How to Actually Analyze Your Spoonflower Sales

What the CSV Misses

By zabzablab  ·  September 12, 2026

I built Seller Lab because I kept running into the same walls analyzing my own Spoonflower shop. The earnings CSV is a starting point — it has your sales rows, what sold, when, for how much — but it leaves out exactly the things you need to understand what’s actually working. These are the gaps that drove every design decision in Seller Lab.

There are no order IDs

Each item in a multi-item order gets its own row with nothing linking them. A buyer who ordered six 9-foot wallpaper rolls — someone papering a whole room — shows up as six separate rows at $7 each. Without knowing those rows belong to one order, that design looks like it has six transactions worth of traction. But that's not the same as six different people independently discovering and buying it. One bulk order and genuine repeat interest look identical in the raw data, and they shouldn't. So if you want to know how many times someone actually checked out, not just how many line items sold, you have to infer the groupings yourself. Guest checkouts make this harder: all guests share the same anonymous identifier, so you can't match by name at all.

Seller Lab runs that inference on every upload and gives you consistent order counts without you having to build or re-run any logic.

You can't tell if swatch buyers came back

A swatch sale often means someone is testing a design before ordering more. Knowing how often that follow-up happens is useful — but a lot of buyers check out as guests, and all guest rows carry the same anonymous identifier. A swatch in March and a yard order in May both show up as "a guest user." They might be the same person, or they might not.

Seller Lab makes a best-effort estimate and shows it as a conversion rate — so you can actually look at it, rather than never knowing where to start.

Keywords and sales are in separate places

The CSV has no tag data. Your listing tags live on Spoonflower's website, and connecting them to your sales — to see which keywords actually show up on your best-selling designs — means pulling that data separately and keeping it up to date as you edit listings.

Seller Lab's Chrome extension pulls your live listing tags and connects them to your sales history. Instead of relying on intuition, you can see exactly which keywords appear on your best-selling designs and use that to inform how you tag the rest of your catalog.

Design-level trends are hard to see

The CSV has design IDs and titles but no thumbnails. With a large catalog, a list of names doesn't tell you much — you need to see the design. And a lifetime total isn't the whole picture either: 35 sales in the last 90 days looks very different from 50 sales spread across three years.

Seller Lab pulls thumbnails via the extension and shows sales velocity per design, so you can see what's gaining traction and what's slowed down without building a separate chart for each one.

Colorways and size variants scatter the data

Each colorway is a separate listing with its own design ID, so the same design in six colors produces six rows in your CSV. Sizes work the same way — fat quarter, yard, and swatch each appear separately. To see how a design family is performing as a whole, you have to group and aggregate manually.

In Seller Lab you group designs once and every view — revenue, orders, trends — reflects the family as a whole.

What actually helps

Upload your CSV and Seller Lab takes care of the rest — inferring orders, pulling in your listing tags, showing thumbnails, tracking velocity, grouping colorways. All the things you'd otherwise have to set up and maintain yourself, updated automatically every time you add new data.

But the bigger picture is that none of these data points mean much in isolation. Knowing a design sold well is more useful when you can also see which keywords it carried, whether swatch buyers came back for it, and how it compares to the rest of your catalog over time. Seller Lab connects those threads — so instead of jumping between spreadsheets and trying to hold it all in your head, you get one place that tells you what to pay attention to and where to focus your next designs.