Method and system for providing one or more recommendations to a user on a platform

Abstract

The present disclosure relates to a method and a system for providing one or more recommendations to a user on a platform The method comprises receiving, by a transceiver unit [202], an activity data related to the platform; creating, by a log creator [204], a set of logs based on the activity data; identifying, by a processing unit [206], a pattern of usage of a set of users based on the set of logs; receiving, by the transceiver unit from a set of user devices, a user feedback based on the pattern of usage; generating, by the processing unit [206], one or more notifications and one or more recommendations based on the pattern of usage and the user feedback; and providing, by a delivering unit [208] on the set of user devices and the platform, the one or more notifications and the one or more recommendations.

Description

METHOD AND SYSTEM FOR PROVIDING ONE OR MORE RECOMMENDATIONS TO A USER ON A PLATFORMTECHNICAL FIELD

[0001] Embodiments of the present disclosure generally relate to system for providing one or more recommendations. More particularly, embodiments of the present disclosure relate to methods and systems for providing one or more recommendations to a user on a platform in order to enhance a user experience on the platform.BACKGROUND

[0002] The following description of the 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 is used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of the prior art.

[0003] Over the past few years digital technology and wireless technology have been enhanced to a great extent. Also, as the digital technology and the wireless technology are enhancing, the number of customers associated with different digital platforms and the wireless communication platforms are also increasing with a rapid rate. It is important for these digital and wireless communication platforms to retain their customers and control a chum rate of their customers. Further, the customer retention rate is the rate at which a business / digital platform / wireless communication platform keeps its customers within a given period of time. The detection of the retention rate i.e., the customer retention rate helps businesses / companies understand the connection between what services they offer and the outcomes they achieve. A high retention rate indicates customers return with some degree of regularity. Moreover, such data points help in making important decisions, like investment in ads to attract new customers etc. Also, where the retention rate indicates repeat customers or purchases, a chum rate or user chum rate reflects how often customers stop doing business with a company / digital platform / wireless communication platform. The chum rate is measured to identify the percentage of customers that transact with a company only once within a designated period. These customers may have cancelled their subscription service or given their business to any competitor.

[0004] Further, over the period of time various solutions have been developed to manage the retention and chum of the customers. However, there are certain challenges with existing solutions. Mainly, the existing solutions are inefficient and fail to provide an efficient and effective solution of retention and chum management. Also, the existing solutions fail to consider the data points thatmay be collected at different stages of an entire customer journey of customers with an organisation, for providing a better retention and chum management solution. Moreover, in the existing solutions there is a lack of business intelligence (BI) and hence these solutions are not efficient and have many limitations.

[0005] Thus, there exists an imperative need in the art to provide an improved solution for retention and churn management that can overcome the limitations of the existing solutions and can provide better output, which the present disclosure aims to address.SUMMARY

[0006] This section is provided to introduce certain 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.

[0007] An aspect of the present disclosure may relate to a method for providing one or more recommendations to a user on a platform. The method comprises receiving, by a transceiver unit, an activity data related to the platform. The method further comprises creating, by a log creator, a set of logs based on the activity data. The method further comprises identifying, by a processing unit, a pattern of usage of a set of users based on the set of logs. The method further comprises receiving, by the transceiver unit from a set of user devices, a user feedback based on the pattern of usage. The method further comprises generating, by the processing unit, at least one of one or more notifications and one or more recommendations based on at least one of the pattern of usage and the user feedback. The method further comprises providing, by a delivering unit on at least one of the set of user devices and the platform, at least one of the one or more notifications and the one or more recommendations.

[0008] In an exemplary aspect of the present disclosure, the identified pattern of usage of the set of users is one of a daily data consumption pattern parameter associated with a target user in comparison to one or more users from the set of users, a recharge patterns parameter associated with the set of users, a call drop pattern parameter associated with the set of users, a network parameter associated with the set of users, a recharge patterns parameter associated with the set of users, a voice call service usage parameter associated with the set of users.

[0009] In an exemplary aspect of the present disclosure, the one or more recommendations is one of a predefined recommendation associated with the identified pattern of usage of the set of users.

[0010] In an exemplary aspect of the present disclosure, the pattern of usage indicates at least one of a pattern of one or more activities of the set of users on the platform and a comparison of the pattern of the one or more activities of the set of users on the platform with a pattern of one or more activities of one or more target users on the platform.[Oi l] In an exemplary aspect of the present disclosure, the activity data comprises a data related to the one or more activities of the set of users on the platform for a predefined period of time.

[0012] In an exemplary aspect of the present disclosure, the data related to the one or more activities of the set of users on the platform comprises at least an information related to at least one of a type of the one or more activities and a timestamp of the one or more activities.

[0013] In an exemplary aspect of the present disclosure, the set of logs comprises one or more logs associated with the one or more activities of the set of users on the platform.

[0014] In an exemplary aspect of the present disclosure, the platform is one of a wireless communication platform and a digital platform.

[0015] In an exemplary aspect of the present disclosure, at least one of the one or more notifications and the one or more recommendations are generated by the processing unit using a first artificial intelligence engine and the pattern of usage is identified by the processing unit using a second artificial intelligence engine.

[0016] In an exemplary aspect of the present disclosure, the tone or more notifications and the one or more recommendations are generated using the first artificial intelligence engine based on receiving, by the first artificial intelligence engine, the pattern of usage of the set of users based on the set of logs, fetching, by the first artificial intelligence engine from a set of user devices, a user feedback based on the pattern of usage; and analyzing, by the first artificial intelligence engine, at least one of the pattern of usage and the user feedback.

[0017] In an exemplary aspect of the present disclosure, the pattern of usage is identified using the second artificial intelligence engine based on, identifying, by the second artificial intelligence, the activity data related to the platform, fetching, by the second artificial intelligence from the log creator, the set of logs based on the activity data; and analyzing, by the second artificial intelligence, the set of logs.

