Asking the Right Questions
The quality of your data analysis depends on the questions you ask. Vague questions get vague answers. Specific questions get actionable insights.
The Problem with Vague Questions
Bad: "What does my data show?"
This is too open-ended. AI might focus on irrelevant details or miss what you actually care about.
Good: "What are the top 3 products by revenue, and how has their sales trend changed over the last 6 months?"
This is specific and actionable. You'll get exactly what you need.
Types of Questions That Work
1. Summary Questions
Ask AI to condense large amounts of data into key points.
2. Comparison Questions
Compare different segments, time periods, or categories.
3. Trend Questions
Identify patterns over time.
4. Outlier Questions
Find unusual data points that deserve attention.
5. Ranking Questions
Identify top and bottom performers.
The SMART Question Framework
Make your questions:
- Specific: Name exactly what you want to know
- Measurable: Ask for numbers, percentages, or counts
- Actionable: Focus on information you can act on
- Relevant: Tie questions to business decisions
- Time-bound: Specify the time period
Before SMART
"How are we doing?"
After SMART
"What was our month-over-month revenue growth rate for each of the last 6 months, and which product categories drove the most growth?"
Follow-Up Questions
Don't stop at the first answer. Good analysis is a conversation.
Key Takeaway
Think like a manager preparing for a meeting. What specific numbers or insights would help you make better decisions? Ask for those directly.