VenueYield - Dynamic Seat Pricing Engine for Independent Event Venues

Independent music venues and comedy clubs are still pricing tickets in spreadsheets while StubHub scalpers print money on the delta. VenueYield is a plug-and-play dynamic pricing engine that watches demand signals and automatically adjusts ticket prices to maximize revenue without alienating regulars.

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Difficulty

intermediate

What is it?

Independent event venues — clubs, comedy rooms, small theaters — operate on razor-thin margins yet price tickets statically weeks in advance. They lose revenue on sold-out nights by underpricing and bleed unsold inventory on slow nights. VenueYield monitors day-of-week patterns, time-to-event, local weather and competing events from Ticketmaster's Discovery API, and adjusts prices in real-time via native Eventbrite and Stripe integrations. The venue owner gets a dead-simple dashboard showing demand score, current price, and projected revenue lift. Target: 10,000 independent venues in the US with fewer than 1,000 seats who manage events on Eventbrite or Stripe. Fully buildable now with public APIs and a simple rule-based ML pricing model that outperforms static pricing without needing neural nets.

Why now?

Eventbrite's API now supports ticket tier price updates programmatically — a capability that was read-only until mid-2025, making automated pricing finally possible without a custom ticketing stack.

▸Eventbrite OAuth sync pulls all upcoming events and current ticket inventory automatically.
▸Demand scoring engine uses time-to-event, day-of-week, and Ticketmaster competing events to set a 1-10 score.
▸Price adjustment rules fire via Vercel Cron and update Eventbrite ticket tiers via API with configurable floor/ceiling guards.
▸Revenue lift dashboard shows projected vs actual revenue per event with one-click price override.

Target Audience

Independent music venues, comedy clubs, and small theaters — 10,000 venues in the US averaging 200-800 seats, most running under 5 staff.

Example Use Case

Rosa owns a 300-seat comedy club. VenueYield detects that Saturday shows sell out 10 days early and auto-raises prices 20% for weeks 3 and 4 — netting her an extra $2,400 per month with zero manual effort.

User Stories

▸As a venue manager, I want ticket prices to adjust automatically based on demand, so that I capture revenue on sell-out nights without manually repricing.
▸As a venue owner, I want a price floor and ceiling guard on every event, so that I never accidentally price below cost or above what the market accepts.
▸As a venue booker, I want a weekly email showing actual vs projected revenue lift per event, so that I can prove the tool's ROI to my owner.

Acceptance Criteria

Eventbrite sync: done when all upcoming events and ticket tiers load within 10 seconds of OAuth connect. Demand scoring: done when score updates hourly without manual trigger. Price update: done when Eventbrite ticket tier price reflects the computed adjustment within 5 minutes of cron run. Floor/ceiling guard: done when price never updates outside the venue-defined range regardless of demand score.

Is it worth building?

$99/month x 40 venues = $3,960 MRR by month 3. Revenue share adds $500+ at 20 venues averaging $5k monthly ticket sales. $5k MRR realistic by month 4.

Unit Economics

CAC: $50 via direct email outreach and back-test demos. LTV: $1,188 (12 months at $99/month). Payback: 1 month. Gross margin: 93%.

Business Model

SaaS subscription $99/month plus 0.5% of incremental revenue uplift

Monetization Path

Flat $99/month base plus optional 0.5% revenue uplift share for venues that want performance-aligned billing.

Revenue Timeline

First dollar: week 3 via first paid beta venue. $1k MRR: month 2. $5k MRR: month 5.

Estimated Monthly Cost

Vercel: $20, Supabase: $25, Ticketmaster Discovery API: $0 (free tier), Eventbrite API: $0, Resend: $10, Fly.io for scikit-learn worker: $15. Total: ~$70/month.

Profit Potential

Strong at $8k–$20k MRR if 100 venues onboard — venue owners pay for clear ROI tools.

Scalability

High — marketplace of venue types, white-label for ticketing platforms, and API access for venue management software are V3 plays.

Success Metrics

Month 1: 5 venues in beta. Month 2: 15 paid venues. Month 3: average revenue lift of 12% per venue proven.

Launch & Validation Plan

Cold email 30 venue managers offering a free historical back-test showing how much they left on the table last quarter — close 5 betas before writing pricing logic.

Customer Acquisition Strategy

First customer: email 20 local venue managers offering a free 30-day trial with back-test showing last quarter revenue gap — convert on ROI proof. Ongoing: venue industry newsletters like Pollstar, r/eventplanning, direct outreach to Eventbrite venue partner list.

What's the competition?

Competition Level

Low

What's the roadmap?

Feature Roadmap

V1 (launch): Eventbrite sync, demand scorer, auto price updates, floor/ceiling guards, revenue dashboard. V2 (month 2-3): Stripe ticketing support, competing event alerts, Slack notifications. V3 (month 4+): per-venue ML model tuning, white-label for ticketing platforms, multi-venue dashboard.

Milestone Plan

Phase 1 (Week 1-2): Eventbrite OAuth, event sync, scikit-learn demand scorer working on historical data. Phase 2 (Week 3-4): price update API, Vercel Cron, dashboard live, Stripe billing. Phase 3 (Month 2): 5 paying venues, back-test report feature, Ticketmaster API integrated.

