DESC:RESERVATION OF RIGHTS
[0001] A portion of the disclosure of this patent document contains material which is subject to intellectual property rights such as, but are not limited to, copyright, design, trademark, integrated circuit (IC) layout design, and/or trade dress protection, belonging to Jio Platforms Limited (JPL) or its affiliates (herein after referred as owner). The owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all rights whatsoever. All rights to such intellectual property are fully reserved by the owner.

TECHNICAL FIELD
[0002] The present disclosure relates to a field of Long-Term Evolution (LTE)/4G/5G mobile networks, and specifically to a system and a method for user feedback loop management thereby addressing customer experience management and network operations.

BACKGROUND
[0003] The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.
[0004] In most of the mobile communication networks, network operations teams may depend on Fault Management, Configuration Management, Accounting Management, Performance Management, and Security Management (FCAPS) functions provided by various network nodes/functions. The use of Fault Management and Performance Management functionalities enables a mobile network operator to carry out certain aspects – such as, but not limited to, restoration of a fault on receiving an alarm or augmentation of capacity of a network node or signalling link when the performance counters indicate utilization going beyond certain pre-defined threshold. The existing methods implemented by network operations are very useful for any mobile network operator in addressing network node level issues or capacity planning related aspects. However, the existing methods of network operations lack in aspects related to identification of customer perceived issues (e.g., slow internet speed/throughput, poor voice quality, frequent call drops, and the like). Further, a majority of issues faced by customers may be due to a dynamic Radio Frequency (RF) environment. More particularly, the existing systems and methods do not provide for any feedback mechanism subsequent to executing a corrective action or resolution mechanism.
[0005] Therefore, there is a well-felt need to create a product/service that can effectively address customer-perceived issues and address at least the issues highlighted above.

OBJECTS OF THE PRESENT DISCLOSURE
[0006] It is an object of the present disclosure to provide a system and a method for addressing customer experience management and network operations.
[0007] It is an object of the present disclosure to provide a best customer experience through automated/proactive actions and a closed-loop feedback mechanism.
[0008] It is an object of the present disclosure to provide improved customer experience leading to higher customer satisfaction by focusing on issues that continue to impact the customer experience even after the resolution or corrective action.
[0009] It is an object of the present disclosure to reduce customer complaints and improve an efficiency of network operations teams through automated and accurate diagnosis of issues.
[00010] It is an object of the present disclosure to determine a user experience score to identify issues facing by users.
[00011] It is an object of the present disclosure to automatically implement the corrective actions corresponding to the root cause of each issue.

SUMMARY
[00012] This section is provided to introduce certain objects and aspects of the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.
[00013] In an aspect, the present disclosure relates to a system for user feedback loop management. The system includes one or more processors and a memory operatively coupled to the one or more processors, wherein the memory includes processor-executable instructions, which on execution, cause the one or more processors to receive user experience data from a plurality of users and determine a first user experience score based on the received user experience data. The one or more processors are to determine one or more issues faced by each user based on the first user experience score and determine a root cause of the one or more issues faced by said each user. Further, the one or more processors are to determine one or more corrective actions corresponding to the root cause of the one or more issues and determine a critical level of the root cause of the one or more issues. Furthermore, the one or more processors are to prioritize the one or more corrective actions based on the critical level of the root cause of the one or more issues and automatically implement the one or more corrective actions corresponding to the root cause of the one or more issues based on the prioritization.
[00014] In an embodiment, the user experience data may include at least one of: voice services, high speed internet services, Radio Frequency (RF) experiences, an average network coverage experience of a user, user device experiences, Key Performance Indicators (KPIs), Key Quality Indicators (KQIs), user complaints, a model of user device, a Subscriber Identity Module (SIM) card version, performance counters of all cells in a network, configuration data of all the cells, user activities, various alarms, indications of service outage, and interactions between the user and the network.
[00015] In an embodiment, the one or more issues may include at least one of: poor network availability, radio performance issue, backhaul outages, front haul outages, load imbalance, capacity issue, and a network coverage.
[00016] In an embodiment, the one or more corrective actions may be performed with respect to work orders, wherein the one or more corrective actions may include at least one of: automated corrective actions and manual corrective actions.
[00017] In an embodiment, the automated corrective actions may include at least one of: an RF optimization via a Remote Electrical Tilt (RET), a physical optimization work order, a capacity augmentation work order, an infrastructure related work order, and a connectivity related work order. The automated corrective actions are at least one of physical or digital.
[00018] In an embodiment, the one or more processors may track a completion status of the implemented one or more corrective actions and determine a second user experience score based on the completion status of the implemented one or more corrective actions. Further, the one or more processors may compare the first user experience score and the second user experience score and adjust a prioritization technique to assign higher priority to at least one action that has maximum positive outcome related to a customer experience.
[00019] In an embodiment, the system may include a user interface to display information related to the user experience data of said each user, the first user experience score of said each user, a second user experience score of said each user, an outage view of said each user, a prioritized task view for said each user, and a task resolution action for said each user.
[00020] In another aspect, the present disclosure relates to a method for user feedback loop management. The method includes receiving, by one or more processors, user experience data from a plurality of users and determining, by the one or more processors, a first user experience score based on the received user experience data. Further, the method includes determining, by the one or more processors, one or more issues faced by each user based on the first user experience score and determining, by the one or more processors, a root cause of the one or more issues faced by said each user. The method includes determining, by the one or more processors, one or more corrective actions corresponding to the root cause of the one or more issues and determining, by the one or more processors, a critical level of the root cause of the one or more issues. Furthermore, the method includes prioritizing, by the one or more processors, the one or more corrective actions based on the critical level of the root cause of the one or more issues and automatically implementing, by the one or more processors, the one or more corrective actions corresponding to the root cause of the one or more issues based on the prioritization.
