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Get website visitor location, time and frequency of visit
Hacker NewsGet website visitor location, time and frequency of visit
Whurthay is a tool to track visitors on your website. Easy to use tool, with clean UI, that allows to get demographics and frequency of visit of users using your web based product. It segments users into different user pools, to identify different niche market segments. It also allows to identify and predict user behaviour, based on which market segment the new visitor belongs to https://whurthay.com
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive66%66% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, using · Missing: mac, agents, macos56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal55%55% 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 released48%48% 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, revenue10%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, crypto1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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