Pocompo is an app designed to provide real-time guidance to users on framing their photographs using established photography techniques like the Rule of Thirds, Symmetry, and Leading Lines. The app automatically suggests compositions to help users capture better photographs, making the learning process seamless and intuitive.
How might we educate users quickly while guiding their photograph?
Today everyone has the ability to become a photographer with accessibility to great cameras at their fingertips. But what people don't have, is a quick way to learn standard framing techniques to help guide them to capturing what they see aesthetically.
This was a solo project for a 12-week General Assembly UX design course. Initially I had set out to create an app where photographers could analyze their composition & framing; however, the discovery phase revealed that there was no need for the problem I set out to solve.
From user interviews and surveys, we identified that many aspiring photographers struggled with the time commitment required to master composition techniques. Users expressed a desire for real-time feedback while shooting, rather than having to spend hours studying photography principles.
Users often mentioned that they wanted to quickly learn composition rules, but existing resources were too time-consuming or difficult to apply in real-time while shooting.
At the discovery phase of my project, I conducted 5 user interviews in order to get a better understanding of the thought process behind different people's photography habits. A recurring theme emerged around the need for a second opinion when taken photos -- despite the subject.
Travis needs a photography assistant, because he enjoys capturing what he sees but the photos don’t turn out well.
After pivoting to a new focus problem, I wanted to gather feedback around when, why, and how someone would look up photography techniques. If they did not, I also wanted to gain insight on why. I set up an online survey, and posted it to photography Reddit threads, work channels, and amongst peers.
Travis represents our target user—an amateur photographer who enjoys capturing photos on the go but lacks the time and knowledge to frame them well. He needs quick, practical guidance on composition techniques without the hassle of formal learning.
Travis's frustration with poor framing and lack of guidance led to the creation of an AI-driven assistant in Pocompo, which would provide real-time feedback on composition techniques like the Rule of Thirds.
In the initial steps, the user can explore the app through a tutorial, guiding them through basic composition rules. Once in action, Pocompo helps the user select their subject, recommends the best composition based on that subject, and provides visual feedback on the photo’s framing.
For example, by automating composition suggestions, the app helps users like Travis take well-framed shots without having to study or apply composition rules manually.
In the initial design phase, I explored several low-fidelity wireframes to iterate on how users would experience the MVP – a live AI photo guide. My focus was on how to guide users in framing their photographs using The Rule of Thirds. Each iteration incorporated subtle visual indicators such as color, arrows, and gridlines to direct the user.
During hallway usability testing with peers, valuable questions arose, such as:
These insights guided my iterations, particularly focusing on accessibility and user clarity.
I also experimented with various representations of the composition library, ensuring users could easily select a specific framing technique. By refining the design, I aimed to strike a balance between offering users the creative freedom to explore compositions while providing clear, actionable guidance on how to improve their photography skills.
Following the sketching process, I developed high-fidelity wireframes in Figma to showcase the MVP's functionality. These wireframes emphasized the user's interaction with the AI photo guide, guiding them on how to frame their subject using various composition techniques.
Key adjustments:
In parallel, I designed low-fidelity wireframes to map out the navigation and structural elements of the app. The main focus was on the sequence of screens and the visual hierarchy to help users easily navigate between functionalities (composition library, camera, and tips).
This combination of high and low-fidelity wireframes provided a holistic understanding of the app’s usability, helping me answer practical questions such as:
By refining these wireframes, I was able to create a balance between creativity, user guidance, and navigation efficiency.
