Google: CS in Media Quiz

Client:

Google

Year:

2016

Role:

Product Design Lead, Front-End Dev

Visit Project:

Link
Challenge

Show Google's influence on media through a data collection process that results in fun and interesting insights for the fans, but also creates a solid searchable dataset for media companies

Goal

Translate Google’s CS decision model into a data collection tool that measures perceptions that influence computer science career choices

Outcome

We won client work with Google for shows including The Fosters and a YouTube Red series called Hyperlinked

Overview

Underrepresented youth, including girls and minorities, don't pursue Computer Science careers due to a misconception of computer science being irrelevant beyond coding and a general negative perception of the field. Google is setting out to break these stereotypes in the mainstream media. Through shows like Silicon Valley, they were able to spread a new message to youth, but they needed a way of measuring this influence. That's where Thicket Labs came in. 

We designed a survey process that allowed us to measure that change in perception. The survey I first designed was not about a specific show but a proof-of-concept. Google bought it, and we ended up being selected to measure several of their shows: The Fosters and a YouTube Red series called Hyperlinked.

Inspiration & Research

Together with the strategy team, we pulled together a list of insights that the client wanted and that we thought would be valuable. They focused on collecting demographic information as well as character and personality traits of the characters and the survey taker. Some of our data was sensitive information, such as health issues or sexuality, so we had to be careful with how we framed the copy. We also had to make sure to be inclusive with our answer choices while not overwhelming them with options. From there, we listed out interesting results for an individual to gather and also brainstormed results that Google and other media companies might find interesting.

Userflow

My main concern was: how we would convince the survey taker to go through so many questions asking them to input a lot of personal information. We decided to frame it as something fun - a “Who are you most similar to?” quiz.

Wireframes

I suggested we implement the data collection for mobile first and the client results for tablet and desktop. This would allow faster and easier data collection and the ability to display more complex insights. 

Wireframes for the data collection process

Visual Design & Implementation

For our personal media survey, we wanted it to have a lighthearted quiz aesthetic, so we went with bright colors and soft edges. From there, I led the project management of developing these prototypes, working closely with the development team and implementing some front-end styling myself.

Feel free to interact with the final prototype here!

User Testing

After a quick turn around, I outlined a plan for testing our prototype with users both remotely and in person. I designed a questionnaire with a set of interview instructions to guide other team members on how to interview effectively as well as record issues, errors, and observations. We were able to implement a majority of the solutions that came from user testing before our tight deadline.

Results & Press

In addition to completing the data collection prototype, we built a dashboard to test new characters based on the data we collected. You can see a preview of this below in the information packet here and interact with the prototype here.

We presented our results at Demo Day Marketplace by Made in NY Media Center. Google hired us. They were impressed with our methodology, collection methods, and designs. We have since designed and built one survey for The Fosters and another for a new YouTube Red original series Hyperlinked. To see more about that project and those results, feel free to visit my co-worker and friend's portfolio here.

Google's CS Education in Media program's findings were published in a USA Today article here and the more detailed findings here.

Featured Work