What was broken
Local live music is fragmented. Shows are scattered across venue pages, social posts, and ticket sites, so fans miss gigs and artists and venues lose audiences they had already earned.
Marketplace
Local Music Live
Live-music discovery platform — events, artists, and venues, city by city
- My role
- Founder and owner — direction across the business model, monetization, listing data operation, marketplace dynamics, go-to-market, product design, and AI-assisted development
- Current status
- Beta launch phase. No user, revenue, or growth figures are published.
Shown as case studies of my work; not offered as products or services.
Visit the live site
The origin of the platform
Local Music Live began during the initial COVID lockdown. I saw people losing work while musicians were performing livestreams on Facebook, so I created a Facebook group where musicians could play for an audience and invite voluntary donations. The donations went directly to Feeding America of Northeast Wisconsin. I ran the effort until conditions began to normalize, then continued managing the group and let it grow organically as a hobby project.
When AI-assisted development became more capable in 2025, I turned the idea into a working platform as a practical and enjoyable build. It wasn’t conceived as a major growth business. It is now a legal operating entity and a live, functional product, and the process gave me direct experience designing the data operation, marketplace dynamics, and user experience behind this kind of platform.
The decisions and workstreams I directed
I set the direction across these business, operating, market, and product workstreams. AI-assisted development is one part of the work — not the whole of it.
Business and ownership structure
Local Music Live LLC, and the decision underneath it: build a consumer marketplace that’s free for fans and earns through advertising, rather than charging the people the platform exists to serve.
Financial model and unit economics
Advertising as the revenue model, structured against the real cost of the operation — which in an aggregation business is dominated by sourcing and maintaining accurate data, not serving pages.
Operations and data logistics
The core of the business: sourcing, verifying, and refreshing event listings across cities, week after week, plus community-submitted events with review. Stale listings are indistinguishable from no listings.
Marketplace dynamics
Three sides — fans, artists, venues — and each needs the others before the platform is useful to any of them. Density in one region beats thin coverage everywhere.
Market and go-to-market
City by city across Wisconsin first — Madison, Milwaukee, Appleton, Green Bay, and more — building real density in one state rather than a national shell with nothing in it.
Product, workflow and AI-assisted development
The events, venues, and artists model; search and browse by date, region, or artist; saved shows, reminders, calendar sync and notifications; an installable app; and the AI-assisted development behind it.
Why the system exists
What became possible
Aggregation done well is an operations problem, not a scraping problem. Whoever keeps accurate, fresh listings across a region becomes the place that region checks — and the place local businesses want to be seen.
How I designed the response
Win one region properly before expanding. Build the listing operation as a repeatable process with community submissions and review, make the product genuinely useful to fans, artists, and venues at once, and let density — not coverage — be the growth metric.
What was designed
- Event, venue, and artist model browsable by date, region, or artist
- Listing pipeline: sourcing, verification, and refresh across cities
- Community event submission with review
- Saved shows, reminders, and calendar sync
- Notifications and an installable companion app
- City-level pages so each market has its own front door
- Advertising placement for local businesses
- Self-service promotion selection, duration, regional availability, and checkout
- Campaign history with placement status, views, clicks, and click-through rate
Directing a live marketplace whose usefulness depends on the data operation behind it — listings sourced, reviewed, and refreshed across cities, with fans, artists, and venues each needing the others.
- Marketplace design
- Data operations and logistics
- Advertising monetization
- Community submission workflows
- Go-to-market strategy
- Marketplace incentive design
- Consumer product design
- AI-assisted product development
How the System Works
A local data operation with a consumer product on top: listings are gathered and checked, organized city by city, and turned into something people come back to.
Layer 1
Listing operation
Keeping hundreds of upcoming shows accurate.
- Repeatable process for gathering upcoming shows (Automation)
- Community submissions reviewed before publishing (Human decision)
Layer 2
Local markets
Each city has its own front door.
- City-level pages across Wisconsin markets (Data)
- Events, venues and dates organized by market (Data)
Layer 3
Consumer experience
The retention layer.
- Installable companion app (Output)
- Saved shows, reminders and calendar sync (Communication)
- Notifications (Communication)
Layer 4
Commercial and support
A working promotion operation supports a free experience for fans.
- Event boosts, priority listings, and featured venue or artist placements (Workflow)
- Advertiser selects a market, placement, and duration (People)
- Regional slot availability and secure checkout (Outside service)
- Campaign status, views, clicks, and click-through reporting (Data)
- AI support with escalation (AI)
- Participant and admin boundaries (Security)
- Automation
- Human decision
- Data
- Output
- Communication
- Workflow
- People
- Outside service
- AI
- Security
Features that are part of the product, not separate products
Listing operation
The unglamorous core: a repeatable process for keeping hundreds of upcoming shows accurate across cities, with community submissions folded in after review.
Companion app
Installable app with saved shows, reminders, notifications, and calendar sync — the retention layer that turns a directory into a habit.
Multi-tenant separation
Participant and administrative boundaries enforced by the platform rather than by process.
AI Support
A reusable AI support layer built into the platform: platform-specific knowledge grounding, AI chat support, escalation to a human, support-ticket handoff, and administrative controls.
AI Support and multi-tenant separation are architectural patterns reused across the platforms rather than rebuilt each time.
What I took from it
In an aggregation business the data operation is the product. The interface is the easy part; accuracy, freshness, and coverage week after week are what people actually come back for.
This is a marketplace and operations business before it’s a music product. Directing the data operation, three-sided incentives, advertising model, and product draws on my background in company ownership, operations, revenue, and AI-assisted development.
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