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Upda – Find places near you to do work

Hacker News

Upda – Find places near you to do work

This summer I started working with some partners on a software consulting company to tackle a bunch of the issues I see happening at local small businesses and startups. (Check out parkandeaton.com and the blog there [or email me] for more details.) To drum up support for and interest in my company, we demonstrate Upda (beta), a small application to find decent workplaces near you. I find myself in the city constantly worried I'll pick the wrong coffee shop that has no restroom or no wifi. It may have been easier to simply make a Google doc. But this is slightly more fun and there are many ways in which Upda can engage users in the future. It is local only to Philadelphia (where we are based) right now. You can still use it, but only locations in the Philadelphia area are accepted. We will definitely look into expanding as we vet the idea. A true MVP, this is one of our first ventures into "app"-space as a company and we look forward to receiving your thoughts and criticisms. https://updaapp.com

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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, user, email · Missing: mac, agents, macos
59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
54%54% 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: google, users, way · Missing: mobile apps, ios, personal
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: started · Missing: supports, reddit linkedin, podcasting
32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
29%29% 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
16%16% 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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