Designing dog park experience through transparent profiles, check-ins, and community features
Designing dog park experience through transparent profiles, check-ins, and community features
Unleash the fun! Meet pups and pals in your neighborhood.
Unleash the fun! Meet pups and pals in your neighborhood.
Unleash the fun! Meet pups and pals in your neighborhood.
TL;DR
[Type]
Part-time, Early Startup
[My Role]
Lead Product Designer
[Timeline]
May 24 - April 25
[Team]
Founder, PM & Myself
[Team]
Founder, PM, Developers
Context
The founder (a Stanford alum) came with one goal: make dog parks feel safer. With no product yet, my role was to shape the vision from scratch and turn vague pain points into a clear, user-centered experience.
The Outcome
I designed Dogamigos, a mobile app built around three interconnected systems:
→ Detailed dog profiles (Deep-dive in this case study)
→ Real-time park data
→ A local support network
Navigation: High-Fidelity Prototype
The Impact
✅ 90% said they’d feel more confident visiting a park with this app
✅ 100% preferred having layered info over auto-matching
✅ 4.6 / 5 average clarity rating for profile transparency
The walk in the shoes of a dog owner
Instead of a kickoff call, the founder took me to a Palo Alto dog park and said, “Just observe.” I didn’t own a dog, but it was easy to see the tension:
Anxious dog-parents constantly scanning the park, ready to leave quickly if needed
Fights breaking out due to mismatched energy levels
Hesitance to approach dogs due to unclear vaccination status
Fig. Dog fight breaking out at the dog park
Fig. Dog fight breaking out at the dog park
Starting with observation helped me ask sharper questions, validate assumptions with data, and root the design in real user behavior.
I shadowed dog owners, conducted 40+ interviews, and visited four Bay Area parks to document behaviors, triggers, and patterns.
Key Pain Points:
Safety Gaps
1. Safety Gaps
"Last week, a pit bull attacked my dog. Now I’m scared to go back."
"Last week, a pit bull attacked my dog. Now I’m scared to go back."
Emily, dog mom to a terrier
Emily, dog mom to a terrier
70% witnessed aggressive incidents.
No way to check vaccination status or park hazards.
Social Awkwardness
2. Social Awkwardness
"I’d love to meet other owners, but I’m not giving my number to strangers."
"I’d love to meet other owners, but I’m not giving my number to strangers."
Jason, first-time dog owner
Jason, first-time dog owner
40% felt embarrassed by their dog’s behavior.
65% wanted local dog friends but lacked a safe platform.
Lack of Real-Time Info
3. Lack of Real-Time Info
"I don’t know if other dogs are vaccinated. Mine got kennel cough last month."
"I don’t know if other dogs are vaccinated. Mine got kennel cough last month."
Rina, rescue dog parent
Rina, rescue dog parent
50% avoided parks due to unreliable Google Maps data.
Not knowing what dogs are there at the park at their time of visit
These recurring themes of safety, social hesitation, and information gaps made one thing clear: dog parks were failing due to a lack of context and confidence. They needed clarity, control, and community.
How might we design for confidence by giving owners the right context before, during, and after a park visit?
After card sorting and testing with 5 users and the internal team, I distilled the product into three core systems:
Dog Profiles: nuanced, layered, and scannable for compatibility
Community Feed: structured to foster trust, not just engagement
Real-Time Park Awareness: contextual, privacy-first, and owner-led
I mapped the full user journey and translated it into five key low-fidelity wireframes to align on product scope and engineering constraints.
User creates
profile
User creates
profile
Checks park
updates
Checks park
updates
Visits park with
confidence
Visits park with
confidence
Posts back to
community
Posts back to
community
→
→
→
→
→
→
Fig. User Journey / Flow
Fig. Low Fidelity Wireframes
Deep Dive: Designing Detailed Profiles
Exploring risks and tradeoffs with stakeholders
When our PM suggested auto-matching based on breed and energy, I raised a concern: what if users relied on it and their dogs still fought?
This Slack exchange shows how I navigated the discussion, proposing we test both approaches instead of making assumptions.
When our PM suggested auto-matching based on breed and energy, I raised a concern: what if users relied on it and their dogs still fought?
