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GeoTreat.com: Delight Website Visitors by Geolocation

Hacker News

GeoTreat.com: Delight Website Visitors by Geolocation

Hi everyone, this is my second Show HN attempt.. I would really love to see what the community thinks. I went from idea to implementation extremely fast, but I am also quite happy with the value that a simple prototype can deliver. https://GeoTreat.com/ - With a tiny snippet of code, you can drop "Treats" on your web pages. That means, depending on your visitors location, they will be shown a special (modal popup) promotion of your choice. The treat can be placed anywhere in the world and have any radius. Have a moment to spare any feedback on GeoTreat.com? The home page has a quick (and sloppy) 1min 30sec video that gives a quick overview and demo. If anyone has any criticism, feedback, questions, I would absolutely love to hear what you have to say. If anyone wants to see a Live demo, let me know your general whereabouts in the comments. I will place a treat on your area and send you a URL. -Jordan

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4points
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Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: tiny, code · Missing: mac, agents, macos
67%67% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
40%40% 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
15%15% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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