Understanding the type of domain associated with an email address can be crucial for various applications, from targeted marketing to filtering emails. Using the AI Column Node in Tabula.io, you can automatically detect and categorize the domain type of email addresses in your dataset, enhancing your data's utility and insights.
Segmenting email lists based on domain type for more targeted email campaigns.
Personalizing email content depending on whether the domain is commercial, educational, or non-profit.
IT and Security
Filtering and categorizing incoming emails to detect potential phishing or spam threats.
Enhancing email security protocols by recognizing and categorizing email sources.
Customer Support
Routing customer queries more efficiently by recognizing educational domains that might need academic-related support.
Prioritizing responses based on domain types to ensure critical commercial queries are addressed promptly.
Step-by-step instruction
Step 1. Set Input Dataset
Consider a dataset containing customer email addresses. Here is a sample dataset before adding the domain category:
{{line}}
Step 2. Define the AI Prompt
The most crucial aspect of leveraging AI effectively is crafting a precise and relevant prompt. A well-defined prompt ensures the AI understands the task clearly, leading to accurate and useful outputs. This involves being specific about the desired outcome, providing necessary context, and avoiding ambiguity.
Prompt Example
Categorize the email domain in the Email_Address column as either 'commercial', 'educational', 'non-profit', 'network', or 'other'.
Why This Prompt Is Good
Clearly states the task (categorization) and the relevant column (Email_Address).
Specifies the possible categories, ensuring the AI has clear criteria for classification.
Helps maintain consistency and accuracy in categorizing various domain types.
{{line}}
Step 3. Configure the Flow Designer
Add the input dataset to the flow designer.
Select the AI Column node from the tools panel and enter the prompt.
Start with a row-by-row execution to fine-tune your prompt.
Correct your prompt, regenerate any single row, or remove all previous results.
Once you satisfied with the prompt, apply the AI Column Node to all rows (it will be applied only for empty cells).
For very large datasets that are bigger than 10,000 rows, run the flow for runtime processing over the whole dataset. Be aware that it can be costly for a large amount of data.
{{line}}
Step 4. Get Final Result
Here is the dataset after using the AI Column Node to categorize the domain types:
