Use n8n to prioritize trade-show booth visits

Andre Moreira built Tradeshow Scanner to prepare a prioritized list of exhibitors for business-development visits. The workflow begins with a trade-show website and extracts company names, descriptions, booth numbers and URLs. It processes companies in batches so testing does not require researching every exhibitor at once.

The AI Agent researches each company through search and targeted website scraping. Moreira supplied context about his firm, lyfX.ai, and its preferred customers: smaller businesses with an interest in data, AI and automation. The agent assesses company size and public initiatives, assigns a low, medium or high fit score and explains the decision.

Results are appended to Google Sheets with the company details, score and reasoning, producing a queue for booth visits and later follow-ups. Moreira linked a demonstration and sanitized workflow while retaining its prompts. The account describes a functioning prototype and criteria-driven research. It does not establish that every scored company became a customer, and it does not describe autonomous outreach or an approval checkpoint before spreadsheet output.

Prompt
Original prompt

Source: dev.to · Andre Moreira