Quality training data is the cornerstone of a well-performing GPT model. It should be reflective of your brand's tone, style, and the type of interactions you have with your customers.

• Customer service transcripts

• Email exchanges with clients

• Social media posts

• Blog articles and press releases

• Product descriptions and promotional material

• Cleaning: Ensure the data is free from typos, irrelevant information, and sensitive customer information.

• Categorization: Organize the data into categories (e.g., customer inquiries, product descriptions) to facilitate targeted training.

• Consistency: Check for consistency in tone and style across all data to reinforce your brand's voice.

▢ Identify sources of brand-relevant data within your organization.

▢ Clean the data by removing any irrelevant or sensitive information.

▢ Categorize the data according to the type of content (e.g., marketing, customer service).

▢ Ensure the data consistently reflects your brand's voice and tone.

▢ Prepare a final dataset ready for model training.