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I

I made it easy to find and contact Streamers who would play your game

Hacker News

I made it easy to find and contact Streamers who would play your game

When releasing my games on Steam I needed to find Streamers that would play my game as a form of marketing before release. I used a platform called Woovit which is now shut down. I liked the platform as I got to connect with Streamers and they played my game. What I found difficult was finding the right one and would have to dig through so many profiles. For my next release I wanted to find an alternative way to be able to connect with Streamers. I wanted to contact them directly, but it's hard and labor intensive to do all the research and manually finding emails. There must be a better way. There's a few providers that have email lists, but it's not cheap. I know that I'm not alone, so I've done the hard work and collected a bunch of emails and put a price that's super affordable compared to others in the market. I can now easily find the right group of streamers that would play my game and can easily contact them with very little effort and digging around. More time to do game dev and less time spent on finding emails for marketing. My goal is to make marketing less painful for indie developers to give their game the best possible chance.

Visit productView on Hacker NewsSep 18, 2025
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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
79%79% 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.
TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal
58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews
57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: email · Missing: mac, agents, macos
42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide · 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 · Missing: arr, mrr, revenue
19%19% 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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