[0018] Another aspect of the present disclosure may relate to a system for providing one or more recommendations to a user on a platform. The system comprises a transceiver unit configured to receive an activity data related to the platform. The system further comprises a log creator unit connected with the transceiver unit, the log creator unit configured to create, a set of logs based on the activity data. The system further comprises a processing unit connected to the log creator unit and the processing unit configured to identify, a pattern of usage of a set of users based on the set of logs. The transceiver unit is further configured to receive, from a set of user devices, a user feedback based on the pattern of usage. The processing unit is further configured to generate, at least one of one or more notifications and one or more recommendations based on at least one of the pattern of usage and the user feedback. The system further comprises delivering unit connected to the processing unit and the delivering unit configured to provide, on at least one of the set of user devices and the platform, at least one of the one or more notifications and the one or more recommendations to provide retention and chum management on the platform.

[0019] Another aspect of the present disclosure may relate to a user equipment for providing one or more recommendations to a user on a platform. The user equipment comprises a memory and a processor. The processor is configured to transmit, to a system, a request for generating one or more notifications and one or more recommendations for set of users. The processor is configured to receive from the system a response comprising the one or more notifications and the one or more recommendations associated with the request. The response is received based on receiving, by the system, an activity data related to the platform. The response is further based on creating, by the system, a set of logs based on the activity data. The response is further based on identifying, by the system, a pattern of usage of a set of users based on the set of logs, the response is further based on receiving, by the from a set of user devices, a user feedback based on the pattern of usage. The response is further based on generating, by the system, at least one of one or more notifications and one or more recommendations based on at least one of the pattern of usage and the user feedback.

[0020] Yet another aspect of the present disclosure may relate to a non-transitory computer readable storage medium storing instructions for providing one or more recommendations to a user on a platform, the instructions include executable code which, when executed by a one or more units of a system, causes: a transceiver unit of the system to receive an activity data related to the platform, a log creator unit of the system to create, a set of logs based on the activity data, a processing unit of the system to identify a pattern of usage of a set of users based on the set of logs, the transceiver unit of the system to receive, from a set of user devices, a user feedback based on the pattern of usage, the processing unit of the system to generate, at least one of one or more notifications and one or more recommendations based on at least one of the pattern of usage and the user feedback, a delivering unit of the system to provide, on at least one of the set of userdevices and the platform, at least one of the one or more notifications and the one or more recommendations to provide retention and chum management on the platform.OBJECTS OF THE INVENTION

[0021] Some of the objects of the present disclosure, which at least one embodiment disclosed herein satisfies are listed herein below.

[0022] It is an object of the present disclosure to provide a system and a method for providing one or more recommendations to a user on a platform.

[0023] It is another object of the present disclosure to provide a system and a method for providing one or more recommendations to enhance the user experience.

[0024] It is another object of the present disclosure to provide a system and a method for providing retention and churn management using 360 degrees of data such as an activity data, a patten of usage data and a log data associated with the activity data of a user on a platform.

[0025] It is another object of the present disclosure to provide a system and method for solution for hand holding of a customer that may further lead to a clearance of a payment of a service by the customer.

[0026] It is another object of the present disclosure to provide a solution that takes into consideration multiple stages that may be present in an entire customer journey on a platform to provide an effective and efficient retention and chum management.

[0027] It is yet another object of the present disclosure to provide a solution to that may use business intelligence for identifying the patterns of customers such as a customer’s usage pattern of a service etc., to provide various recommendations or notifications for a better retention and chum management.DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Also, the embodiments shown in the figures are not to beconstrued as limiting the disclosure, but the possible variants of the method and system according to the disclosure are illustrated herein to highlight the advantages of the disclosure. It will be appreciated by those skilled in the art that disclosure of such drawings includes disclosure of electrical components or circuitry commonly used to implement such components.

[0029] FIG. 1 illustrates an exemplary block diagram of a computing device upon which the features of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure.

[0030] FIG. 2 illustrates an exemplary block diagram of a system for providing one or more recommendations to a user on a platform, in accordance with exemplary implementations of the present disclosure.

[0031] FIG. 3 illustrates a method flow diagram for providing one or more recommendations to a user on a platform, in accordance with exemplary implementations of the present disclosure.

[0032] The foregoing shall be more apparent from the following more detailed description of the disclosure.DETAILED DESCRIPTION

[0033] 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 may each be used independently of one another or with any combination of other features. An individual feature may not address any of the problems discussed above or might address only some of the problems discussed above.

[0034] 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 disclosure as set forth.

[0035] 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,processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail.

[0036] 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 may 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.

[0037] 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.

[0038] As used herein, a “processing unit” or “processor” or “operating processor” includes one or more processors, wherein processor refers to any logic circuitry for processing instructions. A processor may be a general-purpose processor, a special purpose processor, a conventional processor, a digital signal processor, a plurality of microprocessors, one or more microprocessors in association with a (Digital Signal Processing) DSP core, a controller, a microcontroller, Application Specific Integrated Circuits, Field Programmable Gate Array circuits, any other type of integrated circuits, etc. The processor may perform signal coding data processing, input / output processing, and / or any other functionality that enables the working of the system according to the present disclosure. More specifically, the processor or processing unit is a hardware processor.

[0039] As used herein, “a user equipment”, “a user device”, “a smart-user-device”, “a smartdevice”, “an electronic device”, “a mobile device”, “a handheld device”, “a wireless communication device”, “a mobile communication device”, “a communication device” may be any electrical, electronic and / or computing device or equipment, capable of implementing the features of the present disclosure. The user equipment / device may include, but is not limited to, a mobile phone, smart phone, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, wearable device or any other computing device which is capable of implementing the features of the present disclosure. Also, the user device may contain at least one input meansconfigured to receive an input from at least one of a transceiver unit, a processing unit, a storage unit, a detection unit and any other such unit(s) which are required to implement the features of the present disclosure.

