
When this happens...
New Activity
Deal Won
Update Deal
Update Organization
Update Person
New Deal
New Person
New Organization
Deal Lost
Deal Stage Updated
Deal Deleted
Automatically do this!
Enable Integrations or automations with these events of Agendor and Coursera: Data Science Specialization
Triggers when new activity created.
Check whether the deal status has been updated to **Won**.
Triggers when deal is updated.
Check if an organization has been updated.
Triggers when person is updated.
Triggers when new deal is created.
Create a task for a deal
Create organization task
Add a task to a person.
Update a deal using its ID
Get details for a deal by ID
Create a new deal for an organization by org id.
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To start, connect both your Agendor and Coursera: Data Science Specialization accounts to viaSocket. Once connected, you can set up a workflow where an event in Agendor triggers actions in Coursera: Data Science Specialization (or vice versa).
Absolutely. You can customize how Agendor data is recorded in Coursera: Data Science Specialization. This includes choosing which data fields go into which fields of Coursera: Data Science Specialization, setting up custom formats, and filtering out unwanted information.
The data sync between Agendor and Coursera: Data Science Specialization typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Agendor and Coursera: Data Science Specialization. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
Customer relationship management platform where user can manage organizations, people, task and deals.
Learn MoreMaster the art of data science with Coursera’s Data Science Specialization, created by Johns Hopkins University. This program guides you through the full data science pipeline—from data wrangling and statistical analysis to machine learning and data visualization—using R and real-world projects.
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