Pawfect
｜ UX AWARDS NEW TALENT WINNER ｜
My Role
UX Research & Strategy
Duration
3 months
Introduction video
Pet adoption is an emotionally driven yet high-stakes decision-making process.
Based on UK & global shelter data, 2020–2024
+24%
year-on-year rise, driven largely by the cost-of-living crisis
Pets surrendered to UK rescues
7–20%
of all adoptions end up back at the shelter
Shelter adoptions returned within 6 months
59%
the single leading cause of failed adoptions
Dog returns caused by behavioral mismatch
(Dogs Trust, UK)
While many online platforms connect adopters with animals, they often lack intelligent tools to guide suitable matches. Adopters are left to rely on fragmented information, while shelters face inefficiencies in managing applications and assessing adopter suitability.
This isn't a hypothetical problem. RSPCA recorded a 24% rise in pets surrendered to UK rescues in 2022 alone. Across shelter studies, an estimated 7–20% of adopted pets are returned within six months — and among dogs, 59% of those returns trace back to behavioral mismatches that better screening and matching could have flagged earlier.
With growing interest in responsible, long-term pet ownership, there is a clear need for an intelligent experience that builds trust and leads to long-term ownership — supporting smarter, more confident adoption decisions for both people and animals.
Sources: RSPCA Annual Statistics & Abandonment Reports (2022–2025); Dogs Trust Annual Report; cross-shelter return-rate research including 'Characterizing unsuccessful animal adoptions' and 'The impact of returning a pet to the shelter on future animal adoptions,' Scientific Reports (2021–2022).
Previous Problems & Design Goals
Previous Problems
Adopters can't see why is compatible.
Matching logic lacks transparency.
Two users, two mental models. Adopters want reassurance; shelters want efficiency and complete documentation, but the interface treats them the same.
Design Goals
Build trust through explainable AI.
Serve both the Adopter and Shelter mental models
Reduce returns caused by mismatched expectations.
USER-CENTRIC RESEARCH
DEFINING USERS
Adopter
Inefficiency Pets Exploration
Adopters seek rich, detailed information to make informed decisions, but most platforms provide only simple descriptions and low-quality visuals, making it hard to truly understand each pet.
Shelter
Pet-Adopter Mismatch
Current platforms make it difficult for users to anticipate a pet’s behaviour and personality based on limited profiles and surface-level first impressions. This often leads to misaligned expectations and unsuccessful adoptions.
DESIGN and PROTOTYPE
Adopter
🐾 Create Account
By completing a guided, step-by-step sign-up with lifestyle details, adopters receive smarter recommendations while staying confident and engaged in the process.
🐾 AI-Powered Pet Profiles
AI analyses both pet and adopter data to explain why the match works—helping adopters look beyond appearance, build emotional connection, and make confident, well-informed decisions.
Shelter
🐾 AI Personality Insights
Shelters can upload pet photos or videos, and our AI generates personality traits and behaviour tags.
This saves time and adds depth to profiles, making each pet easier to understand and more likely to be matched.
🐾 Application Overview
Shelters can see all incoming applications with match scores and key adopter info within few steps. This streamlines evaluation, supports better decisions, and ensures every animal is placed with the right person.
ROLE and RESPONSABILITIES
I identified a systemic gap in pet adoption platforms: matching mechanisms prioritize availability over compatibility, contributing to adoption returns. I led the product concept, research, and usability validation for Pawfect, from early ideation to real-user testing and public-facing storytelling.
My main contributions included:
-
Product ideation and problem framing
Defined the product vision around reducing pet adoption mismatch and return rates. -
Secondary research and competitive analysis
Conducted literature review and market analysis to identify gaps in existing adoption platforms. -
Usability testing (20 participants)
Product storytelling and communication: produced the product introduction video and designed marketing & social media visuals to communicate the concept clearly to the public and judges.
I worked closely with teammates on interaction and visual execution, while primarily driving the user research, insight generation, and experience logic behind key product decisions.
JURY FEEDBACK FROM UX AWARDS
“Pawfect addresses pet abandonment by improving adoption matching and reducing returns.”
→ Problem framing and social impact
“Offering strong user value with emotionally resonant and well-crafted experience.”
→ Experience design and emotional UX
“AI logic shows promising potential.”
→ Forward-looking product vision
“Could evolve into a high-impact product with further refinement.”
→ Scalability and system thinking