[00021] In an embodiment, the method may include performing, by the one or more processors, the one or more corrective actions with respect to work orders, wherein the one or more corrective actions may include at least one of: automated corrective actions and manual corrective actions.
[00022] In an embodiment, the method may include tracking, by the one or more processors, a completion status of the implemented one or more corrective actions and determining, by the one or more processors, a second user experience score based on the completion status of the implemented one or more corrective actions. Further, the method may include comparing, by the one or more processors, the first user experience score and the second user experience score and adjusting, by the one or more processors, a prioritization technique to assign higher priority to at least one action that has maximum positive outcome related to a customer experience.

BRIEF DESCRIPTION OF THE DRAWINGS
[00023] In the figures, similar components and/or features may have the same reference label. Further, various components of the same type may be distinguished by following the reference label with a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label.
[00024] The diagrams are for illustration only, which thus is not a limitation of the present disclosure, and wherein:
[00025] FIG. 1A illustrates an exemplary network architecture 100A in which or with which embodiments of the present disclosure may be implemented.
[00026] FIG. 1B illustrates an example block diagram 100B of a system 108 for user feedback loop management, in accordance with an embodiment of the present disclosure.
[00027] FIG. 2 illustrates an exemplary process flow diagram 200 for capturing true customer experience in a Customer Health Card (CHC), in accordance with an embodiment of the present disclosure.
[00028] FIG. 3 illustrates an exemplary alarm correlation for depiction of outage and interference 300, in accordance with embodiments of the present disclosure.
[00029] FIG. 4 illustrates a high level architecture 400 and process flow for capturing true customer experience in the CHC, in accordance with embodiments of the present disclosure.
[00030] FIG. 5 illustrates a high level process flow 500 for capturing true customer experience in the CHC and for providing a closed loop feedback based on the customer experience, in accordance with an embodiment of the present disclosure.
[00031] FIG. 6 illustrates an exemplary flow chart of a method 600 for user feedback loop management, in accordance with an embodiment of the disclosure.
[00032] FIGs. 7A-7V illustrate example representations 700A-700V depicting User Interface (UI) used in user feedback loop management, in accordance with an embodiment of the disclosure.
[00033] FIG. 8 illustrates an exemplary computer system 800 in which or with which embodiments of the present disclosure may be implemented.

DETAILED DESCRIPTION
[00034] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[00035] The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the invention as set forth.
[00036] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments.
[00037] Also, it is noted that individual embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.
[00038] The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive—in a manner similar to the term “comprising” as an open transition word—without precluding any additional or other elements.
[00039] Reference throughout this specification to “one embodiment” or “an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[00040] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items.
[00041] The disclosed system takes the approach of starting with daily mapping of individual customer experience in a “Customer Health Card” score. The Customer Health Card (CHC), a concept introduced herein, may use data captured by cells (i.e., Radio Heads) for all the interactions that take place between a customer and a network. Using CHC data, various customer experience impacting issues are identified using automated process. Root-causes for all the issues identified are determined through automated process and all solutions/corrective actions for all the root-causes are identified. In some embodiments, through a specialized method, corrective actions are prioritized to implement only those actions through which majority of the issues are resolved. The corrective actions or solutions may be related to automated actions or manual actions through Service Level Agreement (SLA) driven work-orders/workflows assigned to concerned engineers. All the automated/manual actions are tracked for completion and on completion of all the actions, the efficacy of the whole process is judged by comparing CHC score after completion of corrective actions against the score before starting the whole cycle. In an embodiment, if no significant improvement in the customer experience is observed, then prioritization technique may be tweaked based on detailed analysis of all the actions identified through automated process. The whole process may be referred to as “Customer Close Looping.”
[00042] Various embodiments of the present disclosure will be explained in detail with reference to FIGs. 1A-8.
[00043] The terms “user” and “customer” are used interchangeably throughout the specification.
[00044] FIG. 1A illustrates an exemplary network architecture 100A in which or with which embodiments of the present disclosure may be implemented.
[00045] As illustrated in FIG. 1A, by way of an example and not by limitation, the exemplary network architecture 100A may include a plurality of computing devices 104-1, 104-2…104-N, which may be individually referred as the computing device 104 and collectively referred as the computing devices 104.
[00046] In an embodiment, the computing device 104 may include smart devices operating in a smart environment, for example, an Internet of Things (IoT) system. In such an embodiment, the computing device 104 may include but is not limited to, smart phones, smart watches, smart sensors (e.g., mechanical, thermal, electrical, magnetic, etc.), networked appliances, networked peripheral devices, networked lighting system, communication devices, networked vehicle accessories, networked vehicular devices, smart accessories, tablets, smart television (TV), computers, smart security system, smart home system, other devices for monitoring or interacting with or for the users and/or entities, or any combination thereof.
[00047] A person of ordinary skill in the art will appreciate that the computing device or a user equipment 104 may include, but is not limited to, intelligent, multi-sensing, network-connected devices, that may integrate seamlessly with each other and/or with a central server or a cloud-computing system or any other device that is network-connected.
