How Shopify analytics help choose the best-selling painting formats
8 min read · by Walensky
GAZELLE PAINTINGS
Three paintings, three formats, one spot on the homepage. It's the question every wall decor store owner asks themselves on a Tuesday morning in front of their Shopify dashboard: which one to push? The square? The panoramic? The large A2 that costs a fortune to store but makes a real impact?
The answer doesn't come from aesthetic intuition. It comes from Shopify Analytics reports, as long as you know where to look and what to cross-reference.
The direct answerShopify Analytics lets you identify the best-selling painting formats by cross-referencing three native reports: sales by variant (format/material), conversion rate per product page, and browsing behavior (clicks, add-to-cart actions). By comparing these data format by format within the same collection, you can quickly see whether the square converts better than the panoramic, or whether a large format generates more margin despite lower traffic.- The "Sales by variant" report reveals which format (L, XL, XXL...) actually sells, beyond the generic product.
- The conversion rate per product page distinguishes the formats that attract clicks from those that turn into orders.
- Cross-referencing format and material (acrylic glass or Dibond aluminum) further refines your reading of customer preferences.
Why format is a key performance variable on Shopify
The same visual offered in several formats never sells equally. It's almost counterintuitive: one imagines the customer first chooses the image, then the size that suits them. In reality, the format often shapes the purchase decision itself, before the aesthetic choice even comes into play.
Take a 120x40 cm panoramic painting: it targets a specific use, above a sofa or a wide headboard. A 100x100 cm square format meets a different need, that of a dense central wall. These two formats don't address the same buyer, and their conversion rates often prove it.
This proportion rule partly explains why certain formats dominate certain collections. A living room with a 220 cm sofa naturally calls for a wide format, while a hallway or entryway pushes toward more compact pieces. Analytics simply confirm, with figures, what spatial logic already suggests.
Format isn't a minor product-page detail: it's often the first variable that decides whether a visitor buys or closes the tab.
The Shopify reports to monitor for analyzing sales by format
Three native reports are enough in most cases, without any third-party app. You just need to know how to read them together rather than in isolation.
Sales by product variant report
In Analytics > Reports > Sales, the "by variant" breakdown shows the quantities sold for each format/material combination of a single product. It's the most telling report: it shows in black and white whether the XL sells three times more than the 4XL on a given visual.
Export this report over several months, not fifteen days. Wall decor purchases follow cycles (back-to-school, holidays, spring) that distort a reading that's too short.
Browsing behavior and click-through rate per product page report
The "Most viewed products" report, cross-referenced with sessions per page, shows which formats generate clicks without necessarily converting. A format that draws a lot of attention but few sales deserves a price or photo adjustment, not removal from the catalog.
The conversion rate per variant isn't native on every Shopify plan. If your plan doesn't show it in detail, combine the sales-by-variant report with the sessions-per-product report to recalculate it manually.
Shopify Analytics is enough for this first analysis. A third-party app (Triple Whale, Lifetimely, or equivalent) only becomes useful if you manage several hundred references and want to automate recurring dashboards.
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Discover this paintingStep-by-step method for cross-referencing sales data and painting formats
Here is the sequence that turns raw figures into a concrete catalog decision.
- Isolate a coherent collection. Compare formats with each other within the same visual universe (abstract, animal, geometric), never across mixed collections.
- Export sales by variant over 3 to 6 months. For each format, note: quantity sold, revenue, share of the total.
- Calculate the conversion rate per format. Divide orders by the sessions that viewed that specific variant.
- Cross-reference with the chosen material. Acrylic glass and Dibond aluminum don't attract the same buyer: a format that underperforms in acrylic glass may do very well in Dibond aluminum, and vice versa.
- Decide tier by tier. A format that underperforms across several different visuals of the same collection isn't an accident: it's a signal to drop it from your featured placements, or even from custom sizing.
how performance data already guides the choice of best-selling paintings details the overall logic behind this method, if you want the pure data angle rather than the format focus.
— Our selection
Concrete examples with paintings from the store
On an animal collection, comparing sales by variant often reveals clear gaps between landscape and square formats. A graphic feline painting in brown and beige tones, designed in a wide landscape format, usually attracts buyers looking for a statement piece above a sofa.
Conversely, a more graphic, high-contrast visual, such as an animal composition in black and green, may perform better in very large sizes (3XL or 4XL) if the data shows a higher average basket on those sizes, even with lower sales volume.
In a street art or graphic collection, panoramic formats often come into play differently: a visual with fine geometric lines lends itself well to a stretched width, while a more figurative subject remains better suited to a classic landscape format.
It's by repeating this reading visual by visual, format by format, that a real map takes shape: some subjects call for the square, others for the wide landscape, others still for the stretched panoramic. Analytics don't guess anything; they confirm or refute a starting hypothesis.
Going further: combining format analytics, loading speed and performance sharing
A format that converts poorly may hide a speed problem, not a taste problem. A product page with several large-size variants sometimes loads more slowly, especially if the visuals aren't optimized, which mechanically skews the measured conversion rate.
Before condemning a format based solely on the numbers, check the loading speed of the page concerned. our guide on sharing Shopify performance explains how to circulate these findings internally, between the product and marketing teams, without the information getting lost in a forgotten spreadsheet.
Format data only has value when shared: a store that analyzes sales by variant but never passes the conclusion on to whoever handles restocking or featured placements redoes the same work every quarter, for nothing.
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Discover this painting →Frequently asked questions
Which Shopify reports show sales by product format?
The "Sales by variant" report, accessible from Analytics > Reports > Sales, displays the quantities and revenue for each format/material combination of a given product.
How do you know which painting format sells best online?
Compare the conversion rate by variant across several visuals of the same collection, over a period of at least three months, isolating seasonal effects.
Is Shopify Analytics enough or do you need a third-party app?
Native reports are sufficient for most stores. A third-party app only becomes useful beyond several hundred references, to automate recurring dashboards.
How can you use analytics data to reduce dead stock of certain formats?
Identify the formats that underperform across several different visuals of the same collection: that's a reliable signal to reduce their featured placement or remove them from custom sizing, rather than judging a single isolated product.
Analytics never replace the eye that chooses a work for its living room. But they keep you from betting an entire stock on a fragile intuition. Cross-referencing format, material and conversion, visual after visual, turns a catalog into a sales tool rather than a static collection.
The Gazelle Paintings collection remains a good practical testing ground for this method: several formats, a single visual universe, and data that speaks for itself once you know where to look.
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