in the industry, various features are not drawn to scale. In fact, the dimensions of the various features may be arbitrarily increased or reduced for clarity of discussion.