[00048] In an embodiment, the computing device 104 may include, but is not limited to, a handheld wireless communication device (e.g., a mobile phone, a smart phone, a phablet device, and so on), a wearable computer device(e.g., a head-mounted display computer device, a head-mounted camera device, a wristwatch computer device, and so on), a Global Positioning System (GPS) device, a laptop computer, a tablet computer, or another type of portable computer, a media playing device, a portable gaming system, and/or any other type of computer device with wireless communication capabilities, and the like. In an embodiment, the computing device 104 may include, but is not limited to, any electrical, electronic, electro-mechanical, or an equipment, or a combination of one or more of the above devices such as virtual reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other computing device, wherein the computing device 104 may include one or more in-built or externally coupled accessories including, but not limited to, a visual aid device such as a camera, an audio aid, a microphone, a keyboard, and input devices for receiving input from the user or the entity such as touch pad, touch enabled screen, electronic pen, and the like. A person of ordinary skill in the art may appreciate that the computing device 104 may not be restricted to the mentioned devices and various other devices may be used.
[00049] In an exemplary embodiment, the computing device/user equipment 104 may communicate with the system 108 through a network 106. The network 106 may include, by way of example but not limitation, at least a portion of one or more networks having one or more nodes that transmit, receive, forward, generate, buffer, store, route, switch, process, or a combination thereof, etc. one or more messages, packets, signals, waves, voltage or current levels, some combination thereof, or so forth. The network 106 may include, by way of example but not limitation, one or more of: a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a public-switched telephone network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, some combination thereof.
[00050] In an embodiment, the system 108 may receive user experience data from users and determine a first user experience score based on the received user experience data. The system 108 may determine issues faced by each user based on the first user experience score and determine a root cause of the issues faced by the users. Further, the system 108 may determine corrective actions corresponding to the root cause of the issues and determine a critical level of the root cause of the issues. Further, the system 108 may prioritize the corrective actions based on the critical level of the root cause of the issues and automatically implement the corrective actions corresponding to the root cause of the issues based on the prioritization.
[00051] Although FIG. 1A shows exemplary components of the network architecture (100A), in other embodiments, the network architecture 100A may include fewer components, different components, differently arranged components, or additional functional components than depicted in FIG. 1A. Additionally, or alternatively, one or more components of the network architecture 100A may perform functions described as being performed by one or more other components of the network architecture 100A.
[00052] FIG. 1B illustrates an example block diagram 100B of a system 108 for user feedback loop management, in accordance with an embodiment of the present disclosure.
[00053] Referring to FIG. 1B, the system 108 may include one or more processors 110, a memory 112, and an interface(s) 114. The one or more processors 110 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that manipulate data based on operational instructions. Among other capabilities, the one or more processor(s) 110 may be configured to fetch and execute computer-readable instructions stored in the memory 112 of the system 108. The memory 112 may store one or more computer-readable instructions or routines, which may be fetched and executed to create or share the data units over a network service. The memory 112 may include any non-transitory storage device including, for example, volatile memory such as Random-Access Memory (RAM), or non-volatile memory such as Erasable Programmable Read-Only Memory (EPROM), flash memory, and the like.
[00054] The interface(s) 114 may comprise a variety of interfaces, for example, a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) 114 may facilitate communication of the system 108 with various devices coupled to it. The interface(s) 114 may also provide a communication pathway for one or more components of the system 108. Examples of such components include, but are not limited to, processing engine(s) 116 and a database 120, where the database 120 may include data that is either stored or generated as a result of functionalities implemented by any of the components of the processing engine(s) 116.
[00055] In an embodiment, the processing engine(s) 116 may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) 116. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) 116 may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the one or more processor(s) 110 may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) 116. In such examples, the system 108 may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the system 108 and the processing resource. In other examples, the processing engine(s) 116 may be implemented by an electronic circuitry. The processing engine(s) 116 may include a user experience score determination module 122, root cause determination module 124, corrective action determination module 126, and other module(s) 128.
[00056] The system 108 may receive user experience data from a plurality of users, where the user experience data may include, but not limited to, voice services, high speed internet services, Radio Frequency (RF) experiences, an average network coverage experience of a user, user device experiences, Key Performance Indicators (KPIs), Key Quality Indicators (KQIs), user complaints, a model of user device, a Subscriber Identity Module (SIM) card version, performance counters of all cells in a network, configuration data of all the cells, user activities, various alarms, indications of service outage, interactions between the user and the network and the like.
[00057] In an embodiment, the user experience score determination module 122 may determine a first user experience score based on the received user experience data from the users. The root cause determination module 124 may determine issues faced by the users based on the first user experience score, where the issues may include, but not limited to, poor network availability, radio performance issue, backhaul outages, front haul outages, load imbalance, capacity issue, and a network coverage. Once the issues are determined, the root cause determination module 124 may determine a root cause for the issues faced by the users. Once the root cause of the issues are identified, the corrective action determination module 126 may determine corrective actions corresponding to the root cause of the issues, where the corrective action determination module 126 may determine a critical level of the root cause to prioritize the corrective actions based on the critical level of the root cause of the issues. Once the corrective action determination module 126 prioritizes the corrective action, the one or more processors 110 may automatically implement the corrective actions corresponding to the root cause of the issues based on the prioritization. In an embodiment, the corrective actions may include automated corrective actions or manual corrective actions, where the automated corrective actions may include, but not limited to, an RF optimization via a Remote Electrical Tilt (RET), a physical optimization work order, a capacity augmentation work order, an infrastructure related work order, and a connectivity related work order. In some embodiments, the automated corrective actions are physical. In some embodiments, the automated corrective actions are digital. In some embodiments, the corrective actions are performed with respect to work orders.
[00058] In an embodiment, the system 108 may track a completion status of the corrective actions that are implemented based on the prioritization. The user experience score determination module 122 may determine a second user experience score after the completion of the corrective actions to compare the first user experience score with the second user experience score. The user experience score determination module 122 may determine whether the second user experience score is equal to or greater than the first user experience or not. If the second user experience score is equal or greater than the first user experience, the system 108 may adjust a prioritization technique to assign higher priority to at least one action that has maximum positive outcome related to a customer experience.
