phaseI

Phase I: Analyzing Users, Competitors, and Initial Designs

Introduction

Sorting through past and current photos is a tedious and frustrating process. DuoSort aims to innovate and improve upon this, allowing the user to access and sync multiple photo sources at the same time, enlarge target images, and delete or keep with only one click.

Methods

When we conducted the research for DuoSort, our UX team used research methods to understand the challenges users face when organizing photos across multiple platforms, especially applications like Apple Photos and Google Photos. The goal of this research was to identify shortcomings of competitive existing apps and then determine how DuoSort could improve on said shortcomings to fill a gap in the market. The two research methods used were competitive analysis and heuristic evaluation.

The first research method we performed was a Competitive Analysis of five other options similar to DuoSort. Our UX team focused the examination of possible alternatives that the users may currently rely on when transferring or organizing photos between Apple, Google Photos, other cloud based services, and locally. The competitors selected for analysis included PhotoSync, Mylio, Ente, Google Takeout, and the option of manually sorting photos between applications. To find the top competitors our team used a Google search for applications for accessing photo libraries across devices. We picked the top four and added in manually sorting photos/media as another option. Then each team member did an evaluation on one of the companies, one member did two do to the odd number. The areas for analysis were Strengths, Weaknesses, Quality Level, Cost, and the Platform the application could run on. Quality level was rated low to high based on the ratio of strengths to weaknesses, though cost also influenced it. Cost was measured monetarily, though the manual method does have a high cost in time.

The second research method used was Heuristic Evaluation. The purpose of this method is to analyze the usability of an existing product in the same market we are hoping to enter by evaluating it against a set of usability principles. From the competitive analysis, PhotoSync was identified as the competitor most similar to the intended functionality of DuoSort, making it the most appropriate application for deeper evaluation. The four members of our UX team each conducted heuristic evaluations of the PhotoSync application using Nielsen’s 10 Usability Heuristics. These heuristics provide a standard guide for identifying usability strengths and weaknesses within an application or product. They are:

• Visibility of System Status evaluates whether the system keeps users informed about what is happening through appropriate and timely feedback.
• Match Between the System and the Real World evaluates whether the interface uses language, concepts, and workflows that are familiar to users in other common technologies or everyday life.
• User Control and Freedom evaluates whether users are able to easily undo or redo actions and navigate freely without feeling confused o frustrated by the interface.
• Consistency and Standards evaluates whether the design follows common conventions and expectations so users do not have to wonder whether different words or actions mean the same thing, again to steer clear of confusion.
• Error Prevention evaluates whether the system is designed to help prevent problems from happening rather than simply displaying error messages after the fact.
• Recognition Rather than Recall evaluates whether the interface minimizes the amount of information users must remember by making options and actions visible.
• Flexibility and Efficiency of Use evaluates whether the system supports both novice and experienced users by allowing more advanced interaction through alternative workflows.
• Aesthetic and Minimalist Design evaluates whether the interface avoids unnecessary information or visual clutter that could distract or frustrate the users from their current tasks.
• Help Users Recognize, Diagnose, and Recover from Errors evaluates whether error messages clearly explain the problem and suggest possible solutions.
• Help and Documentation evaluates whether the system provides clear guidance or documentation to assist users when they encounter issues.

To research Photosync the team members used documentation off of Photosync's company page, available app store pages, by downloading the application, and further information found online. Then each member of the team assigned a score between 1 and 10 for each heuristic principle to indicate how well the application meet that particular principle, with a 1 being the lowest and a 10 the highest score. In addition to the numerical score, we each gave a brief explanation for reasoning behind our choice. After completing the evaluations, the team compared scores and the brief explanations to come to a consensus on what the agreed overall scores would be for the Heuristic Evaluation. These methods lead to findings that helped our team better understand the limitations in the existing product. We then used these insights gathered to design DuoSort, and it helped the team focus on how we could improve usability and create a more intuitive interface for users who need to organize and manage photos across multiple platforms.

Findings

The competitive analysis revealed several limitations in existing photo management tools. Many of the competing applications specialize in only one part of the photo management process. For example, PhotoSync excels at transferring media between devices but does not provide a reliable way to remove photos across multiple sources simultaneously. Manual photo sorting provides full control but becomes extremely tedious when users must review hundreds or thousands of images. Other tools such as Mylio and Ente provide strong syncing or security features, but they either require paid subscriptions or lack efficient workflows for quickly reviewing and organizing large libraries. These findings suggest that existing tools either prioritize transfer/syncing or storage security but do not focus on efficient large-scale organization of photos across multiple platforms. 

The heuristic evaluation further identified usability strengths and weaknesses in existing photo management interfaces. Google Photos performed well in areas such as recognition rather than recall, aesthetic design, and search functionality, which reduce cognitive load for users. However, several usability concerns were also identified. Some cloud-storage behaviors and syncing processes are not always clearly communicated to users, which can cause confusion about whether files are stored locally or in the cloud. Additionally, automatic syncing features sometimes limit the user’s feeling of control, particularly when managing backups or deleting media across devices. These issues highlight the importance of clearly communicating system status and providing users with transparent control over their media management actions. 

The personas and scenarios also revealed several common user needs. Users managing large photo libraries, such as photographers or students, require efficient tools to review and organize large numbers of images without risking important files. Less technical users often struggle with understanding where photos are stored across devices or cloud services. Many users experience anxiety when deleting photos because they are unsure whether backups exist. In addition, several scenarios demonstrated that users often want to quickly free up storage space without spending large amounts of time manually reviewing each image. These findings suggest that users need clearer storage visibility, faster sorting workflows, and greater confidence that important photos will not be accidentally lost. 

Conclusions

The research conducted in Phase I suggests that current photo management tools do not adequately support efficient organization across multiple storage platforms. Many existing solutions focus either on syncing, storage security, or photo viewing, but they do not provide an intuitive workflow for quickly reviewing and managing large photo libraries. As a result, users often rely on time-consuming manual sorting processes or become uncertain about where their photos are stored.

Based on these findings, several design recommendations were identified for DuoSort. First, the application should provide a unified interface that allows users to view photos from multiple storage locations in one place. This reduces the need for users to switch between applications or platforms while organizing their photos. Second, the interface should clearly indicate where each photo is stored or backed up so users can confidently delete unnecessary files without fear of losing important images. Third, the sorting process should be optimized for speed by allowing users to quickly review photos and mark them to keep or delete with minimal interaction. Finally, the system should provide clear feedback during syncing, transferring, or deletion processes so users always understand the current state of their photo library.

These recommendations will guide the design of wireframes and prototypes in the next phase of the project. By focusing on improved visibility, efficient workflows, and user confidence when managing photos, DuoSort aims to address the most significant usability gaps identified during the research process.

Caveats

• Our methods did not include any user analysis, only input from the UX team members.
• The evaluated competitors were chosen and evaluated quickly, any information behind paywalls was not accessed.
• This was exploratory, early stage research. Information found may not be fully accurate and conclusions drawn should be validated through additional testing.
• Quality ratings were subjective, and influenced by perceived strengths and weaknesses, not a standardized metric.
• The heuristic evaluation was based only on set characteristics, a list was limited in scope and may have been incomplete.
• The heuristic evaluation focused primarily on PhotoSync, and was not preformed on any of the other competitors.
• Assumptions were made about user anxiety, storage confusion, and workflow inefficiencies based on team analysis, not user data.