How to ask data questions

This guide will help you interact effectively with your AI agent to gain valuable insights from your company's data.

Remember, each agent is custom-built by your data team, so specific capabilities may vary based on how your data team has configured it.

What Can You Ask Your Agent?

Your Wobby agent can handle a wide variety of data-related requests:

• Data Exploration: "Show me our top-selling products this quarter"

• Analysis Guidance: "How should I analyze our customer churn rate?"

• Specific Visualizations: "Create a line chart showing monthly revenue trends for the past year"

• Lookup Information: "What's the status of order #12345?"

• Comparative Analysis: "Compare sales performance across all regions for Q1 vs Q2"

Crafting Effective Data Questions

What Makes a Good Data Question?

Good data questions are specific, include relevant context, and clearly state what you're trying to learn.

✅ Good Examples:

• "What was our customer retention rate in the Northeast region during Q1 2023 compared to Q1 2022?"

• "Show me the conversion rate for our email campaign last month, broken down by customer segment"

• "Which products had the highest profit margin in our online stores during the holiday season?"

❌ Less Effective Examples:

• "Give me data on customers" (unclear what aspect of customers you're interested in)

• "Is our business doing well?" (subjective and lacks specific metrics)

• "How did sales go in Benelux last month?" (too broad, lacks specific metrics)

Formatting Tips:

1. Specify metrics: Clearly state what you want to measure (revenue, units sold, conversion rate)

2. Include time frames: Mention the time period you're interested in

3. Add context: Note any specific segments, categories, or comparisons

4. State visualization preferences: If you want a specific chart type, mention it

Understanding Agent Responses

Interpreting Charts and Visualizations

Your agent can generate various chart types, each suited for different insights:

• Bar Charts: Great for comparing quantities across categories

  • Example: Regional sales comparison showing which territories outperform others

• Pie Charts: Useful for showing proportions within a whole

  • Example: Market share distribution across product lines

• Line Charts: Ideal for visualizing trends over time

  • Example: Monthly revenue growth highlighting seasonal patterns

• Funnel Charts: Perfect for illustrating stages in a process

  • Example: Sales conversion funnel showing drop-offs between stages

• Scatter Plots: Excellent for identifying relationships between variables

  • Example: Price vs. rating correlation for your product catalog

Getting More from Your Visualizations

• Ask for annotations: "Can you highlight the key insights in this chart?"

• Request different views: "Can you show this data by week instead of month?"

• Drill down: "Show me a breakdown of this spike in June"

Follow-up Strategies

Conversations with your agent can be iterative. Try these follow-up approaches:

• Ask why: "Why did we see this drop in engagement in March?"

• Request context: "How does this compare to industry benchmarks?"

• Explore correlations: "Is this metric correlated with our marketing spend?"

• Test hypotheses: "Does customer satisfaction impact retention in our premium tier?"

When to Ask for Clarification

• If the response contains unfamiliar metrics or terminology

• When data seems to contradict your existing knowledge

• If you need additional context to make a decision

• When you want to verify the data sources behind the answer

Common Use Cases

• Sales Analysis: Track performance by product, region, or time period

  • Example: "Which product category had the highest growth rate this quarter?"

• Inventory Management: Monitor stock levels and identify optimization opportunities

  • Example: "Which items are at risk of stockout in the next 30 days?"

• Profitability Analysis: Understand margin drivers and cost structures

  • Example: "Show me our least profitable product lines after accounting for all costs"

• Customer Behavior: Analyze patterns and identify improvement opportunities

  • Example: "What's the typical journey for customers who make repeat purchases?"

Troubleshooting Tips

• If you get unexpected results, try rephrasing your question with more specificity

• For complex analyses, break down your request into smaller, related questions

• Remember that your agent works best with the data it has access to; some questions may require data your organization hasn't connected

By following these guidelines, you can leverage your custom Wobby agent to gain meaningful insights and make informed data-driven decisions.