Systems and methods for managing electronic activity driven targets

• US 10,504,050 B1
• Filed: 05/23/2019
• Issued: 12/10/2019
• Est. Priority Date: 05/24/2018
• Status: Active Grant

• Current Assignee: People.ai, Inc.
• Original Assignee: People.ai, Inc.
• Inventors: Rogynskyy, Oleg, Hai, Wei, Shah, Kavita
• Primary Examiner(s): Truong, Cam Y T
• Application Number:
  US16/421,298
• Publication Number:
  US 20190362290A1
• Time in Patent Office: 201 Days
• CPC Class Codes: G06F 11/3024 where the computing system component is a central processing unit [CPU]
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis
• CPC Class Codes: G06F 11/3495 for systems
• CPC Class Codes: G06F 16/122 using management policies backup systems G06F11/1446; file migration policies for HSM systems G06F16/185
• CPC Class Codes: G06F 16/1734 Details of monitoring file system events, e.g. by the use of hooks, filter drivers, logs
• CPC Class Codes: G06F 16/178 Techniques for file synchronisation in file systems
• CPC Class Codes: G06F 16/182 Distributed file systems
• CPC Class Codes: G06F 16/212 with details for data modelling support
• CPC Class Codes: G06F 16/215 Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• CPC Class Codes: G06F 16/219 Managing data history or versioning querying versioned data G06F16/2474; querying temporal data G06F16/2477
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/221 Column-oriented storage; Management thereof
• CPC Class Codes: G06F 16/2228 Indexing structures
• CPC Class Codes: G06F 16/2264 Multidimensional index structures
• CPC Class Codes: G06F 16/2272 Management thereof
• CPC Class Codes: G06F 16/23 Updating
• CPC Class Codes: G06F 16/235 Update request formulation
• CPC Class Codes: G06F 16/2358 Change logging, detection, and notification replication G06F16/27
• CPC Class Codes: G06F 16/2365 Ensuring data consistency and integrity
• CPC Class Codes: G06F 16/2379 Updates performed during online database operations; commit processing
• CPC Class Codes: G06F 16/2386 : Bulk updating operations data conversion details G06F16/258
• CPC Class Codes: G06F 16/245 : Query processing
• CPC Class Codes: G06F 16/24558 : Binary matching operations
• CPC Class Codes: G06F 16/24564 : Applying rules; Deductive queries
• CPC Class Codes: G06F 16/2457 : with adaptation to user needs
• CPC Class Codes: G06F 16/24575 : using context
• CPC Class Codes: G06F 16/24578 : using ranking
• CPC Class Codes: G06F 16/2477 : Temporal data queries
• CPC Class Codes: G06F 16/254 : Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06F 16/256 : in federated or virtual databases
• CPC Class Codes: G06F 16/26 : Visual data mining; Browsing structured data
• CPC Class Codes: G06F 16/27 : Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
• CPC Class Codes: G06F 16/273 : Asynchronous replication or reconciliation
• CPC Class Codes: G06F 16/28 : Databases characterised by their database models, e.g. relational or object models
• CPC Class Codes: G06F 16/285 : Clustering or classification
• CPC Class Codes: G06F 16/288 : Entity relationship models
• CPC Class Codes: G06F 16/289 : Object oriented databases
• CPC Class Codes: G06F 16/29 : Geographical information databases
• CPC Class Codes: G06F 16/313 : Selection or weighting of terms for indexing
• CPC Class Codes: G06F 16/337 : Profile generation, learning or modification
• CPC Class Codes: G06F 16/355 : Class or cluster creation or modification
• CPC Class Codes: G06F 16/901 : Indexing; Data structures therefor; Storage structures for retrieval from the web G06F16/951
• CPC Class Codes: G06F 16/9024 : Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06F 16/90344 : by using string matching techniques
• CPC Class Codes: G06F 16/9035 : Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/906 : Clustering; Classification
• CPC Class Codes: G06F 16/93 : Document management systems
• CPC Class Codes: G06F 16/9535 : Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 21/6218 : to a system of files or objects, e.g. local or distributed file system or database
• CPC Class Codes: G06F 21/6245 : Protecting personal data, e.g. for financial or medical purposes
• CPC Class Codes: G06F 40/20 : Natural language analysis semantic analysis of natural language G06F40/30
• CPC Class Codes: G06F 40/205 : Parsing
• CPC Class Codes: G06F 40/237 : Lexical tools
• CPC Class Codes: G06F 40/295 : Named entity recognition
• CPC Class Codes: G06F 40/30 : Semantic analysis
• CPC Class Codes: G06F 7/14 : Merging, i.e. combining at least two sets of record carriers each arranged in the same ordered sequence to produce a single set having the same ordered sequence
• CPC Class Codes: G06F 9/542 : Event management; Broadcasting; Multicasting; Notifications
• CPC Class Codes: G06N 20/00 : Machine learning
• CPC Class Codes: G06N 3/08 : Learning methods
• CPC Class Codes: G06N 5/022 : Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/025 : Extracting rules from data
