Analyze sales data prompt

What most people type

here's my shopify sales export for the last 6 months [CSV pasted]. what trends do you see and what should I do about them?

It works, but the AI has to guess your what you sell, current business goal and known events in period, so the first answer usually needs another round. The version below asks for exactly what a professional would deliver.

Analyze my Shopify sales export for the last 6 months and tell me the key trends and what I should do about them.

Data:
[CSV pasted]

Context (use only what's given; ask me nothing, and flag assumptions):
- Business/product type: [what you sell]
- Goal right now: [e.g. grow revenue, improve margin, reduce returns, other]
- Known events in this period: [promotions, launches, stockouts, ad spend changes]

First, briefly check the data: columns found, date range, row count, and any gaps or oddities (refunds, discounts, duplicates, missing values). Calculate every figure from the CSV and show the math where it isn't obvious. Don't invent numbers or benchmarks.

Then cover:
1. Headline trends, grouped by revenue and orders, average order value, products and collections, customers (new vs returning, if the data allows), and discounts/refunds. Include month-over-month changes, seasonality or day-of-week patterns, and standout products or outliers.
2. For each important trend: what it likely means, how confident you are, and what other data would confirm it.
3. A prioritized action list (top 5), each with the trend behind it, the specific step, and the metric to track. Mark which are quick wins versus bigger bets.

Format: short summary first, then compact tables where they help, in markdown. If the CSV lacks fields needed for a point (e.g. customer IDs, costs), say so instead of guessing.

Replace the [brackets] with your details before you send it: CSV pasted, what you sell, e.g. grow revenue, improve margin, reduce returns, other, promotions, launches, stockouts, ad spend changes.

Why this version works

• Added data check before analysis. Catches export gaps before conclusions are drawn.
• Defined trend categories to cover. Gets a structured, expert-level analysis, not generic remarks.
• Added prioritized actions with metrics. Turns 'what should I do' into a usable plan.
• Added context placeholders and no-invention rule. Advice fits their goal; figures come only from the CSV.

What a professional analyze sales data prompt covers

• Asks for trends with supporting numbers from the data
• Asks for prioritized actions
• Asks to state assumptions or data gaps

Watch out for

• Invents numbers or trends

Best AI model for this prompt

This is a hard reasoning task: multi-step data analysis and business recommendations; a wrong calculation undermines the advice. You don't need the most expensive model. The cheapest model at each company that handles it well:

Pay-per-use list prices for this prompt and its expected answer (about 1,100 tokens). On a monthly chat plan, the same choice shows up as more messages before you hit your limit. See today's AI prices.