Turning quality doubt into purchase confidence
Turning quality doubt into purchase confidence | A product properties system built from user research
~60% of users expressed quality concerns before purchasing. I led the discovery, framing, and design of a cross-journey quality signal system, from user interviews to approved solution heading into A/B test.
Context
This project started with a pattern I kept seeing during continuous discovery, users hesitating or dropping off not because they couldn’t find a product, but because they didn’t trust what they were buying. Print-on-demand clothing is an inherently uncertain category: you can’t feel the fabric, you don’t know the brand, and price alone doesn’t communicate quality.
I flagged the pattern, framed it as an opportunity, and led the project from initial hypothesis through to a validated solution approved by POs and stakeholders.
Problem
Across 50+ user interviews conducted during continuous discovery, quality concern was the single most recurring theme — spanning both print-on-demand buyers and general clothing shoppers.
~60% of users
expressed quality doubts before purchasing.
From user interviews 50+ users and unmoderated tests 70 users.
Discovery | what quality actually means to users
I ran focused discovery sessions to understand how users defined quality in their own words. The most frequently mentioned attributes were: durability, washing resistance, material (cotton), fabric thickness, fit, softness, and print quality. These became the foundation of the solution from the actual words users used.
Users described quality using these words
Three user intent profiles emerged from the research:
- Best quality, no compromise Willing to pay more. Needs signals that justify premium pricing.
- Good quality for daily wear Value-conscious but quality-aware. Needs clarity on what they’re getting for the price.
- Cheapest option Price-first. Properties still matter for setting expectations and avoiding returns.
Validating hypothesis | properties vs. tier names
Users remember concrete product properties that they care about. Not tier names.
Before committing to the direction, I collaborated with another Product Designer to test a core hypothesis: do users respond better to concrete product properties with icons, or to abstract tier names like “Classic / Durable / Long Lasting”?
We ran an unmoderated test between Version A & Version B, all participants were shown both versions.
Version A (Winner)
Concrete product properties with icons
Prototype was built with V0
Version B
Abstract tier names
Prototype was built with V0
100% preferred version A
20 participants (10 POD* shoppers + 10 general clothing shoppers)
All participants preferred durability signals (30+ washes) and properties with icons over tier names in the unmoderated test.
*POD → Print on demand
Users remembered what mattered to them specifically, durability, material, fabric thickness, fit. Not an abstract tier label. This confirmed our hypothesis and the proposed solution.
The pivot | when the ideal solution wasn’t feasible
The initial direction was a durability tier system using wash counts (10, 30+, 50+ washes) as a clear, comparable quality signal and supported by sub-product properties (material, fabric thickness, fit). Users responded well to the concept. But when we aligned with the assortment team, wash count data wasn’t available or verifiable across the full catalogue, making it impossible to roll out honestly.
Wash count tiers (10, 30+, 50+ washes) across full assortment, data not verifiable across all brands.
Rather than compromising on accuracy or dropping durability entirely, I reframed the problem: our private label products are our best quality, most sustainable, and highest-margin products, and they do carry a credible durability claim. The question became how to use that strength honestly.
How we navigated the constraints:
Communicate 4 core properties across all products. Give our private label* an additional, credible durability claim (Best for print. Long-lasting.) with elevated visual treatment.
*Our private label brand → SPREAD+
4 core properties
All other brands
4 core properties
SPREAD brand
4 core properties + Best for print & Long-lasting claims
This also satisfied the founder’s desire to elevate the private label brand transparently, in a way that made sense to users. Also, the private label are highest-margin products.
Solution | a cross-journey quality signal & brand recognition
Four product properties: Material, Fabric Feel, Fabric Weight, Fit. Communicated consistently across the full purchase journey, with SPREAD private label given additional differentiation.
New property-based filters | PLP
Material, Fabric Feel, Fabric Weight, and Fit introduced as filters on the PLP, letting users self-select by what matters to them.
New property-based filters | PLP
4 core properties to act as quality signals
Quality signals + Brand recognition
We took advantage of our good reviews and made them part of the PLP product tile as a strong social proof quality signal.
Quality signals + Brand recognition
PLP tiles changes
- Product ratings
- 100% cotton label
- Brand recognition → “Our Pick” tag
PDP | Stanley/Stella product
Four product properties: Material, Fabric Feel, Fabric Weight, Fit. Communicated consistently across all PDPs.
PDP | Stanley/Stella product
4 core properties
PDP | SPREAD product
Four product properties: Material, Fabric Feel, Fabric Weight, Fit. Additionally SPREAD private label given additional differentiation:
- More prominent colourful component.
- Best for print & Long-lasting claims.
PDP | SPREAD product
4 core properties + Best for print & Long-lasting claims
Status & expected impact
The solution is approved by POs and stakeholders and is part of the next OKR tertial, heading into development and A/B testing.
- ↑ CVR on private label products By reducing quality uncertainty at the point of decision, the moment users currently hesitate most.
- ↑ AOV By helping users justify choosing private label over the cheapest option, quality signals make the price difference legible.
- Private label brand awareness “Our Pick” tagging and elevated PDP treatment begin building recognition of the SPREAD+ brand across the catalogue.
Reflection
This project is a good example of how continuous discovery creates product opportunities that wouldn’t appear in a roadmap driven by stakeholder requests alone.
The pivot away from wash count tiers was the most important design decision. It would have been easy to water down the solution or drop durability entirely. Instead, using the private label’s genuine quality strength as the durability signal turned a constraint into an advantage, for users, for the business, and for brand positioning simultaneously.
Users don’t remember ambiguous tier names.They remember what matters to them. Design that speaks their language removes doubt faster than any marketing claim.