Our leadership team spends too much time arguing over which operational issues to address first during our weekly Level 10 Meeting. How do we use a basic machine learning setup to analyze our raw customer feedback and automatically prioritize our Issues List before the meeting starts?

Question

Tyler Smith · Accepted Answer

To stop your team from debating what to solve first, stop relying on subjective opinions during your Level 10 Meeting. You can use a basic machine learning classifier to analyze your raw customer feedback, support emails, and client satisfaction surveys as they come in.

By running this data through a simple classification model, you can automatically group issues into clear operational buckets such as delivery delays, communication gaps, or billing errors. The system then assigns a frequency and impact score to each category. This list is then automatically pushed to your Level 10 Meeting Issues List before your team gathers.

When you transition to the IDS portion of your meeting, your leadership team is no longer wasting time trying to guess what needs attention. You are looking at a hard, data-backed list of your actual operational vulnerabilities. This shifts the team's energy entirely toward solving root-cause issues.

Never frame this as an AI project to your team. Frame it strictly as an operations-improvement project that cleans up your meeting preparation and ensures you are working on the issues that have the highest impact on your capacity and customer retention.