Method for determining and notifying users of pending activities on CRM data

Patent metadata

Field	Value
Publication number	US-11893427-B2
Application number	US-201916398963-A
Country	US
Kind code	B2
Filing date	Apr 30, 2019
Priority date	Oct 17, 2018
Publication date	Feb 6, 2024
Grant date	Feb 6, 2024

Abstract

The disclosure describes various embodiments for determining emails that each need a response based on data from a customer relationship (CRM) system. In one embodiment, a method of determining such emails includes the operations of retrieving open tasks assigned to a user from a task database; determining one or more source email domains for one or more source contacts, and one or more target email domains for one or more target contacts; and determining one or more threads emails exchanged between the source contacts and the target contacts based on the source email domains and the target email domains. The method further includes the operations of creating an email list from the threads of emails, including a latest email from a group that was sent by a target contact; and generating a subset of the list of emails by analyzing contents of each of the list of emails using a machine learning model.

First claim

What is claimed is:

1. A computer-implemented method for identifying and notifying users of pending emails, the method comprising:
retrieving, by a cloud server, task metadata describing a task pending to be completed from a task database hosted by a task management server over a network, the task management server being a different server than the cloud server, wherein the task metadata includes source contact information and target contact information associated with the task;
determining, based on the task metadata, a plurality of user identifiers (IDs) identifying one or more source contacts and one or more target contacts associated with the task;
retrieving, from a persistent storage device, a source set of activity identification rules and a target set of activity identification rules;
determining one or more source email domains for the one or more source contacts based on the source contact information and the source set of activity identification rules;
determining one or more target email domains for the one or more target contacts based on the target contact information and the target set of activity identification rules;
accessing an email server over the network to retrieve email metadata based on the one or more source email domains and the one or more target email domains, the email server being a separate server than the cloud server and the task management server, the email metadata describing a plurality of emails associated with the task;
identifying a plurality of email threads associated with the task from the plurality of emails based on the email metadata, each email thread including one or more emails exchanged between one of the one or more source contacts and one or more of the one or more target contacts;
for each of the plurality of email threads associated with the task,
identifying, within the email thread and based on a timestamp of the email, a latest email that was sent by a user ID associated with one of the one or more target email domains,
determining that the latest email has not been replied to by a user ID associated with any one of the one or more source email domains,
subsequent to the determining that the latest email has not been replied to by the user ID, retrieving a body of the latest email from the email server,
performing a content analysis on content of the body of the latest email using a machine-learning model to determine whether the latest email needs a response, and
transmitting a notification to one or more source email addresses associated with the task in response to determining that the latest email needs a response; and

creating a list of emails from the plurality of email threads associated with the task based on the notification associated with each email thread, wherein the list of emails includes only one email from each of one or more of the plurality of email threads associated with the task, wherein each email in the list of emails has been determined to need a response; and
sending the list of emails to a client device, wherein the client device displays the list of emails in a graphical user interface for a user to respond to, and periodically alerts the user of any email in the list of emails that the user needs to respond to.

2. The method of claim 1 , further comprising:
removing one or more emails with a timestamp more recent than a preconfigured timestamp from consideration in creating the list of emails.

3. The method of claim 1 , wherein each email in the list of emails includes metadata of the email without a body, the metadata including one or more of the following: a timestamp, a sender and a receiver, a source email domain, a target email domain, or a subject line.

4. The method of claim 1 , wherein emails in the plurality of email threads exchanged between the one or more source email domains and the one or more target email domains are retrieved from the task database in response to the user logging on to an application with the graphical user interface.

5. The method of claim 1 , wherein emails in the plurality of email threads exchanged between the one or more source email domains and the one or more target email domains are retrieved from a database in the cloud server, wherein the database is periodically synchronized with an activity database server that stores emails of users.

6. The method of claim 1 , wherein the machine-learning model is a neural network model.

7. The method of claim 1 , wherein the one or more target contacts include a task contact and an account contact and determining the one or more target email domains for the one or more target contacts based on the target contact information and the target set of activity identification rules comprises utilizing the task contact instead of the account contact to determine the one or more target email domains based on the target set of activity identification rules.

8. The method of claim 1 , further comprising:
extracting a first target email domain of the one or more target email domains from an email address of a first target contact of the one or more target contacts; and
identifying an email address of a second target contact of the one or more target contacts based on the first target email domain extracted from the email address of the first target contact.

9. The method of claim 1 , wherein determining the one or more target email domains for the one or more target contacts based on the target contact information and the target set of activity identification rules comprises:
identifying a web address in the target contact information; and
utilizing the web address to determine the one or more target email domains based on the target set of activity identification rules.

10. The method of claim 1 , wherein determining the one or more target email domains for the one or more target contacts based on the target contact information and the target set of activity identification rules comprises:
determining an account name associated with the task; and
accessing a name-to-domain mapping table to obtain the one or more target email domains based on the account name associated with the task.

11. The method of claim 1 , wherein the one or more target contacts include a first contact and a second contact and determining the one or more target email domains for the one or more target contacts based on the target contact information and the target set of activity identification rules comprises:
determining the first contact is associated with a predetermined number of accounts, wherein the predetermined number of accounts comprises two or more accounts; and
utilizing the second contact instead of the first contact to determine the one or more target email domains based on association of the first contact with the predetermined number of accounts.

12. The method of claim 1 , further comprising:
identifying an email exchanged between one of the one or more source contacts and one or more of the one or more target contacts prior to creation of the task; and
removing the email exchanged prior to creation of the task from consideration in creating the list of emails.

13. A non-transitory machine-readable storage medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations, the operations comprising:
retrieving, by a cloud server, task metadata describing a task pending to be completed from a task database hosted by a task management server over a network, the task management server being a different server than the cloud server, wherein the task metadata includes source contact information and target contact information associated wi

Assignees

• Clari Inc

Inventors

• Subedi Mahesh

Classifications

• G06N3/0499

  Feedforward networks · CPC title

• G06N3/09

  Supervised learning · CPC title

• G06F9/542 Primary

  Event management; Broadcasting; Multicasting; Notifications · CPC title

• G06N3/08

  Learning methods · CPC title

• G06N20/00

  Machine learning · CPC title