A calmer, smarter way for remote customer service teams to manage support requests
Prio is a mobile-first support tool designed to help remote customer service agents triage and respond to tickets under time pressure. The goal was to reduce cognitive overload, improve prioritisation, and support agent wellbeing in a high-volume support environment.
Constraints: Mobile first, remote teams, high ticket volume, emotionally demanding work.
Role: UX/UI Designer | Client: Independent Project | Tools: Figma
Key constraints shaping the product
Across interviews and product audits, four constraints consistently shaped the design
Cognitive Overload
Too many incoming tickets, cluttered dashboards and constant notifications made it difficult for agents to focus, stay organised, or begin their day calmly.
Repetitive Tasks
Agents often retyped the same responses with only minor variations, losing valuable time and mental energy.
Difficulty Prioritising
With unclear hierarchy, vague labels, and long lists of similar looking tickets, agents struggled to quickly identify urgent or high-value requests.
Stress & Burnout
Remote agents lacked easy ways to ask for support, communicate workload pressure, or signal when they need a break.
Cognitive Overload
Cluttered dashboards showing too much information at once, multiple competing notifications, and no clear hierarchy for tasks. Discovered through competitor audits, heuristic evaluation of leading support platforms, and interviews revealing feelings of “not knowing where to look first” when starting a shift.
Prio features a distraction-free dashboard with intentional hierarchy – using whitespace, clear visual hierarchy, and simplified task grouping. Agents start their day with clarity rather than chaos. The dashboard gives them exactly what they need first – nothing more – creating a calmer entry point into a demanding workflow.
Repetitive Tasks
Frequent manual re-typing of common answers, inconsistent tone expectations, and limited quick-reply tools that didn’t adapt to context. Discovered through interviews where agents described spending “half the day saying the same thing in slightly different ways”.
Through AI smart responses – Prio suggests content-aware reply options based on ticket type, previous messages, and common FAQ topics. Agents can edit responses to match tone or context, reducing repetitive effort while still supporting personalised communication.
Difficulty Prioritising
Long list of assigned tickets with unclear urgency indicator, inconsistent tagging conventions, and limited filtering capabilities. Discovered through interviews and observation of agents scrolling from top to bottom because “there was no obvious way to know what needed attention first”.
Prio introduces clear priority tags and filters for urgency, source, and time received. Priority labels and improved metadata surface critical ticket details instantly, filters allow agents to triage based on urgency, channel or how long a customer has been waiting – supporting faster, more confident decision-making.
Stress and Burnout
No simple method for requesting help, uneven team workload, limited human connection with managers in remote environments, and no regular check-ins. Discovered through interviews where agents described feeling isolated, overwhelmed, and unsure when it was “acceptable” to ask for support.
A well-being check-in tool featuring a low-pressure slider lets agents quickly express how they’re feeling. If needed, they can request a check-in using a short, non-intrusive form. Team leads receive the information and follow up with support – restoring a sense of human connection and psychological safety.
"It finally feels like an app designed for us - simple, calm, and helpful" - User testing participant.
Testing showed that Prio provided a noticeably calmer and more intuitive workspace. Agents felt more confident triaging tickets, less overwhelmed by the interface, and more supported thanks to the integrated well-being check-in. The blend of clarity, prioritisation, and emotional support resonated strongly across participants.
