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My objective was to use the power of research to explore practical solutions for enhancing the success of pet adoptions.
Fueled by my love for animals and a desire to strengthen my research and design skills, I set out to acquire meaningful insights into why this overwhelming surge of pet returns was happening, and deploy the power of research to develop a solution that might strengthen future pet adoptions.
To gather valuable insights into the adoption process and the associated problem, I conducted interviews with three distinct groups: pet adopters, pet buyers from breeders, and shelter employees.
Participant Sourcing:
Interview Methods:
Total Interviews Conducted: 32 participants
I gathered qualitative data from my research, leading me to discover common patterns and themes in the following insights.
• Payoff: Adoption was often chosen for the emotional connection it provides, while buying was favored for meeting specific preferences.
• Availability: Respondents leaned towards adoption when accessible, while buying was preferred for rare or desired breeds.
• Lifestyle: Many participants saw adoption as a suitable choice for mature and low-maintenance pets, whereas buying was considered for customization of preferences.
• Financial: A significant number of interviewees mentioned opting for adoption due to its affordability, while buying was seen as a means to acquire pets with specific traits or breeds
According to 5 shelter employees, behavioral problems, financial constraints, and personal circumstances are the most common reasons for pet returns post-pandemic.
The following pain points were consistently observed during interviews.
Developing a tool that assists adopters in making informed decisions and provides curated resources will empower users to create better connections with pets, while also assisting adoption shelters in more effectively vetting potential pet parents.
To gain insights into the competitive landscape and assess how other applications tackle similar challenges, I conducted an evaluation of comparable solutions.
This process encompassed a review of their features, accessibility to user goals, and the presence of functionalities that aligned with the research-backed goals for my solution.
The two most similar solutions in this case were PetFinder and Petdar.
I created a visual map for a high-level view of the solution, with a focus on seamless navigation and user-friendly access to key goals.
I created a wireframe prototype of the solution and gathered qualitative feedback from a group of 13 participants selected from my research pool. Observing them interact with a low-fidelity prototype, I aimed to uncover pain points, address usability concerns, and mitigate potential bias from a design system.
Participants engaged in a range of tasks:
After this testing session, I gained valuable insights into iterations to be made to improve the solution.
The survey was enhanced by adding a progress bar and separate screens for a clearer sense of completion, enabling multiple-choice questions, and addressing personalization gaps with relevant user questions.
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The Search Filter was improved to reduce cognitive overload by isolating the overlay and adding customization for breed searches, characteristics, special needs, and house-trained pets for a more tailored search experience.
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The Matching System was refined to simplify the user interface by focusing on essential information. Redundant features like image and location/favorite functions were removed, streamlining the user experience.
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The Social Poll module was enhanced by improving information hierarchy, introducing intuitive thumbnails, reducing user steps, and enabling seamless profile connections for effortless social sharing.
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I made donating more user-friendly by simplifying custom amount entry, enabling card-saving for future donations, providing a clear payment review, and ensuring users receive emailed receipts.
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All screens were designed using a 4-point grid system to ensure consistency, alignment, and balance. In the case of development, this methodology reduces errors.
The initial research interviews revealed that 51.85% (14 out of 27) pet seekers felt overwhelmed by the abundance of available pets.
By harnessing the onboarding process to curate a personalized selection of pets tailored to the user's needs, drawn from compatibility assessments provided by shelter volunteers, the solution mitigates this overwhelming experience and increases the likelihood of a successful adoption.
66.67% (18 out of 27) pet seekers I had interviewed confirmed consulting friends and family during their decision-making process, emphasizing the importance of involving loved ones in pet adoption choices.
With a personalized poll creation tool, users can build customized surveys for two or more pets from their favorites list, enabling them to gather feedback from loved ones and share it through social media or links.
To better cater to pet seekers and their unique needs, I introduced a compatibility feature that takes into account the information provided in users' onboarding surveys and the specific traits of the pets available.
Moreover, I've added an inquiry box beneath the chart to encourage direct communication between pet seekers and shelters, enhancing their access to essential pet information.
81.48% (22 out of 27) pet seekers started their search by researching specific breeds online, through friends, or other sources.
To address this, I introduced a feature that provides information on various breeds, detailing their characteristics and care requirements.
This enables those interested in a particular breed to conveniently locate a nearby pet using the breed locator.
Usability testing revealed that users wanted a way to save and revisit pets they were interested in.
A "favorites list" empowers users to create a personalized collection, making it easy to revisit potential matches and preferred shelters.
85.19% (23 out of 27) pet seekers were interested in supporting shelters even if they couldn't adopt a pet.
The donation module was incorporated to fulfill this desire, offering payment storage and emailed tax receipts for convenient contributions.
I integrated curated pet and breed lists designed to cater to specific needs identified in the onboarding survey, such as child-friendly and hypoallergenic pets, in line with the app's primary mission of enhancing pet-user compatibility.
44.44% (12 out of 27) pet seekers had very specific criteria for their ideal pet. Advanced filtering features were implemented to cater to these needs and deliver highly personalized results.
Please note that this prototype is specifically optimized for desktop use, and it may not provide an optimal experience when accessed via mobile phones.
