Prodscape.net – Map your mobile app

Hacker News

Hello HN, Long-time lurker, first-time poster here. I've created a service that creates a "flow map" of your mobile app. Check it out at: https://prodscape.net . The goal is to reduce last-minute regressions, promote holistic discussion, and help develop more ownership within an organization. This is something that I would have liked to have had when I was working at a big company. Some caveats: 1.) Only iOS is currently supported but Android-support will be coming soon. 2.) You need a developer-signed IPA file (see the guide on creating an IPA file here: https://prodscape.net/finding-ipa.html). I would appreciate your thoughts on: 1.) your barriers to trying it 2.) your impressions of the map 3.) whether you're interested in applying this within your team 4.) anything else. Don't have access to an IPA file? Email me at illahi@prodscape.net and I will send you one to try. Thanks!

Visit product View on Hacker NewsMar 7, 2022

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

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best fitHighest predicted score across all platforms for this description.

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

56%56% 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, io · Missing: https docs, excited, just released

46%46% 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 · 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: soon · Missing: plus, platform, intuitive

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

21%21% 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.

Incorrect prediction on native model

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