• CPC Class Codes: G06N 5/04 : Inference or reasoning models
• CPC Class Codes: G06N 7/02 : using fuzzy logic computing arrangements based on biological models G06N3/00; computing arrangements using knowledge-based models G06N5/00
• CPC Class Codes: G06Q 10/04 : Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/063114 : Status monitoring or status determination for a person or group
• CPC Class Codes: G06Q 10/06312 : Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
• CPC Class Codes: G06Q 10/06315 : Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/06393 : Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 10/06398 : Performance of employee with respect to a job function
• CPC Class Codes: G06Q 10/10 : Office automation; Time management
• CPC Class Codes: G06Q 10/107 : Computer-aided management of electronic mailing [e-mailing]
• CPC Class Codes: G06Q 10/109 : Time management, e.g. calendars, reminders, meetings or time accounting
• CPC Class Codes: G06Q 10/1091 : Recording time for administrative or management purposes
• CPC Class Codes: G06Q 10/1095 : Meeting or appointment
• CPC Class Codes: G06Q 30/0201 : Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 50/01 : Social networking
• CPC Class Codes: G06Q 50/22 : Social work or social welfare, e.g. community support activities or counselling services
• CPC Class Codes: G16H 15/00 : ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment
• CPC Class Codes: H04L 12/14 : Charging , metering or billing arrangements for data wireline or wireless communications
• CPC Class Codes: H04L 12/1407 : Policy-and-charging control [PCC] architecture
• CPC Class Codes: H04L 12/1831 : Tracking arrangements for later retrieval, e.g. recording contents, participants activities or behavior, network status
• CPC Class Codes: H04L 2101/00 : Indexing scheme associated with group H04L61/00
• CPC Class Codes: H04L 2101/35 : containing special prefixes
• CPC Class Codes: H04L 2101/37 : E-mail addresses
• CPC Class Codes: H04L 41/082 : the condition being updates or upgrades of network functionality
• CPC Class Codes: H04L 41/14 : Network analysis or design
• CPC Class Codes: H04L 43/026 : using flow identification
• CPC Class Codes: H04L 43/045 : for graphical visualisation of monitoring data
• CPC Class Codes: H04L 43/062 : related to network traffic
• CPC Class Codes: H04L 43/065 : related to network devices
• CPC Class Codes: H04L 43/067 : using time frame reporting
• CPC Class Codes: H04L 43/08 : Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
• CPC Class Codes: H04L 43/0876 : Network utilisation, e.g. volume of load or congestion level
• CPC Class Codes: H04L 43/14 : using software, i.e. software packages network security related monitoring H04L63/1408
• CPC Class Codes: H04L 51/046 : Interoperability with other network applications or services
• CPC Class Codes: H04L 51/212 : using filtering or selective blocking
• CPC Class Codes: H04L 51/234 : for tracking messages
• CPC Class Codes: H04L 51/42 : Mailbox-related aspects, e.g. synchronisation of mailboxes
• CPC Class Codes: H04L 61/45 : Network directories; Name-to-address mapping
• CPC Class Codes: H04L 61/4594 : Address books, i.e. directories containing contact information about correspondents telephone directories in user terminals H04M1/27453
• CPC Class Codes: H04L 67/125 : involving control of end-device applications over a network
• CPC Class Codes: H04L 67/30 : Profiles
• CPC Class Codes: H04L 67/303 : Terminal profiles
• CPC Class Codes: H04L 67/306 : User profiles
• CPC Class Codes: H04L 67/535 : Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04M 15/00 : Arrangements for metering, time-control or time indication ; Metering, charging or billing arrangements for voice wireline or wireless communications, e.g. VoIP
• CPC Class Codes: H04M 15/41 : Billing record details, i.e. parameters, identifiers, structure of call data record [CDR]
• CPC Class Codes: H04M 15/50 : for cross-charging network operators
• CPC Class Codes: H04M 15/58 : based on statistics of usage or network monitoring
• CPC Class Codes: H04M 15/60 : based on actual use of network resources
• CPC Class Codes: H04M 15/66 : Policy and charging system
• CPC Class Codes: H04M 15/755 : Account identification
• CPC Class Codes: H04M 2203/556 : Statistical analysis and interpretation
• CPC Class Codes: H04M 3/2218 : Call detail recording
• CPC Class Codes: H04M 3/436 : Arrangements for screening incoming calls , i.e. evaluating the characteristics of a call before deciding whether to answer it based on the calling party profile H04M3/42059; based on location H04M3/42348; based on presence H04M3/42365; diversion H04M3/54
• CPC Class Codes: H04M 3/5175 : Call or contact centers supervision arrangements
• CPC Class Codes: H04M 3/56 : Arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities video conference systems H04N7/15
• CPC Class Codes: H04W 4/24 : Accounting or billing

