Caffeinator – New coffee shops delivered over text

Hacker News

Hey HN, I built caffeinator https://www.caffeinator.co/ as a side project around finding/discovering new coffee shops as a fun way to explore my neighborhood and go for a walk. We send a text at your desired frequency (daily to weekly) with a coffee shop near you. Honestly, there's nothing different here then going to to google maps/yelp, searching for a cafe, then discovering it that way, I'm just lazy and I felt like there were too many choices. It's definitely in an early stage, but would love any feedback. Surprisingly, someone picked it up on Nextdoor and wrote an article https://missionlocal.org/2020/01/caffeinator/

Visit product View on Hacker NewsJan 31, 2020

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

59%59% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

43%43% predicted probability of success on TrustMRR, 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

41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

18%18% 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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