I

I made a tool to help dev find the best streamers to promote their game

Hacker News

I made a tool to help dev find the best streamers to promote their game

I've worked with many indie game studios (even been a C-level in one). I've seen many of them spending days searching for streamers adapted to their game niche. There are thousands of great and creative streamers but most developers ended up only sending Steam Keys to the big names. It often was a waste of time because they're swamped, charge high fees, and their broad audience is not even the studio's ideal players. On the other hand, you have thousands of passionate micro-streamers that: - have hyper-engaged niche communities (higher conversion!). - mostly promote for free because they are eager for content to stream - often play very specific niches (cozy puzzle games for instance), so their audience is super-aligned with some game genres. But these hidden gems are hidden for a reason: it’s highly time-consuming to find them. You have to browse Twitch for hours and hours. Twitch mostly shows the bigger streamers so you'll be lucky to find 5 streamers that enjoy playing your precise game niche and that have the audience size you are looking for. As someone who's been in the video game trenches (and now a indiepreneur launching products), I felt there had to be a better way. That's why I built Seedbomb. It helps game developers spot and connect with relevant Twitch streamers in minutes because they can instantly download a list of streamers who play games similar to theirs. Then they can filter by audience size, language, and more to match their marketing strategy. They get the email of each streamers so they can reach them in 1 clic. Hopefully they'll start making their game viral. Sometimes, all it takes is 1 email to the right streamer!

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
88%88% 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: email · Missing: mac, agents, macos
64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios, video, way · Missing: mobile apps, personal, entrepreneurs
57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
47%47% 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, io · Missing: https docs, excited, just released
37%37% 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 · Missing: arr, mrr, revenue
14%14% 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.

Correct prediction on native model

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