Connect Visualvisitor and kazm to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Visualvisitor
Choose an Action
Automatically do this!
- Request a new Action for kazm
Enable Integrations or automations with these events of Visualvisitor and kazm
Enable Integrations or automations with these events of Visualvisitor and kazm
Actions
Get all users
Here you will get all user details.
Get a user
Here you will get a specific user details.
PlusPerson Search for leads
This is for plus person allows you to search for leads.
PlusPerson Create a bulk leads job
Create a job to bulk upload leads efficiently in one go.
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Frequently Asked Questions
To start, connect both your Visualvisitor and kazm accounts to viaSocket. Once connected, you can set up a workflow where an event in Visualvisitor triggers actions in kazm (or vice versa).
Absolutely. You can customize how Visualvisitor data is recorded in kazm. This includes choosing which data fields go into which fields of kazm, setting up custom formats, and filtering out unwanted information.
The data sync between Visualvisitor and kazm 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 Visualvisitor and kazm. 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 Visualvisitor
VisualVisitor is a powerful lead generation and visitor tracking tool designed to help businesses identify and engage with potential customers visiting their website. It provides insights into visitor behavior, company information, and contact details, enabling businesses to convert anonymous website visitors into actionable leads.
Learn MoreAbout kazm
Kazm is the data-driven CRM for Web3. We plug into every community touchpoint to create unified customer profiles, then apply machine learning and other methods to label, segment, and help personalize experiences for users.
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