[00059] The system 108 may include a user interface 118 which may be, but not limited to, a touchscreen display, monitor, and the like. The user interface 118 may display information related to the user experience data of the user, the first user experience score of the users, the second user experience score of the users, an outage view of the users, a prioritized task view for the users, and a task resolution action for the users. The other module(s) 128 may implement functionalities that supplement applications/functions performed by the processing engine 116.
[00060] FIG. 2 illustrates an exemplary process flow diagram 200 for capturing true customer experience in CHC, in accordance with an embodiment of the disclosure.
[00061] With respect to FIG. 2, the CHC is built on top of a Big Data Lake (BDL) platform, and data collected from various data sources is ingested into the BDL. In an embodiment, the data may be, for example, (a) RF transaction data/traces including measurement reports received from individual customers/their devices, (b) performance counters of all the cells (radio head) in the network, (c) configuration data of all the cells (including latitude/longitude, azimuth, height, tilt, MIMO configuration, propagation model, etc.), various alarms (e.g. cell or site outage alarms, interference alarms, infra alarms, etc.). The alarms may be, for example, (i) outage alarms, and (ii) interference alarms.
[00062] In case of outage alarms, whenever a cell site (radio head) experiences an outage (e.g. due to infrastructure failures such as power outage, poor battery or diesel generator (DG) failure, etc. or due to connectivity loss due to fiber cut, etc.), all the customers being served by the cell site, loose their radio connection with the site that has failed. Some of the customers may get latched on to neighbouring cell sites (radio heads) that may have overlapping radio coverage with a cell site that has failed. However, some of the customers may not be able to latch on to any other cell site due to a coverage hole created due to an outage of the cell site to which such customers were latched on or neighbouring cells that had overlapping coverage already in overload conditions so that they cannot accommodate additional customers. In another case, some of the customers may get latched on to neighbouring cells, but due to temporary overload conditions prevailing in those cells, some of the customers may face poor service quality (though, not a complete service outage). Further, all such customer experience impacts (degradation of service quality or no service at all) due to cell site outages are indicated in the CHC. Such data when available on a daily basis for several days helps in identifying the cells that are frequently affected and the impact of their outage (like a number of affected customers) may be easily gauged through gathered CHC data. The CHC data may then be used to prioritize and perform corrective actions.
[00063] In case of interference alarms, whenever a cell site (radio head) experiences heavy (i.e. interfering radio frequency has signal strength beyond a pre-defined threshold) interference in its radio frequency band, then such cell sites generate an alarm. Whenever the signal strength of interfering signal goes below a predefined threshold, the alarm is closed. During the time period between these two events, i.e., an onset of alarm and its abatement, all the customers being served by the given cell site are temporarily rendered non-communicative with the network as exchanges of information between mobile devices of the customers and the cell site shall be intelligible. In such conditions, the mobile devices of some of the customers may get served by different frequency bands (if available) and served by the same site that may not have any interference issue, or neighbouring cells have overlapping coverage with different frequency bands than the interfering signal. However, some of the customers may not get any service. This is due to their mobile devices not being able to latch onto another frequency band or some of them getting degraded service due to latching onto a different cell that is already overloaded. All such customer experience impacts (i.e., degradation of service quality or no service at all) arising due to interference is indicated in the CHC. Data captured with the CHC may be available on a daily basis for several days and may help in identifying, for example, the cells that are frequently affected, for gauging impact of interference issues (like the number of affected customers), and prioritizing corrective actions.
[00064] In an exemplary embodiment, the BDL further includes device details (e.g., make, model, bands supported, capabilities – like CA supported or not, etc.), SIM card details (e.g., SIM version, etc.), usage data of the customer, and many other data sources that are ingested in the BDL. Existing modules that may use these data sources may be integrated into the disclosed methods and systems for a closed customer looping.
[00065] As is illustrated in FIG. 2, using the various data sources mentioned above, the CHC is generated. The CHC contains different customer-perceived RF Coverage/service/usage/Mobile Device/SIM Card experience as well as a voice of the user and information about other events (like site/cell outage/interference etc.) that may result in providing a poor customer experience.
[00066] Further, with respect to FIG. 2, as a first step, an ingestion of data in the BDL is performed, where data from various data sources are ingested in an in-house big data platform called “Big Data Lake (BDL)”. Some of the most critical data sources that are ingested in the BDL such as, but not limited to 1. RF trace data 202, where the RF signalling traces and measurement reports generated by mobile devices are captured by each cell/site (RF head). The RF trace data captures all of the radio network events with key parameters such as (i) RF signal strength reported by mobile device, (ii) distance of the customer (i.e. customer’s mobile device) from the cell (RF head), (iii) location of the customer, where location is derived as accurately as possible by tweaking the methods, (iv) Reason for new RF connection (i.e., handover, fresh attach, redirection, etc.), (v) reason for the release of the RF connection, (vi) RF environment (e.g. inter-site-distance, signal strengths of neighbouring cells as ported by customer’s mobile device, etc.) of the cell to which the customer is latched-on; and (vii) Volume of the data exchanged (i.e., downloaded and uploaded) for each service (e.g., voice and packet data service), 2. RF performance counters 204, where the various RF performance counters are ingested in the BDL. Some of the critical performance counters that may cause poor customer experience are (i) Resource utilization reports, where these reports may indicate the utilization of various resources of each cell (RF Heads). If radio resources are overloaded, then customer experience is degraded, (ii) Service Usage Reports, where these reports indicate the data volume exchanged in each direction (from mobile to cell and vice versa), etc., 3. Fault or alarm data 204, where the fault or alarm data may indicate the onset or abatement of certain events such as outage or interference in the network, (i) various types of configuration data is ingested in the BDL. Some of the key configurations are (i) Configuration data of all the cells (including latitude/longitude, azimuth, height, tilt, MIMO configuration, propagation model, etc.), (ii) Configuration data of all the mobile devices (mapping of mobile device identifier (ID) with make, model, features supported, end-of-life status, etc.), (iii) Configuration data of all the SIM cards, etc. A subscription data 206 of the customers are ingested in the BDL platform.
