91.5% fewer data loss complaints through UX Research
How I helped rebuild user trust and reduce critical complaints through a research approach centered on users’ real-world context.
- Role
- UX Designer & Researcher
- Context
- Public healthcare app
- Focus
- UX Research · Data loss perception · Trust
- Outcome
- 91.5% reduction in complaints
Overview
Have you ever been using a system, working for hours, and suddenly it feels like an important piece of information just disappeared? Trust in the software vanishes, along with the time you’ll spend trying to figure out what went wrong.
Usually, our first instinct is to blame the code. But in this case, it was actually a UX issue that created the perception of data loss — inside an app used by public healthcare professionals to register and monitor citizens’ health data.
The project focused on rebuilding user trust through better communication and clearer system visibility.
I led the entire discovery process as UX Designer & Researcher.
- Research planning and method definition
- Quantitative and qualitative research
- In-depth interviews
- Data analysis and insight synthesis
- Workshop facilitation and co-creation
- Wireframing and prototyping
- Continuous feedback loops with the product team
91.5%
Reduction in complaints related to perceived data loss within one year — from 20% of total support requests to just 1.7%.
Of total support tickets classified as “data loss”.
Diagnosis
Although users reported data loss and “disappearing records”, deeper investigation revealed the issue was not a technical failure but a UX one — specifically, the absence of Nielsen’s heuristic “Visibility of System Status”.
Due to data-protection regulations, only one professional could be responsible for a citizen’s record at a time. When another professional re-registered the same citizen with a different login, the previous professional would lose access to that data — and the system provided no visibility about what had happened.
Without feedback, users interpreted this as data loss. The lack of communication generated frustration, duplicate work in notebooks and spreadsheets, mistrust in the platform, and a high volume of support tickets.
Visibility of System Status
A usability principle that refers to a system’s ability to inform users about what is happening through clear and timely feedback. Its absence here was the root cause behind the entire perception of data loss.
Design Process
From stakeholder mapping to results — a research-led sequence.
- 01Stakeholder Mapping
Gathering existing knowledge across teams.
- 02Questionnaire
20 open and closed-ended questions.
- 03Persona
Realistic profiles based on evidence.
- 04Brainstorm Workshop
Aligning the team and shaping research questions.
- 05User Interviews
In-depth conversations with healthcare professionals.
- 06Prioritization
Categorising issues by urgency and impact.
- 07Solution
Co-created with the product team.
- 08Results
Monitoring impact via tickets and surveys.
Stakeholder Mapping
Before defining the research stages, I assessed the information already available inside the company about users and the app’s usage context. This step was essential to identify knowledge gaps and to optimise the research process.
- Technical support tickets and informal user feedback.
- Usage reports extracted from the system, when available.
- Conversations with support and quality assurance teams.
- Reports from the product team.
Although perceptions existed about issues like data loss and system slowness, there was still a lack of structured, up-to-date information about the reality of the professionals using the app. That reinforced the need for deeper field research combining quantitative and qualitative data.
Persona
To better understand who the app’s users were, I developed a structured questionnaire with 20 open and closed-ended questions, distributed online via Google Forms.
The quantitative analysis was complemented by in-depth interviews, which validated behavioural patterns and contextual nuances. Combined, these approaches produced realistic personas that reflected both the technical and emotional realities of healthcare professionals working in the field.
- Work routines and responsibilities
- Technology usage and internet access
- Pain points, frustrations and workarounds
- Motivations, goals and personal challenges
- Accessibility needs (vision, hearing, etc.)
Brainstorm
I facilitated a brainstorming session to align the team’s expectations and discuss findings from the first stage of research. Everyone had the opportunity to share their questions and uncertainties — the things they hoped users could clarify.
From the analysis of previous data and the questions raised in the session, I built a semi-structured interview script to deepen understanding of the critical issues identified.
User Interviews
After defining the personas and facilitating a brainstorming workshop with the product team and stakeholders, I conducted in-depth interviews with healthcare professionals.
The brainstorming session helped align everyone's assumptions and identify the key questions we still needed to answer.
Using these questions as a foundation, I created a semi-structured interview script to explore the users' daily routines, pain points, decision-making process and the real context in which the application was used.
These interviews allowed me to validate assumptions, uncover unexpected behaviours and identify the root causes behind the perceived data loss reported by users. The insights gathered during this phase became the foundation for the final design decisions and solution proposal.
Prioritization
Throughout the research process, several issues were identified and categorised — together with other stakeholders — into three priority levels. This case study focuses on the highest-priority issue: perceived data loss.
Perceived data loss
Issues that required immediate attention — chosen as the focus of this case study.
Workflow friction
Issues to be addressed after the urgent ones.
Improvement opportunities
Issues to be further explored and implemented in the future.
Proposed Solution
A set of research-backed improvements focused on visibility, feedback and control.
Clear synchronization status
A visual indicator that always shows the current data-saving state, so users know exactly where they stand.
Visual feedback
Immediate, contextual feedback for every relevant action, closing the loop between user intent and system response.
Smart notifications
Alerts when records are deactivated, deleted or re-registered by other professionals.
History of changes
Action history and synchronization logs to increase transparency and user control.
Identification of the actor
Clear identification of who performed each action inside the system.
Re-registered patients page
A dedicated view for patient records deactivated due to re-registration by another professional.
Results
After the improvements were delivered, we monitored their impact through two main channels: technical support tickets and a structured user satisfaction survey.
📉 Reduction in support tickets
Complaints related to “data loss” dropped by 91.5% in April 2024 compared to April 2023 — clear evidence that the main pain point was directly resolved. The transparency introduced by the new module for viewing deactivated records reduced frustration and duplicate work, and cut the time spent by support teams on explanations and reorientations.
📈 Feature evaluation
The feature that allows users to see patient records deactivated due to re-registration received an average satisfaction score of 3.54 out of 4 points. Most users perceived direct value in the improvement, regaining a clearer understanding of what was happening to their records and control over their information.
- 01
91.5% reduction in complaints related to perceived data loss.
- 02
Reduced workload for the support team.
- 03
Improved user confidence and trust in the platform.
- 04
Better understanding of the system’s behaviour.
- 05
Lower operational cost across support and product.
Key Learnings
Research showed the problem was not technical. Simple UX improvements solved a problem initially believed to require engineering effort. Sometimes visibility creates more value than complexity.
Complex problems can have simple solutions
If we know the right questions to ask. Visual feedback about re-registrations proved more effective than any major technical refactor.
Empathy for real-world context transforms products
Understanding the actual working conditions of healthcare professionals — in the field, offline and under pressure — was essential to build empathy within the team.
Cross-functional collaboration is key
Involving support, business, QA and development teams from the beginning made the implementation process more aligned and efficient.
Thank you for your attention!
This case study has been anonymized. The flows, screens and data presented have been adapted and recreated exclusively for portfolio purposes.