This Slack exchange shows how I navigated the discussion, proposing we test both approaches instead of making assumptions.
40
40
Canvas
Canvas
Today, July 25th
Today, July 25th
Sam (PM)
Sam (PM)
2:43 PM
2:43 PM
Was thinking … could we prioritize auto-matching next? Suggesting 'Your dog might get along with [X]' with a % match score based on breed/size/energy.
Was thinking … could we prioritize auto-matching next? Suggesting 'Your dog might get along with [X]' with a % match score based on breed/size/energy.
Me (Designer)
Me (Designer)
2:43 PM
2:43 PM
Interesting! But what if our algorithm suggests a 'good match' and the dogs don’t get along? Could make us liable. Maybe we test two versions - one with scores, one just showing info so user can make their own decision?
Interesting! But what if our algorithm suggests a 'good match' and the dogs don’t get along? Could make us liable. Maybe we test two versions - one with scores, one just showing info so user can make their own decision?
Guru (Founder)
Guru (Founder)
2:43 PM
2:43 PM
That’s right. We shouldn’t overpromise safety. Let’s see both approaches.
That’s right. We shouldn’t overpromise safety. Let’s see both approaches.
1
1
😬
😬
Sam (PM)
Sam (PM)
2:43 PM
2:43 PM
Can you show both versions? Let's test it.
Can you show both versions? Let's test it.
Me (Designer)
Me (Designer)
2:43 PM
2:43 PM
Cool, I’ll mock up both by EOD. One with matches and one transparency-focused. I can run a A/B usability test this week so we can move quickly.
Cool, I’ll mock up both by EOD. One with matches and one transparency-focused. I can run a A/B usability test this week so we can move quickly.
2
2
👍
👍
Message
Message
Fig. Stakeholder Conversation: Slack Thread Exploring Risks and Tradeoffs of Auto-Matching Feature
Fig. Stakeholder Conversation: Slack Thread Exploring Risks and Tradeoffs of Auto-Matching Feature
❌ Version 1: Algorithmic matching (did not ship)
❌ Version 1: Algorithmic matching (did not ship)
I designed profile for quick discovery and connection to build familiarity and spark engagement.
The compatibility score was intended to simplify decision-making by showing a quick match based on breed, age, and size. It aimed to reduce effort and nudge users toward likely playmates combined with recent posts and general info.
24
24
Amigos
Amigos
POSTS
POSTS
Milo & Ash
Milo & Ash
Hello everyone, Me and my Milo are looking for some friends and would love to get to know you all 👋🐶
Hello everyone, Me and my Milo are looking for some friends and would love to get to know you all 👋🐶
Milo & Ash
Milo & Ash
Golden Retriever
Golden Retriever
Adult Male
Adult Male
3 y/o
3 y/o
+ Add Post
+ Add Post
Edit Profile
Edit Profile
223
223
Amigos
Amigos
POSTS
POSTS
Mishu & Ron
Mishu & Ron
Playing at @Watson’s Dog Park. 5 mins ago
Playing at @Watson’s Dog Park. 5 mins ago
Mishu met some new dogs at the park today
Mishu met some new dogs at the park today
Mishu & Ron
Mishu & Ron
Playing at @Watson’s Dog Park. 7 July
Playing at @Watson’s Dog Park. 7 July
Guess our favourite season?
Guess our favourite season?
Mishu & Ron
Mishu & Ron
85% Match
85% Match
Poodle
Poodle
Puppy Female
Puppy Female
8 months
8 months
+ Add Amigo
+ Add Amigo
Message
Message
My Profile
My Profile
DOg’s Profile
DOg’s Profile
Crucial but minimal dog info
Crucial but minimal dog info
show both dog owner and dog to reflect a shared journey
show both dog owner and dog to reflect a shared journey
Quick
connect actions
Quick
connect actions
Match % to show compatibility
Match % to show compatibility
build trust through shared experiences
build trust through shared experiences
posts to connect and enagage
posts to connect and enagage
Fig. UI Screenshot: V1 Prototype Showing Dog-Owner Profiles, Match Score, and Community Posts for Quick Discovery
Fig. UI Screenshot: V1 Prototype Showing Dog-Owner Profiles, Match Score, and Community Posts for Quick Discovery
Despite a simple and lightweight design, this version introduced more uncertainty than confidence.
