Maximizing Chatbot Accuracy with Good Data
Training an AI chatbot on PDFs is incredibly simple. However, the quality of your bot's answers depends entirely on how well your PDF documents are structured. Here are the best practices for structuring your training data.
1. Use Clear, Semantic Headings
Vector embedding systems split your PDFs into text chunks. If your headers are vague, the system won't understand where sections begin or end.
- Incorrect: 'Policies.'
- Correct: 'Return and Refund Policy for Damaged Shipments.'
2. Format with Direct Q&A Pairs
If you have common questions, lay them out directly as Q&As in your document. This helps the semantic search engine match customer queries perfectly.
- Example:
* Question: What are the batch timings for JEE classes?
* Answer: Our JEE batches run Monday through Friday. Morning batches are from 8:00 AM to 12:00 PM, and evening batches are from 4:00 PM to 8:00 PM.
3. Eliminate Non-Standard PDF Fonts
Make sure your PDF uses standard, searchable text characters. Scanned image PDFs cannot be parsed by text extractors unless they have been processed with high-quality Optical Character Recognition (OCR). If you cannot highlight and copy the text inside the PDF, the chatbot crawler won't be able to read it either.
4. Keep Tables Simple
Complex nested tables are difficult for AI vector models to parse. If you have a pricing table, try to write it out in clear paragraphs.
- Instead of a complex grid, write: 'Our Starter Plan costs ₹799 per month and includes 2,000 messages. Our Pro Plan costs ₹2,499 per month and includes 10,000 messages.'
By following these simple steps, your AI assistant will provide highly accurate, reliable responses.