Representing the team as the point of contact for users to schedule interviews and testing sessions.
Prototyped experiences at low and high fidelity through concept sketches, wireframes, and interactive prototypes.
Conducted competitive analysis, user testing, and surveys.
Led the team in the affinity mapping and journey mapping process.
user's confidence in going out alone at night
SUS Score: 77
No. of Clicks: 2.2
Time on Task: 7.5 Seconds
Nearly half of young women say they feel unsafe walking alone at night. This causes them to avoid going out at night alone.
Despite the high statistics showing the effect that this issue is having on women, we feel that a product or system to address our user's pain points does not currently exist. Our team chose to explore what creating a system to help keep women safer at night could look like.
There is no clear information about the safety levels of unfamiliar areas and cities.
Quickly contacting friends and family can be difficult.
Information about foot traffic levels along a user's route is not available in order to help them stay near crowds
Understand the safety levels of unfamiliar areas
Be connected to safe routes when walking at night
Unsure which areas are truly unsafe
Always worried about her safety
Unsure if anyone else will be walking on her daily route
Not likely to call the police if she is in danger due to mistrust
To stay near crowds or groups of people when walking at night
A quick way to connect with others when feeling unsafe
26 / Single / Student
28 / Single / Accountant
How Might We
How might we connect users to other people quickly?
How might we share authentic safety information about areas users may walk through?
We used what we learned about our users to begin to brainstorm different ways to solve the pain points identified. A Creativity vs. Feasibility Graph was utilized in order to narrow our solutions down to a few ideas that addressed the pain points at different points of the users' journey.
We wanted to think outside the box, but we also did not want to create systems that were too expensive to implement or too far ahead of current technology.
Users also wanted to be able to see the related neighborhood and news information directly on the routes view of the page.
Users enjoyed being able to see the news and neighborhood information that went along with their selected routes.
We used the graph and the ideas in the optimal zone to help us create three possible solutions. Next, we created detailed sketches and wireframes of each potential solution.
We referred back to user research, user pain points, and the "How Might We" questions in order to make sure we stayed focused on user needs. Finally, we got feedback on each idea from users.
Transportation App & Key Fob
This transportation application presents users with two modes to use when feeling unsafe. Users can select SOLO and be directed to a bike, scooter, or rental car to drive. Users can select DUO and be directed to a projected meeting spot for pickup by a ride share service.
Users liked the familiarity of the app in comparison to other ride share apps.
They did not want to worry about how they would know if they were on the fastest route to a ride in a dangerous situation.
News & Media Solution
This application presents users with the safest route to walk based on safety ratings. Users are guided audibly by a corresponding wearable technology that calls loved one in emergencies. Users also see local news reports for areas along their route
Users liked the ability to see local news stories for areas near them.
However, they stated they were unsure of how to interact with the wearable.
Buddy Walking Solution
This application shows other people nearby that are walking to a similar destination. Users can join trips and gain a group of walking buddies to accompany them to their destination.
Users liked the idea of not having to walk alone.
Many users worried about the potential stereotypes that this idea may enable people to make.
In iteration 2, we completed more user testing and feedback sessions. We continued to hear users requests for more of a focus on our neighborhood and news sections of Convoy. Users stated that they did not yet trust the app, and wanted explanations about the logic behind the neighborhood ratings and the source of the news stories.
Users are also now able to see incidents that have been reported near their neighborhood. Police activity and the people in the area are reported with each incident.
Receive real time updates about safety incidents reported in your neighborhood. Users can also see the amount of people walking in their neighborhood to keep them connected with others.
Identify Safe Routes
Search for a place or address and be immediately shown the safest route that you can use to walk alone at night.
Each route shows any incidents reported along the route, as well as the amount of people along the route to keep you connected to others.
User testing was completed via Expert Testing & In-person moderated usability testing. We asked Usability & Accessibility experts to participate in a Cognitive Walkthrough and a Heuristic evaluation. We also had visually impaired users & users with unimpaired vision to participate in usability tests onsite at NCR's Usability Lab.
Key Takeaway: Keep it simple.
Once again, our passion got the best of us as first year, first semester, masters students. We overloaded our app with too many features, because we excitedly wanted to solve all of our user's pain points. This project taught me the importance of keeping things simple. Emergency UX is really challenging, and the last thing users need when they are in trouble is to be confused by their safety app!
August 2019 - December 2019
Anjali, Yujin, and Nektar
I helped design an app called Convoy to help women avoid danger when walking alone.
of women prefer to reach out to someone when walking.
of users would not reach out to the police if they needed help.
of women prefer to have company when walking.
of our users wanted to stay alert, stick to their daily routine, and avoid areas with a bad reputation for safety.
from our research
Press the volume button twice and shake your phone three times in order to instantly alert selected contacts through call or text in case of an emergency.
Alert Emergency Contacts
Users stated that they did not yet trust the app, and wanted explanations about the logic behind the neighborhood ratings as well as the source of the news stories.
Users wanted more clarity on the different types of crime neighborhoods had, and the frequency of those crimes during different parts of the day.
Our users were still not understanding the wearable device. Many users stated that they would prefer not to keep walking in a dangerous situation, and would instead call an Uber. This left us questioning the necessity of the wearable.
I would never call the police as a preventative measure. I think it would just be a waste of their time.
We studied safety applications and wearable technology aimed at keeping women safe. We wanted to understand what current market products were offering and what they may be missing.
To better understand our users we conducted semi-structured interviews with 9 women. Going into the interview we had many assumptions. We thought our users would definitely want a weapon and that they probably would just call the police in the instance of danger. However, our interviews did not confirm our assumptions.
Next, a survey was created based on what was learned from our initial interviews to confirm our interview findings. In this survey, 36 women helped us understand what they truly needed to feel safe.
An Affinity Map was used to organize the information we learned from our users. They were unable to use self-service kiosks in their current state, but we wondered if there was something to be learned from the assistive technologies they already used.
What one user does to feel safe at night
What makes one user feel unsafe
Pain point identification helped us to narrow down to the following problems that were within our scope to solve.
After receiving feedback from usability tests, I saw a need to scale down the amount of features available to users. We did not address our "How Might We" questions, but users got lost in the amount of features available. They feared that this would be too complicated during an emergency. I decided to complete iteration 3 after the project ended to focus more closely on these questions.
The second iteration was completed in Fall 2020 after receiving feedback on iteration two. Iteration 3 is shown in detail below.