Abstract

Methods, systems, and storage media for managing electronic activity driven targets are disclosed. Example implementations may: maintain a plurality of node profiles; select, for a first node profile, using one or more field-value pairs of the first node profile, an endpoint profile generated using electronic activities of second node profiles including one or more field-value pairs that match the one or more field-value pairs of the first node profile, the endpoint profile specifying electronic activity driven targets that can be tracked by parsing electronic activities corresponding to the first node profile; store in one or more data structures, an association between the first node profile and the endpoint profile specifying the electronic activity driven targets; parse a plurality of electronic activities corresponding to the first node profile; and update a metric relating to the electronic activity driven targets responsive to parsing the second plurality of electronic activities.

Claims

1. A method comprising:

maintaining, by one or more processors, a plurality of node profiles respectively corresponding to a plurality of entities, each node profile including a plurality of field-value pairs;

accessing, by the one or more processors, data from a first plurality of electronic activities transmitted or received via electronic accounts associated with one or more data source providers, the one or more processors configured to update the plurality of node profiles using the data from the first plurality of electronic activities;

generating, by the one or more processors, for a first node profile of the plurality of node profiles, an endpoint profile using data from electronic activities of at least one second node profile, the at least one second node profile including one or more field-value pairs that match one or more field-value pairs of the first node profile, the endpoint profile specifying targets that can be tracked based on electronic activities corresponding to the first node profile, the first node profile different from the at least one second node profile, wherein generating the endpoint profile comprises

generating, by the one or more processors, for each second node profile of the at least one second node profile, a respective electronic activity pattern based on a second plurality of electronic activities transmitted or received via electronic accounts of the second node profile, and

setting, by the one or more processors, one or more target values for the endpoint profile based on each respective electronic activity pattern;

storing, by the one or more processors, in one or more data structures, an association between the first node profile and the endpoint profile specifying the targets;

parsing, by the one or more processors, data from a third plurality of electronic activities corresponding to the first node profile;

updating, by the one or more processors, a metric relating to the targets responsive to parsing the data from the third plurality of electronic activities;

determining, by the one or more processors, that the updated metric does not satisfy a threshold value; and

transmitting, by the one or more processors, responsive to determining that the updated metric does not satisfy the threshold value, a notification to a contact identifier corresponding to a third node profile, the notification referencing at least one of the targets.

2. The method of claim 1, wherein generating the respective electronic activity pattern for the second node profile comprises:

parsing, by the one or more processors, data from each electronic activity of the second plurality of electronic activities;

generating, by the one or more processors, for each electronic activity of the second plurality of electronic activities, one or more activity field-value pairs corresponding to respective node field-value pairs of node profiles of participants of the electronic activity; and

using, by the one or more processors, the one or more activity field-value pairs to generate the respective electronic activity pattern.

3. The method of claim 2, wherein using the one or more activity-field value pairs to generate the respective electronic activity pattern comprises using a volume of electronic activities that identify participants corresponding to node profiles including node field value pairs that specify a predetermined value of a predetermined field.

4. The method of claim 1, wherein updating the metric comprises generating an updated metric and further comprising:

determining, by the one or more processors, that the updated metric is below a threshold value; and

transmitting, by the one or more processors responsive to determining that the updated metric is below the threshold value, a notification to a contact identifier specified by the first node profile, the notification referencing at least one of the targets.

5. The method of claim 1, wherein:

the metric is a count of a number of record objects associated with the first node profile and having a stage status indicating that a last stage of an ordered set of stages has been completed, and

one of the targets requires meeting at least a threshold value for the metric.

6. The method of claim 1, wherein each second node profile of the second node profiles is associated with at least a threshold number of record objects having a stage status indicating that a specified stage of an ordered set of stages has been completed.

7. The method of claim 1, wherein the electronic activities corresponding to one of the second node profiles used to generate the endpoint profile correspond to a predetermined time period from a trigger time of the second node profile, and a current time is within the predetermined time period of a trigger time of the first node profile.

