Asking Effective Questions
The quality of your questions directly impacts the quality of aidnn’s responses. Learn how to ask questions that get you the insights you need.The Anatomy of a Good Question
Three Key Components
1. What You Want (The Goal) Be clear about what you’re trying to accomplish. ❌ “Look at this data” ✅ “Calculate total revenue” 2. Which Data (The Source) Specify what data to use. ❌ “Show me sales” ✅ “Show me sales from my QuickBooks connection” 3. How to Present It (The Format) Describe the output you want. ❌ “Show sales data” ✅ “Show monthly sales totals as a line chart”Complete Question Example
“Calculate total revenue by product category from my 2024 sales file and show it as a bar chart sorted from highest to lowest”Breaks down to:
- What: Calculate total revenue by product category
- Which: 2024 sales file
- How: Bar chart, sorted highest to lowest
Question Types
Exploratory Questions
Purpose: Understand your data Good Examples:“What does this dataset contain?”
“Show me summary statistics”
“What’s the date range and how many records?”
“Are there any data quality issues?”When to Use:
- First time working with data
- Unfamiliar dataset
- Before detailed analysis
Analytical Questions
Purpose: Find specific insights Good Examples:“What are the top 10 products by revenue?”
“How does Q4 compare to Q3?”
“What’s the correlation between price and sales volume?”
“Are there any seasonal patterns in the data?”When to Use:
- You have a specific question
- Looking for patterns or trends
- Making comparisons
- Testing hypotheses
Action Questions
Purpose: Transform or prepare data Good Examples:“Remove rows with missing revenue values”
“Create a new column calculating profit margin”
“Join this data with my customer file”
“Export the top customers to CSV”When to Use:
- Cleaning data
- Creating new calculations
- Combining datasets
- Preparing reports
Being Specific
Time Periods
❌ Vague:- “Recent sales”
- “Last quarter”
- “This year”
- “Sales from January 1 to March 31, 2024”
- “Q4 2023 (October through December)”
- “Calendar year 2024”
Metrics and Calculations
❌ Vague:- “Average performance”
- “Total sales”
- “Best customers”
- “Average order value (revenue / number of orders)”
- “Sum of all revenue in the revenue column”
- “Top 20 customers ranked by lifetime value”
Filtering and Criteria
❌ Vague:- “Show good customers”
- “Recent orders”
- “Big transactions”
- “Show customers with lifetime value over $10,000”
- “Orders from the last 30 days”
- “Transactions where amount is greater than $1,000”
Common Pitfalls
Pitfall 1: Too Vague
❌ Problem:“Analyze this”Why It’s Bad: aidnn doesn’t know what kind of analysis you want. ✅ Better:
“Show me summary statistics and check for missing values”
Pitfall 2: Multiple Questions at Once
❌ Problem:“Show me revenue trends, top products, customer segments, and regional performance”Why It’s Bad: Too much at once makes it hard to get focused results. ✅ Better: Ask one at a time:
- “Show me revenue trends by month”
- “What are the top 10 products?”
- Then build from there
Pitfall 3: Assuming Context
❌ Problem:“Compare them”Why It’s Bad: aidnn doesn’t know what “them” refers to. ✅ Better:
“Compare the monthly totals we just calculated to last year’s monthly totals”
Pitfall 4: Technical Jargon Without Explanation
❌ Problem:“Run a two-sample t-test on cohort performance”Why It’s Bad: Might work, but simpler language often works better. ✅ Better:
“Test if there’s a statistically significant difference between group A and group B performance”
Pitfall 5: No Output Format Specified
❌ Problem:“Calculate monthly revenue”Not Bad, but Could Be Better: ✅ Better:
“Calculate monthly revenue and show it as a line chart”Or:
“Calculate monthly revenue and display as a table”
Progressive Questioning
Start Broad, Then Narrow
Step 1 - Overview:“Show me a summary of this sales data”Step 2 - Identify Interest:
“What are the top products?”Step 3 - Dig Deeper:
“Show me weekly sales trend for the #1 product”Step 4 - Specific Analysis:
“Why did sales spike in week 3?”
