Most product research tools try to guess what sells. CatalogCSV doesn't guess. It gives you what the store actually stocks: every product it shows publicly, with its vendor, product type, tags, options, price, compare-at (sale) price, SKU, in-stock status and image links. Everything lands in one CSV you can sort, filter and pivot in Excel, Google Sheets or Numbers.

That makes it the factual half of product research. You can see how deep a store's range is, which brands or suppliers it carries, where its prices sit and what it has just added. Whether any of it sells is a separate question, and this page is clear about where that line falls.

Five ways to read a store's range

Use the Variant rows format (26 columns). It has one row per variant, so a T-shirt in four sizes takes four rows. When you want to count products, count distinct values in the handle column, not rows.

  1. Where the range is deep. Build a pivot table with product_type as rows and a count of distinct handle values. A type with 60 products is a category the store is committed to. A type with 2 is probably a test. product_type is a free-text label the merchant sets, so some stores fill it carefully and others leave it blank. If it is empty, try tags instead.
  2. Which brands or suppliers it carries. Do the same with vendor. On some stores it is a real brand. On others it is the store's own name on every product, which tells you something too. There's more on this in find every vendor sold on a Shopify store.
  3. The price spread per type. For each product_type, take the MIN, MEDIAN and MAX of price. In Google Sheets or Excel 365, =MEDIAN(FILTER(Q:Q, D:D="Dresses")) gives the median variant price for one type, with price in column Q and product_type in column D. This shows the price band a store has picked for a category, which is often more useful than any single price.
  4. What's on sale. Add a helper column that flags rows where compare_at_price is filled in and greater than price. Filter on it to see which products the store is marking down and by how much.
  5. The newest additions. Sort by created_at, newest first. The top rows are the products the store added most recently, which is a decent hint about what it is testing right now. published_at and updated_at are in the file as well.

Compare several stores

Export each store separately. In each file, add a column called store and fill it with that store's name, then paste the files under one another in a single sheet. They share the same 26 columns in the same order, so they stack cleanly. Now one pivot table with product_type as rows, store as columns and the median price as values puts each store's price band for the same kind of product side by side.

Each export is a snapshot of the moment you clicked. To see price changes over time, export again later and compare the two files. CatalogCSV doesn't track stores for you.

Images for your research board

The Image URLs only format gives you every image link with its position, alt text, width, height and the variants it belongs to (8 columns). That's handy for a mood board or for spotting stores that use the same supplier photos. CatalogCSV exports the links only and does not download the images. Open them in a browser, or download them with another tool.

What this does not do

Here's the plain version, so you can pick the right tool:

  • No sales estimates and no best-seller data. The store's catalog doesn't show what sells.
  • No ad research.
  • No app or theme detection.
  • No store tracking over time. Every export is a one-off snapshot.
  • No XLSX or JSON files. You get CSV, which opens directly in Excel.

If you need those things, a competitor-research ("spy") extension such as Koala Inspector is built for them. It lists best-sellers, installed apps, the theme, estimated traffic and sales, and ad campaigns. CatalogCSV does one narrower job: a clean, complete catalog in a spreadsheet.

It also only reads stores whose products are publicly visible. It can't read a store that is running a bot check, and a password-protected store needs its password entered first.

Use it for research, not to copy a store

The export is for understanding a market. Another store's product descriptions and photos belong to that store or its suppliers. Don't republish them as your own. Use the sheet to decide what to sell and at what price, then write your own copy and get your own images from your supplier.

Free vs Pro

Every format and every column is free, with no account. Each free export includes the first 100 products. On a bigger store, that's a sample rather than the whole range, so the pivots and price spreads above describe those 100 products only. Pro removes the limit for $9 a month or $79 a year, with one key for up to three browsers or computers. Cancel any time. In testing, the exporter paged through a 6,498-product catalog to the end.