Project Type
UX/UI Design
Year
2023
Overview
I participated in a five-day Design Sprint for GramCity, aimed at quickly developing a solution to help users discover the most Instagram-able locations in any city. The goal was to create an easy-to-use platform that inspires and guides users to cool photography spots.
Problem Space
GramCity users want a simple platform to discover visually interesting locations—whether famous spots or hidden gems—while exploring the city. The app needs to inspire creativity and provide easy navigation to these locations.
Solution
We developed a feature that allows users to explore new locations through visual inspiration, browse categorized spots, and build a community by sharing photos.
User Research Findings
I reviewed user interview data provided by the GramCity team. Common themes emerged:
Users want to discover interesting and visually stimulating locations, ranging from tourist spots to hidden gems.
Some users prefer planning locations in advance, while others seek spontaneous exploration options.
Users value an easy-to-navigate platform with a strong visual component and simple, intuitive access to location details.
Key Insights:
Photo Tags: Tags help users filter and find specific location types.
Visual Inspiration: Showing others’ photos inspires exploration.
Map Functionality: Users want a city map with category and proximity filters.
Categorization: Interest categories include bold colors, architecture, film spots, and nature.
User Journey Map
We mapped the end-to-end user journey to visualize the steps users take from discovering the app to exploring locations and engaging with the community.
Lighting Demos
I analyzed comparable apps—NoFilter, PhotoMapper, and Yelp—to gather inspiration for GramCity’s design:
NoFilter: Allows viewing photos before account creation, offers follow functionality, and provides directions to locations.
PhotoMapper: Emphasizes photo upload sequences and categorization for visibility.
Yelp: Demonstrates effective use of photo categories and user interactions.
Crazy 8 Exercise
Through the Crazy 8 exercise, I rapidly sketched eight different approaches to designing the main functionality—how users search for and find photo locations. The most promising ideas focused on a visually engaging search screen and a map-based interface where users could filter categories dynamically.
Three Critical Screens
I identified and sketched the three most critical screens:
Category Selection Screen: Allows users to pick photo categories or locations.
Location Map Screen (Critical Screen): Displays a populated map based on chosen filters and categories.
Photo Details Screen: Shows detailed information and inspiration photos for each selected location.
I sketched a storyboard outlining the user’s journey from opening the app to discovering and interacting with different locations:
Step 1: The user sees a populated map upon opening the app.
Step 2: The user selects a category or searches directly on the map.
Step 3: The map updates based on the selection, showing location points with photos.
Step 4: The user taps on a location for a brief overview and chooses to explore further, accessing a detailed photo gallery and information about the spot.
Step 5: The user can save locations, view directions, or interact with other users’ photos.
Design Decisions:
Engaging the User: Users begin by viewing a populated map, removing the need for immediate account creation. The initial interaction is simplified to maximize exploration.
Photo Categories: Categories included visually stimulating elements like architecture, bold colors, and natural scenes, catering to varied user interests.
Visual Hierarchy: I emphasized photo content while balancing it with map functionality. Adjustments were made to avoid clutter.
Prototype Walkthrough:
Opening Map: The map is pre-populated with locations. Users can zoom in/out, select categories, or search for specific spots.
Location Overview: Tapping on a location gives a quick glance—distance, directions, and a save option.
Detailed View: Users can expand the view to see a full gallery of photos, interact with other users’ content, and access more details.
I conducted usability testing with five users from the Springboard community to gather feedback on the prototype’s intuitiveness and functionality. The testing focused on:
Initial Engagement: Whether users could intuitively explore categories and locations from the first screen.
Map Navigation: Users’ understanding of the map interface and how they interacted with location points.
User Interaction: Evaluating if the photo and location details provided were sufficient and engaging.
Key Adjustments Based on Testing:
Simplified Onboarding: Users found the initial categories confusing, so I refined the home screen to focus on location searches or immediate map exploration. Categories became a secondary option.
Enhanced Overlay Function: Users suggested expanding the information box for location details, so I added a “More Info” indicator, making it more obvious that additional content is available.
Photo Feed Expansion: Increased the photo gallery size on each location’s page to improve visual engagement and make the photo browsing experience richer.
Final Prototype Iterations
The final version of the app starts with a user-friendly map interface and grows into a community-based platform as users engage, share, and tag their photos. The app offers:
Quick Exploration: A seamless interface for both planners and spontaneous explorers to find locations easily.
Community Engagement: Users can follow others, creating an active and visually inspiring network.
Personalized Experience: The app learns from user behavior to suggest locations and categories tailored to individual preferences.
The design sprint for GramCity led to a well-received prototype that balances usability with visual inspiration. Through iterative testing and feedback, we developed an engaging platform that helps users discover and capture the most Instagram-able spots in any city. The next phase would involve refining the community features and building out a personalized recommendation engine to enhance user retention and engagement.