How do you build it?

Tech Stack

Next.js, Eventbrite API, Stripe Checkout, Ticketmaster Discovery API, Supabase, scikit-learn for pricing model, Resend, Vercel Cron — build with Cursor for pricing logic, Lovable for dashboard UI

Suggested Frameworks

scikit-learn, Next.js, Eventbrite API

Time to Ship

3 weeks

Required Skills

Eventbrite API OAuth, Stripe API for ticket price updates, scikit-learn linear model, Next.js dashboard.

Resources

Eventbrite API docs, Ticketmaster Discovery API docs, scikit-learn regression tutorial, Stripe API reference.

MVP Scope

pages/dashboard.tsx (event list + demand scores), pages/event/[id].tsx (price rule config), api/sync.ts (Eventbrite pull), api/price-update.ts (Eventbrite price push), lib/demand_scorer.py (scikit-learn model), lib/eventbrite_client.ts, lib/ticketmaster_client.ts, api/cron.ts (Vercel Cron scheduler), db/schema.sql (Supabase tables).

Core User Journey

Connect Eventbrite -> view demand scores for upcoming events -> set price floor and ceiling -> approve first automated adjustment -> see revenue lift in dashboard.

Architecture Pattern

Vercel Cron fires hourly -> Eventbrite API pulls ticket inventory and sales pace -> Ticketmaster Discovery API fetches competing events -> scikit-learn demand scorer generates score -> price adjustment rules compute new tier price -> Eventbrite API updates ticket price -> result logged to Supabase -> dashboard renders updated projections.

Data Model

Venue has many Events. Event has many TicketTiers. TicketTier has many PriceAdjustments. DemandScore belongs to one Event and is computed hourly.

Integration Points

Eventbrite API for event and ticket management, Ticketmaster Discovery API for competing event data, scikit-learn for demand scoring, Supabase for event data, Stripe for SaaS billing, Resend for weekly revenue digest, Vercel Cron for scheduled price updates.

V1 Scope Boundaries

V1 excludes: Stripe-native ticketing support, multi-venue franchise accounts, mobile app, custom ML model training per venue, white-label.

Success Definition

A venue owner the founder has never met signs up, connects their Eventbrite account, approves the first automated price adjustment, and renews after month one citing measurable revenue lift.

Challenges

Convincing venue owners to trust an algorithm with their pricing requires showing clear ROI from a historical back-test on their own past events — build the back-test demo as the sales tool, not a features list. Distribution requires direct outreach to venue managers, not self-serve discovery.

Avoid These Pitfalls

Do not build ML complexity before proving a simple linear demand model outperforms static pricing on back-tests — overthinking the model kills the timeline. Do not target Ticketmaster venues — they have proprietary systems and long sales cycles. Finding first 5 beta venues requires in-person or phone outreach, not landing pages.

Security Requirements

Eventbrite OAuth tokens stored in Supabase Vault with AES-256 encryption. RLS on all venue and event tables scoped to venue_id. Rate limit: 60 Eventbrite API calls per minute per venue. Input validation on all price floor/ceiling fields to prevent negative or zero values.

Infrastructure Plan

Next.js on Vercel, FastAPI demand scorer on Fly.io (1 CPU, 512MB), Supabase for Postgres and Vault, Sentry on both services, GitHub Actions CI on main branch deploys.

Performance Targets

Event sync for 50-event venue under 8 seconds. Demand score computation under 200ms per event. Price update API call under 500ms. Dashboard loads under 1.5s LCP.

Go-Live Checklist

☐Eventbrite price update tested in sandbox
☐Stripe payment tested end-to-end
☐Sentry live on Vercel and Fly.io
☐Vercel analytics configured
☐Custom domain with SSL live
☐Privacy policy and terms published
☐3 beta venues signed off on price adjustment accuracy
☐Fly.io rollback via fly deploy --image documented
☐Outreach email template drafted for 30 venue cold contacts.

How to build it, step by step

1. Scaffold Next.js project with Tailwind and Supabase client. 2. Set up Eventbrite OAuth flow and store access tokens in Supabase Vault per venue. 3. Build api/sync.ts that pulls all upcoming events and ticket tier data from Eventbrite API on schedule. 4. Build lib/demand_scorer.py as a FastAPI microservice using scikit-learn linear regression on days-to-event, day-of-week, tickets-sold-pace, and competing-event-count features. 5. Deploy FastAPI scorer to Fly.io and call it from api/price-update.ts. 6. Build price adjustment logic with configurable floor/ceiling per event stored in Supabase. 7. Build Vercel Cron job that runs api/price-update.ts hourly for all active venues. 8. Fetch Ticketmaster Discovery API for local events on same date and include in demand score. 9. Build Next.js dashboard with Lovable showing event list, demand scores, current price, and projected revenue with override controls. 10. Add Stripe Checkout for $99/month subscription and deploy to Vercel with custom domain.

Generated

April 5, 2026

Model

claude-sonnet-4-6

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