How to chat with a CSV file and get charts, not paragraphs

What you need

• A CSV file. Any export works: orders, subscriptions, ad spend, support tickets. On the free Explore plan, files can be up to 50 MB, and Excel files work too.
• A question you care about. "Why were sales lower last month?" is a better starting point than "show me the data".
• Five minutes.

This walkthrough uses an example orders export from an online store, with one row per order and these columns:

Step 1: Prepare the file (two minutes)

A few small fixes make every answer more reliable:

1. Use clear column names. order_value_usd is better than val or Amount (incl. tax) - USD. Keep them short, lowercase and without special characters.
2. Keep one row per record. One row per order here. Remove subtotal rows, blank rows and notes at the bottom of the sheet.
3. Put dates in one format. YYYY-MM-DD avoids the 03/04 problem (March 4 or April 3?).
4. Keep numbers as numbers. Remove currency symbols and thousands separators inside cells: 1250.00, not $1,250.00.
5. Drop columns you don't need, especially personal fields such as email addresses and phone numbers.

Step 2: Upload and let the columns be profiled

Create a free account, then upload the CSV. DashboardGPT profiles each column as it loads: it detects that order_date is a date, order_value_usd is a currency amount, region and category are categories, and order_id is an identifier that should be counted, not summed.

Take ten seconds to check the profile. If a date was read as text, or an ID was read as a number, fix it now. Every later answer depends on it.

Step 3: Ask one headline question

Start with the number that matters most. For an orders file, that is usually revenue over time:

You get a line chart of monthly revenue on the canvas, with a short written insight underneath, for example that August was the lowest month since March and down about 12% on July.

That is a chart, not a paragraph. The written insight explains it and cites the figures, but the chart is the answer.

Step 4: Follow up on the chart

Select the chart and ask the next question. Because the follow-up knows which chart you are pointing at, you do not need to repeat the dataset, the metric or the time window:

1. Break August down by region. The drop is almost all in the West region.
2. Now by channel, West only. Paid search orders fell by half; other channels were flat.
3. Compare paid search orders per week in July and August. The fall starts in the second week of August.

Three follow-ups turn "revenue is down" into "paid search in the West dropped from the second week of August". That is something you can act on: check whether a campaign was paused or a budget ran out.

Step 5: Get the chart you want

The tool picks a sensible chart for each result, but you can ask for a specific one:

You can also refine a chart after it appears: "Show this as a percentage change", "Exclude cancelled orders" or "Only include orders over $50".

Step 6: Check the numbers

Before you share anything, confirm one figure you already know. If your store dashboard says July revenue was $412,000, ask "What was total order value in July?" and compare.

If it does not match, the cause is usually one of these:

• Returned or cancelled orders are included. Ask again with "only delivered orders".
• Discounts are counted differently. Decide whether revenue is before or after discount_usd.
• Dates cut off differently. The export may use UTC while your dashboard uses local time.
• The file is not complete. Exports are sometimes capped at a row limit.

You can also ask "How was this calculated?" to see the query and the columns used.

Step 7: Organise and share the canvas

Every answer stays on the canvas, so the analysis builds up as you go. Before sharing:

• Group related answers: the headline chart, the regional breakdown and the channel breakdown together.
• Delete dead ends that did not lead anywhere.
• Put the conclusion first: the chart that explains the drop goes at the top.

On the Team plan you can share the canvas with colleagues, so they see the answers and the questions that produced them.

Ten questions to try on an orders CSV

1. What was total order value by month for the last 12 months?
2. What is the average order value by channel?
3. Which 5 categories grew fastest this quarter compared with last quarter?
4. What share of orders were returned, by category?
5. How many new vs returning customers ordered each month?
6. Which region has the highest average discount?
7. What day of the week has the most orders?
8. Which customers placed more than 5 orders this year?
9. How does order value differ between discounted and full-price orders?
10. Which channel brings customers with the highest repeat rate?