Build on Previous Answers
Use Context: Instead of:“Calculate average order value for transactions between 100 in Q4 2023”Build Step by Step:
- “Filter to Q4 2023 transactions”
- “Now filter to amounts between 100”
- “Calculate average order value for these orders”
Question Patterns That Work
Pattern 1: Describe Then Request
Structure:- Describe what you have
- State what you want
“I have sales data with customer, product, date, and revenue. Show me total revenue by product for Q4 2023.”
Pattern 2: Goal Then Format
Structure:- State your goal
- Specify output format
“I need to identify our top customers. Show me the top 20 customers by total revenue as a table with customer name, total spent, and number of orders.”
Pattern 3: Filter Then Analyze
Structure:- Filter the data
- Analyze the subset
“Filter to transactions in California from 2024. Then calculate monthly revenue totals and create a trend chart.”
Pattern 4: Compare Then Contrast
Structure:- Define what to compare
- Specify comparison method
“Compare Q1 2024 revenue to Q1 2023 revenue. Show both totals and calculate the percentage change.”
Advanced Techniques
Conditional Logic
Use “if/then” structure:“If revenue is greater than $10,000, label it as ‘high-value’. Otherwise, label as ‘standard’.”
Multiple Criteria
Combine conditions with AND/OR:“Show me customers where total spend is over $5,000 AND last purchase was within 30 days”
Grouped Analysis
Specify dimensions to group by:“Calculate average order value grouped by customer segment and month”
Time-Based Comparisons
Use relative time periods:“Compare this month to same month last year”
“Show year-over-year growth for each quarter”
When aidnn Doesn’t Understand
Rephrase More Simply
If aidnn seems confused: Original:“Elucidate the longitudinal revenue trajectory”Simpler:
“Show me revenue over time”
Break It Down
Instead of one complex question:“Perform cohort analysis with retention curves and revenue per cohort showing month-over-month changes”Break into steps:
- “Create customer cohorts by signup month”
- “Calculate retention rate for each cohort”
- “Show retention rates over time”
- “Add revenue per cohort”
Provide Examples
If aidnn isn’t getting it:“I want to see each product with its category. For example: ‘Widget A, Electronics’ or ‘Gadget B, Home Goods‘“
Ask for Clarification
Let aidnn ask back:“Show me customer performance”aidnn might ask:
“What metric would you like to see for customer performance? Options include:
- Total revenue per customer
- Number of orders per customer
- Average order value
- Customer lifetime value”
Quick Checklist
Before sending your question, verify:- Is my goal clear?
- Did I specify which data?
- Did I mention the time period (if relevant)?
- Did I describe the output format?
- Am I asking one thing at a time?
- Did I provide enough context?
- Is my language clear and specific?
Examples: Before and After
Example 1: Sales Question
❌ Before:“Sales?”✅ After:
“Show me total sales by month for 2024 from my QuickBooks data”
Example 2: Customer Analysis
❌ Before:“Who are the good customers”✅ After:
“Show me the top 25 customers ranked by total lifetime revenue, including customer name and total spent”
Example 3: Trend Analysis
❌ Before:“Chart it”✅ After:
“Create a line chart of the monthly revenue totals we just calculated”
Example 4: Comparison
❌ Before:“How does this year compare”✅ After:
“Compare 2024 monthly revenue to 2023 monthly revenue and calculate the percentage change for each month”
Practice Exercise
Try turning these vague questions into specific ones: Vague: “Show me the data” Your Version: _____? Vague: “What’s the trend” Your Version: _____? Vague: “Best products” Your Version: _____? Suggested Answers:- “Show me the first 50 rows of my sales data with all columns”
- “Show me monthly revenue trend for the past 12 months as a line chart”
- “Show me the top 10 products by total revenue for Q4 2023”
Next Steps
- Working with Large Datasets - Handle big data efficiently
- Use Cases - See examples in action
- Conversations Guide - Master interactions