AI · Live Events

EventBooker — Designing Conversational UX in the Age of AI

Planning an end-to-end trip around a live music event means juggling flights, hotels, merch, ticketing and fan communities across half a dozen disconnected apps. Fans lose context (PNRs in email, tickets in another app, hotel details in a browser tab), miss limited drops, and arrive stressed instead of hyped. There is an opportunity to unify the fan ecosystem into a single platform that amplifies event energy, simplifies planning, and unlocks new revenue streams for partners.

Role: UX Lead
Duration: Concept
Company: Concept project
Domain: Live Events · Consumer · AI Concierge

The problem

The approach

Design a unified fan ecosystem that takes a user from sign-in to the live event — booking travel, stay and apparel, joining the live stream and fan chat, unlocking membership perks and syncing with Spotify / YouTube / Weverse.

02.01

Opportunity spotting — identifying the market gap

Before sketching a single screen, I mapped where the fan economy was leaking value across five dimensions — cultural, behavioral, ecosystem, revenue and partner-side.

Cultural shifts — the rise of the idol economy and fandom travel as a primary reason to fly.
Behavioral patterns — group chats, merch drops and paid memberships as the connective tissue of fandom.
Ecosystem gaps — no unified platform stitching travel, ticketing, merch and community together.
Revenue blind spots — organizers leaving travel and membership leads on the table.
Partner needs — travel and hotel platforms hungry for high-intent, event-driven traffic.

02.02

Personas — who EventBooker is for

Five archetypes anchor the design — two fan-side, three business-side — so every screen has a clear primary user and a clear secondary beneficiary.

🌸 Young Vibing Traveler — energetic, spontaneous, books on impulse with friends to chase the next festival.
💎 Premium Fan — stylish, loyal, splurges for VIP access, collects merch, lives for exclusive experiences.
🎤 Event Organizer — strategic and metrics-driven, manages large events and tracks fan engagement.
✈️ Travel Partner — marketer chasing high-intent leads during event season.
🎪 Event Ecosystem Manager — connector of sponsors, hotels, merch and fans, builds partnerships from day one.

02.03

Parent → inner screen flow

Mapped a Login → Event Home → {Flights · Hotels · Merch · AI Assistant · Live Event · Membership · Integrations} flow so every parent surface had a single clear job and every inner screen extended it without breaking context.

Auth — social login via Google / Spotify / Apple.
Main — Lolla 2024 overview with quick nav across Flights, Hotels, Merch, Live, Membership.
Booking — flights (Booking.com / MakeMyTrip), hotels near venue, merch & apparel, AI concierge for end-to-end planning.
Inner — live stream + fan chat + fan-meet slot, membership tiers with holo sticker collectibles, and Spotify / YouTube / Weverse account sync.

02.04

Frame-by-frame screen map

Eleven frames walk through the end-to-end Lollapalooza Mumbai 2024 journey — from auth to event home, booking, inner experiences and secure payment — color-coded by surface type.

Frames 1–11: Auth → Main → Booking (Flights, Hotels, Merch, AI Assistant) → Inner (Live, Membership, Integrations) → Payment (Checkout, Success).

02.05

Live event as the emotional peak

Event-day surfaces collapse to what matters: live stream, fan chat ranked by signal, and a fan-meet reservation slot — designed so the app gets out of the way during the show.

02.06

Designing the Conversational Layer

fans ask it to plan stay + travel + outfit, and it stitches together inventory from booking, merch and ticketing partners into one confirmable plan.

Scenario

Guardrail: Sensitive or Restricted Actions

Scenario: User tries to share payment details or asks the assistant to complete a financial transaction.
Risk: Security, compliance, and data‑handling boundaries.
Designed assistant behaviour: Detect sensitive information, stop the conversational flow, redirect user to secure UI, maintain calm, supportive tone.
Response pattern: I can help you compare and prepare your booking, but I can't take payment details here. You can complete the payment securely on the booking screen. Want me to open it for you?
Outcome: User stays safe, assistant stays predictable, and the flow continues without friction.

Scenario

Human‑in‑the‑Loop: Policy or Legal Ambiguity

Scenario: User asks about room‑sharing rules, hotel policies, or anything requiring human confirmation.
Risk: Incorrect guidance, liability, misinterpretation of partner policies.
Designed assistant behaviour: Avoid giving policy or legal advice, encourage direct contact with the hotel, provide the correct next step, maintain trust and clarity.
Response pattern: Room‑sharing rules vary by hotel, so it's best to confirm directly with the property. I can pull up the hotel's contact details if you'd like to check with them.
Outcome: Assistant stays helpful without overstepping, and users reach the right human authority.

Scenario

Fallback: Out‑of‑Scope or Risky Intent

Scenario: User asks about reselling tickets at a higher price.
Risk: Legal issues, platform misuse, unethical behavior.
Designed assistant behaviour: Recognize out‑of‑scope intent, decline without judgment, offer safe alternatives, keep the conversation moving.
Response pattern: I can't help with reselling tickets at a higher price, but I can help you explore options like cancellations, transfers, or adjusting your travel plans. What would you like to do next?
Outcome: A graceful refusal that maintains momentum and trust.

02.07

Design Process

A separate, detailed case study documents the full research and design process behind EventBooker — from problem framing and competitive audit to personas, journey mapping, information architecture and iterative testing.

Read the design process case study →

The outcomes guiding project road map

Designing Connective Tissue — When a user journey spans multiple partner apps, APIs, and business models, the design challenge isn't to reinvent flights or hotels — it's to orchestrate the connective tissue. EventBooker's strength lies in how each surface (Flights, Hotels, Merch, Live, Membership) remains focused, while the AI concierge stitches them into a seamless, confidence-building experience.

Recommended Next Steps

Conversational AI Style Guide — Establish a style guide for tone, fallback logic, and micro-interactions to ensure consistency across all conversational surfaces.
Scenario Expansion — Gradually expand scenarios (e.g., cancellations, upgrades, loyalty rewards) to cover edge cases and maintain user confidence.
User Testing — Validate flows with a representative set of fans to ensure the AI concierge and unified booking journey feel intuitive and trustworthy.
Beta Rollout — Run controlled pilots with known fan groups to observe adoption, refine conversational flows, and stress-test integrations.

Membership and collectibles work when they're earned during the experience, not sold before it.
Emotional peaks drive action as much as feature lists do.