[00067] At a second step 208 in FIG. 2, a correlation and analytics engine is used. Typically, custom logic and methods are used to analyze huge data available in the Big Data Lake (BDL) platform and correlate data from various sources to generate accurate customer experience KPIs. Further, automated logic and methods are used to indicate customer experience impact, within the CHC, due to the certain reasons such as, but not limited to RF coverage issues, Cell/Site outage impact in customer experience, Impact on customer experience due to high interference in a cell/site, Device issues (e.g. End-of-Life (EOL) devices having software bugs), Subscriber Identity Module (SIM) card issues.
[00068] At a third step 210 in FIG. 2, a daily customer health card is generated. Using the huge data available from various data sources within the BDL platform, the CHC module may generate a per-subscriber health card.
[00069] FIG. 3 illustrates at 300 an exemplary alarm correlation for the depiction of outage and interference, in accordance with embodiments of the present disclosure.
[00070] As illustrated in FIG. 3, an alarm file and a duration threshold may be sent as an input to an automation job module 302. The automation job module executes to provide information related to impacted customers that includes categorization, and impacted cells/evolved Node B (eNB) that includes a list of indirectly impacted International Mobile Subscriber Identity (IMSI).
[00071] FIG. 4 illustrates a high-level architecture and process flow 400 for capturing true customer experience in the CHC, in accordance with embodiments of the present disclosure.
[00072] With respect to FIG. 4, a system of records 404 may maintain network data 404A, customer data 404B, and device data 404C. The set of records is passed onto a system of instrumentation and data engineering 406 that includes information related to customer health card 406A, poor experience cells 406B, and poor experience locations 406C. Further, a system of intelligence 408 may use a Root Cause Fix (RCF) engine through a Big Data Lake (BDL) platform 408A and link it to a Network Performance and Optimization (NPO) engine 408B. The system of intelligence may extract data from the system of instrumentation and data engineering to execute next steps. Next, a system of interaction 410 may include a partner world hub 410A, and work orders 410B is executed. A field engineer working in the geography views and consumes these outputs on the system of interaction. These execute a system of operation and execute experience improvement verification through engineer 412. As may be appreciated, the system of records 404, the system of instrumentation and data engineering 406, the system of intelligence 408, and the system of interaction 410 together make up for a system of integration 402.
[00073] The disclosed system and method provide a holistic approach to address various current shortcomings, as RF issues are most difficult to address. To address one of the customer’s complaints, if a Mobile Network Operator (MNO) makes some changes in antenna configurations, it may lead to a poor experience for many other customers. Using big data analytics, capabilities to churn huge data generated by all the customers coupled with specialized methods that prioritize corrective actions ensures maximum benefit of a number of customers. This leads to ensuring that the actions for the benefit of the customers are holistic.
[00074] The disclosed system and method provide a fully automated approach where the whole process is automated that can be easily tweaked with configurable parameters. In addition, the disclosed system and method provide a modular and scalable solution that is highly modular so that it can accommodate new modules whenever they are developed and the framework built on top of a big data analytics platform is highly scalable. Further, the disclosed system and method have minimal manual efforts that cannot be automated.
[00075] FIG. 5 illustrates a high-level process flow 500 for capturing true customer experience in the Customer Health Card (CHC) and for providing closed-loop feedback based on customer experience, in accordance with an embodiment of the present disclosure.
[00076] At step 502, the CHC module/engine generates and aggregates the CHC details and saves it in the Big Data Lake (BDL) platform. For example, all customer events for the last 30 days that capture coverage, data speed, cell quality index, consumption, voice, location, and availability details are aggregated. The generated CHCs and the aggregated data are stored in the BDL platform.
[00077] Steps 504 and 506 may be executed by a Root-Cause-Fix (RCF) engine/module that includes executing methods to access the BDL and analyze the issues related to outage service site/neighbour cell, backhaul problems, quality issues, capacity/coverage issues. The RCF engine/module may further propose actions for the identified/analysed issues, for example, availability improvement actions, availability/augmentation actions, optimization actions, planned BTG actions, etc. The RCF analysis is performed on every cell impacting customer experience as per the data aggregated at step 504 to identify digital and physical actions.
[00078] At step 508, a work order engine/module may analyze the digital and physical actions to be executed across all customers/sites. Further, the work order engine may scrub all actions against customer complaints and port out request data for priority actions. In an embodiment, the actions to be executed may be presented or published as a work order by the work order engine. The work order engine may be configured to facilitate the planning of actions based on capacity/coverage issues and planned BTG actions.
[00079] At step 510, a presentation module/engine (or the user interface application/module) may publish or present physical and digital action assignments, tracking information, and Service Level Agreements (SLAs). In an embodiment, all work orders and actions through the work engine/module, are extracted and provided to field organization leadership through a presentation module/engine which leads to effective governance on the field.
[00080] At step 512, a tracking module/engine is configured to track the experience improvement of the customer based on insights about the corrective actions or resolution implemented and the newly acquired customer health card data from the BDL. In an embodiment, the tracking module/engine implements a closed loop feedback between the outcomes of the actions performed or executed to resolve the issues identified earlier and the improvement in the same issues post the implementation of corrective actions.
