Shashwath Santosh is a designer and researcher based in New York. Previously at Doris Dev.


About
Instagram




2023



Stooper App



Role:
UI/UX, Research, Prototyping, Usability Testing, 
Visual Design, Enthonographic research 

Team Member: Krithi Nalla


This platform aims to turn New York City into a playground by enabling users to participate in a never-ending quest to find and rescue free items that have been abandoned on the streets.










CONTEXT
"Stooping" refers to the act of rescuing a desirable abandoned object from the street. This culture is popular among young adults in New York City. Currently, it is largely dependent on word of mouth and random chance.







PROBLEM


Generous Instagram pages and second-hand resale sites have long helped stooping communities. But these are not tailored specifically for the unique sub-culture. Perhaps a dedicated system could be developed to help improve the success rate of finding items.




INTERVENTION


Introducing Stooper, a community-based app designed by and for stoopers. It provides live updates and an interactive map-based feed that displays all the interesting finds nearby. With real-time information on the availability and location of objects on the street, Stooper makes it easy for you to decide where to go.














Map-based Discovery Experience








Relevant Object Information








Report As Taken














AI Assited Posting Experience
































RESEARCH ROADMAP

Acknowledging that the research method was not linear but rather cyclical, it was important to keep the community involved from the beginning. Designing an experience that kept the community's values close to its core was an good challenge.











MARKET ANALYSIS
Fundamentally, Stooper is an experience based on maps. We analyzed a variety of app interfaces and user flows that involve navigation and geography.

By studying existing products and their level of community contribution, we learned which familiar features could be adapted to the stooping experience.





















MAIN USER INSIGHTS 
Enthusiasts like to follow Instagram pages but often don't end up going out to get the things they see because they lack real-time information.

Enthusiasts would like to know if there's anything nearby when they're already on the go.

There's a certain entertainment factor to this. Users enjoy seeing other people's success and imagining what they could have potentially experienced themselves.











OPPORTUNITY STUDY 
After creating a frustration map based on insights from user interviews and surveys, it became clear what the gap in the market was. This helped to define the opportunities.
























INFORMATION ARCHITECTURE
To ensure that the app is both enjoyable and easy to use, we planned the onboarding experience and posting process to be engaging and youthful, while also being efficient and effective.






























ETHNOGRAPHIC RESEARCH
One of our main issues was how to convey the dimensions and weight of an object through a shared image without using actual numbers.

To solve for this, we used references that are common and easy to visualize, such as city-specific landmarks and everyday objects. Phrases like "as wide as a microwave", "as tall as a refrigerator", and "as heavy as a gallon of milk" helped people understand scale and weight more easily than numbers.











EXAMPLE FEATURE FOCUS
Another issue with existing platforms was the lack of searchability. With Stooper, we wondered: what if users could receive specific notifications for categories such as 'green', 'chair', or 'green chair'?

Users also wanted to receive notifications of interesting finds nearby while they were out and about. Therefore, location-based notifications were added to let them know quickly if there was something nearby to check out.












NEXT STEPS
Find a balance between strict rules and fool proof user experience to allow community rules to govern platform etiquette.

Integrate revolutionary technologies like machine learning and AI to enable image detection and automatic self-description for effortless posting.

Place greater emphasis on location data privacy.









Team Member:
Krithi Nalla, UX Researcher 

Project Timeline:
6 weeks

Email for Full Project Case Study