Connect Badger Maps and Nyckel to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Badger Maps
Choose an Action
Automatically do this!
Import to Classifier
Classify
Center Detect
Train Classifier
Enable Integrations or automations with these events of Badger Maps and Nyckel
Enable Integrations or automations with these events of Badger Maps and Nyckel
Actions
List Users Profile
List all Users Profile
List Account
Get list of all accounts
Create Check In
Create check-in for an account.
Get Check In
Retrieve user's check-ins for an account with customer_id.
Get Account
Find an exisiting Account by ID or Other fields.
Get Users
Find an exisiting user by email or id.
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Frequently Asked Questions
To start, connect both your Badger Maps and Nyckel accounts to viaSocket. Once connected, you can set up a workflow where an event in Badger Maps triggers actions in Nyckel (or vice versa).
Absolutely. You can customize how Badger Maps data is recorded in Nyckel. This includes choosing which data fields go into which fields of Nyckel, setting up custom formats, and filtering out unwanted information.
The data sync between Badger Maps and Nyckel 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 Badger Maps and Nyckel. 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 Badger Maps
Badger Maps is a sales productivity and planning app for outside salespeople.
Learn MoreAbout Nyckel
Nyckel is a platform that provides machine learning as a service, enabling users to easily integrate AI capabilities into their applications without needing extensive knowledge in data science or machine learning. It offers tools for creating, training, and deploying machine learning models with ease.
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