Decision Architecture
Industry
E-commerce
Service
Trust System & UX Strategy
Challenge
Choice overwhelm
Outcome
Credibility-stacked structure
(01)
Project overview.
Toy Finder was an experiment in decision architecture for parents drowning in toy choices. Instead of presenting hundreds of options, I designed a system showing only 3 expert-backed recommendations organized through a 4-tier trust framework.
The project challenged a fundamental assumption: Do parents need more choices, or more confidence in fewer choices?
I built a trust architecture system that organised disparate credibility signals, expert reviews, brand recognition, parent testimonials, lifestyle imagery, into a coherent decision framework that matched how parents actually evaluate toys.
Project Status: Paused due to content scalability constraints. The editorial infrastructure required to maintain expert-vetted recommendations across age ranges and developmental stages exceeded available resources.
(02)
Challenge.
Parents face overwhelming choice when selecting toys online. Hundreds of options across multiple retailers, conflicting reviews, unclear age appropriateness, and no clear signal of what's actually worth buying.
The real problem wasn't finding toys, it was knowing which toys to trust. Should they follow expert recommendations? Trust parent reviews? Look for award winners? The cognitive load of evaluating all these signals while filtering by age, developmental stage, and play type created decision paralysis.
Traditional e-commerce patterns (endless catalogues, filter overload) abdicate this organizational work to users. Parents don't need more options. They need structure that builds confidence.
(03)
Approach.
I started by mapping the parent decision journey: What questions do they ask? What builds confidence? When do they commit to purchase?
My research revealed four trust signal types parents use:
Expert Authority - Professional recommendations, developmental appropriateness
Brand Recognition - Familiar brands signal quality and safety
Social Proof - Other parents' testimonials and experiences
Visual Evidence - Lifestyle imagery showing real play
I organised these into a 4-tier trust architecture, designing how each layer reinforced the others rather than competing for attention.
Then I mapped the cognitive flow: qualification (age/developmental stage) → consideration (trust signals) → validation (purchase confidence). The information architecture needed to mirror this natural buyer journey, not impose e-commerce convention structure.
(04)
Solution.
I designed a trust system with four integrated layers:
Tier 1: Expert Authority
Developmental psychologist endorsements positioned at the top, immediately establishing credibility and educational value.
Tier 2: Brand Recognition
Recognizable brand logos appeared consistently without overwhelming the primary message—familiar names that signal reliability.
Tier 3: Social Proof
Parent testimonials structured to answer specific questions: "Does this hold attention?" "Is it worth the price?" "Will my child actually use it?"
Tier 4: Visual Evidence
Lifestyle photography showed toys in context, helping parents visualise actual play rather than studio shots.
The cognitive flow matched the buyer journey:
Qualification - "Is this right for my child's age?" (developmental filtering)
Consideration - "Why should I trust this?" (4-tier credibility stack)
Validation - "Can I picture this working?" (visual confirmation + 3-option structure reduced paralysis)
(05)
Decisions.
Decision 1: Credibility Stacking
Instead of presenting trust signals sequentially, I layered them so multiple indicators appear together. This "credibility stack" builds confidence faster than isolated signals. Parents see expert endorsement + brand recognition + social proof simultaneously, reducing the need to hunt for validation.
Decision 2: Visual Hierarchy Over Alphabetical Lists
Rejected standard e-commerce patterns (grid layouts, alphabetical sorting). Instead, structured content around attention flow: age → benefit → trust → image. Natural scanning order matched decision-making order.
Decision 3: Three Options, Not Unlimited Choice
The entire system relied on curation. Showing 3 expert-backed options instead of 100+ removed decision fatigue. This constraint forced me to design a trust system strong enough to justify "Why these three?"
Decision 4: Cognitive Flow Mirroring Buyer Journey
Content sequence (qualification → consideration → validation) matched how parents actually evaluate toys, not how products are traditionally organised (category → filter → sort).
(06)
Result.
Structural Improvements:
Organised 4 disparate trust signal types into coherent hierarchy
Designed cognitive flow that matched natural buyer behaviour
Created reusable trust framework applicable across age ranges and toy categories
User Benefits:
Clear mental model for "why should I trust this recommendation"
Reduced decision paralysis through structured choice (3 options, not 100+)
Faster path to confident purchase through layered credibility signals
What I Learned:
Trust architecture requires both structural clarity (organising signals) and content depth (maintaining quality). I solved the structure problem but couldn't solve the content scalability problem within project constraints.
The IA worked. The editorial model didn't scale.