[0040] As used herein, “storage unit” or “memory unit” refers to a machine or computer-readable medium including any mechanism for storing information in a form readable by a computer or similar machine. For example, a computer-readable medium includes read-only memory (“ROM”), random access memory (“RAM”), magnetic disk storage media, optical storage media, flash memory devices or other types of machine-accessible storage media. The storage unit stores at least the data that may be required by one or more units of the system to perform their respective functions.

[0041] As used herein “interface” or “user interface refers to a shared boundary across which two or more separate components of a system exchange information or data. The interface may also be referred to a set of rules or protocols that define communication or interaction of one or more modules or one or more units with each other, which also includes the methods, functions, or procedures that may be called.

[0042] As used herein Churn rate, in the context of customer retention and business management, refers to the percentage of customers or subscribers who stop using a product or service during a certain time period. It is a crucial metric for businesses, particularly those with subscription-based models or recurring revenue streams, as it indicates the rate at which customers disengage or "chum out" from their relationship with the company. Further, “The chum rate” of customers, may be expressed as a percentage that represents the proportion of customers or subscribers who discontinue their relationship with a company's product or service within a specific period, typically on a monthly, quarterly, or annual basis. It is calculated by dividing the number of customers lost during that period by the total number of customers at the beginning of the period.

[0043] All modules, units, components used herein, unless explicitly excluded herein, may be software modules or hardware processors, the processors being a general-purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASIC), Field Programmable Gate Array circuits (FPGA), any other type of integrated circuits, etc.

[0044] As used herein the transceiver unit include at least one receiver and at least one transmitter configured respectively for receiving and transmitting data, signals, information or a combination thereof between units / components within the system and / or connected with the system.

[0045] As discussed in the background section, improvement and advancement in the field of digital and wireless technologies have raised a customer engagement across various platforms. Also, the process of retaining the customer is important for business perspective. Conventionally, manual solutions were used to retain the customer on a specific platform, however with the development in technology several solutions were introduced to automate the process of retaining the customer by processing a set of data via one or more standard protocols. Despite of these developments, the existing solutions fails to utilize the set of data comprehensively to manage customer retention and customer attrition (i.e. customer churn). Hence, the current known solutions have several shortcomings. The present disclosure aims to overcome the above-mentioned and other existing problems in this field of technology by providing method and system for providing one or more recommendations to enhance a user experience. The one or more recommendations are provided by analysing an activity data, creating one or more logs, identifying one or more usage patterns, receiving one or more user feedbacks and generating one or more notifications or recommendations based on the one or more usage patterns and the one or more user feedbacks.

[0046] FIG. 1 illustrates an exemplary block diagram of a computing device

[1000] upon which the features of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure. In an implementation, the computing device

[1000] may also implement a method for providing one or more recommendations to a user on a platform utilising the system. In another implementation, the computing device

[1000] itself implements the method for providing the one or more recommendations to the user on the platform using one or more units configured within the computing device

[1000] , wherein said one or more units are capable of implementing the features as disclosed in the present disclosure.

[0047] The computing device

[1000] may include a bus

[1002] or other communication mechanism for communicating information, and a hardware processor

[1004] coupled with the bus

[1002] for processing information. The hardware processor

[1004] may be, for example, a general purpose microprocessor. The computing device

[1000] may also include a main memory

[1006] , such as a random access memory (RAM), or other dynamic storage device, coupled to the bus

[1002] for storing information and instructions to be executed by the processor

[1004] , The main memory

[1006] also may be used for storing temporary variables or other intermediate information during execution of the instructions to be executed by the processor

[1004] . Such instructions, when stored in non-transitory storage media accessible to the processor

[1004] , render the computing device

[1000] into a special-purpose machine that is customized to perform the operations specified in the instructions. The computing device

[1000] further includes a read only memory (ROM)

[1008] or other static storage device coupled to the bus

[1002] for storing static information and instructions for the processor

[1004] ,

[0048] A storage device

[1010] , such as a magnetic disk, optical disk, or solid-state drive is provided and coupled to the bus

[1002] for storing information and instructions. The computing device

[1000] may be coupled via the bus

[1002] to a display

[1012] , such as a cathode ray tube (CRT), Liquid crystal Display (LCD), Light Emitting Diode (LED) display, Organic LED (OLED) display, etc. for displaying information to a computer user. An input device

[1014] , including alphanumeric and other keys, touch screen input means, etc. may be coupled to the bus

[1002] for communicating information and command selections to the processor

[1004] , Another type of user input device may be a cursor control

[1016] , such as a mouse, a trackball, or cursor direction keys, for communicating direction information and command selections to the processor

[1004] , and for controlling cursor movement on the display

[1012] , This input device typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allow the device to specify positions in a plane.

[0049] The computing device

[1000] may implement the techniques described herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware and / or program logic which in combination with the computing device

[1000] causes or programs the computing device

[1000] to be a special-purpose machine. According to one implementation, the techniques herein are performed by the computing device

[1000] in response to the processor

[1004] executing one or more sequences of one or more instructions contained in the main memory

[1006] , Such instructions may be read into the main memory

[1006] from another storage medium, such as the storage device

[1010] , Execution of the sequences of instructions contained in the main memory

[1006] causes the processor

[1004] to perform the process steps described herein. In alternative implementations of the present disclosure, hard-wired circuitry may be used in place of or in combination with software instructions.

[0050] The computing device

[1000] also may include a communication interface

[1018] coupled to the bus

[1002] , The communication interface

[1018] provides a two-way data communication coupling to a network link

[1020] that is connected to a local network

[1022] , The local network

[1022] is connected to the host

[1024] , For example, the communication interface

[1018] may be an integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, the communication interface

[1018] may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links may also be implemented. In any such implementation, the communication interface

[1018] sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information.

