A step-by-step walkthrough of exporting orders from Shopify admin, cleaning the data, and formatting it correctly for AI forecasting analysis.
Your Shopify admin contains all the data you need for accurate inventory forecasting — daily sales velocity, product trends, and stock movement. The first step is getting that data into a CSV format that an AI forecasting tool can read.
- 1Log in to your Shopify admin (yourstore.myshopify.com/admin)
- 2Go to Orders in the left sidebar
- 3Click the Export button (top right corner)
- 4Select the date range — we recommend the last 90 days for best forecast accuracy
- 5Choose "All orders" and export as CSV for Excel
- 6Download and open the CSV file
Tip
Use the last 60–90 days for the best balance of recency and pattern detection. Less than 30 days doesn't give the AI enough data to detect trends reliably.
Shopify's order export contains many columns. For inventory forecasting, these are the ones that matter:
| Shopify Column | What It Means | Used For |
|---|---|---|
| Created at | Order date and time | Calculating daily sales velocity |
| Lineitem name | Product name as listed in your store | Identifying the product |
| Lineitem sku | Your product SKU code | Matching products to inventory |
| Lineitem quantity | Units sold in this order | Sales volume calculation |
| Lineitem price | Selling price per unit | Revenue at risk calculation |
Shopify's orders export does not include current stock levels — you need to add those manually. Go to Products → Inventory in your Shopify admin. For each product/variant, note the current stock level. Add a column called current_stock to your CSV.
Warning
Current stock must reflect what's physically available to sell right now — not including reserved units, damaged stock, or inventory in transit.
Forestock accepts Shopify's native order export format. For best results, your CSV should have these columns:
| Column Name | Example Value | Required? |
|---|---|---|
| product | Yoga Mat — Black | Yes |
| sku | YM-BLK-001 | Recommended |
| date | 2026-02-15 | Yes |
| units_sold | 12 | Yes |
| current_stock | 145 | Yes |
| price | 1299 | Optional (for revenue at risk) |
- Remove cancelled and refunded orders — they artificially inflate your sales numbers
- Remove test orders (you'll recognize them by names like 'Test Customer')
- If you have product variants (size, color), keep them as separate rows with unique SKUs
- Delete rows with blank product names or zero quantity
- Make sure dates are in YYYY-MM-DD format or DD/MM/YYYY — both work
Once your CSV is clean, upload it to Forestock, set your supplier lead time in days, and click Run Forecast. Within 30 seconds you'll see every product ranked by stockout risk, with exact dates and reorder quantities.
Tip
Save a clean copy of your export template. Once you've set it up correctly once, future exports just need a date range change — it takes under 5 minutes.
Try it free
Upload your CSV and see which products are at risk in 30 seconds.