[Sub-Society]

[Sub-Society]

Full Experience

Case Study

4 Months

2024

[Sub-Society]: Fashion App

Project Description

Introduction:

Sub-Society is a concept app for fashion designers, creators, and enthusiasts a place where inspiration, community, and shopping live together. The goal: cut the jump between “I love this look” and “I own it,” while building real trust between brands, creators, and buyers. Over ~4 months I led the full cycle: idea validation, research, brand/identity, UX architecture, and high-fidelity UI.

Challenge:

  • Fashion discovery and purchasing are fragmented across apps; buying from social content is clunky.

  • Low trust: it’s hard to tell who’s credible or which products fit your style.

  • Personalization must feel helpful (not creepy) and respect user consent.

  • Pack rich community + commerce features into one app without bloat.

Solution:

Research & Strategy: Interviews with fashion-savvy users, market/literature study, benchmarking of shopping/community apps, and Reddit ethnography. From this, I built personas, mind maps, IA, and user flows.
Brand & Identity: Name “Sub-Society” reflects an insider community; wordmark-first logo; black/white with signal-red for a bold, youth-forward feel.
Product Design:

  • Taste-matching feed driven by explicit signals (likes, saves, follows, purchases, wardrobe combos) and opt-in analytics.

  • Social layer (looks, posts, brand drops), plus an in-app store so content can convert in one tap.

  • Creator Level System to surface credible voices and give brands a clean way to sponsor and reward.

  • Wardrobe (auto-saves purchases) and Outfit Builder to mix pieces and discover smart recommendations.

  • Discovery & Trending, brand profiles, and moderation/trust mechanics.

  • Delivery: Extensive wireframes → iterative tests → high-fidelity screens and design system.

Impact:

From validation and prototypes:

  • Shorter path from discovery to purchase vs. typical social → shop flows.

  • Higher purchase intent and session depth when shopping is embedded in content.

  • Clearer brand creator fit via levels; easier sponsorship decisions.

  • Rich “preference signals” enable relevant, consent-based recommendations.

  • Business upside: community flywheel (UGC → engagement → sales), multiple revenue streams (affiliate, sponsored drops, brand partnerships), and strong foundations for retention and LTV.

From validation and prototypes:

  • Shorter path from discovery to purchase vs. typical social → shop flows.

  • Higher purchase intent and session depth when shopping is embedded in content.

  • Clearer brand creator fit via levels; easier sponsorship decisions.

  • Rich “preference signals” enable relevant, consent-based recommendations.

  • Business upside: community flywheel (UGC → engagement → sales), multiple revenue streams (affiliate, sponsored drops, brand partnerships), and strong foundations for retention and LTV.

From validation and prototypes:

  • Shorter path from discovery to purchase vs. typical social → shop flows.

  • Higher purchase intent and session depth when shopping is embedded in content.

  • Clearer brand creator fit via levels; easier sponsorship decisions.

  • Rich “preference signals” enable relevant, consent-based recommendations.

  • Business upside: community flywheel (UGC → engagement → sales), multiple revenue streams (affiliate, sponsored drops, brand partnerships), and strong foundations for retention and LTV.

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