Despite a simple and lightweight design, this version introduced more uncertainty than confidence.
❌ V1 Usability Findings
❌ V1 Usability Findings
⚠️ Privacy concerns - 60% felt uncomfortable with public location visibility
⚠️ False confidence - 50% assumed the match score meant guaranteed compatibility
⚠️ Liability Issues: 4 users flagged legal/safety concerns from inaccurate matches
The Pivot: Empower human judgment through better information architecture
Version 2: Transparent Profiles
Version 2: Transparent Profiles
Every dog has unique needs, some are shy, some hyper, some reactive to certain breeds. Owners needed a way to communicate these nuances upfront.
Design decision: In V2, I removed the match score and added layered personality, energy, health, and warning tags visible only after a mutual connection for privacy.
Fig. UI Screenshot: V2 Profile Designed for Transparency and Informed Choice with Layered, Consent-Based Dog-Owner Info
Even though it was slower than auto-matching, it was safer and more human so it worked.
Even though it was slower than auto-matching, it was safer and more human so it worked.
V2 Usability Impact
V2 Usability Impact
✅ Increased confidence: 90% felt safer before arriving at the park
✅ Improved trust: 100% preferred detailed info over match scores
✅ Higher clarity: 4.6 / 5 avg. clarity rating for profile transparency
Supporting Flows That Built a Cohesive Experience
Real-Time Park Map
I designed an interactive map showing live dog check-ins, park features, and community-submitted alerts built with privacy in mind and gentle location-based nudges to encourage participation.
✅ Impact: Helped users plan visits more confidently. Boosted check-in intent during testing.
EXPLORE PAGE
EXPLORE PAGE
DOG PARKS PAGE
DOG PARKS PAGE
Explore
Explore
Neighbourhood
Neighbourhood
Checked In
Checked In
Separate Dog Areas
Separate Dog Areas
Events
Events
Private Dog Parks
Private Dog Parks
Del Monte Park
Del Monte Park
(24)
(24)
118 St James San Jose. 2.1 miles
118 St James San Jose. 2.1 miles
4 Pups
4 Pups
Open. Closes 10 PM
Open. Closes 10 PM
Check-In
Check-In
Navigate
Navigate
Watson’s Dog Park
Watson’s Dog Park
(34)
(34)
Search for Dog Parks
Search for Dog Parks
Home
Home
Create
Create
Explore
Explore
24 photos
24 photos
Del Monte Park
Del Monte Park
(24 Reviews)
(24 Reviews)
118 St James San Jose. 2.1 miles
118 St James San Jose. 2.1 miles
Open. Closes 10 PM
Open. Closes 10 PM
Check-In
Check-In
Navigate
Navigate
Description
Description
Del Monte Dog Park is a spacious, fenced-in park with separate areas for small and large dogs.
Del Monte Dog Park is a spacious, fenced-in park with separate areas for small and large dogs.
Pups Playing in the Park (4)
Pups Playing in the Park (4)
Features
Features
Benches
Benches
Waste Station
Waste Station
Large Dog Separate Area
Large Dog Separate Area
Agility Equipment
Agility Equipment
Water Fountain
Water Fountain
Small Dog Separate Area
Small Dog Separate Area
9:41
9:41
Find parks with check-ins, events, or separate areas
Find parks with check-ins, events, or separate areas
Shows live-activity without exposing owners
Shows live-activity without exposing owners
Simple CTA to boost participation
Simple CTA to boost participation
Helps users pick parks that fit their dog’s needs
Helps users pick parks that fit their dog’s needs
Community Social Feed
Structured, purpose-driven posts (e.g., park tips, alerts, reviews), inspired by Nextdoor. Smart defaults guided users toward valuable content.
✅ Impact: 70% of users engaged in session one. Shifted tone from passive social to trust-driven local support.
Visual & Systems Design Decisions
I built a calming, nature-inspired interface using structured layouts and reusable tokens. Tag systems and visual clarity guided behavior and scaled easily across screens.