[0051] The computing device

[1000] can send messages and receive data, including program code, through the network(s), the network link

[1020] and the communication interface

[1018] , In the Internet example, a server

[1030] might transmit a requested code for an application program through the Internet

[1028] , the ISP

[1026] , the Host

[1024] , the local network

[1022] and the communication interface

[1018] , The received code may be executed by the processor

[1004] as it is received, and / or stored in the storage device

[1010] , or other non-volatile storage for later execution.

[0052] Referring to FIG. 2, an exemplary block diagram of a system

[0200] for providing one or more recommendations to a user on a platform, is shown, in accordance with the exemplary implementations of the present disclosure. The system

[0200] comprises at least one transceiver unit

[0202] , at least one log creator unit

[0204] , at least one processing unit

[0206] , at least one delivering unit

[0208] , and at least one storage unit

[0210] , Also, all of the components / units of the system

[0200] are assumed to be connected to each other unless otherwise indicated below. As shown in the figures all units shown within the system should also be assumed to be connected to each other. Also, in FIG. 2 only a few units are shown, however, the system

[0200] may comprise multiple such units or the system

[0200] may comprise any such numbers of said units, as required to implement the features of the present disclosure. Further, in an implementation, the system

[0200] may be present in a user device to implement the features of the present disclosure. The system

[0200] may be a part of the user device / or may be independent of but in communication with the user device (may also referred herein as a UE). In another implementation, the system

[0200] may reside in a server or a network entity. In yet another implementation, the system

[0200] may reside partly in the server / network entity and partly in the user device.

[0053] Further, in accordance with the present disclosure, it is to be acknowledged that the functionality described for the various the components / units can be implemented interchangeably. While specific embodiments may disclose a particular functionality of these units for clarity, it is recognized that various configurations and combinations thereof are within the scope of the disclosure. The functionality of specific units as disclosed in the disclosure should not be construed as limiting the scope of the present disclosure. Consequently, alternative arrangements and substitutions of units, provided they achieve the intended functionality described herein, are considered to be encompassed within the scope of the present disclosure.

[0054] The system

[0200] is configured for providing the one or more recommendations to the user on the platform with the help of the interconnection between the components / units of the system

[0200] ,

[0055] In order to provide the one or more recommendation to the user on the platform, the transceiver unit

[0202] is configured to receive an activity data related to the platform. The present disclosure encompasses that the activity data comprises a data related to the one or more activities of the set of users on the platform for a predefined period of time.

[0056] As used herein, “platform” refers to a framework upon which one or more activities are supported. The platform is one of a wireless communication platform and a digital platform. The present disclosure encompasses that the platform may refer to a network platform, a digital platform, an engagement platform, a computing platform, a marketplace platform, a content platform, a utility platform.

[0057] The present disclosure encompasses that the data related to the one or more activities of the set of users on the platform comprises at least an information related to at least one of a type of the one or more activities and a timestamp of the one or more activities.

[0058] Further, the activity data is related to a set of users such as details of one or more activities and timestamps of one or more activities performed over the platform by the set of users. For instance, the user subscribes an international plan every month and use one or more calling services associated with the international plan every week. So, the subscription of international plan is the activity and purchased every month is the timestamp.

[0059] Thereafter, the activity data is transmitted to the log creator unit

[0204] via the transceiver unit

[0202] , The log creator unit

[0204] is connected to the transceiver unit

[0202] , The log creator unit

[0204] receives the activity data which is transmitted by the transceiver unit

[0202] to create a set of logs based on the activity data. The present disclosure encompasses that the set of logs comprises one or more logs associated with the one or more activities of the set of users on the platform.

[0060] For instance, the transceiver unit

[0202] transmits the activity data related to a subscription event to the log creator unit

[0204] , The log creator unit

[0204] receives the activity data related to the subscription event for generating a log indicating about the subscription event. The log generated by the log creator unit

[0204] may include one or more details such as type of subscription and timestamp of the subscription. Likewise, the set of logs are generated by the log creator unit

[0204] according to the set of users i.e., a type of users.

[0061] Thereafter, the set of logs generated by the log creator unit

[0204] is transmitted to the processing unit

[0206] by the log creator unit

[0204] , The processing unit

[0206] is connected to the log creator unit

[0204] and the processing unit

[0206] is configured to identify, a pattern of usage of a set of users based on the set of logs.

[0062] Initially, the processing unit

[0206] receives the set of logs i.e., a historic data associated with the set of users, that are generated by the log creator unit

[0204] and process the set of logs for identifying the pattern of usage of the set of users based on the set of logs. In an implementation the pattern of usage of the set of users based on the set of logs may be identifies based on analysing the received the set of logs and a current user activity by one or more users on the platform.

[0063] The present disclosure encompasses that the identified pattern of usage of the set of users is one of a daily data consumption pattern parameter associated with a target user in comparison to one or more users from the set of users, a recharge patterns parameter associated with the set of users, a call drop pattern parameter associated with the set of users, a network parameter associated with the set of users, a recharge patterns parameter associated with the set of users, a voice call service usage parameter associated with the set of users.

[0064] The present disclosure encompasses that the pattern of usage indicates at least one of a pattern of one or more activities of the set of users on the platform and a comparison of the pattern of the one or more activities of the set of users on the platform with a pattern of one or more activities of one or more target users on the platform.

[0065] For example, the log creator unit

[0204] transmits the set of logs to the processing unit

[0206] .The processing unit

[0206] receives the set of logs from the log creator unit

[0204] to process the set of logs via one or more processing protocols that may be known to a person skilled in the art for identifying the pattern of usage of the set of users such as frequency of daily data consumption, occurrence of subscription events, instance of call drops, one or more network performance metrics and voice call service usage. Additionally, the processing unit

[0206] may compare the one or more pattern of usage of the set of users with other set of users on the platform to identify the pattern of usage of said set of users.

