1 Minute Summary
1 Minute Summary
This was a mixed-methods UX research study aimed at understanding why first-time dog owners often surrender their pets, and how a technology tool could help reduce that. The central research question: How can a digital tool help prospective dog owners find the right breed and understand what ownership actually entails?
methods used:
Observations (7 participants), semi-structured interviews (5 participants), and a survey (30 respondents) — all targeting people who had never owned a dog but wanted one.
key findings
- People were motivated by companionship and social environments, but had significant knowledge gaps around costs, care, and breed behaviors
- Pain points included poor filtering on existing adoption sites and lack of personalized guidance
- Existing tools like Petango and Pedigree's breed quiz were limited — either buried the care info or were too basic
Design recommendations surfaced:
Refined search filters, dog biographies, expense estimator, breed comparison tool, map-based adoption finder, and community comment sections per breed.
Want the full story?
The sections below dives deeper into research, design decisions, iterations, and learnings.
About
My Role
Researcher
Research Design, Data Collection, Analysis, Feature Synthesis
project type
User Research
Methods
Observation, Interview, Survey
Mixed-Methods
Participants
18 across all studies
7 obs • 5 interviews • 30 survey
duration & status
Q1 2019
Research Complete
Exploring how to reduce dog relinquishment through better-informed adoption decisions.
Every year approximately 6.5 million animals enter United States animal shelters and 1.5 million shelter animals are euthanized. Research shows that a major contributing factor is misinformed expectations — new owners surrender dogs not because the animals are bad, but because they weren't prepared for the reality of that breed or their individual dog's needs.
This research explored the expectations and motivations of people considering dog adoption for the first time. The central question: how can a technology-based tool help potential new dog owners assess whether a breed is a good fit, and educate them on what ownership actually requires?
Behavioral problems are the most cited reason for dog relinquishment — but in many cases, those "problems" are the natural traits of the breed the owner chose without fully understanding. The issue is a mismatch between expectation and reality.
Competitive Landscape
Existing tools didn't go far enough.
Top Tools Used To Find Potential Dogs for Adoption
- Petango
- Offers a filterable database with a "PetMatch" questionnaire, but care information is buried in tip blog posts on a separate page — not integrated into the decision journey.
- Pedigree Dog Breed Selector Quiz
- Helps users explore breeds but relies on a limited set of basic parameters. Effectively a marketing tool for Pedigree dog food — not built around the full complexity of real adoption needs.
Neither tool adequately bridges the gap between finding a dog and understanding what owning that dog actually involves. That gap was the focus of this research.
Methods
A three-phase approachto understand needs across the full spectrum of prospective owners
- Observations
-
7 Participants with no prior dog ownership were observed searching for a dog online. Sessions were screen-recorded and coded using AEIOU framework.
- Interviews
-
5 In-depth semi-structured interviews focused on mental models, criteria, expectations, and knowledge gaps. Transcribed and coded inductively via Atlas.ti.
- Survey
-
30 Mixed-experience respondents. Included experienced and prospective owners to test whether observation and interview themes held at scale.
Participant Criteria
Observation and interview participants were required to (1) never have previously owned a dog and (2) be actively considering adoption. Survey participants were 18+ and either owned a dog previously, currently own one, or are interested in getting one — allowing for cross-experience comparison.
Findings
Three themes emerged consistently across all three methods
- Finding 1:
-
7 Observation participants — all had pre-formed criteria before session began.
- Finding 2:
-
4.7 Mean helpfulness rating for visual results (photo/video) — highest of all features tested.
- Finding 3:
-
2.1 Mean self-rated knowledge score (of 5) for adoption options among inexperienced owners.
- Motivating Preferences: All participants had pre-formed dog preferences — ranging from general descriptors ("big and strong") to highly specific criteria (breed, fur color, temperament, age). Four of five interview participants wanted puppies specifically.
