# Tips for Asking Questions

This guide will help you get the best results when asking your AI Analyst for insights.

## What Can You Ask?

Your AI Analyst can handle a wide variety of data-related requests:

* **Data exploration**: "What sort of analyses can you do about our shipment data? Give me some ideas."
* **Specific visualisations**: "Create a line chart showing monthly revenue trends for 2025"
* **Lookup information**: "What's the delivery status of order #12345?"
* **Comparative analysis**: "Compare total revenue across all regions for Q1 vs Q2 2025, specifically for our premium products"
* **Comprehensive reports**: "Put together a report on our Q3 carrier performance"

## Crafting Effective Questions

### What Makes a Good Question?

Good 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

### 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 visualisation preferences** — if you want a specific chart type, mention it

## Requesting Charts

Your AI Analyst can generate various chart types:

* **Bar charts** — great for comparing quantities across categories. *Example: regional sales comparison*
* **Pie charts** — useful for showing proportions within a whole. *Example: market share distribution*
* **Line charts** — ideal for visualising trends over time. *Example: monthly revenue growth*
* **Scatter plots** — excellent for identifying relationships between variables. *Example: price vs. rating correlation*

## Follow-up Strategies

Conversations with your AI Analyst are iterative. Try these follow-up approaches:

* **Request different views**: "Can you show this data by week instead of month?"
* **Drill down**: "Show me a breakdown of this spike in June"
* **Clarification**: "How did you calculate this?"
* **Build a report**: "Can you pull all of this together into a report?"

## Troubleshooting

* If you get unexpected results, try rephrasing your question with more specificity
* For complex analyses, break your request into smaller, related questions
* Your AI Analyst works with the data it has access to — some questions may require data your organisation hasn't connected yet

## Using Plan Mode for Complex Questions

For multi-step analyses where you want to stay in control of the approach, enable [Plan Mode](/explorer/working-with-agents/plan-mode.md). The AI Analyst will outline its approach before starting, and you can approve or adjust the plan before it runs.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.wobby.ai/explorer/working-with-agents/tips-for-quick-analysis.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.