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Automatically add leads to Customer.io using data extracted from documents with OCR Space. Latenode's visual editor makes building this automation easy and affordable, while JavaScript support allows advanced data transformation.
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In the workspace, click the “Create New Scenario” button.

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

Select the OCR Space node from the app selection panel on the right.

OCR Space
Click on the OCR Space node to configure it. You can modify the OCR Space URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Next, click the plus (+) icon on the OCR Space node, select Customer.io from the list of available apps, and choose the action you need from the list of nodes within Customer.io.

OCR Space
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Customer.io
Now, click the Customer.io node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Customer.io settings. Authentication allows you to use Customer.io through Latenode.
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Use various Latenode nodes to transform data and enhance your integration:

JavaScript
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AI Anthropic Claude 3
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Customer.io
Trigger on Webhook
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OCR Space
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Iterator
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Webhook response
After configuring OCR Space, Customer.io, 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.
Run the scenario by clicking “Run once” and triggering an event to check if the OCR Space and Customer.io integration works as expected. Depending on your setup, data should flow between OCR Space and Customer.io (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
OCR Space + Customer.io + Google Sheets: When a new image is processed by OCR Space, the extracted text is used to update a customer's profile in Customer.io, and the extracted data is also logged into a Google Sheet for record-keeping.
Customer.io + OCR Space + Slack: When a customer profile is created or updated in Customer.io, a scanned document is processed by OCR Space to extract address information. If the address extraction is successful, a notification is sent to a Slack channel with the updated customer and address details.
About OCR Space
Need to extract text from images or PDFs? Use OCR Space in Latenode to automatically process documents and integrate the data into your workflows. Automate invoice processing, data entry, or compliance checks. Latenode adds flexible logic, file parsing, and destinations to your OCR results, scaling beyond single-document processing.
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About Customer.io
Use Customer.io in Latenode to automate personalized messaging based on real-time user behavior. React instantly to events like purchases or sign-ups. Build flows that segment users, trigger custom emails, and update profiles automatically. Orchestrate complex campaigns and keep data consistent across platforms.
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How can I connect my OCR Space account to Customer.io using Latenode?
To connect your OCR Space account to Customer.io on Latenode, follow these steps:
Can I update Customer.io profiles using data extracted from scanned invoices?
Yes, you can! Latenode's visual editor makes it simple to automatically update Customer.io profiles with data extracted from invoices processed by OCR Space. Improve data accuracy and personalize customer interactions.
What types of tasks can I perform by integrating OCR Space with Customer.io?
Integrating OCR Space with Customer.io allows you to perform various tasks, including:
How does Latenode handle large volumes of documents with OCR Space?
Latenode's architecture scales to handle significant document processing volumes via OCR Space. Use parallel processing and queue management for efficiency.
Are there any limitations to the OCR Space and Customer.io integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: