Seller Sessions Amazon FBA and Private Label

How to Optimize Fashion Listings on Amazon | Conversion Monthly


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In this Conversion Monthly episode, the team takes on a real-world Amazon fashion listing -- a ladies jumper from Adam Jagger's clothing brand. Adam launched this knitwear product last year with strong initial sales, but the relaunch has stalled despite refreshed images and PPC data.

Matt Kostan shares consumer feedback from Product Opinion videos revealing that shoppers found the secondary images too text-heavy and "fast fashion" looking, with inconsistent color rendering across photos. Dorian then presents a complete visual overhaul inspired by Zara's photography style -- low-angle shots, model-camera interaction, and stripped-back secondary images that let the product speak for itself.

The result: a 45% improvement in click share during simulated testing, jumping from 11% to 16% against competitors. The episode is packed with actionable advice on fashion-specific listing optimization, the power of "less is more" in secondary images, and why pre-launch polling is essential in design-led categories.

Key Topics
  • Live listing teardown -- Adam Jagger's ladies jumper analyzed by the full Conversion Monthly panel
  • Consumer video feedback -- What real shoppers said about the listing (color inconsistency, text-heavy images, fast fashion feel)
  • Main image testing -- Baseline vs. Zara-inspired low-angle photography concepts
  • Secondary image overhaul -- Stripping back text and adopting a premium, warm aesthetic
  • Pre-launch polling -- Why design-led fashion products should be tested before manufacturing
  • Selling through the female lens -- Understanding emotional and aspirational buying in women's fashion
Timestamps
  • [00:00] Introduction and welcome to Adam Jagger
  • [01:24] Adam explains the product -- ladies jumper relaunch that stalled
  • [02:28] Category rules -- how much creative freedom do clothing listings have?
  • [03:45] Matt shares Product Opinion video feedback from real shoppers
  • [07:25] Dorian's approach -- studying Zara and H&M for photography inspiration
  • [10:30] The "less is more" philosophy for fashion secondary images
  • [14:02] Matt reveals test results -- 11% to 16% click share improvement
  • [19:22] Sim's take on AI-generated images and warmth in the image stack
  • [20:39] AI-generated video concepts for sponsored brand ads
  • [22:50] Adam's reaction and takeaways
  • [26:17] Danny's deep dive -- cognitive overload, decision paralysis, and the female lens
  • [37:31] Adam's final thoughts and next steps
  • [38:30] Sim on pre-launch polling for design-led niches
  • [40:47] Final roundup and upcoming Seller Sessions event announcement
Key Takeaways
  1. Strip back your fashion images -- Text-heavy, icon-filled secondary images can make clothing look like fast fashion. Clean, warm, product-focused images convert better.
  2. Study leading brands for photography direction -- Dorian reverse-engineered Zara's low-angle, model-interaction photography style and applied it to the Amazon listing with a 45% click share improvement.
  3. Consumer video feedback reveals what data cannot -- Ten 4-minute shopper videos uncovered issues like inconsistent pink shading across images that no one on the team had noticed.
  4. Pricing inconsistency kills trust -- Having one color variation priced higher than others confused shoppers and reduced confidence in the listing.
  5. Poll before you launch in fashion -- For design-led categories, spending $100 on pre-launch testing can steer you away from a bad product or nail the positioning first time.
  6. Sell the transformation, not the features -- Women's fashion is an emotional, aspirational purchase. The listing should make the shopper feel "this could be me" rather than listing fabric specs.
  7. Beware of over-optimizing click-through rate -- Pushing CTR too hard can lead to image fatigue and diminishing returns. Balance scroll-stopping visuals with long-term brand consistency.
...more
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Seller Sessions Amazon FBA and Private LabelBy Danny McMillan

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