- Motivating Factors: Two primary drivers emerged — a desire for companionship and the environment presence of dogs (neighbors, coworkers, social media). These weren't just reasons to want a dog; they were active triggers for beginning the search.
- Social Resources: Four of five interview participants actively sought advice from friends and family. Social validation played a significant role in both the decision to adopt and criteria used to evaluate a dog.
Personas
Two users with very different starting points and the same need for better tools
Lisa: Inexperienced First-Timer
Wanted a dog for a while, no ownership experience. Prefers researching over consulting staff. Very limited knowledge of adoption processes, care requirements, and realistic expectations. Needs guidance.
Patrick: Experienced Owner
Has cared for dogs before but is learning about a new breed. Busy and doesn't have time for deep research. Knows what he wants but lacks breed-specific knowledge. Needs depth when he wants it, without friction.
Design Implications
Research Findings translated into 10 prioritized feature recommendations
The goal of the proposed tool — working title "DogMatch" — is to help users find a more compatible dog while building the knowledge needed to care for it long-term. Each feature was grounded directly in research data, not assumption.
- Refined Search (Filters): Support filtering by breed, size, age, distance, temperament, and medical status. Participants who couldn't find filters resorted to keyword searches — with worse results.
- Personal Dog Biography: Medical history, ownership background, behavioral quirks, and age. Participants wanted to know the full picture of a dog before moving forward, not just its photo and breed.
- Photos and Videos: The highest-rated feature across both experienced and inexperienced users. Video in particular shifted participant affect from browsing to genuine connection.
- Personalized Expense Report Generator: Inexperienced owners severely underestimated ownership costs. Using data from experienced owners, the tool would generate realistic cost projections.
- Dog Breed Database: Most experienced owners only knew the breeds they'd personally owned. A comprehensive, searchable breed reference addresses knowledge gaps for all user types.
- Adoption Finder on Map: Distance was a top concern. A proximity-based map view of available dogs directly addresses the discovery pain point of not knowing what's nearby.
- Informative Articles: Knowledge gaps on care, adoption processes, and expenses were consistent across inexperienced users. Articles provide a scalable, low-friction education layer.
Statistical Findings
Hypothesis testing surfaced one significant finding that directly informed feature prioritization
Three hypotheses were tested via Mann-Whitney U tests comparing experienced owners (n=19) and inexperienced prospective owners (n=10).
Inexperienced owners rate breed as more important
A significant difference was found (p = .008). Inexperienced owners place higher weight on breed during their search — reinforcing the need for strong breed education and recommendation tools targeted at first-timers.
Prior research doesn't predict ownership satisfaction
No significant link was found between pre-adoption research and positive ownership experience (p = .36) — suggesting that what information people access matters more than whether they researched at all.
Both groups value temperament equally
No significant difference in temperament ratings (p = .36). Both experienced and inexperienced users care about temperament — making it a universal field to surface in both search and breed profiles.
Quality of information beats quantity
Taken together, the hypotheses point to a consistent design implication: the tool's value lies in surfacing the right information at the right moment, not just delivering more content to research-oriented users.
Limitations & Future Work
What this study couldn't answer and where the research should go next
- Small, homogeneous samples. Observation (n=7) and interview (n=5) participants were predominantly Chicago-area, full-time students, ages 22–28. Findings should be validated across more diverse demographics before informing production decisions.
- Single-session observation. Real-world dog searching spans multiple sessions and is influenced by offline factors (shelter visits, conversations with friends). The study captured a snapshot, not the full journey.
- Missing the relinquishment perspective The survey captured why people want dogs and how they search — but didn't include owners who had previously surrendered a pet. That voice would have directly validated whether the proposed tool addresses the root cause.
- Future opportunity: disability and special needs adoption. Whether participants would consider adopting a disabled dog was never explored — a topic that could meaningfully expand the tool's scope and impact.
Thank you for reading!
Contents
don't be a stranger!
Let's collaborate and create something amazing!