The AI Condition feature in eGrow allows you to create smarter automations by asking the AI a question (prompt) about your data. Based on the AI's answer, a condition is evaluated, and the automation moves forward depending on the result. This is particularly useful for tasks like managing duplicate orders, customer follow-ups, or workflow optimization.
Example: Automatically Moving Duplicate Orders to a Specific Stage
In this example, we’ll create an automation that detects duplicated orders (orders with the same products from the same customer within the same day) and moves them to a designated stage (e.g., “Duplicate / Canceled”).
Step 1: Create an Automation Trigger
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Navigate to Automations in your eGrow dashboard.
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Click Create New Automation.
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Choose the Order Trigger and select Order created.
This ensures the automation starts whenever a new order is created.
Step 2: Add an AI Condition
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Click Add Condition and select AI Condition.
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In the Prompt field, enter a question or instruction for the AI. For example:
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Add the relevant Data fields that the AI should analyze:
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Customer
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Products
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Purchase History
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Team History
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Conversations
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Shipping Tracking
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The AI will analyze the data and evaluate whether the condition is met.
Step 3: Define the Action Based on the AI Condition
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Add an Action after the AI Condition.
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Choose Update order stage action.
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Select the stage to move the order to if it meets the condition, for example:
Step 4: Save and Activate the Automation
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Review the automation to ensure the trigger, AI condition, and action are correctly set.
Click Save and Activate.
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From now on, any new order that matches the duplicate criteria will automatically be moved to the selected stage.
Tips for Using AI Conditions
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Use clear and specific prompts for the AI to ensure accurate evaluations.
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Combine AI Conditions with other automation steps for more complex workflows.
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Test your automation with sample orders before applying it to live data.
This setup saves time and ensures duplicated orders are automatically handled, reducing errors and improving workflow efficiency.
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