Oyster Alerts is live and looking for testers in London, England

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Hi everybody, I am happy to share my latest side project in the hope of gaining some value first users and feedback. If you use railways in London you will (or maybe not) be aware of the concept of "incomplete journeys". If you forget to tap in/out of a station with your travel card you will get charged the maximum fare. To rectify this you are required to manually log in to the TFL website and check for a refund. I find that awkward and time consuming. I decided to built Oyster Alerts to check for incomplete journeys and thought you might also find it useful. The site is very much an MVP now but does function and you will be alerted of incomplete fares. It would be awesome if you could check it out and give any feedback.. http://oysteralerts.com Thank you

Visit product View on Hacker NewsNov 22, 2018

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Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos

42%42% 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.

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

32%32% predicted probability of success on Indie Hackers, 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

27%27% 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

10%10% 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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