Developing a messaging framework
A foundational study with innovative research methods
Overview
A major ecommerce marketplace needed to optimize their communication strategy for a specific user segment. The project required deep insight into how users process, prioritize, and respond to different types of platform communications.
My Role
As a UX researcher on the team, I spearheaded the analytical phase of this project, implementing an innovative mixed-methods approach to derive meaningful insights from our research data. I developed and executed a novel analytical framework that combined social network analysis with traditional UX research methods, enabling deeper understanding of users’ mental models and behavior patterns.
Goals
• to understand how users make sense of and respond to different types of messages
• to identify users’ preferred communication channels for different types of messages
• to inform a more intuitive and effective messaging strategy
• to identify users’ preferred communication channels for different types of messages
• to inform a more intuitive and effective messaging strategy
Social network analysis provides an analytical toolbox for exploring relationships.
Research Design
Methodology
I developed a multi-layered research approach that combined:
• Participatory design sessions with card sorting exercises (10+ participants)
• Social network analysis (SNA) of card sorting data
• Discourse analysis of message content
• Thematic analysis of interview transcripts
• Social network analysis (SNA) of card sorting data
• Discourse analysis of message content
• Thematic analysis of interview transcripts
Innovation in Analysis
I introduced social network analysis as a novel method for analyzing card sort data, which allowed us to:
• Quantify the strength of associations between different message types
• Measure participant agreement on message relationships
• Generate data-driven visualizations of users’ mental frameworks
• Identify patterns that might have been missed using traditional analysis methods
• Measure participant agreement on message relationships
• Generate data-driven visualizations of users’ mental frameworks
• Identify patterns that might have been missed using traditional analysis methods
Deep-Dive Analysis
The multi-method approach enabled three levels of insight:
Structural Analysis: Using SNA to map relationship patterns between messages
Linguistic Analysis: Applying discourse analysis to identify specific language patterns that influenced user perception of message priority
Behavioral Analysis: Understanding how users’ past experiences shaped their responses to different message types
Linguistic Analysis: Applying discourse analysis to identify specific language patterns that influenced user perception of message priority
Behavioral Analysis: Understanding how users’ past experiences shaped their responses to different message types
Key Findings
User Behavior Patterns
The research revealed that users primarily categorize messages based on:
• Required action type
• Action urgency
• Previous experiences with similar communications
• Action urgency
• Previous experiences with similar communications
Strategic Insights
The analysis uncovered several critical gaps:
• Misalignment between official message priority levels and user perception
• Inconsistent message structures affecting user comprehension
• Channel preference patterns linked to message type and urgency
• Inconsistent message structures affecting user comprehension
• Channel preference patterns linked to message type and urgency
Through card sorting exercises, participants identified five distinct message categories, with strong agreement (>66% of participants) on message groupings within each category. This categorization revealed an important gap in the platform’s existing four-category messaging framework, suggesting opportunities for revising the framework and message content to better match user expectations.
Core Competencies Demonstrated
• Research design and methodology innovation
• Advanced quantitative analysis (social network analysis)
• Qualitative research methods (discourse analysis, thematic analysis)
• Stakeholder management and communication
• Data visualization and presentation
• Strategic insights development
• Advanced quantitative analysis (social network analysis)
• Qualitative research methods (discourse analysis, thematic analysis)
• Stakeholder management and communication
• Data visualization and presentation
• Strategic insights development
Tools & Methods
• Card sorting facilitation
• Social network analysis (using Gephi and Excel)
• Video editing and analysis tools
• Participatory design techniques
• Interview facilitation
• Social network analysis (using Gephi and Excel)
• Video editing and analysis tools
• Participatory design techniques
• Interview facilitation