[0066] Thereafter, the transceiver unit

[0202] is further configured to receive, from a set of user devices, a user feedback based on the pattern of usage. The present disclosure encompasses that the user feedback includes an information about a plurality of opinions provided by the set of users of the set of user devices. The user feedback may include but not be limited to experience, preference, rating, review, comments or any other input from the set of user devices. Furthermore, the user feedback may be received via a user interface on the user device based on utilising one or more feedback method such as a choosing options, a voice recorded feedback, a text input feedback, or any other feedback method that may be obvious to the person skilled in the art.

[0067] Further, the processing unit

[0206] is configured to generate, at least one of one or more notifications and one or more recommendations based on at least one of the pattern of usage and the user feedback.

[0068] The present disclosure encompasses that the one or more recommendations is one of a predefined recommendation associated with the identified pattern of usage of the set of users.

[0069] The present disclosure encompasses that at least one of the one or more notifications and the one or more recommendations are generated by the processing unit

[0206] using a first artificial intelligence engine and the pattern of usage is identified by the processing unit

[0206] using a second artificial intelligence engine.

[0070] The present disclosure encompasses that the first artificial intelligence engine and the second artificial intelligence engine may utilize one or more standard protocols for generating the one or more notifications and the one or more recommendations respectively.

[0071] The present disclosure encompasses that the notification may be a message or an alert that is delivered to the set of users based on the pattern of usage associated with the set of users via one or more ways such as electronic mail, short messages, mobile application. The notification is used to inform the set of users about an important event, update that require their attention. The notification may range from a simple message and message update to a complex notification that may include a personalized information. The personalized information is related to a specific user and may be based on a preference or an interest or a location of the set of users, wherein the preference or the interest or the location may be determined based on the pattern of usage associated with the set of users or the user feedback.

[0072] The present disclosure encompasses that the recommendation is a suggestion or an advice that may provide to the set of users based on the pattern of usage associated with the set of users and the comparison of the pattern of usage associated with a user with one or more users from the set of users. The suggestion or advice may be personalized to the user and may be based on a preference or an interest or location of the user for improving the user experience and user engagement.

[0073] The present disclosure encompasses that the first artificial intelligence engine to generate the one or more notifications and the one or more recommendations is configured to receive, the pattern of usage of the set of users based on the set of logs. The first artificial intelligence engine is further configured to fetch, from a set of user devices, the user feedback based on the pattern ofusage. The first artificial intelligence engine is further configured to analyze, at least one of the patterns of usage and the user feedback.

[0074] The present disclosure encompasses that the second artificial intelligence engine to identify the pattern of usage are identified is configured to identify, by the second artificial intelligence, the activity data related to the platform. The second artificial intelligence engine is further configured to fetch, by the second artificial intelligence from the log creator

[0204] , the set of logs based on the activity data. The second artificial intelligence engine is further configured to analyze, by the second artificial intelligence, the set of logs.

[0075] For instance, the processing unit

[0206] receives the pattern of usage and the feedback data related to purchase of subscription event on the platform that indicates the set of users engaging on the platform for exploring and purchasing one or more subscription plans. The processing unit

[0206] processes the pattern of usage and the feedback data via the first artificial intelligence engine and the second artificial intelligence engine for generating one or more notifications and / or one or more recommendations such as best subscription plans for the set of users, benefits of the subscription plans for enhancing the user experience on the platform.

[0076] The present disclosure encompasses that the first artificial intelligence engine and the second artificial intelligence engine may be based on one or more artificial intelligence models and or machine learning model that provides a higher computation density due to which the first artificial intelligence engine and the second artificial intelligence engine may quickly perform within a specified time frame.

[0077] As used herein, “artificial intelligence engine” refers to a system or a platform that works on the basis of one or more protocols, one or more data models and one or more machine learning techniques. The artificial intelligence engine may include but not limited to at least one processing module, at least one decision making module, at least one interface.

[0078] Further, the delivering unit

[0208] is connected to the processing unit

[0206] , The delivering unit

[0208] configured to provide, on at least one of the set of user devices and the platform, at least one of the one or more notifications and the one or more recommendations to provide retention and chum management on the platform.

[0079] Upon generation of at least one of one or more notifications and one or more recommendations based on at least one of the pattern of usage and the user feedback, the delivering unit

[0208] is configured to provide the on at least one of the set of user devices and the platform,the at least one of the one or more notifications and the one or more recommendations to provide retention and chum management on the platform.

[0080] As used herein, “retention and churn management” refers to one or more strategies or processed which are generally utilized by an organization to maintain and increase a customer (i.e. user) loyalty while minimizing the customer attrition or chum for improving customer satisfaction, experience and reduce acquisition cost of the customer.

[0081] Referring to FIG. 3, an exemplary method flow diagram

[0300] for providing one or more recommendations to a user on a platform, in accordance with exemplary implementations of the present disclosure is shown. In an implementation the method

[0300] is performed by the system

[0200] , Further, in an implementation, the system

[0200] may be present in a server device to implement the features of the present disclosure. Also, as shown in FIG. 3, the method

[0300] starts at step

[0302] ,

[0082] At step

[0304] , the method

[0300] comprises receiving, by a transceiver unit

[0202] , an activity data related to the platform. The present disclosure encompasses that the activity data comprises a data related to the one or more activities of the set of users on the platform for a predefined period of time.

[0083] As used herein, “platform” refers to a framework upon which one or more activities are supported. The platform is one of a wireless communication platform and a digital platform. The present disclosure encompasses that the platform may refer to a network platform, a digital platform, an engagement platform, a computing platform, a marketplace platform, a content platform, a utility platform.

[0084] The present disclosure encompasses that the data related to the one or more activities of the set of users on the platform comprises at least an information related to at least one of a type of the one or more activities and a timestamp of the one or more activities.

[0085] Further, the activity data is related to a set of users such as details of one or more activities and timestamps of one or more activities performed over the platform by the set of users. For instance, the user subscribes an international plan every month and use one or more calling services associated with the international plan every week. So, the subscription of international plan is the activity and purchased every month is the timestamp.

