Systems and methods for generating performance profiles using electronic activities matched with record objects

• US 10,649,999 B2
• Filed: 05/23/2019
• Issued: 05/12/2020
• Est. Priority Date: 05/24/2018
• Status: Active Grant

• Current Assignee: People.ai, Inc.
• Original Assignee: People.ai, Inc.
• Inventors: Rogynskyy, Oleg, Brunets, Yurii, Jeske, Eric, Dingwall, Nicholas
• Primary Examiner(s): Hasan, Syed H
• Application Number:
  US16/421,328
• Publication Number:
  US 20190361926A1
• Time in Patent Office: 355 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 and systems for generating performance profiles using electronic activities linked to record objects are disclosed. Exemplary implementations may: access a record objects of a system of record of a data source provider; identify, from the record objects, a subset of record objects associated with a node profile corresponding to an entity; identify, for each record object of the subset, electronic activities linked to the record object; determine, for each record object of the subset, a respective entity engagement profile for the entity based on the electronic activities linked to the record object and one or more object field-value pairs of the record object; generate a composite entity engagement profile of the entity based on each respective entity engagement profile corresponding to each record object of the subset of record objects; and store, in one or more data structures, an association between the entity and the entity performance profile.

Claims

1. A method comprising:

accessing, by one or more processors, a plurality of first record objects of a system of record of a data source provider, each first record object of the plurality of first record objects comprising one or more object fields having one or more object field values, each of the plurality of first record objects associated with one or more electronic activities;

identifying, by the one or more processors, from the plurality of first record objects, a subset of first record objects associated with a node profile corresponding to an entity;

identifying, by the one or more processors, for each first record object of the subset of first record objects, electronic activities linked to the first record object;

determining, by the one or more processors, for each first record object of the subset of first record objects, a respective entity engagement profile for the entity based on i) the electronic activities linked to the first record object and ii) one or more object field-value pairs of the first record object;

generating, by the one or more processors, a composite entity engagement profile of the entity based on each respective entity engagement profile corresponding to each first record object of the subset of first record objects;

storing, by the one or more processors, in one or more data structures, an association between the entity and the composite entity engagement profile;

identifying, by the one or more processors, a second record object having one or more object field-value pairs; and

matching, by the one or more processors, the second record object with the entity based on i) the composite entity engagement profile of the entity and ii) the one or more object field-value pairs of the second record object.

2. The method of claim 1,

matching the second record object with the entity based on i) the composite entity engagement profile of the entity, ii) the object-field value pairs of the second record object, and iii) the electronic activities linked to the second record object.

3. The method of claim 2, further comprising:

identifying, by the one or more processors, one or more participants of the electronic activities linked to the second record object;

determining, by the one or more processors, that the identified one or more participants match participants of electronic activities linked to record objects of the subset of record objects; and

matching, by the one or more processors, the second record object with the entity based on i) the composite entity engagement profile, ii) the object-field value pairs of the second record object, iii) the electronic activities linked to the second record object, and iv) the one or more participants of the electronic activities linked to the second record object that match the participants of electronic activities linked to the first record objects of the subset of first record objects.

4. The method of claim 1, wherein the entity is a first member entity of a first group entity and wherein the one or more object field-value pairs of the second record object correspond to a first field identifying a size value of the second record object or a second field identifying a second group entity of the second record object.

5. The method of claim 1, wherein the entity is a first member entity and wherein the one or more object field-value pairs of the second record object correspond to a first field identifying a second entity linked to a first group entity to which the first member entity is linked and a second field identifying a third member entity linked to a second group entity.

6. The method of claim 1, further comprising:

determining, by the one or more processors, a classification of each first record object based on the one or more object field-value pairs of the respective first record object, wherein the entity engagement profile corresponding to the first record is determined based on the classification of the first record object.

7. The method of claim 6, further comprising:

determining, by the one or more processors, a status of each first record object based on a field-value pair of the respective first record object, wherein the composite entity engagement profile corresponding to the first record is determined based on the classification of the first record object.

8. The method of claim 1, wherein the entity is a first entity, the node profile is a first node profile, and the composite entity engagement profile is a first composite entity engagement profile, further comprising:

identifying, by the one or more processors, a second node profile of a second entity associated with the second record object;

identifying, by the one or more processors, a second composite entity engagement profile corresponding to the second node profile; and

generating, by the one or more processors, a match score between the first composite entity engagement profile and the second composite entity engagement profile, wherein matching the second record object to the first entity is performed responsive to the match score satisfying a threshold.

