VOZZi is a regional roadside assistance platform designed to modernize how drivers access help on the road. Through the VOZZi mobile app, users could purchase assistance plans, request towing services, or call for immediate support.
Role
UX/UI design lead
Timeline
March 2021 -
October 2023
Tools used
Results
400%
growth in digital
product sales
200k
growth in the
active user base
80%
reduction in service
waiting time
35%
increase in
user activation
Context
I led the UX/UI design of VOZZi, the first digital roadside assistance app in the Balkans. I designed core flows to reduce trust friction, introduced transparent user guidance, and built a visual system that powered major campaigns, contributing to a 400% revenue increase.
Problem
Beyond established local unreliable services, VOZZi faced a bigger hurdle: trust. Drivers in the Balkans were wary of sharing personal data with an app. Digital roadside assistance didn’t exist here before, so people had no mental model, no proof it worked, and no reason to trust it.
Data from analytics, call-center calls, and POS feedback showed one thing: users weren’t rejecting roadside assistance, but the uncertainty around it. I ran targeted research to understand their trust barriers and dropout points.
Research Methods
1:1 semi-structured interviews
To explore mental models, trust gaps and past experiences.
Prototype usability tests (Maze for Figma)
To validate flow clarity and spot drop-offs.
Call-center transcript analysis
To extract recurring complaints, questions and patterns.
POS (point of sale) seller feedback
To understand in-person purchase objections.
Interviews
I interviewed 8 drivers across the Balkans. Their varied experience and low digital trust helped uncover why drivers hesitate to rely on digital roadside assistance.
Target users
Active drivers in Serbia, Bosnia, North Macedonia
Age range
23–57
Criteria
Mix of young as well as experienced drivers with past roadside assistance experience
Digital trust profile
Medium to low
Recruitment method
Personal networks, referral from towing partners, call-center leads
Wireframes
After several sessions with the dev team, I introduced a gifting flow to drive trusted referrals. I created low-fidelity prototypes and validated them with users in Maze before moving to high-fidelity design.
Registration user flow - main user flow for new users registering to the app.
Registration user flow - main user flow for new users registering to the app.
Gifting plans user flow - gifting a free plan to an old or new user.
Testing
To validate the new onboarding and referral introduction, I ran a usability study with 100 users, of which 80 completed the full flow.
Insight
Users had no issues with onboarding and understood the plan was tied to their account, not their car. The friction appeared in the referral flow, where over 20 participants misunderstood the gifting mechanic and expected benefits from gifting free plans. This revealed a gap in communication and perceived value.
Solution
Based on feedback, I proposed an, incentive-driven referral model:
Refer 4 people → automatic plan upgrade
Refer 8 people → unlock the highest-tier plan
If already on the top plan → receive a base plan to gift
Every referred person gets a 5% discount
Validation
I suggested to the marketing team that we test the concept publicly by launching it as a small social media campaign to gauge real-world sentiment before development. The response was highly positive, confirming both the clarity and appeal of the new feature.
Revision
After positive initial feedback, I refined the flow and retested it. All 75 participants immediately understood the new gifting mechanic and reported a positive experience, confirming the direction was right.
Gifting plans user flow - gifting a free plan to an old or new user.
Shipped design
After the updates, the app gained 15,000 users in the first month. Better onboarding, clearer referrals, and coordinated TV, and brand campaigns boosted trust and helped drive 4× revenue and a doubled user base.
Final shipped designs - polished through iteration and validated by real user behavior.
Outcome
Improved onboarding, clearer referral flows, and stronger brand communication helped drive VOZZi’s growth. Between 2020 and 2023, these combined efforts supported a steady rise in daily revenue, peaking at $29,902 in a single day.
What I'd do next
Personalize onboarding to user context
Tailor the first-time experience based on trust level, driving experience, and region. New drivers and older, skeptical drivers need different explanations and reassurance.
Introduce in-app trust indicators
Surface live towing metrics, verified partner ratings, and average response times in context to reinforce reliability and reduce hesitation for first-time users.
A/B test plan explanations and pricing clarity
Run UX copy experiments on how coverage, response times, and plan differences are presented to further reduce confusion and improve purchase flow completion.