Getting ready has never been easier.
Yelp Design Challenge
OVERVIEW
Illuminate is a browser extension that helps Twitter users better understand what accounts they are interacting with on their feeds without disrupting the current Twitter browsing experience. 
The project is currently under implementation.
TEAM
Ann Peng 
Likang Sun
Luca Damasco 
Shen Lu
DURATION
MY ROLE
User research
Rapid Prototyping
Visual Design
Motion Design
8 Weeks
 
 
SOLUTION OVERVIEW

To combat the challenge, we present illuminate, a browser extension designed to take your Twitter feed out of the dark. By automatically parsing through the accounts on a user's Twitter Feed, Illuminate generates tags of potentially unwanted content in order to flag that content to the end user.

 
INITIAL RESEARCH 
What are the unresolved issues?

After taking a look at the app store, I realized there were already dozens of apps made and aimed to solve the same problem of choosing what to wear in the morning. To avoid reinventing the wheel, I decided to do some competitive analysis to understand what were the missing gaps as well as user interviews to take a closer look at what were actually the unmet needs.

I put down my notes from feature analysis and user interviews on sticky notes, and started to regroup and cluster them in order to find patterns behind. This allowed me to identify the 4 important touch-points in a user's journey.

NARROWING DOWN

After synthesizing my research insights, I decided to focus on the following 3 main problems that people currently encounter and navigate my design goals around them.

Problem 01

People make outfit choices based on a myriad of factors, but current apps don't understand what to prioritize. 

People take into consideration of multiple factors when choosing what to wear, e.g. weather, mood, occasion, novelty or comfort level. However, existing solutions were not able to make a suggestion that incorporates all these factors. The suggestions end up being very mechanic

Problem 02 

Organizing and searching in digital wardrobes is a hassle instead of convenience in current solutions. 

In reality, finding an item in  our closet is actually not that difficult. People organize their closets based on certain heuristics that are easy to follow, such as color, category or wearing frequency and they have 'muscle memory' for where things are.  However, current digital wardrobes are actually making that searching process more complex - users need to go through levels of information hierarchy in order to find a specific item

Problem 03

Outfit suggestions are either too generic or of small-value

Many users have their own dressing styles or preferences. They have some ideas of which items will go well together. However, suggestions from some current wardrobes are mostly based on generic color palette and barely incorporate the user's personal styles. In some other apps, it is the end of the other spectrum - users basically have to configure every outfit combination manually and all that the apps do is to pick one from these pre-configured outfits from users. 

Goals

A digital wardrobe that well leverages user control and smart system 
  • Occasion first - prioritize occasion when suggesting users on what to wear. After users choose the occasion, give users the flexibilities of choosing among different colors, styles...

  • Intuitive searching - help organize the items in a way that that users could see their closets at a glance and quickly search for items

  • Customized outfit suggestions  - learn about what outfit ideas users already have and save users troubles of manually creating looks on the app

 
IDEATION 
  • It’s self-explanatory - tags themselves provide enough context for user to understand what they mean.

Features - 

  • It’s self-explanatory - tags themselves provide enough context for user to understand what they mean.

  • It’s neutral - compared to alert information, displaying tags makes user feel being informed instead of being told what to do.

  • It’s less intrusive - tags deliver the important message to users without impeding users' reading experience on Twitter or desire to share

Feedbacks from users - 

  • It’s self-explanatory - tags themselves provide enough context for user to understand what they mean.

  • It’s neutral - compared to alert information, displaying tags makes user feel being informed instead of being told what to do.

  • It’s less intrusive - tags deliver the important message to users without impeding users' reading experience on Twitter or desire to share

 
WIREFRAMING 
Tagging Twitter accounts with synthesized data from their past tweets.

Following the feedback we got, we landed on a design solution that would tag twitter accounts on user's twitter feeds with synthesized data from the accounts' past posts.

 
DESIGN DECISIONS

How did we get to the final design? After we decided on our design direction, the team conducted another round of parallel prototyping to validate our ideas. We interviewed avid Twitter users and from their feedbacks, we further refined our designs as follows.   

Decision 01 

Tag topics instead of concepts 

Problem: what to tag?

When we first came up with the tagging solution, we wanted to label accounts with concepts that users could understand at a glance. For example, an account would be labelled as 'racism' if the algorithms detect words related to racism in its past tweets. However, users found such assertive tags too arbitrary and again, directive in a sense. 

Initial design of tagging concepts were seen as arbitrary labelling by users.

Action:

Our final design tags topics that might be potentially controversial instead of concepts. So instead of tagging an account as 'racism', Illuminate would simply assign the 'race' tag to that account, informing users to look into more information and leaving some space for them to make autonomous decisions.

Final design tag topics instead of concepts.

 
REFLECTIONS
A simple solution doesn't come from an easy process

Our hindsight bias might have succeeded in making us feel that our final design looked fairly simple, but the team knew that the process of getting to a simple solution was never easy. As designers, we don't always have the correct answers right in hand, but what is more important is that we are always passionate about finding that right answer even if that means going through hundreds of trials and errors. What worked really well in this project was that we explored as many alternatives as possible and we did not get fixated on our own ideas early. As we progressed through the prototyping, we were excited to learn what worked as well as what didn't work, which helped us come to a better understanding of the problem. 

© 2019 designed by ann peng.