US 12,271,926 B2
Methods and systems for automated generation of personalized messages
Marco Lagi, Medford, MA (US); Vedant Misra, Cambridge, MA (US); Kevin M. Walsh, Marion, MA (US); and Scott Judson, Boston, MA (US)
Assigned to HubSpot, Inc., Cambridge, MA (US)
Filed by HubSpot, Inc., Cambridge, MA (US)
Filed on Apr. 1, 2022, as Appl. No. 17/657,687.
Application 17/657,687 is a continuation of application No. 16/668,696, filed on Oct. 30, 2019, granted, now 11,321,736.
Application 16/668,696 is a continuation of application No. PCT/US2018/032348, filed on May 11, 2018.
Claims priority of provisional application 62/504,549, filed on May 11, 2017.
Prior Publication US 2022/0222703 A1, Jul. 14, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 30/02 (2023.01); G06F 16/95 (2019.01); G06F 16/9535 (2019.01); G06F 16/9538 (2019.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06Q 30/0251 (2023.01)
CPC G06Q 30/0254 (2013.01) [G06F 16/9535 (2019.01); G06F 16/9538 (2019.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06Q 30/0269 (2013.01)] 24 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
dynamically updating a knowledge data structure to reflect a new entity identified by a crawler of a crawling system extracting information from an external data source over a communication network by:
identifying, by a machine learning system utilizing a classification model, the new entity from the information extracted by the crawler; and
dynamically updating the knowledge structure for the new entity by creating a new node and a new edge between the new node and an existing node within the knowledge data structure, wherein the new node represents the new entity and the new edge represents a new relationship identified by the machine learning system between the new entity and an existing entity represented by the existing node, wherein the knowledge structure is populated with:
entity data representing business entities and individual entities stored as objects within a customer relationship database (CRM) system and tracked using the knowledge structure;
relationship data of relationships between the business entities and individual entities; and
event data relating to events associated with the business entities and individual entities, wherein the event data is associated by the knowledge structure with the new node and the new edge connecting the new node to the existing node based upon the event data specifying an event that occurred between the new entity represented by the new node and the existing entity represented by the existing node;
determining, by a processing system using attributes of an ideal recipient identified based upon an objective of a message and historical data related to outcomes associated with previously sent messages generated to achieve the objective of the message, a recipient list based on a recipient profile and the knowledge data structure that stores entity data relating to entities and relationships between the entities;
generating and providing, by the processing system, a personalized message personalized to an individual in the recipient list based on the entity data and the relationships, wherein the processing system automatically generates the personalized message by:
automatically inferring a message template from historical data of users;
constructing personalized content based upon an objective of communicating with the individual; and
populating the message template with the personalized content to automatically generate the personalized message, wherein the message template is populated with directed content generated using the event data associated by the knowledge structure with the new node and the new edge.