Landbot.io and MongoDB Integration

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Capture Landbot.io conversation data directly in MongoDB for analysis and reporting. Latenode's visual editor and flexible API nodes simplify data extraction and storage, saving time. Scale efficiently with affordable execution-based pricing.

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Landbot.io

MongoDB

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Landbot.io and MongoDB

Create a New Scenario to Connect Landbot.io and MongoDB

In the workspace, click the “Create New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Landbot.io, triggered by another scenario, or executed manually (for testing purposes). In most cases, Landbot.io or MongoDB will be your first step. To do this, click "Choose an app," find Landbot.io or MongoDB, and select the appropriate trigger to start the scenario.

Add the Landbot.io Node

Select the Landbot.io node from the app selection panel on the right.

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Configure the Landbot.io

Click on the Landbot.io node to configure it. You can modify the Landbot.io URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Add the MongoDB Node

Next, click the plus (+) icon on the Landbot.io node, select MongoDB from the list of available apps, and choose the action you need from the list of nodes within MongoDB.

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Authenticate MongoDB

Now, click the MongoDB node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your MongoDB settings. Authentication allows you to use MongoDB through Latenode.

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Configure the Landbot.io and MongoDB Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Run node once

Set Up the Landbot.io and MongoDB Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring Landbot.io, MongoDB, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking “Run once” and triggering an event to check if the Landbot.io and MongoDB integration works as expected. Depending on your setup, data should flow between Landbot.io and MongoDB (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Landbot.io and MongoDB

Landbot.io + MongoDB + Slack: Capture survey responses from Landbot.io using the Watch Events trigger. Insert these responses as new documents into MongoDB. Notify relevant teams in Slack about the new submission via a channel message.

MongoDB + Landbot.io + Google Sheets: Monitor MongoDB for updated user data using Search Documents. Trigger personalized Landbot surveys by sending a text message. Log the Landbot responses in Google Sheets by adding a new row.

Landbot.io and MongoDB integration alternatives

About Landbot.io

Use Landbot.io in Latenode to build no-code chatbots, then connect them to your wider automation. Capture leads, qualify prospects, or provide instant support and trigger follow-up actions directly in your CRM, databases, or marketing tools. Latenode handles complex logic, scaling, and integrations without per-step fees.

About MongoDB

Use MongoDB in Latenode to automate data storage and retrieval. Aggregate data from multiple sources, then store it in MongoDB for analysis or reporting. Latenode lets you trigger workflows based on MongoDB changes, create real-time dashboards, and build custom integrations. Low-code tools and JavaScript nodes unlock flexibility for complex data tasks.

See how Latenode works

FAQ Landbot.io and MongoDB

How can I connect my Landbot.io account to MongoDB using Latenode?

To connect your Landbot.io account to MongoDB on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Landbot.io and click on "Connect".
  • Authenticate your Landbot.io and MongoDB accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I save chatbot data from Landbot.io to MongoDB?

Yes, you can! Latenode allows you to seamlessly save Landbot.io chatbot data directly into MongoDB, enabling powerful data analysis and personalized customer experiences.

What types of tasks can I perform by integrating Landbot.io with MongoDB?

Integrating Landbot.io with MongoDB allows you to perform various tasks, including:

  • Storing chatbot conversation data in a structured database.
  • Triggering personalized follow-up messages based on user input.
  • Updating MongoDB records based on chatbot interactions.
  • Analyzing user behavior patterns from chatbot conversations.
  • Creating custom reports using chatbot data stored in MongoDB.

Can I use custom JavaScript with Landbot.io on Latenode?

Yes! Latenode allows you to use JavaScript code within your Landbot.io workflows, enabling advanced data manipulation and logic.

Are there any limitations to the Landbot.io and MongoDB integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Complex data transformations may require JavaScript knowledge.
  • Large data transfers can impact workflow execution time.
  • Real-time synchronization depends on network conditions.

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