Connect BugHerd and kazm to Build Intelligent Automations
Enable Integrations or automations with these events of BugHerd and kazm
Enable Integrations or automations with these events of BugHerd and kazm
Triggers
Comment Created
Trigger when a comment is created.
Task Created
Trigger when task is created.
Task Updated
Trigger when task is created or updated.
Actions
Create Project
Create a project in BugHerd.
Add Member
Add a member to a project.
Add Guest
Add an existing guest to a project, or invite someone by email address.
Update Project
Update settings for an existing project under your control
Delete Project
Delete a project and all associated data.
Add Task to a Project
Add a new task in a project.
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Automate Instagram DM Replies, Reactions, and Team Alerts
- has responseSendDMMessageAdd Step
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Frequently Asked Questions
To start, connect both your BugHerd and kazm accounts to viaSocket. Once connected, you can set up a workflow where an event in BugHerd triggers actions in kazm (or vice versa).
Absolutely. You can customize how BugHerd 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 BugHerd 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 BugHerd 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 BugHerd
BugHerd is a simple yet powerful web-based bug tracking tool that acts like a sticky note on your website. It allows teams to easily manage feedback and track issues directly on web pages.
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About 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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