2025
introduction
Exploring how AI and language filtering can simplify event discovery
Prototype
Wireframes
Lo-Fi Prototypes
Test
Usability Testing
A/B Testing
Feedback Sessions
Empathize
User Interviews
Empathy Map
Hypotheses
Define
Personas
CJM
POV-statements
How Might We
Ideate
Brainstorming
Crazy 8s
context
Designing a chatbot experience for finding events based on mood, interests, and location
Welo is a self-initiated concept app that helps users discover local events through an AI-powered assistant. The chatbot tailors recommendations based on plain language input — considering context, mood, and language preferences — making discovery faster and more relevant.
“
We don’t need another event app—we need one that rethinks how recommendations work.
main problem
Users struggle to find relevant local events across fragmented, language-biased platforms
Most event discovery tools require manual filtering, switching between apps, or scrolling through irrelevant lists. For users who prefer English or other languages, the experience is even more disjointed and unwelcoming.
research
Understanding how people discover events — and why it often feels overwhelming
I conducted 5 in-depth interviews with people living in different cities (Hamburg, Moscow, Tbilisi, Belgrade, and more) who occasionally or regularly attend local events. Participants varied in age, language preference, and digital habits.
Most platforms defaulted to German, and users couldn’t easily switch to English.
62%
Said they spend too much time searching for events.
46%
Open several websites and close them without choosing anything.
77%
Want recommendations that feel like they’re from a friend.
Based on user interviews, I created three personas representing distinct user needs and behaviors. These helped me empathize with different motivations — from planning family weekends to spontaneous social outings.
I mapped out the end-to-end journey of finding and attending an event — from the initial thought to post-event reflection. This helped identify emotional drop-off points and opportunities for product intervention.
Top Pain Points:
Too many events, but nothing feels right. Users feel overwhelmed by the volume of listings. Nothing truly resonates with them, so they often give up and stay home.
Searching takes too much time and effort. People browse multiple websites, spend 20–30 minutes looking, and still can’t find something they like. They want quick, relevant suggestions in one place.
Lack of trust in recommendations. Users don’t know who the event is for, what the vibe will be, or who else is going. They want suggestions that feel personal — like a friend’s tip — not a random list.
To move from insights to solutions, I translated qualitative data into pain points, opportunities, and testable hypotheses. I formulated clear problem statements for each persona and used them to guide ideation. I also wrote a GOAT statement, defined product value, and considered accessibility needs — showing my ability to think holistically about UX, business goals, and inclusivity.