User Research
Conducted interviews and surveys with pet owners, shelter employees, as well as online research.
Areas of focus for research:
Field Research
Visited 3 facilities to observe the adoption process.
Tools used to conduct research:
Exploring Analogous Solutions
Conducted market research on existing products and systems
How do other markets solve these problems?
UX Design and Prototyping
After brainstorming ideas I started sketching, prototyping, and collecting feedback.
Tools and mediums used:
Visual design Comps
Final development of the visual identity, feel, and consumer experience.
Tools and mediums used:
"Never know how you will mesh until you meet In person"
"The temperament of a dog being much different than the picture"
"I found a puppy in the market, it had lots of bugs"
"Dogs also behave so differently at home then in a shelter"
"Coming home with a new dog for the first time and not knowing what to do was a bit intimidating."
"Visiting the puppies for the first time was a highlight"
"You can buy one or adopt, it's pretty easy."
"I worried that this breeder was not legit"
"My friend give me as gift, I think adoption is similar to America"
"I would socialize them with humans and other pets much more in the first several months"
"We went to some dog shows, talked to the breeders and looked up on internet."
"We have no such laws for pets, just need money
"My boyfriend checked the rescue for 3-4 mo and decided to find a breeder on craigslist"
"...Much like a wand choosing a wizard a cat chooses an owner!"
"I found a breeder through Craigslist and contacted the breeder."
Many pet owners felt that they knew which animal was the right match yet ended up being overwhelmed with the care and training required.
60% or 9/15 did not use apps or sites to locate their pets.
53% said they wouldn’t change anything about the process.
Most people don’t ask what dogs they should have, rescues say they want to find the right adapter, but they really don’t have the time.
Pet chip might be able to locate and track origin of a pet to help build empathy. Also getting a better idea of it’s previous life.
Use machine learning to study the positioning of animals, see if certain patterns increase adoption frequency. Similar to shelf placement in a store, certain locations are more attractive than others.
Use machine learning to prevent people from adopting when they don't have a conducive lifestyle or if they have a history of bad ownership.
Some kennels are marked with “Project Dog” which means a dog that has some sort of issues or problem, however to learn what they are you have to ask the front desk.
When in the kennel it’s hard to see both animals side by side, maybe it’s not important, but maybe it would help people decide. I met couples that couldn’t decide between 2 dogs.
Using VR, share your experience with your partner in real time. Place QR codes on dog kennel to allow people to view profile on mobile.
Digital records are not always available however, by placing a QR code next the pet or scannable chip pet profiles can be loaded on demand via VR enabling instant access and storage
The dogs are in small kennels and don’t really have a way to express themselves, or have displays of individuality, they seem depressed.
After walking a dog I was asked if I wanted to adopt, I felt bad saying no however, I wonder how many people say yes and pair with a animal that might not be the best match.
Most of the leading tools and websites are in need of a modern refresh. Although pet matching apps exist, they're dated.
The industry is in need of a decentralized knowledge base where 3rd parties can connect and facilitate the process with update to date listings.
Some sites ask basic questions to make recommendations, however deep compatibility matching doesn't appear to be accessible.
Health diagnostics questions are personal and sensitive allowing the user to build trust and comfort. Could a chatbot help facilitate the pet matching process?
Finding love can be slow, difficult, and taxing much like finding an pet companion. The onboarding and profile layouts within eharmony are very detailed and informative.
When creating performance rating for athletes, players, it's important to see how they compare. Matching a teammates is like matching pets to people, they need to be compatible.
Design searchable pet archetypes based off breed and personality that relate to adopters. People can overlay their own for proper matching. E.g “The Explorer”, “Cuddles”, “The Guardian”, etc.
"A digital archive of pet breeds with videos, pictures, and info sounds really cool. If you were able to fill out your own profile and the your ideal pet profile"
By informing a patient of the benefits of pet ownership individuals with disabilities and special needs could be connected with the proper companion and reduce mental illness.
"People with Alzheimer's disease, many patients will get a dog after being diagnosed, and they can’t stop talking about how much joy the dog brings to them. It’s like hearing someone talk about their kids."
Overlay your personalized profile with your recommended companion to see the similarities visually. Freely bookmark and share profiles.
Once user data is collected future matches will be automatically served to user. Users are able to train the algorithm by 'liking' or 'removing' results.
Companion animals have been know to improve the quality of life for many, by highlighting lifestyle benefits with certain pets connecting patients, the elderly, and vets should be easier.
I would like to further test the concept of a bot acting on the behalf of a person. At what point does a person build trust in digital agents?
For this type of system to work there needs to be a large knowledge base. I would like to use Tensorflow and Google Assistant to prototype and test this concept.
As with all experiments I would like to follow up with users to collect feedback further iterating the user experience.