THE PROBLEM
Millions of animals are currently in shelters and foster homes awaiting adoption. Design an experience that will help connect people looking for a new pet with the right companion for them. Help an adopter find a pet which matches their lifestyle, considering factors including breed, gender, age, temperament, and health status. Provide a high-level flow and supporting wire frames.
PRIMARY GOAL
Connect a user with a compatible pet from a local shelter.
SECONDARY GOALS
Share pets to a user’s social network to increase the chances for adopted.
Donate to the local shelters.
Inject relevant advertising to create revenue for the company and as well as help the user get into the mindset to prepare for their new addition to the family.
RESEARCH
Through the research process, my assumptions on why people adopt pets and the process they engage in to adopt these pets was challenged. Initially, I assumed that the location of the animal would be the top priority in an adopters search and that the videos and photos of the animals were bonuses to a pet search.
However, research demonstrated the opposite. Itthe primary factors that contribute to choosing a pet include:
Appearance and social behavior
Information gathered from a staff member or volunteer
Interacting with the animal
Viewing the animal in a natural environment rather than in its kennel
With these factors in mind, decisions were made and applied to the user experience. The decision to lead the interface with large videos of the animal provides the potential adopter with a greater sense of the animal’s temperament and behavior. Given the situation that the user is unable go to see the pet in-person, providing the option of utilizing a VR headset enables the viewer to engage in a semi-realistic interaction with the animal of interest, simulating engagement in a natural environment. The built-in option for potential adopters to engage with a staff member or volunteer via email and/ or phone enhances the chances of pet adoption, as this is another method to obtain direct information about the animal.
For those looking to become pet owners, societal misconceptions of shelters themselves, as well as the animals within them, present a barrier to shelter adoptions. The idea that shelter animals are “damaged goods” deters people from utilization of a shelter.By providing the user with Google Business Ratings and the aforementioned pet viewer, the user can see for themselves the quality of these care centers.
Because shelters are also often thought to house only dogs and cats, potential adoptees looking for other animals do not look into using a shelter, although a variety of pets can be found there. A solid advertising strategy and clear filters can help the visibility of the other animals.
An analysis of interfaces of current competitors in the market revealed that either very little information or an overwhelming amount of information was presented to the user, creating difficulty with engaging in the site in an efficient, meaningful, and productive way. For example, many sites forced users to create a profile to gain access to photos of animals, which according to my research is counter-productive. The experience I propose, eliminates such experiences of friction users too often come across when searching for pets on shelter sites.
**Mention competitors**
PROCESS
After gathering some research I started by doing a brain dump of everything I can think of that would be related to the goal. This includes features, filters, inspiration, challenges and other notes that popped into my head.
Brain dump of ideas
After the brain dump, I recruited some friends and family so I can interview them. I talked to 4 people; 2 pet owners, 1 that is interested in a dog and another is actively looking for a pet. After speaking to them, I saw that there were two main paths, intent and explore. The users that were going to go to the site with intent already had something in mind and just needed tools to help them find that special pet. The other, has a looser grasp on what they are looking for and were more open to options.
Speaking to the users I started to understand their motivations. I took what I learned and created two personas. Loralei Lovejoy, an existing dog owner and Edward Feelgood, a empty nester who is looking for a new companion.
I had a couple users participate in an open card sorting activity where they started to group similar content together and labeled the categories theirselves. The two users worked together and spoke aloud to make decisions. When they completed the task, I compiled the data.
Armed with clear goals and user’s motivations. I started with developing a user flow that ended up with the user going to the shelter and meeting the pet or “Booking a Playdate” which I found from the card sort to be more fun and something to look forward to.
I then created paper prototypes to test the user flow with the users. They hated the first round! I had included a profile builder upfront to help narrow down animals when they get to the feed. The most important part for the participant was to see the animal profiles. I revised my approach and as much friction upfront and got them straight to pets. I can cut more friction by building the experience as a web app, downloading a native app may discourage the user to move forward.
Book a Play Date flow
I started the wireframe stage by designing out key screens in Sketch and prototyped them in InVision. I was able to flush out the concept of a favorites section where users can scroll down a feed and quickly add something to their favorites.
To lean into the user’s desire to get to the content, I opted to use a help tile that is easily dismissed or scroll past. There's an option for the user to create a profile but it is not mandatory. The user can more information in help section if they need it.
Homepage annotations
Favorites Annotations
For the user that has an animal in mind, could use the search, filter and sort options to narrow down the results to quickly find a set of pets that meet their criteria. If the user has created an account or is signed in, their sessions will be logged and the search criteria will be saved when visit the site again.
The user’s profile houses their information and preferences. This will help the system serve up pet that fit their lifestyle.
The site would use machine learning to help create a more relevant feed for the users who is more open at looking at a broader set of options. The more the user uses the site, the smarter the recommendations. It can be achieved by finding similarities in the animals that the user has interacted with. For example, the user continually places brown dogs in her favorites but watches a video on white cats on occasion, the feed would then be sorted with brown dogs higher up than white cats. This would work in conjunction with the defaulted ranked based on location and their user profile.
The pet cards are displayed with large videos with actions the user can take below. The interaction pattern is similar to an instagram feed. This cuts down on the learning curve on the user’s first impression. A view counter is implemented to display the views of a certain pet to create a sense of urgency.
While the goal of the homepage feed is to have the user place pets in the favorites, the favorites section is focused on “Booking a Playdate”. The cards look similar to those on the homepage with the exception of prominent call-to-action.
After the user is finished with their session, it is best to follow up on with an email or other notifications letting them know that they have pets in their favorites. This will encourage the user to pick up where they left off.
The visual design of Pet Finder should be playful and make the animals the key focus and the call-to-actions should be bright and stand out. We would encourage the shelters to create better content and stress the importance of making the videos and photos share worthy to increase the chances for people to post on their social channels or urge them to adopt.
CONCLUSION
It puts the users desires first by removing as much friction from the process of to connect them with their ideal pet.
The feed is based on machine learning, the users lifestyle and the location of the pet that prioritizes the most relevant options for them.
OTHER CONSIDERATIONS
Develop a paid search and social advertising strategy to drive to the site.
Create an experience to help shelter workers and volunteer to create better content.