Connect SurveyMonkey and Neo4j to Build Intelligent Automations
Choose a Trigger
When this happens...
New Survey
Choose an Action
Automatically do this!
- Request a new Action for Neo4j
Enable Integrations or automations with these events of SurveyMonkey and Neo4j
Enable Integrations or automations with these events of SurveyMonkey and Neo4j
Triggers
New Survey
Triggers when new a survey is created in SurveyMonkey.
Actions
Create a Contact
Creates a new contact in you address book.
Find Survey
Find one of your Surveys by survey id.
Find collector
Find collector for one of your survey
Find message
Find message in surveymonkey
Find Contact By Email
Search for a contact by their email address in database.
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Frequently Asked Questions
To start, connect both your SurveyMonkey and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in SurveyMonkey triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how SurveyMonkey data is recorded in Neo4j. This includes choosing which data fields go into which fields of Neo4j, setting up custom formats, and filtering out unwanted information.
The data sync between SurveyMonkey and Neo4j 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 SurveyMonkey and Neo4j. 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 SurveyMonkey
SurveyMonkey is a cloud-based survey tool that helps users create, send, and analyze surveys. Users can use a variety of question types, deploy surveys across multiple platforms, and utilize tools for data analysis and integration with other services.
Learn MoreAbout Neo4j
Neo4j is a leading graph database platform that enables organizations to unlock the value of connections, influences, and relationships in data. It is designed to handle highly connected data and is used for a variety of applications such as fraud detection, real-time recommendations, and network management.
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