[0086] The present disclosure encompasses that the platform is one of a wireless communication platform and a digital platform.

[0087] At step

[0306] , the method

[0300] comprises creating, by a log creator

[0204] , a set of logs based on the activity data.

[0088] The present disclosure encompasses that the set of logs comprises one or more logs associated with the one or more activities of the set of users on the platform.

[0089] For instance, the transceiver unit

[0202] transmits the activity data related to a subscription event to the log creator unit

[0204] , The log creator unit

[0204] receives the activity data related to the subscription event for generating a log indicating about the subscription event. The log generated by the log creator unit

[0204] may include one or more details such as type of subscription and timestamp of the subscription. Likewise, the set of logs are generated by the log creator unit

[0204] according to the set of users i.e., a type of users.

[0090] At step

[0308] , the method

[0300] comprises identifying, by a processing unit

[0206] , a pattern of usage of a set of users based on the set of logs.

[0091] In an exemplary scenario, the processing unit

[0206] receives the set of logs i.e., a historic data associated with the set of users, that are generated by the log creator unit

[0204] and process the set of logs for identifying the pattern of usage of the set of users based on the set of logs. In an implementation the pattern of usage of the set of users based on the set of logs may be identifies based on analysing the received the set of logs and a current user activity by one or more users on the platform.

[0092] The present disclosure encompasses that the identified pattern of usage of the set of users is one of a daily data consumption pattern parameter associated with a target user in comparison to one or more users from the set of users, a recharge patterns parameter associated with the set of users, a call drop pattern parameter associated with the set of users, a network parameter associated with the set of users, a recharge patterns parameter associated with the set of users, a voice call service usage parameter associated with the set of users.

[0093] The present disclosure encompasses that the pattern of usage indicates at least one of a pattern of one or more activities of the set of users on the platform and a comparison of the pattern of the one or more activities of the set of users on the platform with a pattern of one or more activities of one or more target users on the platform.

[0094] The present disclosure encompasses that the pattern of usage indicates at least one of a pattern of one or more activities of the set of users on the platform and a comparison of the patternof the one or more activities of the set of users on the platform with a pattern of one or more activities of one or more target users on the platform.

[0095] For example, the log creator unit

[0204] transmits the set of logs to the processing unit

[0206] .The processing unit

[0206] receives the set of logs from the log creator unit

[0204] to process the set of logs via one or more processing protocols that may be known to a person skilled in the art for identifying the pattern of usage of the set of users such as frequency of daily data consumption, occurrence of subscription events, instance of call drops, one or more network performance metrics and voice call service usage. Additionally, the processing unit

[0206] may compare the one or more pattern of usage of the set of users with other set of users on the platform to identify the pattern of usage of said set of users.

[0096] At step

[0310] , the method

[0300] comprises receiving, by the transceiver unit

[0202] from a set of user devices, a user feedback based on the pattern of usage. The present disclosure encompasses that the user feedback includes an information about a plurality of opinions provided by the set of users of the set of user devices. The user feedback may include but not be limited to experience, preference, rating, review, comments or any other input from the set of user devices. Furthermore, the user feedback may be received via a user interface on the user device based on utilising one or more feedback method such as a choosing options, a voice recorded feedback, a text input feedback, or any other feedback method that may be obvious to the person skilled in the art.

[0097] At step

[0312] , the method

[0300] comprises generating, by the processing unit

[0206] , at least one of one or more notifications and one or more recommendation based on at least one of the pattern of usage and the user feedback.

[0098] The present disclosure encompasses that the one or more recommendations is one of a predefined recommendation associated with the identified pattern of usage of the set of users.

[0099] The present disclosure encompasses that the at least one of the one or more notifications and the one or more recommendations are generated by the processing unit

[0206] using a first artificial intelligence engine and the pattern of usage is identified by the processing unit

[0206] using a second artificial intelligence engine.

[0100] The present disclosure encompasses that the first artificial intelligence engine and the second artificial intelligence engine may utilize one or more standard protocols for generating the one or more notifications and the one or more recommendations respectively.

[0101] The present disclosure encompasses that the notification may be a message or an alert that is delivered to the set of users based on the pattern of usage associated with the set of users via one or more ways such as electronic mail, short messages, mobile application. The notification is used to inform the set of users about an important event, update that require their attention. The notification may range from a simple message and message update to a complex notification that may include a personalized information. The personalized information is related to a specific user and may be based on a preference or an interest or a location of the set of users, wherein the preference or the interest or the location may be determined based on the pattern of usage associated with the set of users or the user feedback.

[0102] The present disclosure encompasses that the recommendation is a suggestion or an advice that may provide to the set of users based on the pattern of usage associated with the set of users and the comparison of the pattern of usage associated with a user with one or more users from the set of users. The suggestion or advice may be personalized to the user and may be based on a preference or an interest or location of the user for improving the user experience and user engagement.

[0103] The present disclosure encompasses that the one or more notifications and the one or more recommendations are generated using the first artificial intelligence engine is based on receiving, by the first artificial intelligence engine, the pattern of usage of the set of users based on the set of logs. The one or more notifications and the one or more recommendations are generated using the first artificial intelligence engine is further based on fetching, by the first artificial intelligence engine from a set of user devices, a user feedback based on the pattern of usage. The one or more notifications and the one or more recommendations are generated using the first artificial intelligence engine is further based on analysing, by the first artificial intelligence engine, at least one of the pattern of usage and the user feedback.

[0104] The present disclosure encompasses that the pattern of usage is identified using the second artificial intelligence engine is based on identifying, by the second artificial intelligence, the activity data related to the platform. The pattern of usage is identified using the second artificial intelligence engine is based on fetching, by the second artificial intelligence from the log creator

[0204] , the set of logs based on the activity data. The pattern of usage is identified using the second artificial intelligence engine is based on analyzing, by the second artificial intelligence, the set of logs.