9. The method of claim 8, wherein generating the match score comprises:

applying, by the one or more processors, an engagement profile matching policy to the first composite entity engagement profile and the second composite entity engagement profile, the engagement profile matching policy being configured to generate the match score based on complementary characteristics within the first composite entity engagement profile and the second composite entity engagement profile.

10. A system comprising:

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

access a plurality of first record objects of a system of record of a data source provider, each first record object of the plurality of first record objects comprising one or more object fields having one or more object field values, each of the plurality of first record objects associated with one or more electronic activities;

identify, from the plurality of first record objects, a subset of first record objects associated with a node profile corresponding to an entity;

identify, for each first record object of the subset of first record objects, electronic activities linked to the first record object;

determine, for each first record object of the subset of first record objects, a respective entity engagement profile for the entity based on i) the electronic activities linked to the first record object and ii) one or more object field-value pairs of the first record object;

generate a composite entity engagement profile of the entity based on each respective entity engagement profile corresponding to each first record object of the subset of first record objects;

store, in one or more data structures, an association between the entity and the composite entity engagement profile;

identify a second record object having one or more object field-value pairs; and

match the second record object with the entity based on i) the composite entity engagement profile of the entity and ii) the one or more object field-value pairs of the second record object.

11. The system of claim 10, wherein the one or more processors are further configured by machine-readable instructions to:

match the second record object with the entity is based on i) the composite entity engagement profile of the entity, ii) the object-field value pairs of the second record object, and iii) the electronic activities linked to the second record object.

12. The system of claim 11, wherein the one or more processors are further configured by machine-readable instructions to:

identify one or more participants of the electronic activities linked to the second record object;

determine that the identified one or more participants match participants of electronic activities linked to record objects of the subset of record objects;

match the second record object with the entity based on i) the composite entity engagement profile, ii) the object-field value pairs of the second record object, iii) the electronic activities linked to the second record object, and iv) the one or more participants of the electronic activities linked to the second record object that match the participants of electronic activities linked to the record objects of the subset of record objects.

13. The system of claim 10, wherein the entity is a first member entity of a first group entity and wherein the one or more object field-value pairs of the second record object correspond to a first field identifying a size value of the second record object or a second field identifying a second group entity of the second record object.

14. The system of claim 10, wherein the entity is a first member entity and wherein the one or more object field-value pairs of the second record object correspond to a first field identifying a second entity linked to a first group entity to which the first member entity is linked and a second field identifying a third member entity linked to a second group entity.

15. The system of claim 10, wherein the entity is a first entity, the node profile is a first node profile, and the composite entity engagement profile is a first composite entity engagement profile;

wherein the one or more processors are further configured by machine-readable instructions to identify a second node profile of a second entity associated with the second record object;

wherein the one or more processors are further configured by machine-readable instructions to identify a second composite entity engagement profile corresponding to the second node profile;

wherein the one or more processors are further configured by machine-readable instructions to generate a match score between the first composite entity engagement profile and the second composite entity engagement profile, wherein matching the second record object to the first entity is performed responsive to the match score satisfying a threshold.

16. The system of claim 15, wherein generating the match score comprises applying an engagement profile matching policy to the first composite entity engagement profile and the second composite entity engagement profile, the engagement profile matching policy being configured to generate the match score based on complementary characteristics within the first composite entity engagement profile and the second composite entity engagement profile.

17. The system of claim 10, wherein the one or more processors are further configured by machine-readable instructions to:

determine a classification of each first record object or a status of the record object based on at least one of the one or more object field-value pairs of the first record object, wherein the entity engagement profile corresponding to the first record object is determined based on at least one of the classification or the status of the first record object.

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

accessing a plurality of first record objects of a system of record of a data source provider, each first record object of the plurality of first record objects comprising one or more object fields having one or more object field values, each of the plurality of first record objects associated with one or more electronic activities;

identifying, from the plurality of first record objects, a subset of first record objects associated with a node profile corresponding to an entity;

identifying, for each first record object of the subset of first record objects, electronic activities linked to the first record object;

determining, for each first record object of the subset of first record objects, a respective entity engagement profile for the entity based on i) the electronic activities linked to the first record object and ii) one or more object field-value pairs of the first record object;

generating a composite entity engagement profile of the entity based on each respective entity engagement profile corresponding to each first record object of the subset of first record objects;

storing, in one or more data structures, an association between the entity and the composite entity engagement profile;

identifying a second record object having one or more object field-value pairs; and

matching the second record object with the entity based on i) the composite entity engagement profile of the entity and ii) the one or more object field-value pairs of the second record object.