Impact:
✅ Reduced decision fatigue in testing
✅ Enabled faster dev implementation
✅ Reinforced emotional safety
Key Learnings
1️⃣ Learned to translate emotional tension into tangible product systems
2️⃣ Balanced user safety with business liability through evidence-backed decisions
3️⃣ Facilitated tough tradeoff conversations with founders and PMs
Thank you for reading.
[Next Project]
Designed the dog park experience through trust-based profiles, real-time check-ins, and local community features.
Design trade-offs
Deep-dive for 1 feature
Experimentation & Testing
View Full Case Study
The walk in the shoes of a dog owner
Instead of a kickoff call, the founder took me to a Palo Alto dog park and said, “Just observe.” I didn’t own a dog, but it was easy to see the tension:
Anxious dog-parents constantly scanning the park, ready to leave quickly if needed
Fights breaking out due to mismatched energy levels
Hesitance to approach dogs due to unclear vaccination status
Fig. Dog fight breaking out at the dog park
Starting with observation helped me ask sharper questions, validate assumptions with data, and root the design in real user behavior.
I shadowed dog owners, conducted 40+ interviews, and visited four Bay Area parks to document behaviors, triggers, and patterns.
Key Pain Points:
1. Safety Gaps
"Last week, a pit bull attacked my terrier. Now I’m scared to go back."
Dog Owner A
70% witnessed aggressive incidents.
No way to check vaccination status or park hazards.
2. Social Awkwardness
"I’d love to meet other owners, but I’m not giving my number to strangers."
Dog Owner C
40% felt embarrassed by their dog’s behavior.
65% wanted local dog friends but lacked a safe platform.
3. Lack of Real-Time Info
"I don’t know if other dogs are vaccinated. Mine got kennel cough last month."
Dog Owner B
50% avoided parks due to unreliable Google Maps data.
Not knowing what dogs are there at the park at their time of visit
These recurring themes of safety, social hesitation, and information gaps made one thing clear: dog parks were failing due to a lack of context and confidence. Owners didn’t need more content. They needed clarity, control, and community.
How might we design for confidence by giving owners the right context before, during, and after a park visit?
After card sorting and testing with 5 users and the internal team, I distilled the product into three core systems:
Dog Profiles: nuanced, layered, and scannable for compatibility
Community Feed: structured to foster trust, not just engagement
Real-Time Park Awareness: contextual, privacy-first, and owner-led
I mapped the full user journey and translated it into five key low-fidelity wireframes to align on product scope and engineering constraints.
User creates
profile
Checks park
updates
Visits park with
confidence
Posts back to
community
→
→
→
Fig. User Journey / Flow
Fig. Low Fidelity Wireframes
Deep Dive: Designing Detailed Profiles
Exploring risks and tradeoffs with stakeholders
When our PM suggested auto-matching based on breed and energy, I raised a concern: what if users relied on it and their dogs still fought?
This Slack exchange shows how I navigated the discussion, proposing we test both approaches instead of making assumptions.
40
Canvas
Today, July 25th
Sam (PM)
2:43 PM
Was thinking … could we prioritize auto-matching next? Suggesting 'Your dog might get along with [X]' with a % match score based on breed/size/energy.
Me (Designer)
2:43 PM
Interesting! But what if our algorithm suggests a 'good match' and the dogs don’t get along? Could make us liable. Maybe we test two versions - one with scores, one just showing info so user can make their own decision?
Guru (Founder)
2:43 PM
That’s right. We shouldn’t overpromise safety. Let’s see both approaches.
1
😬
Sam (PM)
2:43 PM
Can you show both versions? Let's test it.
Me (Designer)
2:43 PM
Cool, I’ll mock up both by EOD. One with matches and one transparency-focused. I can run a A/B usability test this week so we can move quickly.
2
👍
Message
Fig. Stakeholder Conversation: Slack Thread Exploring Risks and Tradeoffs of Auto-Matching Feature
❌ Version 1: Algorithmic matching (did not ship)
I designed profile for quick discovery and connection to build familiarity and spark engagement.
The compatibility score was intended to simplify decision-making by showing a quick match based on breed, age, and size. It aimed to reduce effort and nudge users toward likely playmates combined with recent posts and general info.
