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Kolibri, a DIY music club in Sweden

Hacker News

Kolibri, a DIY music club in Sweden

We’re Maria and Jonatan, a married couple running a small music night in Norrköping, Sweden, called Kolibri. It’s not a software project. We run it through our own small Swedish company, pay artists, and do the operations ourselves. We do one night a month (usually the last Friday) in a restaurant venue called Mitropa. A typical night is about 50–70 paying guests. The first years it was DJs only, but last year we started doing live bands as well. We made a simple site with schedule plus photos/video so you can see what it looks like: https://kolibrinkpg.com/ On the site: * photos and short videos (size/atmosphere) * the kind of acts we book (post-punk, darkwave, synth, adjacent electronic) * enough context to copy parts of the format if you’re building something similar locally * for the tech-curious: we built our own ticketing system (first used in February) and a media ingestion pipeline for Instagram and external photographers How it started was accidental. I was doing remote music sessions with a friend in London (Ableton projects back and forth on FaceTime), ran out of beer, and walked into the nearest place. I got talking to Nahir, who runs Mitropa, and floated the idea of running a DIY music night there. He was up for it. What made it take off was doing things in person. People will show up alone if they trust the room. Maria ended up doing a lot of that work: greeting newcomers, noticing who looks uncertain, and setting a tone where people treat each other decently. Maria didn’t come from a DJ background. Klubbvärdinnan started as a joke name at Kolibri and then became her DJ moniker. She got good quickly, and after a first gig outside our own night she started getting booked elsewhere too. Marketing-wise, what worked best was very analogue: walking around town, visiting local businesses we genuinely like, buying something, introducing ourselves, and asking if we could leave a flyer. In the beginning we weren’t sure how to present it on social media. So we filmed headphone walks: one person walking through town listening to a track we picked. It looked good, people wanted to be in them, and afterwards we’d buy them a couple of drinks and actually talk. That turned a social media interaction into a real connection. It was a bit of luck, but it worked. Questions welcome about what worked, what failed, costs/logistics, and what we’d do differently if we started over.

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
91%91% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: new, context · Missing: mac, agents, macos
65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: video, month · Missing: mobile apps, ios, personal
62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus · Missing: platform, intuitive, reviews
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, pipe, io · Missing: https docs, excited, just released
40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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