FOMOFix connects two sides of the same problem. Fans struggle to find events that fit them. Venues and artists struggle to see where real demand is building. FOMOFix sits between them as both a discovery product and an intelligence product.
The vision is to become the default layer for personalised live event discovery and demand insight.
Discovery is scattered across socials, ticketing sites and venue pages. Events are easy to miss, and there is no single place that reflects each person's real taste.
Decisions about where to book, what room size to choose and how to route tours are still partly driven by gut feel and partial data.
FOMOFix is a dark themed, modern interface that pulls together event data and fan taste signals into a simple personalised feed.
As fans use the platform, anonymised signals are turned into insight for venues, artists and promoters on where interest lives and how it shifts over time.
The platform is designed to work with existing ecosystems instead of trying to replace ticketing or streaming. It connects taste and intent to the live side in a way those systems usually do not.
The live entertainment and ticketing market is large and established, but there is still no dominant product that focuses on personalised discovery and open, accessible demand intelligence. Streaming platforms know what people listen to. Ticketing companies process transactions. Social platforms carry the conversation. FOMOFix is designed to sit between them, working with their data rather than trying to replace them.
The initial focus is on a single country and a few launch cities with strong live scenes. The model can then be replicated in other regions using the same core technology and playbook, adding local partners as needed.
Deliver a working MVP focused on fan value and event discovery so users have a reason to connect their services and use the platform regularly.
Provide early dashboards and summaries to a small group of venues and artist teams, validating which insights are most useful day to day.
Add tools that help with routing, room sizing and timing decisions using aggregated fan behaviour and long term patterns.
At scale, support labels, agencies and larger partners with aggregate insight into how live demand moves across regions and scenes.
The model blends broad reach on the fan side with deeper value on the industry side.
The early focus is on validating fan engagement and core value. Monetisation deepens as the data set and partner network grow.