
When this happens...
A new lead form is submitted
Automatically do this!
Enable Integrations or automations with these events of Facebook Lead Ads and Coursera: Data Science Specialization
Triggers when a new lead form is submitted from facebook leads.
Retrieve leads from a selected Facebook lead form for the chosen page; returns lead details and a pagination cursor.
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Workflow automation is the process of using technology to execute repetitive tasks with minimal human intervention, creating a seamless flow of activities.
To start, connect both your Facebook Lead Ads and Coursera: Data Science Specialization accounts to viaSocket. Once connected, you can set up a workflow where an event in Facebook Lead Ads triggers actions in Coursera: Data Science Specialization (or vice versa).
Absolutely. You can customize how Facebook Lead Ads 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 Facebook Lead Ads 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 Facebook Lead Ads 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.
Automate the process of capturing and managing leads from Facebook. Seamlessly integrate your Facebook lead generation campaigns with your CRM or email marketing tools to ensure no potential customer is missed.
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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