Connect Aura and MonkeyLearn Legacy to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Aura
Choose an Action
Automatically do this!
- Request a new Action for MonkeyLearn Legacy
Enable Integrations or automations with these events of Aura and MonkeyLearn Legacy
Enable Integrations or automations with these events of Aura and MonkeyLearn Legacy
Actions
List Payments
Enter action Description Here
Create Lead
Create a new lead with email
Record Payment
Record a payment for a lead
Get Campaign Analytics
Retrieve lead and call performance aggregated by UTM source, medium, and campaign including show rate, close rate, and revenue.
Update Call
Update the status or notes of an existing call in Aura
Verify Payment
Manually verify a payment by linking it to a specific call.
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Frequently Asked Questions
To start, connect both your Aura and MonkeyLearn Legacy accounts to viaSocket. Once connected, you can set up a workflow where an event in Aura triggers actions in MonkeyLearn Legacy (or vice versa).
Absolutely. You can customize how Aura data is recorded in MonkeyLearn Legacy. This includes choosing which data fields go into which fields of MonkeyLearn Legacy, setting up custom formats, and filtering out unwanted information.
The data sync between Aura and MonkeyLearn Legacy 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 Aura and MonkeyLearn Legacy. 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.
About MonkeyLearn Legacy
MonkeyLearn is a Text Analysis platform that allows you to classify and extract actionable data from raw texts like emails, chats, webpages, documents, tweets and more! You can classify texts with custom tags like sentiment or topic, and extract any particular data like organizations or keywords.
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