HouseFix, Share and Track Home Projects

Hacker News

Wanted the HN crowds opinions on a re-launch that http://www.housefix.com just went through. It used to be a drupal based site that was pretty lackluster at best. We went through the process of gauging user interest and seeing where there pain points were. We then used that info and went through a redesign using backbone/node/etc. That brings us to the current v2 that is now live. The point of HouseFix is to provide a simple interface to track the home improvement or home maintenance projects that you need to complete. You can upload pictures of the current state of the project, pictures of what you want it to look like, and then the community can share insights and ideas about your project. Once we get enough people using it, the idea is that you could also open the project up to bids for contractors to provide ideas / estimates for your project. We have 10k+ registered users and are tracking engagement to see where there are issues with the UI/UX and see where we can optimize the funnel. Would love to get some feedback from the wisdom of HN on ways we could improve any part of the site and/or things we may have overlooked regarding user flow. Thanks

Visit product View on Hacker NewsSep 10, 2012

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, using, open · Missing: mac, agents, macos

83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: interface, users · Missing: plus, platform, intuitive

55%55% 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

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.

TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

9%9% 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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