9. The system of claim 1, wherein generating the respective electronic activity pattern for the second node profile comprises:

parsing data from each electronic activity of the second plurality of electronic activities;

generating, for each electronic activity of the second plurality of electronic activities, one or more activity field-value pairs corresponding to respective node field-value pairs of node profiles of participants of the electronic activity; and

using the one or more activity field-value pairs to generate the respective electronic activity pattern.

10. The system of claim 9, wherein using the one or more activity-field value pairs to generate the respective electronic activity pattern comprises using a volume of electronic activities that identify participants corresponding to node profiles including node field value pairs that specify a predetermined value of a predetermined field.

8. A system comprising:

one or more hardware processors configured by machine-readable instructions to;

maintain a plurality of node profiles respectively corresponding to a plurality of entities, each node profile including a plurality of field-value pairs;

access a first plurality of electronic activities transmitted or received via electronic accounts associated with one or more data source providers, the one or more processors configured to update the plurality of node profiles using the first plurality of electronic activities;

generate, for a first node profile of the plurality of node profiles, an endpoint profile using data from electronic activities of at least one second node profile, the at least one second node profile including one or more field-value pairs that match one or more field-value pairs of the first node profile, the endpoint profile specifying targets that can be tracked based on electronic activities corresponding to the first node profile, the first node profile different from the at least one second node profile, wherein to generate the endpoint profile, the one or more hardware processors are configured to

generate, for each second node profile of the at least one second node profile, a respective electronic activity pattern based on a second plurality of electronic activities transmitted or received via electronic accounts of the second node profile, and

set one or more target values for the endpoint profile based on each respective electronic activity pattern;

store in one or more data structures, an association between the first node profile and the endpoint profile specifying the targets;

parse data from a third plurality of electronic activities corresponding to the first node profile;

update a metric relating to the targets responsive to parsing the data from the third plurality of electronic activities;

determine that the updated metric does not satisfy a threshold value; and

transmit, responsive to determining that the updated metric does not satisfy the threshold value, a notification to a contact identifier corresponding to a third node profile, the notification referencing the at least one of the targets.

11. The system of claim 8, wherein updating the metric comprises generating an updated metric, and the one or more hardware processors are further configured by machine-readable instructions to:

determine that the updated metric is below a threshold value; and

transmit, responsive to determining that the updated metric is below the threshold value, a notification to a contact identifier specified by the first node profile, the notification referencing at least one of the targets.

12. The system of claim 8, wherein:

the metric is a count of a number of record objects associated with the first node profile and having a stage status indicating that a last stage of an ordered set of stages has been completed, and

one of the electronic activity driven targets requires meeting at least a threshold value for the metric.

13. The system of claim 8, wherein each second node profile of the second node profiles is associated with at least a threshold number of record objects having a stage status indicating that a specified stage of an ordered set of stages has been completed.

14. The system of claim 8, wherein the electronic activities corresponding to one of the second node profiles used to generate the endpoint profile correspond to a predetermined time period from a trigger time of the second node profile, and a current time is within the predetermined time period of a trigger time of the first node profile.

15. A non-transitory computer-readable storage medium having instructions embodied thereon, the instructions being executable by one or more processors to perform a method comprising:

maintaining a plurality of node profiles respectively corresponding to a plurality of entities, each node profile including a plurality of field-value pairs;

accessing a first plurality of electronic activities transmitted or received via electronic accounts associated with one or more data source providers, the one or more processors configured to update the plurality of node profiles using the first plurality of electronic activities;

generating, for a first node profile of the plurality of node profiles, an endpoint profile using data from electronic activities of at least one second node profile, the at least one second node profile including one or more field-value pairs that match one or more field-value pairs of the first node profile, the endpoint profile specifying targets that can be tracked based on electronic activities corresponding to the first node profile, the first node profile different from the at least one second node profile, wherein generating the endpoint profile comprises

generating, for each second node profile of the at least one second node profile, a respective electronic activity pattern based on a second plurality of electronic activities transmitted or received via electronic accounts of the second node profile, and

setting, one or more target values for the endpoint profile based on each respective electronic activity pattern;

storing, in one or more data structures, an association between the first node profile and the endpoint profile specifying the targets;

parsing data from a third plurality of electronic activities corresponding to the first node profile;

updating a metric relating to the targets responsive to parsing the data from the third plurality of electronic activities;

determining that the updated metric does not satisfy a threshold value; and

transmitting, responsive to determining that the updated metric does not satisfy the threshold value, a notification to a contact identifier corresponding to a third node profile, the notification referencing the at least one of the targets.