Connect Microsoft To Do and kazm to Build Intelligent Automations
Enable Integrations or automations with these events of Microsoft To Do and kazm
Enable Integrations or automations with these events of Microsoft To Do and kazm
Triggers
New Task
Triggers when a new task is created.
Updated Task
Triggers when a task is update.
Completed Task
Triggers when a task is completed
Actions
Complete a Task
Marks a task as completed.
Create List
Creates a new list.
Find a Task
Find a task by its id and title.
Create a Task
Creates a new task.
Get All Lists
Get an all lists
Get User Details
Get an existing user details.
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Step by step guides to integrate Microsoft To Do and kazm
Frequently Asked Questions
To start, connect both your Microsoft To Do and kazm accounts to viaSocket. Once connected, you can set up a workflow where an event in Microsoft To Do triggers actions in kazm (or vice versa).
Absolutely. You can customize how Microsoft To Do 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 Microsoft To Do 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 Microsoft To Do 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 Microsoft To Do
Microsoft To Do is a task management app to help you stay organized and manage your day-to-day. You can use Microsoft To Do to make shopping lists or task lists, take notes, record collections, plan an event, or set reminders to increase your productivity and focus on what matters to you.
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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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