[0105] For instance, the processing unit

[0206] receives the pattern of usage and the feedback data related to purchase of subscription event on the platform that indicates the set of users engaging on the platform for exploring and purchasing one or more subscription plans. The processing unit

[0206] processes the pattern of usage and the feedback data via the first artificial intelligence engine and the second artificial intelligence engine for generating one or more notifications and / or one or more recommendations such as best subscription plans for the set of users, benefits of the subscription plans for enhancing the user experience on the platform.

[0106] The present disclosure encompasses that the first artificial intelligence engine and the second artificial intelligence engine may be based on one or more artificial intelligence models and or machine learning model that provides a higher computation density due to which the first artificial intelligence engine and the second artificial intelligence engine may quickly perform within a specified time frame.

[0107] As used herein, “artificial intelligence engine” refers to a system or a platform that works on the basis of one or more protocols, one or more data models and one or more technologies. The artificial intelligence engine may include but not limited to at least one processing module, at least one decision making module, at least one interface.

[0108] At step

[0314] , the method

[0300] comprises providing, by a delivering unit

[0208] on at least one of the set of user devices and the platform, at least one of the one or more notifications and the one or more recommendations to provide retention and chum management on the platform.

[0109] As used herein, “retention and churn management” refers to one or more strategies or processed which are generally utilized by an organization to maintain and increase a customer (i.e. user) loyalty while minimizing the customer attrition or chum for improving customer satisfaction, experience and reduce acquisition cost of the customer.

[0110] The method

[0300] terminates at step

[0316] ,

[0111] The present disclosure may relate to a user equipment for providing one or more recommendation to enhance a user experience on a platform. The user equipment comprises a memory and a processor. The processor is configured to transmit, to a system, a request for generating one or more notifications and one or more recommendations for set of users. The processor is configured to receive from the system a response comprising the one or more notifications and the one or more recommendations associated with the request. The response is received based on receiving, by the system, an activity data related to the platform. The response is further based on creating, by the system, a set of logs based on the activity data. The response is further based on identifying, by the system, a pattern of usage of a set of users based on the set of logs. The response is further based on receiving, by the from a set of user devices, a user feedback based on the pattern of usage. The response is further based on generating, by the system, at leastone of one or more notifications and one or more recommendations based on at least one of the pattern of usage and the user feedback.

[0112] The present disclosure may relate to a non-transitory computer readable storage medium storing instructions for providing one or more recommendations to enhance the user experience, the instructions include executable code which, when executed by a one or more units of a system, causes: a transceiver unit

[0202] to receive an activity data related to the platform, a log creator unit

[0204] of the system to create, a set of logs based on the activity data, a processing unit

[0206] to identify a pattern of usage of a set of users based on the set of logs, the transceiver unit

[0202] to receive, from a set of user devices, a user feedback based on the pattern of usage, the processing unit

[0206] to generate, at least one of one or more notifications and one or more recommendations based on at least one of the pattern of usage and the user feedback, a delivering unit

[0208] to provide, on at least one of the set of user devices and the platform, at least one of the one or more notifications and the one or more recommendations to provide retention and churn management on the platform.

[0113] As is evident from the above, the present disclosure provides a technically advanced solution for providing one or more recommendations to a user on a platform and to enhance the user experience on the platform. The one or more recommendations are provided by comprehensively utilizing the activity data associated with the set of users and the feedback provided by the set of user devices. The present solution provide effective and efficient retention and chum management. Moreover, the present solution encompasses use of business intelligence for identifying the patterns of customers such as a customer’s usage pattern of a service etc., to provide various recommendations or notifications for a better retention and churn management. Therefore, the present disclosure provides a technically advanced solution as compared to the existing solutions for providing the one or more recommendations to the user which enhances the user experience of the user on the platform.

[0114] While considerable emphasis has been placed herein on the disclosed implementations, it will be appreciated that many implementations can be made and that many changes can be made to the implementations without departing from the principles of the present disclosure. These and other changes in the implementations of the present disclosure will be apparent to those skilled in the art, whereby it is to be understood that the foregoing descriptive matter to be implemented is illustrative and non-limiting.

Claims

We Claim:

1. A method [300] for providing one or more recommendations to a user on a platform, the method [300] comprising: receiving, by a transceiver unit [202], an activity data related to the platform; creating, by a log creator [204], a set of logs based on the activity data; identifying, by a processing unit [206], a pattern of usage of a set of users based on the set of logs; receiving, by the transceiver unit [202] from a set of user devices, a user feedback based on the pattern of usage; generating, by the processing unit [206], at least one of one or more notifications and one or more recommendations based on at least one of the pattern of usage and the user feedback; and providing, by a delivering unit [208] on at least one of the set of user devices and the platform, at least one of the one or more notifications and the one or more recommendations.

2. The method [300] as claimed in claim 1, wherein the identified pattern of usage of the set of users is one of a daily data consumption pattern parameter associated with a target user in comparison to one or more users from the set of users, a recharge patterns parameter associated with the set of users, a call drop pattern parameter associated with the set of users, a network parameter associated with the set of users, a recharge patterns parameter associated with the set of users, a voice call service usage parameter associated with the set of users.

3. The method [300] as claimed in claim 1, wherein the one or more recommendations is one of a predefined recommendation associated with the identified pattern of usage of the set of users.

4. The method [300] as claimed in claim 1, wherein the pattern of usage indicates at least one of: a pattern of one or more activities of the set of users on the platform, and a comparison of the pattern of the one or more activities of the set of users on the platform with a pattern of one or more activities of one or more target users on the platform.

5. The method [300] as claimed in claim 1, wherein the activity data comprises a data related to the one or more activities of the set of users on the platform for a predefined period of time.

