Integrations Sangam CRM Coursera: Data Science Specialization
Sangam CRM + Coursera: Data Science Specialization

Connect Sangam CRM and Coursera: Data Science Specialization to Build Intelligent Automations

Choose a Trigger

Sangam CRM

When this happens...

Choose an Action

Coursera: Data Science Specialization

Automatically do this!

Enable Integrations or automations with these events of Sangam CRM and Coursera: Data Science Specialization

Enable Integrations or automations with these events of Sangam CRM and Coursera: Data Science Specialization

Triggers

New Lead Created

New Lead Created

Runs when new lead is created

New Contact Created

New Contact Created

Trigger when new contact is created

New Opportunity Created

New Opportunity Created

Triggerv when new opportunity is created

New Ticket Created

New Ticket Created

Runs when new ticket is created

New Account Created

New Account Created

Runs when new account is created

New Task Created

New Task Created

Runs when new task is created

Actions

Create a new Lead

Create a new Lead

Add a new lead to Sangam CRM using selected custom fields and an optional next follow-up date.

Create an opportunity

Create an opportunity

Adds a new opportunity Sangam CRM.

Fetch all available fields in a specific module

Fetch all available fields in a specific module

Fetch all fields available in specific module

Create a Contact

Create a Contact

Creates a new contact in Sangam CRM.

Create Ticket

Create Ticket

Create a new ticket in Sangam CRM.

Create a Company

Create a Company

Creates a new comppany in sangam CRM.

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Step by step guides to integrate Sangam CRM and Coursera: Data Science Specialization

Frequently Asked Questions

How do I start an integration between Sangam CRM and Coursera: Data Science Specialization?

To start, connect both your Sangam CRM and Coursera: Data Science Specialization accounts to viaSocket. Once connected, you can set up a workflow where an event in Sangam CRM triggers actions in Coursera: Data Science Specialization (or vice versa).

Can we customize how data from Sangam CRM is recorded in Coursera: Data Science Specialization?

Absolutely. You can customize how Sangam CRM 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.

How often does the data sync between Sangam CRM and Coursera: Data Science Specialization?

The data sync between Sangam CRM 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.

Can I filter or transform data before sending it from Sangam CRM to Coursera: Data Science Specialization?

Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.

Is it possible to add conditions to the integration between Sangam CRM and Coursera: Data Science Specialization?

Yes, you can set conditional logic to control the flow of data between Sangam CRM 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.

Sangam CRM

About Sangam CRM

Sangam CRM is a comprehensive customer relationship management platform designed to streamline your business processes, enhance customer interactions, and drive sales growth. With features like contact management, sales automation, and analytics, Sangam CRM helps businesses of all sizes manage their customer data efficiently and improve their overall customer experience.

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Coursera: Data Science Specialization

About Coursera: Data Science Specialization

Master 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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