[00081] In certain other embodiments, the proposed systems and methods improve customer experience of any mobile network (e.g., LTE, 4G, 5G, and 6G) through one or more automated and proactive actions. In an embodiment, the one or more automated/proactive actions include capturing daily experience of all the customers for their usage of Voice service, High Speed Internet service in the mobile operator network, radio frequency (RF) Experience, and Device Experience quantified as a “Customer Experience Score” (CES) included in the CHC.
[00082] The one or more automated/proactive actions include identifying issues faced by each customer while using High-Speed Internet and Voice services as well as any other coverage issues faced by the customer in the mobile network, finding the root-cause of all such issues being faced by the customers, finding solutions for all the identified issues, filtering and prioritizing the solutions in such a way that the issues faced by majority of the customers are addressed effectively. The one or more automated/proactive actions further include initiating automated workflows to implement the solutions identified as above and checking the efficacy of all the above-mentioned actions.
[00083] In an aspect of the disclosure, there is proposed a close looping or feedback process for customer experience improvement. The disclosed method involves implementing/generating the CHC indicating a score of customer’s overall experience in mobile operator’s network. In an embodiment, the disclosed system includes different modules/engines/processing units that are designed to take inputs from the CHC to automatically detect various issues that affect customer experience. In an embodiment, different issues and possible actions to resolve them are then passed through specialized methods to prioritize actions. In an embodiment, the actions finalized in previous step(s) trigger different modules/engines/processing units to initiate automated workflows to fix the identified issues. After different modules complete all their actions, a feedback trigger is generated to check CHC score to confirm whether the customer’s experience has improved or not. The same cycle may be repeated in an automated manner to effectively address customer experience affecting issues.
[00084] In an embodiment, the disclosed CHC is one of the aspects of the overall close looping process of the customer experience. In an embodiment, CHC captures the overall health of customer’s experience in the mobile operator’s network. This includes (A) the proactive/system-generated customer experience score card based on various network events as well as custom events defined in CHC and/or Key Performance Indicators (KPIs) and Key Quality Indicators (KQIs), (B) the customer’s own voice (data associated with customer complaints and any Mobile Number Portability requests generated by the customer), and (C) other allied information such as the mobile device (Make/Model) being used by the customer and version of subscriber identity module (SIM) card being used, etc.
[00085] In addition, the CHC may facilitate in capturing (a) each of customer’s daily average RF coverage experience, (b) service experience related to High Speed Internet (HSI) service and voice service, (c) specific network events such as cell (radio head) outage or high radio coverage interference that caused degradation in customer’s service experience, (d) mobile device (make/model) and SIM card being used by the customer, (e) service experience in different RF environments (indoor, outdoor, stationary, or mobile), etc. Details captured in the CHC help in automating an end-to-end process for proactive problem detection and resolution.
[00086] In an embodiment, the CHC enables to represent customer perceived service experience accurately. An objective of the CHC is to be able to generate a scorecard, for each of the customer, which represents customer satisfaction/dissatisfaction as accurately as possible.
[00087] In an embodiment, to map a customer perceived service experience accurately, some aspects are captured in the CHC The aspects may include, but not limited to, customer’s average (for each day) RF coverage experience in terms of site, sector, cell, and frequency band to which the customer has latched-on for majority of duration of the day, customer’s service experience in terms of percentage of total RF connections that had poor RF coverage, percentage of voice calls that had poor RF coverage, and percentage of packet data sessions that had poor RF coverage, voice of customer in terms of any RF coverage related complaints, any voice call related complaints, any packet data service related complaints and determine whether the customer requested for porting-out mobile number, daily consumption of services in terms of total data volume consumed, number of mobile originating (MO) calls made, total call duration of MO calls, number of mobile terminating (MT) calls received, and total call duration of MT calls, and device(s) used by the customer in terms of make and model of the device, indication of whether the device supports lower frequency band (for example, 850 MHz) for better indoor coverage, indication of whether the device supports carrier aggregation to support higher throughput, and indication of whether the device is an “end-of-life” device.
[00088] In an embodiment, apart from the above-mentioned points, impact of aspects are also captured for each of the user including, indication of whether the given customer faced service degradation or complete service outage due to a site or cell (RF head) outage, indication of whether the given customer faced service degradation or complete service outage due to powerful interference in radio channel, SIM card details (make/model/version), and packet data throughput experienced by the given customer.
[00089] The CHC may be implemented or built on top of a data platform. In an embodiment, data from various data sources, may be ingested into the data platform. The data source may include, but not limited to RF transactions data/traces including measurement reports received from individual customers/their devices, performance counters of all the cells (radio head) in the network, configuration data of all the cells (including latitude/longitude, azimuth, height, tilt, multiple-input/multiple-output (MIMO) configuration, propagation model, etc.), various alarms (e.g. cell or site outage alarms, interference alarms, Infra alarms, etc.), device details (make, model, bands supported, capabilities – like carrier aggregation (CA) supported or not, etc.), SIM card details (SIM version, etc.), and usage data of the customer.
[00090] In an embodiment, many other data sources may be ingested into the data platform. Such data sources may be used by some existing modules/engines/processing units and additional modules as proposed may be integrated into the system for the disclosed close looping process.
[00091] As described earlier, the disclosed closed looping process starts with a customer score card present in CHC and then initiates an automated process flow to identify customers having poor experience (proactively/reactively – based on CHC data). The process may further involve initiating automated workflows whereby Root-Cause-Analysis (RCA) and Root-Cause-Fix (RCF) processes may be executed and a feedback loop may be provided through improvement in the CHC scorecard. As may be appreciated, the CHC is a part of the customer closed looping (CCL) process.
