Should I Use ML Here? AI Prompt

Help me decide whether machine learning is the right tool for my problem, or whether a simpler approach would work better.

My problem: {{problem_description}}
My data: {{data_description}}
My goal: {{goal}}

1. What am I actually trying to do?
   Help me categorize my goal:
   - Am I trying to predict a number? (e.g. forecast next month's sales, estimate customer lifetime value)
   - Am I trying to classify something into categories? (e.g. is this customer likely to churn: yes or no)
   - Am I trying to find groups in my data? (e.g. which customers are similar to each other)
   - Am I trying to understand what causes something? (e.g. what factors drive sales)

2. Do I actually need machine learning?
   For each goal, explain the simpler alternative first:
   - Prediction → Could a trend line or simple average work well enough?
   - Classification → Could a simple rule (IF revenue < $100 AND no purchase in 90 days THEN high churn risk) work?
   - Grouping → Could I just segment by an existing column I already have?
   - Understanding causes → Could a comparison of group averages answer this?

   ML is worth the complexity only when:
   - The patterns are too complex for simple rules
   - Accuracy materially matters (a wrong prediction has real consequences)
   - You have enough data (at least a few hundred labeled examples for prediction/classification)

3. If ML is the right choice:
   - What type of ML would apply here: supervised (you have labeled examples), unsupervised (you want to find structure), or a different approach?
   - What tool is appropriate for my skill level? (Excel add-in, Google Sheets ML, DataRobot, H2O AutoML, Python scikit-learn, MLJAR Studio)
   - What data do I need that I might not have yet?

4. The honest answer:
   Tell me directly: based on my problem, would you start with ML or a simpler approach, and why?