6. The method [300] as claimed in claim 5, wherein the data related to the one or more activities of the set of users on the platform comprises at least an information related to at least one of a type of the one or more activities and a timestamp of the one or more activities.

7. The method [300] as claimed in claim 5, wherein the set of logs comprises one or more logs associated with the one or more activities of the set of users on the platform.

8. The method [300] as claimed in claim 1 , wherein the platform is one of a wireless communication platform and a digital platform.

9. The method [300] as claimed in claim 1, wherein at least one of the one or more notifications and the one or more recommendations are generated by the processing unit [206] using a first artificial intelligence engine and the pattern of usage is identified by the processing unit [206] using a second artificial intelligence engine.

10. The method [300] as claimed in claim 9, wherein the one or more notifications and the one or more recommendations are generated using the first artificial intelligence engine based on: receiving, by the first artificial intelligence engine, the pattern of usage of the set of users based on the set of logs; fetching, by the first artificial intelligence engine from a set of user devices, a user feedback based on the pattern of usage; and analyzing, by the first artificial intelligence engine, at least one of the pattern of usage and the user feedback.

11. The method [300] as claimed in claim 10, wherein the pattern of usage are identified using the second artificial intelligence engine based on: identifying, by the second artificial intelligence, the activity data related to the platform; fetching, by the second artificial intelligence from the log creator [204], the set of logs based on the activity data; and analyzing, by the second artificial intelligence, the set of logs.

12. A system [200] for providing one or more recommendations to a user on a platform, the system [200] comprises: a transceiver unit [202] configured to receive an activity data related to the platform; a log creator unit [204] connected with the transceiver unit [202], the log creator unit [204] configured to create, a set of logs based on the activity data; a processing unit [206] connected to the log creator unit [204], the processing unit [206] configured to identify, a pattern of usage of a set of users based on the set of logs; wherein, the transceiver unit [202] is further configured to receive, from a set of user devices, a user feedback based on the pattern of usage;wherein the processing unit [206] is further configured to generate, at least one of one or more notifications and one or more recommendations based on at least one of the pattern of usage and the user feedback; and a delivering unit [208] connected to the processing unit [206], the delivering unit [208] configured to provide, on at least one of the set of user devices and the platform, at least one of the one or more notifications and the one or more recommendations to provide retention and chum management on the platform.

13. The system [200] as claimed in claim 12, wherein the identified pattern of usage of the set of users is one of a daily data consumption pattern parameter associated with a target user in comparison to one or more users from the set of users, a recharge patterns parameter associated with the set of users, a call drop pattern parameter associated with the set of users, a network parameter associated with the set of users, a recharge patterns parameter associated with the set of users, a voice call service usage parameter associated with the set of users.

14. The system [200] as claimed in claim 12, wherein the one or more recommendations is one of a predefined recommendation associated with the identified pattern of usage of the set of users.

15. The system [200] as claimed in claim 12, wherein the pattern of usage indicates at least one of: a pattern of one or more activities of the set of users on the platform; and a comparison of the pattern of the one or more activities of the set of users on the platform with a pattern of one or more activities of one or more target users on the platform.

16. The system [200] as claimed in claim 12, wherein the activity data comprises a data related to the one or more activities of the set of users on the platform for a predefined period of time.

17. The system [200] as claimed in claim 16, wherein the data related to the one or more activities of the set of users on the platform comprises at least an information related to at least one of a type of the one or more activities and a timestamp of the one or more activities.

18. The system [200] as claimed in claim 16, wherein the set of logs comprises one or more logs associated with the one or more activities of the set of users on the platform.

19. The system [200] as claimed in claim 12, wherein the platform is one of a wireless communication platform and a digital platform.

20. The system [200] as claimed in claim 12, wherein at least one of the one or more notifications and the one or more recommendations are generated by the processing unit [206] using a first artificialintelligence engine and the pattern of usage is identified by the processing unit [206] using a second artificial intelligence engine.

21. The system [200] as claimed in claim 20, wherein the first artificial intelligence engine to generate the one or more notifications and the one or more recommendations is configured to: receive, the pattern of usage of the set of users based on the set of logs; fetch, from a set of user devices, the user feedback based on the pattern of usage; and analyze, at least one of the pattern of usage and the user feedback.

22. The system [200] as claimed in claim 21, wherein the second artificial intelligence engine to identify the pattern of usage are identified is configured to: identify, by the second artificial intelligence, the activity data related to the platform; fetch, by the second artificial intelligence from the log creator [204], the set of logs based on the activity data; and analyze, by the second artificial intelligence, the set of logs.

23. A user equipment (UE) for providing one or more recommendations to a user on a platform, the UE comprises:- a memory, and- a processor coupled to the memory, the processor configured to: o transmit, to a system, a request for generating one or more notifications and one or more recommendations for set of users, and o receive, from the system, a response comprising the one or more notifications and the one or more recommendations associated with the request, wherein the response is received based on: receiving, by the system, an activity data related to the platform; creating, by the system, a set of logs based on the activity data; identifying, by the system, a pattern of usage of a set of users based on the set of logs; receiving, by the from a set of user devices, a user feedback based on the pattern of usage, and generating, by the system, at least one of one or more notifications and one or more recommendations based on at least one of the pattern of usage and the user feedback.

24. A non-transitory computer readable storage medium storing instructions for providing one or more recommendations to a user on a platform, the instructions including executable code, the executable code when executed, may cause:a transceiver unit [202] to receive, an activity data related to the platform; a log creator [204], to create, a set of logs based on the activity data; a processing unit [206] to identify a pattern of usage of a set of users based on the set of logs, the transceiver unit [202] to receive from a set of user devices, a user feedback based on the pattern of usage, the processing unit [206], to generate at least one of one or more notifications and one or more recommendations based on at least one of the pattern of usage and the user feedback, and a delivering unit [208] to provide on at least one of the set of user devices and the platform, at least one of the one or more notifications and the one or more recommendations.

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