24
Amigos
POSTS
Milo & Ash
Hello everyone, Me and my Milo are looking for some friends and would love to get to know you all 👋🐶
Milo & Ash
Golden Retriever
Adult Male
3 y/o
+ Add Post
Edit Profile
223
Amigos
POSTS
Mishu & Ron
Playing at @Watson’s Dog Park. 5 mins ago
Mishu met some new dogs at the park today
Mishu & Ron
Playing at @Watson’s Dog Park. 7 July
Guess our favourite season?
Mishu & Ron
85% Match
Poodle
Puppy Female
8 months
+ Add Amigo
Message
My Profile
DOg’s Profile
Crucial but minimal dog info
show both dog owner and dog to reflect a shared journey
Quick
connect actions
Match % to show compatibility
build trust through shared experiences
posts to connect and enagage
Fig. UI Screenshot: V1 Prototype Showing Dog-Owner Profiles, Match Score, and Community Posts for Quick Discovery
Despite a simple and lightweight design, this version introduced more uncertainty than confidence.
❌ V1 Usability Findings
⚠️ Privacy concerns - 60% felt uncomfortable with public location visibility
⚠️ False confidence - 50% assumed the match score meant guaranteed compatibility
⚠️ Liability Issues: 4 users flagged legal/safety concerns from inaccurate matches
The Pivot: Empower human judgment through better information architecture
Version 2: Transparent Profiles
Every dog has unique needs, some are shy, some hyper, some reactive to certain breeds. Owners needed a way to communicate these nuances upfront.
Design decision: In V2, I removed the match score and added layered personality, energy, health, and warning tags visible only after a mutual connection for privacy.
Fig. UI Screenshot: V2 Profile Designed for Transparency and Informed Choice with Layered, Consent-Based Dog-Owner Info
Even though it was slower than auto-matching, it was safer and more human so it worked.
V2 Usability Impact
✅ Increased confidence: 90% felt safer before arriving at the park
✅ Improved trust: 100% preferred detailed info over match scores
✅ Higher clarity: 4.6 / 5 avg. clarity rating for profile transparency
Supporting Flows That Built a Cohesive Experience
Real-Time Park Map
I designed an interactive map showing live dog check-ins, park features, and community-submitted alerts built with privacy in mind and gentle location-based nudges to encourage participation.
✅ Impact: Helped users plan visits more confidently. Boosted check-in intent during testing.
EXPLORE PAGE
DOG PARKS PAGE
Explore
Neighbourhood
Checked In
Separate Dog Areas
Events
Private Dog Parks
Del Monte Park
(24)
118 St James San Jose. 2.1 miles
4 Pups
Open. Closes 10 PM
Check-In
Navigate
Watson’s Dog Park
(34)
Search for Dog Parks
Home
Create
Explore
24 photos
Del Monte Park
(24 Reviews)
118 St James San Jose. 2.1 miles
Open. Closes 10 PM
Check-In
Navigate
Description
Del Monte Dog Park is a spacious, fenced-in park with separate areas for small and large dogs.
Pups Playing in the Park (4)
Features
Benches
Waste Station
Large Dog Separate Area
Agility Equipment
Water Fountain
Small Dog Separate Area
9:41
Find parks with check-ins, events, or separate areas
Shows live-activity without exposing owners
Simple CTA to boost participation
Helps users pick parks that fit their dog’s needs
Community Social Feed
Structured, purpose-driven posts (e.g., park tips, alerts, reviews), inspired by Nextdoor. Smart defaults guided users toward valuable content.
✅ Impact: 70% of users engaged in session one. Shifted tone from passive social to trust-driven local support.
Visual & Systems Design Decisions
I built a calming, nature-inspired interface using structured layouts and reusable tokens. Tag systems and visual clarity guided behavior and scaled easily across screens.
Impact:
✅ Reduced decision fatigue in testing
✅ Enabled faster dev implementation
✅ Reinforced emotional safety
1️⃣ Learned to translate emotional tension into tangible product systems
2️⃣ Balanced user safety with business liability through evidence-backed decisions
3️⃣ Facilitated tough tradeoff conversations with founders and PMs
Key Learnings
[Next Project]
Designed the dog park experience through trust-based profiles, real-time check-ins, and local community features.
Design trade-offs
Deep-dive for 1 feature
Experimentation & Testing
View Full Case Study