Business Questions to Ask Your Data

The most useful business questions to ask your data are the plain-English ones you already ask in meetings: how is revenue trending, who are our top customers, how many people churned, and where are signups coming from. With an AI data analyst, you ask each question in plain English and it writes the SQL, runs it read-only, and returns a chart and an answer. Below is a practical list of these questions, mapped to the kind of answer you get back.

Revenue and growth questions

• "How has monthly recurring revenue trended over the last six months?" You get a line chart of MRR by month and a one-line summary of the trend.
• "What was total revenue last quarter, broken out by month?" A bar chart by month with the quarter total, computed from a SUM over a date-filtered query.
• "What is our average order value, and how is it changing?" A trend line of AOV with the current figure called out.
• "Which products or plans drive the most revenue?" A ranked bar chart by product or plan.

Each of these maps to a real SQL query the tool writes and shows you, so you can confirm exactly how the number was calculated.

Customer questions

• "Who are our top ten customers by revenue this year?" A ranked table of accounts with their revenue, from a grouped, ordered query.
• "How many active customers do we have, and how is that changing?" A count with a trend, using your definition of active.
• "What is the average revenue per customer?" A single figure with the query behind it, so you can check the denominator.

Churn and retention questions

• "How many customers churned last month, and from which plan?" A breakdown by plan with the total, so you can see where churn concentrates.
• "What is our monthly churn rate over the last year?" A trend line that turns a vague worry into a number you can watch.
• "Which cohort of signups retained best?" A cohort view, with the SQL shown so you can confirm the cohort logic.

Acquisition questions

• "How many signups did we get last week, by day?" A daily bar chart from a date-grouped count.
• "Which signup source brought the most paying customers?" A ranked breakdown by source, joining signups to conversions.
• "What is our signup-to-paid conversion rate, and is it improving?" A ratio over time, with the two underlying counts visible in the query.

Product and engagement questions

• "What were daily active users over the last 30 days?" A daily activity chart from your events table.
• "Which features get used the most?" A ranked usage breakdown.
• "How long does it take a new user to reach their first key action?" A time-to-value figure, with the query shown so the definition is auditable.

A question-to-answer map

How to ask good questions

The clearer your question, the better the answer. Name the metric, the time window, and the grouping: "churn, last month, by plan" beats "how is churn." If the first answer is not quite right, refine in plain English rather than starting over, and glance at the SQL to see exactly how it was computed. Good questions plus visible SQL equals answers you can trust. You can turn any of these into a chart the moment the query runs.

The takeaway

The best business questions to ask your data are the simple, plain-English ones you already care about, and an AI data analyst turns each into a verifiable, charted answer. With Agentsql you ask, it writes and runs the SQL read-only, and you see both the chart and the query. See how it works, then ask your data its first question.