[00092] In an exemplary embodiment, the solution for customer closed looping may be designed/implemented in a modular framework. Various modules/engines may be implemented according to a broad process flow, as described below.
[00093] A CHC module/engine may use the huge data available from various data sources within the big data platform to generate a per subscriber health card may include types of data, not limited to, average coverage experience of the customer (with most frequently latched cell, average RF signal strength experienced by customer, etc.), average High Speed Internet (HSI) service experience of the customer (e.g. average throughput experienced by the customer), average voice experience (number of calls, successful calls count, dropped calls count, etc.), 4device details, and indication of whether customer experienced service outage or degradation due to any cell outage, indication whether customer faced poor RF experience due to interference, etc.
[00094] Another module/engine (e.g., an analysis engine/module or RCF engine/module) may periodically take inputs from the CHC module and identify worst affected customers, issues that are causing degradation in the customer experience and the possible corrective actions. These inputs are passed through a specialized method or a module/engine (e.g., work order engine/module) to arrive at actions that need to be triggered to address majority of the issues. The output of this module may trigger various automated workflows such as, but not limited to, automated RF optimization through Remote Electrical Tilt (RET), manual/physical optimization workflow, planning (e.g. capacity augmentation) actions workflow, infrastructure related actions workflow (e.g. identification and erection of new site to plug coverage hole, augmentation of battery capacity wherever power outages are identified as root-cause, etc.), prioritization of actions for those areas where customer impact is highest, and customer issue identification and corresponding action.
[00095] Yet another module/engine (e.g., efficacy analysis module/engine or tracking module/engine) may keep a track of all such automated workflows and on completion of all the actions, a fresh set of customer scorecard may be generated to verify the efficacy of the actions taken.
[00096] The disclosed system may further include a user interface application/module (or a presentation module/engine) in-sync with above components/modules, which displays different views with respect to different users using it in the most optimized way. For example, the user interface module may be configured to optimize a CHC view, an outage view, a prioritized task view, a task resolution action view, etc.
[00097] Disclosed systems and methods, for closely looping back the customer experience, identify and fix at least the below described issues to improve customer experience. For example, the disclosed method provides improvement in network availability (e.g., by addressing frequent site or backhaul/front haul outages and/or by providing sufficient coverage from neighbouring sites or adding new sites in the vicinity of the identified area, etc. – through automated “Availability/Augmentation” workflow). In another example, the disclosed method provides improvement in resolution of quality issues (e.g., by addressing coverage issues through automated “Optimization” process flow). In yet another example, the disclosed methods provide improvement in capacity issues (e.g., through load-balancing methods in case of load imbalance and/or augmentation of capacity, etc. through automated “planning actions” workflow).
[00098] FIG. 6 illustrates an exemplary flow chart of a method 600 for user feedback loop management, in accordance with an embodiment of the disclosure.
[00099] At block 602, the method 600 may include receiving user experience data from a plurality of users. In some embodiments, the user experience data may include, but not be limited to, voice services, high speed internet services, Radio Frequency (RF) experiences, an average network coverage experience of a user, user device experiences, Key Performance Indicators (KPIs), Key Quality Indicators (KQIs), user complaints, a model of user device, a SIM card version, performance counters of all cells in a network, configuration data of all the cells, user activities, alarms, indications of service outage, and interactions between the user and the network.
[000100] At block 604, the method 600 may include determining a first user experience score based on the received user experience data.
[000101] At block 606, the method 600 may include determining one or more issues faced by each user based on the first user experience score. In some embodiments, the plurality of issues may include, but not be limited to, poor network availability, radio performance issue, backhaul outages, front haul outages, load imbalance, capacity issue, and a network coverage.
[000102] At block 608, the method 600 may include determining a root cause of the one or more issues faced by said each user.
[000103] At block 610, the method 600 may include determining one or more corrective actions corresponding to the root cause of the one or more issues.
[000104] At block 612, the method 600 may include determining a critical level of the root cause of the one or more issues.
[000105] At block 614, the method 600 may include prioritizing the one or more corrective actions based on the critical level of the root cause of the one or more issues.
[000106] At block 616, the method 600 may include automatically implementing the one or more corrective actions corresponding to the root cause of the one or more issues based on the prioritization.
[000107] FIGs. 7A-7V illustrate example representations 700A-700V depicting User Interface (UI) used in user feedback loop management, in accordance with an embodiment of the disclosure.
[000108] With reference to FIGs. 7A-7V, UI used for interaction of field workforce or user feedback loop management may be depicted. FIGs. 7A-7V illustrate various parameters which include, but not limited to, a ratio of customer complaints, user experience score, one or more issues faced by each user, root cause analysis of the one or more issues faced by said each user, one or more corrective actions corresponding to the root cause of the one or more issues, a critical level of the root cause of the one or more issues, and prioritization of the one or more corrective actions based on the critical level of the root cause of the one or more issues.
[000109] FIG. 8 illustrates an exemplary computer system 800 in which or with which embodiments of the present disclosure may be implemented. As shown in FIG. 8, the computer system 800 may include an external storage device 810, a bus 820, a main memory 830, a read-only memory 840, a mass storage device 850, communication port(s) 860, and a processor 870. A person skilled in the art will appreciate that the computer system 800 may include more than one processor and communication ports. The processor 870 may include various modules associated with embodiments of the present disclosure. The communication port(s) 860 may be any of an RS-232 port for use with a modem based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. The communication port(s) 860 may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which the computer system 800 connects. The main memory 830 may be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. The read-only memory 840 may be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or BIOS instructions for the processor 870. The mass storage device 850 may be any current or future mass storage solution, which can be used to store information and/or instructions. Exemplary mass storage device 850 includes, but is not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g., an array of disks.
