Google Pets

Pain Points & Goals

Frame The Design Challenge

We have Airbnb for finding a bed. We have Uber for finding a driver. So, where is your go-to place for finding a new pet?

Adopting a new pet is a daunting and tedious experience. On the one hand, hundreds, if not thousands, of websites and posts are out there with different levels of quality — some are missing photos, others didn't mention their characters. On the other hand, many adopters felt regretful about adopting the pets or even rehomed their new friends because they didn't realize how much time and efforts are needed.

The goal of this project was to create a digital go-to place for pet adopters, which solves the pain points mentioned above. The biggest challenge here is how to match adopters with the right pets since people usually have very different preferences and lifestyles.

Business Strategy

Market Size Business Model

I started the project with thinking the business value within the problem area. First of all, I'm curious about the market size. It turns out there are about 13,600 community animal shelters nationwide. Approximately 7.6 million companion animals enter animal shelters, and 2.7 million shelter animals are adopted each year.

To reveal potential business models, I listed all the people and elements in the system. The reason why I think Google should have such a product is that Google is superb at search engines, deep learning, as well as user experience design. By crawling the scattered information of adoptable pets in different websites, classifying them based on the content, and showing them at a single touch point with top-notch user experience, Google Pets can be an appealing place for millions of adopters who look for pets each year.

The product can potentially provide new growth for services like Google Ads since people need to buy a lot of stuff after an adoption. Or, we can make the customized recommendation of pet food, vet services, and other things based on the information of the pets and their owners.

I had following assumptions after I did the background research:

• The pet searching process could be arduous since too many shelters and websites.

• Huge amount of unstructured knowledge or information about the pet is hidden deeply in each post. Adopters need to dig them one after one.

• Remote adoptions can provide adopters more choices.

• Business opportunities (ads, pet supplies, vet recommendations, etc.)

Human-centered Research

User Observation Interview Secondary Research Card Sorting

To understand how people look for adoptable pets online and what problems they have, I did a user observation with a woman who was considering to adopt a cat. I asked her to show me her search process and think aloud.

The following is a list of key insights from the user observation:

• Images matter — Facebook was the first place where the women searched. She said because the posts there usually have pets’ images.

• Location matters — she searched “animal shelter” in Google Maps, rather than Google Search. She said she need to meet the pet first, so she would not consider remote shelters.

• Affinity matters — she told a story of how her boyfriend chose his cat.

• The whole searching process is troublesome — she had to click on each shelter listed in Google Maps and choose in different filters again and again. What makes things worse is that some shelters only have dogs.

Adopters are just one side of the connection. In order to understand what makes a successful match and what the adoption process looks like, I did a field trip at San Francisco SPCA (they have the highest adoption rates in the city). I did interviews with the volunteers and staff who work there to look for some expert insights.

The following is a list of key insights from the interview:

• A successful match is a personality match — people should look for connections rather than breeds. It is also surprisingly difficult to accurately guess a dog's breed based on its appearance.

• Different species have different kinds and numbers of personalities.

• Adopters are usually not well informed about the meaning behind an adoption before coming to shelters. They also don’t realize how much time and work it might be.

• The adoption process could take a couple of hours, and it’s all about looking for a personality match, education, and building trust.

• No remote adoptions — adopters have to meet pets first, shelter stuff need to see how adopters and the pets interact with each other.

• SFSPCA is sponsored by Purina. They do suggest a few food brands if adopters ask. They also sell pet supplies and give adopters a 20% discount to Pet Food Express.

At the end of the field trip, I also did Card Sorting with adopters and volunteers to help me understand what are the most important aspects when choosing pets. The pictures below shows the results of Card Sorting. The cards in the left column are things people thought important (the higher, the more important).

As I mentioned above, the biggest challenge of this project is how to match adopters with the right pets. Filters play a key role in helping people find a match, so I did a secondary research on existing filters of the most popular adoption websites.

Key insights from the secondary research on filters:

• A constructive, personality-oriented filter is usually missing. Most filters emphasis on people’s preferences (like age), and rarely consider the requirements from the pets (like activity level).

• Although there are several filters have personalities, the systems don’t speak users’ language. No one knows the meaning behind each personality name (like Poet).

Based on all the information I had gathered, I framed the design challenge as following —

How might we simplify the online searching experience for adopters, provide them necessary information and constructive filters to facilitate more successful matches?

Then, I prioritized the top three problems to solve:

1. The existing pet searching process is too complicated and time-consuming.

2. A constructive and adopters friendly filter is also usually missing.

3. Adopters don’t realize what it really means for an adoption, especially for those first-time adopters. This could lead to rehoming.

Interaction Design

Persona Storyboard User Flow Wireframes Data-informed Desicion

The user flow was a place where various plans explored and multiple iterations made.

Plan 1:

Plan 2:

Plan 3:

Version 3.1:

Version 3.2:

The filter system was generated and evolved according to several data sources — key insights from the user observation and interviews, Card Sorting results, requirements for adopters, shared filters of top 3 pet adoption websites, a form that SFSPCA used to find successful matches, as well as user testing results. The following image shows the final version of the filter options.

To maintain the same branding and feeling with other Google's products, I applied Google's visual language — Material Design — to the project. The following images show the typography, icons, and color that I chose.

The high rate of successful match requires high-quality information of pets. Although search engine spiders and deep learning technology can help us dig out some of the critical information from the wild, a more constructed template is needed to help shelters or foster homes improve the quality of their posts. It’s more about designing and building an eco-system.

For the next steps, I would like to make a high-fidelity prototype and do more user studies. Then, have more iterations based on the feedback.