Connect Last.fm and Recras to Build Intelligent Automations
Choose a Trigger
When this happens...
Top Artist Changes
Choose an Action
Automatically do this!
Create Start moment
Update Start moment
Find Customer
Ready to use Last.fm and Recras automations
Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
Top Artist Changes
Runs when top artist changes
New Booking Created
Runs when a new booking is created in Recras.
New Contact
Triggers when a new contact is created.
Invoice Sent
Triggers when an invoice is (marked as) sent.
New Start Moment
Triggers when a new start moment is created.
New Attachment
Triggers when a new attachment is created.
Do thisActions
Action is the task that follows automatically within your Last.fm integrations.
Get Artist Details
Get artist profile and stats
Get Top Artists
Retrieve user's top artists
Find Similar Tracks
Find songs like a given track
Find Similar Artists
Get similar artists
Create Start moment
Creates a start moment in recras.
Update Start moment
Updates a start moment in recras.
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Frequently Asked Questions
To start, connect both your Last.fm and Recras accounts to viaSocket. Once connected, you can set up a workflow where an event in Last.fm triggers actions in Recras (or vice versa).
Absolutely. You can customize how Last.fm data is recorded in Recras. This includes choosing which data fields go into which fields of Recras, setting up custom formats, and filtering out unwanted information.
The data sync between Last.fm and Recras 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 Last.fm and Recras. 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 Last.fm
Tracks and analyzes users' listening history to provide music recommendations and statistics.
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