Find Every Stray Animal A Home
This concept design is met to represent a design thinking process that is user-centered, fact-driven, and iterative. Throughout the process, you can you see there is a strong focus on finding the critical problem to solve, before committing to address it.
Stage 1: Industry research & ideation
In the first round of research, the focus is on the condition of the pet industry in the US. What we found is 2015 alone, US have more than $2.1B of pet sale. $40B of pet food sale. But obviously, we still have an enormous amount of stray animal been euthanasia every year (27% of all animals in the shelters). So my 1st impression is the issue here is the disconnection between supply and demand. So base on this I brainstorm a dozen different ideas and setting the following project goal
Objective: Find every stray animal a home
Key results: Reduce stray animal euthanasia rate by 5%
With this goal in mind, I narrow down the ideas to 2 directions
Idea 1: Sell it, don't give it.
If there are $2.1B of pet sale each year, there must be a way to convert some buyer from the regular pet buying market to adopt the stray animal. So why expose these stray animal at the regular pet purchasing channel? For example listing the stray animal on the pet purchasing website with very low or free price.
Idea 2: Making sure the stray animal's info is digitized
The hypothesis here is the database of stray animal is incomplete. And the cost of putting stray animal info online might be high, and it may lack online marketplace to list these stray animals. So the idea here is to create an app for animal shelter employees and volunteers, to streamline the documentation process of creating stray animal's online profile. Also, create a web service to list these animals and being the to-go place for finding animals to adopt.
Stage 2: Concept validation, user exploratory research, and straw man app experience prototype
I'm very lucky to interview Diana Wu to gather her insight about stray animal adoption.[Full Recording] Diana is the co-founder of Love & Second Chance. Her organization is focusing matching stray animal in Taiwan and potential adopter in the US. So many logistic efforts went into how to make these animals look great on their website with detailed, heart-warming description, great photography and vivid short video clip that brings these animals alive even they are thousands of miles away.
So I run the few ideas I have with here, and they all get invalided in a fascinating way.
Idea #1 - Invalided
Diana mentions this idea won't work because it can't attract pet buyer to adopt stray animals, but it contributes to the cause of why stray animal appears in the first place. The reason why adopted animal has a significant lower abundant rate is because animal shelter and rescue have a very comprehensive screening process for adoptor. Is your environment pet-friendly? Do you plan to move in the next 5 years? Do you have any relatives have fur allergy? This process helped animal shelter identify and educate the concept of "responsible pet ownership." And listing stray animal on pet selling sites simply promote the concept of irresponsible pet ownership. Another shocking example of irresponsible pet ownership is the largest wave of pet abandon is at January each year. Why? Many American families give puppy or kitten as X'mas gift. And when January comes, people realize their busy lifestyle can't afford them to have pets.
Idea #2 - Invalided
Diana mentioned both animal shelter and rescue already have a pretty comprehensive process of putting these animal's info online. And all shelters and rescues already have data integration with Petfinder.com, the largest stray animal, and adopter matching service. If we create another app for logging data will simply add the burden for shelter employees and volunteers to maintain two systems. And creating another web service for matching will compete for the traffic with petfinder.com, which is against the project goal.
Forming New Product Strategy
In the high level, we know there is an enormous demand of pet trading market. We also know most of the stray animal already have some level of online exposure. So the concept here is how we increase the exposure of the stray animal to the right audience, find a way to optimize the efficiency of this workflow, also educate the crowd about responsible pet ownership.
Strategy #1: The power of online marketing
Cross-channel online marketing is a powerful tool to connect supply and demand. But it's a labor intensive effort and needing domain knowledge to execute. So the concept here is to transform any volunteer to experienced marketing campaign manager, with some app magic.
Strategy #2: Explain why you are not a qualified pet owner
If strategy #1 is working, we should have a healthy top of the funnel traffic start to flow in. The next step is to qualify the buyer that can give the stray animal a proper home. But at the same time, the buyers who are qualified out, are equally important. We use this opportunity to explain why they are unqualified, and either intellectually giving up the thought of owning pets, or adjusting their behavior to be a responsible pet owner.
Flow, IA and, interaction Design
Volunteer Campaign Management App: Pet Agent
This design represents the flow of how a volunteer finding the stray animal to support, and how the app guides them to be a successful online marketing campaign manager.
Screening question & responsible pet ownership education example
This design is the flow of a potential adopter, click through the campaign volunteer had set up. They then are greeted with a conversational questionnaire. In this example, this potential adopter is not qualified, and the flow educates them in this opportunity.
Next step: Concept testing with various user types
The next step is to do concept testing with various user types. Shelter employees, volunteer, typical pet buyer, typical pet adopter, are all potential research participants to consider testing this concept and learn more. The design strategies in the last stage now become hypothesis for testing. And how to translate these hypotheses into none-leading question and tasks are the key for next step.