Verdell HomeHome & Garden
A conversion problem that looked like a traffic problem
Verdell was buying more traffic every quarter to hold flat revenue. The detail pages, not the campaigns, were the constraint.
Engagement: Listing and creative programme · 9 months
Headline results
+41%
Conversion rate
Unit session percentage, core SKUs
+18%
Click-through rate
From search results
-9%
Return rate
Driven by accurate sizing imagery
Illustrative figures. This case study is demonstration content. Replace the brand, quote and every number here with verified, client-approved data before publishing — see src/content/case-studies.ts.
The challenge
What was actually wrong.
Sessions were up 34% year on year. Revenue was up 4%. Every extra dollar of advertising was buying traffic that did not convert.
The catalogue's photography had been produced for a wholesale line sheet: white background, single angle, no scale reference and no lifestyle context.
Background
Verdell sells mid-priced home textiles where the two dominant purchase objections are dimensions and material feel — neither of which the existing imagery addressed.
Returns data showed 'not as described' and 'wrong size' accounting for a majority of returns, which confirmed the listing rather than the product was the problem.
Strategy
What we decided to do — and in what order.
Start from the returns data
Return reason codes and review text told us exactly which two objections to answer, so the shot list was written from evidence rather than taste.
Give every image slot a job
Recognition, scale, material detail, objection, lifestyle, comparison. No slot duplicated another.
Change the main image first
It carries the most weight and is the cleanest thing to isolate, so it shipped alone with a four-week read window.
Build A+ around comparison
A size and material comparison chart replaced a brand-story module that restated the bullets.
Execution
The work, week by week.
- Re-shot main images for 22 core SKUs with a consistent scale reference in frame.
- Produced a six-slot image system and applied it across the catalogue.
- Rewrote bullets to lead with the two objections rather than with features.
- Built comparison-led A+ modules for all variation families.
- Ran sequential tests with matched four-week windows, controlling for price and stock.
Before vs after
The movement.
| Metric | Before | After | Note |
|---|---|---|---|
| Unit session percentage | 7.8% | 11.0% | Core SKU average |
| Images per listing | 4 | 7 | Including one video |
| Returns: 'wrong size' | 5.1% | 2.4% | As share of units sold |
| Ad spend | Baseline | Unchanged | Conversion gains came without additional budget |
View the underlying data as a table
| Period | Indexed value |
|---|---|
| Baseline | 78 |
| Main image | 89 |
| Sequence | 98 |
| A+ | 105 |
| Video | 110 |
Timeline
How it unfolded.
Weeks 1–3
Evidence
Review mining, returns analysis and competitor teardown.
Weeks 4–6
Production
Shot list approved, studio and lifestyle production completed.
Weeks 7–18
Sequential testing
Main image, then sequence, then A+ — each with a clean read window.
Months 5–9
Rollout
Visual system applied across the remaining catalogue.
Key learnings
What we'd tell the next brand.
Traffic problems and conversion problems look identical in a revenue chart and need opposite responses.
Returns data is the cheapest creative brief available and almost nobody reads it.
Sequential testing is slower than shipping everything at once, and it is the only way to know what worked.
We assumed we needed more budget. It turned out we needed different photographs.
Placeholder attribution. Client names and quotes are published only with written permission.
Services used in this engagement
Product listing optimization
Titles, bullets, imagery, A+ and video rebuilt around the objection that stops the purchase.
ExploreProduct photography & video
Studio, lifestyle, infographic, A+ and video built for a 320-pixel tile and a scrolling thumb.
ExploreFull-service Amazon management
Strategy, advertising, search, content and operations run by one accountable team against one plan.
Explore
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