Connect Segmetrics and Neo4j to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Segmetrics
Choose an Action
Automatically do this!
- Request a new Action for Neo4j
Enable Integrations or automations with these events of Segmetrics and Neo4j
Enable Integrations or automations with these events of Segmetrics and Neo4j
Actions
Get Contact by Email
Returns the full customer journey of a single contact by email
Add or Update Contact
Adds a contact to the specified SegMetrics integration.
Add Tag to Contact
Add Tags to given contact.
Add Purchase to Contact
Adds a purchase to the specified SegMetrics integration.
Adds subscription
Adds a subscription to the existing contact. If the subscription id already exist, it will be updated.
Remove Tags to Contact
Remove Tags to Contact
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Frequently Asked Questions
To start, connect both your Segmetrics and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Segmetrics triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Segmetrics 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 Segmetrics 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 Segmetrics 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 Segmetrics
SegMetrics gives you clarity on where your leads come from, how they act, and how much your marketing is really worth.
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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