Abstract: The present disclosure provides a method and system for performing unification of data of one or more users across a plurality of communication devices in a plurality of shards. A user unification system receives a first set of data. In addition, the user unification system maps the first set of data to a first natural number. Further, the user unification system assigns a first shard index to the first set of data. Furthermore, the user unification system obtains a second set of data. Moreover, the user unification system maps the second set of data to a second natural number. Also, the user unification system unifies the first natural number and the second natural number. Also, the user unification system assigns the first shard index to the second set of data associated with a first user of the one or more users.

Abstract: The present disclosure provides a method and system for generating a plurality of journeys for engaging a plurality of users in real-time. The system receives a first set of data associated with the plurality of users. In addition, the system fetches a second set of data associated with a plurality of past events on a plurality of platforms through one or more communication devices. Further, the system obtains a third set of data associated with a plurality of live events. Furthermore, the system analyzes the first set of data, the second set of data and the third set of data using one or more machine learning algorithms. Moreover, the system generates the plurality of journeys for engaging the plurality of users through a plurality of channels. Also, the system creates one or more goals for each of the plurality of journeys of the plurality of platforms.

Abstract: The present disclosure provides a system that performs a method for performing unification of data for identifying a user on computing device after reinstalling the application adhering to GDPR compliance. The method includes a first step of receiving a first set of data associated with the computing device. The method includes another step of mapping the first set of data to a first natural number of a plurality of natural numbers using an increment sequence method. The method includes yet another step of hashing of the first set of data in real-time. The method includes yet another step of assigning a first shard index of a plurality of shard indexes to the first set of data based on the first natural number of the plurality of natural numbers. The method includes yet another step of sending the first shard index of the plurality of shard indexes to the server.

Abstract: The present disclosure provides a method and system for creating efficient set data structure of a plurality of communication devices and a plurality of users using a hash-based system. The hash-based system receives a first set of data associated with the plurality of communication devices. The hash-based system obtains a second set of data associated with the plurality of users. The hash-based system converts the first set of data associated and the second set of data to a plurality of natural numbers. The hash-based system assigns a first key value to the first set of data and a second key value to the second set of data. The hash-based system maps the first key value or the second key value to a block index of a plurality of block indexes. The hash-based system creates the efficient data structure.

Abstract: The present disclosure provides a system for performing a method for implementation of a scalable queue with a delay factor. The method includes a first step of creating a disk based queue. The method includes another step of mapping head of the disk based queue and tail of the disk based queue with a primary storage. The method includes yet another step of adding checksum in between data inside the disk based queue. The method includes yet another step of dividing the disk based queue in to a plurality of sub-queues with the delay factor. Furthermore, the checksum is added for identifying tampering in data, maintaining persistence and throughput in the disk based queue. Moreover, the delay factor is achieved by dividing the disk based queue in to the plurality of sub-queues based on a time period. The disk based queue is highly scalable using a network file system.

Abstract: The present disclosure provides a method and system for performing unification of data of one or more users across a plurality of communication devices in a plurality of shards. A user unification system receives a first set of data. In addition, the user unification system maps the first set of data to a first natural number. Further, the user unification system assigns a first shard index to the first set of data. Furthermore, the user unification system obtains a second set of data. Moreover, the user unification system maps the second set of data to a second natural number. Also, the user unification system unifies the first natural number and the second natural number. Also, the user unification system assigns the first shard index to the second set of data associated with a first user of the one or more users.

Abstract: The present disclosure provides a method and system to reduce scan time for single user query using a query processing system. The query processing system receives a first set of data. In addition, the query processing system obtains a second set of data. Further, the query processing system fetches a third set of data. Furthermore, the query processing system stores the first set of data, the second set of data, and the third set of data in a first shard of a plurality of shards. Moreover, the query processing system collects the first set of data, the second set of data, and the third set of data in a first memory region of a plurality of memory regions. Also, the query processing system receives a query request from an administrator. Also, the query processing system scans the first memory region of the plurality of memory regions of the first shard.

Abstract: The present disclosure provides a system for performing a method for scaling one or more query processes elastically. The method includes a first step of receiving a request for running the one or more query processes concurrently. In addition, the method includes another step of pre-determining amount of space required for efficient operation and processing of the one or more query processes. Further, the method includes yet another step of creating one or more virtual spaces in a query space outside the data space for efficient running of the one or more query processes. Furthermore, the method includes yet another step of decompressing compressed data stored in the one or more memory regions of the data space requested by the one or more query processes. Moreover, the method includes yet another step of compressing decompressed data present in the virtual space of the one or more virtual spaces.

Abstract: The present disclosure provides a computer-implemented method and system for assessing an effectiveness of one or more marketing campaigns using RFM matrix in real-time. The computer-implemented method and system corresponds to a marketing campaign evaluation system. The marketing campaign evaluation system receives a first set of data. The marketing campaign evaluation system fetches a second set of data. The marketing campaign evaluation system obtains a third set of data. The marketing campaign evaluation system analyzes the first set of data, the second set of data and the third set of data. The marketing campaign evaluation system enables segmentation of a plurality of users in one or more segments. The marketing campaign evaluation system initiates the one or more marketing campaigns through a RFM grid. The marketing campaign evaluation system creates a transition representation. The marketing campaign evaluation system evaluates the effectiveness of each of the one or more marketing campaigns.

Abstract: The present disclosure provides a computer-implemented method and system for running high performance marketing campaigns for granular-level segments of users in real-time. The computer-implemented method and system corresponds to a user segmentation system. The user segmentation system receives a first set of data associated with a plurality of users. The user segmentation system fetches a second set of data. The user segmentation system obtains a third set of data. The user segmentation system analyzes the first set of data, the second set of data and the third set of data. The user segmentation system enables segmentation of the plurality of users. The user segmentation system assigns one or more segment goals. The user segmentation system creates a plurality of micro-segments. The user segmentation system triggers initialization of one or more marketing campaigns. The user segmentation system predicts performance of each of the one or more marketing campaigns.

Abstract: The present disclosure provides a computer-implemented method and system for granular-level segmentation of users based on online activities in real-time. The computer-implemented method and system corresponds to a user segmentation system. The user segmentation system receives a first set of data associated with a plurality of users. The user segmentation system fetches a second set of data. The user segmentation system obtains a third set of data. The user segmentation system analyzes the first set of data, the second set of data and the third set of data using one or more machine learning algorithms. The user segmentation system creates one or more segments of the plurality of users using one or more categories based on a plurality of filters. The user segmentation system triggers initialization of one or more marketing campaigns for the one or more segments.

Abstract: The present disclosure provides a computer-implemented method and system for granular level segmentation of users based on online activities on a webpage in real-time. The computer-implemented method and system corresponds to a user segmentation system. The user segmentation system receives a first set of data associated with a plurality of users. The user segmentation system fetches a second set of data. The user segmentation system obtains a third set of data. The user segmentation system analyzes the first set of data, the second set of data and the third set of data using one or more machine learning algorithms. The user segmentation system creates one or more segments based on analysis performed on the first set of data, the second set of data and the third set of data. The user segmentation system initiates one or more marketing campaigns for the one or more segments.