DearPaw – From Concept to Trusted Pet Care AI
Product discovery, UX research, and 0-to-1 experience design for an AI-powered pet care app, from research and personas through prototyping and MVP.
ℹ This case study focuses on the product discovery, UX process, and experience design decisions that shaped DearPaw app from concept to MVP.
Overview
Pet owners face a persistent challenge: caring for their pets between veterinary visits. The internet offers endless advice, but it's generic, contradictory, and often unreliable. As CEO and Product Lead at DearPaw, I set out to create an AI-driven wellness coach that delivers personalized, science-backed guidance pet owners can trust.
The Challenge
Through initial market research, I identified a critical gap in the pet care ecosystem. Pet parents are left anxious about whether they're doing enough, unsure if behavioral changes are normal, and uncertain when to seek professional help. Existing solutions offer either expensive veterinary consultations or unreliable internet advice with no middle ground.
The core question became:
How might we empower pet owners with trustworthy, personalized health guidance that bridges the gap between daily care and veterinary visits?
Research & Discovery
I led a comprehensive research initiative to deeply understand both the market landscape and user needs:
- In-depth interviews with 15+ pet owners exploring care routines, pain points, and decision-making processes
- Social media analysis of pet owner communities to understand authentic language and concerns across Reddit
- Competitive analysis of existing pet care apps, veterinary platforms, and wellness tools, and semantic analysis of their reviews
Key Insights
"1. Trust is non-negotiable Pet owners are deeply protective of their pets' wellbeing. Any health-related product must earn trust through transparency, expertise, and proven reliability. One participant told us: "I wouldn't trust just any app with my dog's health. I need to know where the information comes from."
"2. One-size-fits-all doesn't work A senior Labrador with joint issues has entirely different needs than a young Bengal cat. Generic advice feels unhelpful at best and potentially harmful at worst. Personalization isn't a feature, it's a fundamental requirement.
"3. Engagement requires emotional resonance Pet care is fundamentally an emotional domain. Success means celebrating milestones, acknowledging concerns, and supporting the human-animal bond without being manipulative.
Empathize with Users
To deeply understand our target audience, I led a comprehensive user research effort that resulted in three distinct personas representing our core user segments. Each persona was developed through synthesis of interview data, behavioral patterns, and stated needs.
User Personas
Lucas Müller, 35 — The Optimization-Focused Pet Parent
"I want to ensure my cats eat well and stay healthy—no compromises."
Context: Software Developer in Berlin with 2 Siamese cats | High tech comfort
Goals: Optimize diet based on allergies, prevent health issues through data, access reliable nutrition information
Challenges: Needs personalized vs. generic advice, time-consuming multi-pet management, complex ingredient labels
Key Needs: Health tracking, personalized nutrition/activity suggestions, preventive care reminders
Mia Chen, 27 — The Learning-Oriented First-Time Owner
"I want to do things right for my cat, but I need clear and simple guidance."
Context: Marketing Specialist in Shanghai with 1 British Shorthair (new adoption) | Moderate tech comfort
Goals: Learn proper care practices, establish daily routines, ensure cat health and engagement
Challenges: Unclear best practices, limited wellness knowledge, overwhelmed by inconsistent online advice
Key Needs: Simple tracking tools, routine reminders, step-by-step guidance for learning
Sara Cooper, 32 — The Time-Constrained Professional
"I love my dog, but I don't have time for complex care routines."
Context: Management Consultant in New York with 1 Toy Poodle | High tech comfort, automation preference
Goals: Efficiently manage care despite busy schedule, ensure pet wellness when away, minimize manual tracking
Challenges: Unpredictable work hours, guilt about limited quality time, needs automated solutions
Key Needs: Automated reminders, low-effort input methods, behavior insights to optimize care
Empathy Mapping & Journey Mapping
To deepen team understanding of user perspectives, I facilitated collaborative workshops where we mapped user thoughts, feelings, pain points, and behaviors across the pet care journey. These sessions helped align the team around user needs and identified critical moments where DearPaw could deliver value.
Synthesis: Product Direction
Product north star: Build a preventive pet-care companion that pet owners trust, because guidance is personalized, evidence-based, and clearly explained.
What we decided
- Personalization is the core value, not a nice-to-have. Generic tips fail because pet needs vary dramatically by breed, age, health status, and lifestyle.
- Trust must be earned in every interaction. Health guidance requires clear sourcing, transparent reasoning, and the right professional signals.
- Engagement should feel meaningful. Progress comes from small wins, steady routines, and emotional reassurance without manipulation.
Design Principles
Used to guide and evaluate every feature
- Personalization over generic advice
- Science + transparency to build trust
- Progress that feels tangible
- Warmth balanced with professionalism
- Emotional connection through personalized interactions
MVP pillars
These strategic insights shaped our MVP pillars.
Personalized Guidance Engine
Recommendations grounded in the pet profile and evolving habits, always with “why this matters” context.
