The Project
Objectives
Design a mobile-first app that consolidates multiple messaging platforms.
Leverage AI to prioritize, retrieve, and organize messages efficiently.
Reduce the time spent searching for information across different apps.
Problem Statement
Users struggle with fragmented digital communication, causing inefficiencies, missed messages, and loss of control. Signal_ch{ai}n addresses this by consolidating multiple inboxes into one streamlined interface while integrating AI-powered tools to assist with organization, message retrieval, and prioritization—ultimately enhancing efficiency and user satisfaction.
My Role
I was responsible for the entire end-to-end process of this project, from research and data collection to UX design, prototyping, and testing.
This case study was developed as part of the Intermediate UX/UI Design course at OCAD University, where I applied UX research, data visualization, and interaction design principles to solve real-world communication challenges.
Discovery and Planning
Barricades at Entrances
Scope, Goals, Objectives
How Might We Questions
M.V.P. Definition
K.P.I.s
User Interviews & Research
Foundational Interviews
Needs Assessments
Competitor Analysis
Literature Review
Personas
Journey Mapping & User Flows
Identifying Most Important Flow
Card Sorts
Journey Mapping
Competitor Analysis
I.A. Diagramming
User Flow Diagraming
Initial Iterations
Lo-fi Prototyping
Ink Wireframes
Figma Wireframes
High Info Fidelity Wireframes
Usability testing
Moderated Testing
5 Second Tests
Interviews
Analysis & Synthesis
User Stories
Summaries
Reporting
Action Items
Refinement & Iteration
Implement Findings
Act on User Feedback
Refine Flows
Medium Fidelity Prototype
Usability testing
Moderated Testing
5 Second Tests
Interviews
Hi-fi and Feedback Loops
Hi-fi Prototyping
Hi-fi Figma Prototypes
Refine Design Systems
Interaction Design
Usability testing
Moderated Testing
Interviews
Completion & Reflection
Compile Findings
Written Report / Stakeholder
Presentation
Identify Next Steps
Presentation
Reflection
Who Are They?
The target audience consists of busy professionals in their late 20s–30s who frequently switch between multiple messaging platforms and need a more efficient way to manage communication.
Key Pain Points
Their Goals
Competitor Analysis
I analyzed three key industry areas relevant to messaging consolidation:
Project Management Software – Used for collaborative communication.
Social Media Management Platforms – Designed to aggregate multiple accounts.
AI Email Tools – Leveraging AI to organize and summarize communication.
Literature Review: What Makes Messaging Inefficient?
User Scenario
How the Prototype Handles It:
Detects Context & Need
The system recognizes that the user needs to retrieve a song name from a past interaction.
It determines that the required information is related to a past event involving shared location and activity history.
Cross-References Multiple Apps
Spotify (Play History) – Checks what songs were played during the time in question.
Google Maps (Travel History) – Identifies when and where the user was traveling.
Google Calendar (Meeting History) – Confirms if the sender and recipient were together at that time.
By analyzing time, location, and meeting attendees, the AI determines the most likely song played during that moment.
Synthesizes & Suggests a Response
AI drafts a reply containing the probable song title for quick user approval.
The user reviews and sends the message without needing to switch between apps.
Why This Matters:
Saves time by eliminating the need to manually search through multiple apps.
Improves efficiency by automating context retrieval across different data sources.
Maintains control by allowing users to review AI-generated responses before sending.
Usability Testing & Insights
Initial interviews revealed that users preferred a separation of work and personal messages and that a tool like this would be better suited to personal situations over work contexts. This lead to the priority being placed on mobile as opposed to desktop interfaces.
Additionally users wanted the interactions of the AI to be as clear and open as possible displaying how it found the information and why it was taking actions.
Users preferred keeping work & personal messages separate Prioritized mobile-first design over desktop integration.
AI interactions needed to be transparent users wanted to see how AI retrieved information rather than accepting "black box" decisions.
Undo Send feature refinement Initially designed as a persistent button, but testing revealed users preferred a time-sensitive pop-up instead.
Usability Trails
During testing it was revealed that the undo send option that was originally done using a button on screen when the message was sent would be better implemented as an option that would come up on-click when within a time window.
While users were initially delighted on seeing the option, they did expect to grow tired of it after some time and wanted it as a backup in stead of a default option.
Results
Early in the project, KPIs were defined to measure success. Compared to performing the same tasks without the prototype, the results showed:
20% reduction in task completion time.
50% fewer interactions per task.
12.5% improvement in usability scores.
Learning
Designing AI-powered UX requires balancing automation with user control.
Transparency builds AI trust—users wanted to see how data was retrieved.
Reducing cognitive load leads to better engagement—prioritization features were well received.
Next Steps
Refining AI communication styles for more human-like interactions.
Expanding reply methods for different messaging contexts.
Reevaluating features in light of Apple Intelligence and new AI developments.