[000110] The bus 820 communicatively couples the processor(s) 870 with the other memory, storage, and communication blocks. The bus 820 may be, e.g., a Peripheral Component Interconnect (PCI)/PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), USB, or the like, for connecting expansion cards, drives and other subsystems as well as other buses, such a front side bus (FSB), which connects the processor 870 to software system.
[000111] Optionally, operator and administrative interfaces, e.g., a display, keyboard, joystick, and a cursor control device, may also be coupled to the bus 820 to support direct operator interaction with the computer system 800. Other operator and administrative interfaces can be provided through network connections connected through the communication port(s) 860. Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system limit the scope of the present disclosure.
[000112] While the foregoing describes various embodiments of the disclosure, other and further embodiments of the disclosure may be devised without departing from the basic scope thereof. The scope of the disclosure is determined by the claims that follow. The disclosure is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the disclosure when combined with information and knowledge available to the person having ordinary skill in the art.

ADVANTAGES OF THE PRESENT DISCLOSURE
[000113] The present disclosure provides a system and a method to provide best customer experience through automated/proactive actions and a closed feedback loop.
[000114] The present disclosure provides improved customer experience leading to higher customer satisfaction by focussing on areas that are not improving even after resolution.
[000115] The present disclosure reduces customer complaints and improves efficiency of network operations teams through automated and accurate diagnosis of issues.
[000116] The present disclosure provides a system and a method to enhance business growth.
[000117] The present disclosure provides a closed loop feedback system that takes into account the issues that continue to affect the customer experience even after execution of resolution or corrective actions, thereby enhancing the overall customer experience.
,CLAIMS:1. A system (108) for user feedback loop management, comprising:
one or more processors (110); and
a memory (112) operatively coupled to the one or more processors (110), wherein the memory (112) comprises processor-executable instructions, which on execution, cause the one or more processors (110) to:
receive user experience data from a plurality of users;
determine a first user experience score based on the received user experience data;
determine one or more issues faced by each user based on the first user experience score;
determine a root cause of the one or more issues faced by said each user;
determine one or more corrective actions corresponding to the root cause of the one or more issues;
determine a critical level of the root cause of the one or more issues;
prioritize the one or more corrective actions based on the critical level of the root cause of the one or more issues; and
automatically implement the one or more corrective actions corresponding to the root cause of the one or more issues based on the prioritization.
2. The system (108) as claimed in claim 1, wherein the user experience data comprises at least one of: voice services, high speed internet services, Radio Frequency (RF) experiences, an average network coverage experience of a user, user device experiences, Key Performance Indicators (KPIs), Key Quality Indicators (KQIs), user complaints, a model of user device, a Subscriber Identity Module (SIM) card version, performance counters of all cells in a network, configuration data of all the cells, user activities, alarms, indications of service outage, and interactions between the user and the network.
3. The system (108) as claimed in claim 1, wherein the one or more issues comprise at least one of: poor network availability, radio performance issue, backhaul outages, front haul outages, load imbalance, capacity issue, and network coverage.
4. The system (108) as claimed in claim 1, wherein the one or more corrective actions are performed with respect to work orders, and wherein the one or more corrective actions comprise at least one of: automated corrective actions and manual corrective actions.
5. The system (108) as claimed in claim 4, wherein the automated corrective actions comprise at least one of: an RF optimization via a Remote Electrical Tilt (RET), a physical optimization work order, a capacity augmentation work order, an infrastructure related work order, and a connectivity related work order, wherein the automated corrective actions are at least one of: physical or digital.
6. The system (108) as claimed in claim 1, wherein the one or more processors (110) are to:
track a completion status of the implemented one or more corrective actions;
determine a second user experience score based on the completion status of the implemented one or more corrective actions;
compare the first user experience score and the second user experience score; and
adjust a prioritization technique to assign higher priority to at least one action that has maximum positive outcome related to customer experience.
7. The system (108) as claimed in claim 1, comprising:
a user interface to display information related to the user experience data of said each user, the first user experience score of said each user, a second user experience score of said each user, an outage view of said each user, a prioritized task view for said each user, and a task resolution action for said each user.
8. A method for user feedback loop management, comprising:
receiving (602), by one or more processors (110), user experience data from a plurality of users;
determining (604), by the one or more processors (110), a first user experience score based on the received user experience data;
determining (606), by the one or more processors (110), one or more issues faced by each user based on the first user experience score;
determining (608), by the one or more processors (110), a root cause of the one or more issues faced by said each user;
determining (610), by the one or more processors (110), one or more corrective actions corresponding to the root cause of the one or more issues;
determining (612), by the one or more processors (110), a critical level of the root cause of the one or more issues;
prioritizing (614), by the one or more processors (110), the one or more corrective actions based on the critical level of the root cause of the one or more issues; and
automatically implementing (616), by the one or more processors (110), the one or more corrective actions corresponding to the root cause of the one or more issues based on the prioritization.
9. The method (600) as claimed in claim 8, comprising:
performing, by the one or more processors (110), the one or more corrective actions with respect to work orders, wherein the one or more corrective actions comprise at least one of: automated corrective actions and manual corrective actions.
10. The method (600) as claimed in claim 8, comprising:
tracking, by the one or more processors (110), a completion status of the implemented one or more corrective actions;
determining, by the one or more processors (110), a second user experience score based on the completion status of the implemented one or more corrective actions;
comparing, by the one or more processors (110), the first user experience score and the second user experience score; and
adjusting, by the one or more processors (110), a prioritization technique to assign higher priority to at least one action that has maximum positive outcome related to a customer experience.