Credible Knowledge Layer
Research-backed content with citations, veterinary input, and clear confidence/limitations.
Onboarding that proves value fast
A short, conversational flow that delivers the first useful insight within minutes and sets expectations for how the AI works.
Relationship-building moments
Name-based interactions and milestone celebrations that reinforce care routines and reduce anxiety.
Bridge to execution
With the direction and principles set, we moved into Design & Execution to translate these pillars into information architecture, critical user flows, and testable prototypes.
Design & Execution
Information Architecture
I organized features around the user's mental model of pet care: wellness overview, symptom tracking, Chat-based guidance, pet insights library, and profile management. The structure needed to feel intuitive from day one while supporting future feature expansion.
Wireframe: Key User Flows
I focused design efforts on three flows that would make or break the experience:
1. Onboarding & Pet Profile Creation
This flow establishes trust, gathers essential data, and delivers immediate personalized value. Rather than a lengthy form, I designed a conversational multi-step process that feels natural and builds connection.
Key design decisions:
- Progressive disclosure: Start with basics, gather details over time
- Immediate feedback: Show how each answer enables better recommendations
- Value delivery: Provide first personalized insight within 3 minutes
2. Unified User Flow: From Concern to Confident Care
The Complete Journey:
- Pet owner notices an issue — Whether it's unusual scratching, eating changes, or behavioral shifts, the owner opens DearPaw with a concern.
- Conversational guidance through AI chat — They describe the issue to DearPaw's AI agent, which asks clarifying questions and provides personalized, science-backed guidance on what to watch for and potential next steps.
- Seamless transition to tracking — The AI suggests monitoring the issue and offers to add it to their Watchlist with one tap. The owner can then log observations effortlessly through smart prompts and minimal-friction inputs.
- Continuous monitoring with insights — As the owner tracks symptoms, behaviors, or measurements over time, DearPaw identifies patterns and provides ongoing reassurance or flags when professional help may be needed.
- Vet-ready export when needed — If the owner decides to visit the vet, DearPaw generates a detailed timeline report with all observations, making the consultation more productive and informed.
The outcome: Pet owners stay assured, proactive, and focused on enjoying life with their pet — knowing DearPaw is their intelligent care partner bridging daily wellness and professional veterinary care.
This unified flow transforms the two features into a cohesive care journey that addresses the core user need: reducing anxiety through actionable guidance and structured tracking.
Prototype & Validation
Given limited time and resources, we took an innovative approach that accelerated development while maintaining design quality. I started with low-fidelity wireframes and detailed feature specs, then moved directly to vibe coding / coded prototypes to validate functionality and interactions quickly. This allowed us to test real user flows rather than simulated ones.
After establishing core functionality, I imported the coded screens back into Figma to refine visual design and build a scalable design system. This reverse workflow proved efficient: technical constraints informed design decisions early, reducing rework.
Early Testing Insights:
- At first use, the app feels empty—the experience improves only after users start accumulating data.
- Navigation between chat and watchlist lacks clarity.
- The visual tone feels too clinical rather than warm and approachable.
This approach let us move from concept to working prototype in 4 months, positioning us to launch MVP with a functional, validated product.
Iteration & Implementation
Working within startup constraints, we adopted agile development with rapid iteration cycles. The product is in active development, with core features implemented and undergoing continuous refinement.
Technical Approach:
- AI agent for recommendation logic
- Generative AI for personalized content
- Privacy-first security architecture with GDPR compliance
After alpha testing, we iterated several times before moving into MVP development. The product is currently at v1.1 build with beta testing underway.
Impact & Outcomes
While DearPaw is still in early stages, the foundation has been validated through research and testing. The design system provides a scalable foundation, and strategic partnerships with veterinary clinics are being explored.
Target Metrics
User Engagement
- Daily active usage
- Tracking consistency
- Feature adoption
Business Impact
- Conversion to premium
- Retention rates
- Net Promoter Score
Vision for Impact
- For Users: Empower pet parents with personalized guidance that reduces anxiety and supports proactive care
- For Business: Establish DearPaw as the trusted AI wellness coach in pet care with defensible data advantages
Key Learnings
Trust must be designed into every interaction: In health-related products, trust cannot be an afterthought. From content sources to data handling to UX transparency, every design decision either builds or erodes trust.
Personalization requires careful balance: AI-driven personalization is powerful, but users need to understand and control how it works. Avoiding "black box" experiences requires thoughtful design of explainability and user agency.
Onboarding determines success: First experiences must deliver clear, immediate value while setting expectations for long-term engagement. A weak onboarding undermines everything that follows.
Emotional design requires restraint: Pet care is deeply emotional, and design must acknowledge this. But there's a fine line between emotional resonance and manipulation that must be carefully navigated.
Next Steps
The roadmap ahead includes:
- Complete core MVP and launch beta testing program
- Expand AI capabilities based on usage data and user feedback
- Develop community features for peer support
- Build B2B platform for veterinary clinic partnerships
- Explore international market opportunities
Tools & Methods
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