Adapting the tone of text to fit different audiences can be crucial for effective communication. With AI-driven tone adjustment, you can seamlessly transform the tone of large datasets, ensuring the content resonates well with the intended audience.
Adapting promotional emails to sound more friendly and approachable.
Changing social media posts to better match the platform’s tone and audience.
Customer Service
Converting formal customer responses to a more relaxed tone for a friendlier interaction.
Adjusting tone of FAQs to be more engaging and easy to understand.
Corporate Communication
Transforming internal memos to be more conversational and engaging for employees.
Changing formal announcements to a casual tone for a company newsletter.
Step-by-step instruction
Step 1. Set Input Dataset
Consider a dataset containing formal product reviews that need to be converted to a casual tone. Here is a sample dataset before the tone change:
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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
Change the review's tone in @Review_Formal to a casual and friendly tone. Ensure the review remains concise and maintains the original message.
Why This Prompt Is Good
Clearly states the task (changing tone) and specifies the target tone (casual and friendly).
Emphasizes keeping the review concise and true to the original meaning.
Uses column reference (@Review_Formal) to indicate where the input text is located.
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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.
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Step 4. Get Final Result
Here is the dataset after using the AI Column Node to change the tone of the reviews:
