We Build Landing Pages

Hacker News

Introducing my latest project, We Build Landing Pages. https://theredbit.github.io/webuildlandingpages/ Excuse the blatant infancy of the project but I take 'releasing early and often' pretty seriously. The goals of this project are to... 1. Build a solid network of clients who need landing pages while learning how to run a business and to help earn funds to survive while I search for a job. Long story, I'm in a rough spot and I'm trying to get on my feet. 2. Build and release open-source tools and foster the growth of a community based on this work to help developers write landing pages that rock. I would be thrilled to have feedback of any kind at all. Feel free to check us out and if you know someone looking for a landing page for any purpose, suggest that they get in touch! We're not claiming to be the best. We're looking for easier clients at the moment. As we progress and learn on this journey, our value to clients will go up. Persistence and patience is the key. Things will be changing and growing a bit, so stay tuned! I appreciate your time.

Visit product View on Hacker NewsSep 6, 2018

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

73%73% 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: open · Missing: mac, agents, macos

65%65% 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: io · Missing: https docs, excited, just released

42%42% 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 · Missing: mobile apps, ios, personal

37%37% 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

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: growth · Missing: arr, mrr, revenue

17%17% 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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