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Reach4Pitch – simplifying game pitching for developers

Hacker News

Reach4Pitch – simplifying game pitching for developers

As passionate game developers, my brother and I have been creating unique games and prototypes. Through this journey, we've faced a common challenge - effectively reaching and connecting with video game publishers. We noticed that each publisher had their own isolated method for pitch submissions, often through platforms like Gmail or Google Forms or their own forms. These methods lacked transparency, leaving developers uncertain about their pitch status. Enter Reach4Peach - bridging the gap between developers and publishers. Our platform streamlines pitch submissions and offers valuable feedback. We're making communication a two-way street, with transparency and acknowledgment. Watch our explanatory video: https://www.youtube.com/watch?v=uC65VfeC5u8 Though we're 1.5 developers with strong backend and test automation skills, our server-side rendered Django might not be the prettiest. It's live at https://www.reach4pitch.com/ (note: signups are closed, atm). We reached out to 50+ game publishers with cold emails via their public contacts. First wave: 4 positive, 1 negative, 1 neutral response. The second wave, after MVP launch, lacked feedback completely - possibly due to summer vacations or lost interest. Key question: Is pitching games without feedback a widespread concern? Or everyone okay with current one-way methods of communications? Our experience proofs It's still a problem, but we need publisher interest and collaboration - only something around 5-10+ publishers (which we cannot reach) can attract developers and indie studios to our platform With the current state, of things, we're considering moving on from the idea, selling the domain, and deactivating the VPS. Any advice or feedback is welcome, as we are a little bit lost and demotivated ourselves.

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Actual performance

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
76%76% 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: google, email · Missing: mac, agents, macos
62%62% 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: lua, ide, io · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: ios, video, google · Missing: mobile apps, personal, entrepreneurs
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, communications · Missing: plus, intuitive, reviews
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
11%11% 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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