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Resume Reviewers – Get apersonal resume review by email within 48 hours
Hacker NewsResume Reviewers – Get apersonal resume review by email within 48 hours
I run a service called Resume Reviewers. What we are is a small startup that is solely dedicated to providing high quality, personalized resume reviews. All of the reviews are done over email because we feel that it makes for a more personal conversation between the reviewer and the client. I am just looking for some feedback more than anything. Thanks! If you are interested the site is: https://resumereviewers.com/
Share cardActual performance
5points
2comments
Did not reach leaderboard
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting73%73% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: email · Missing: mac, agents, macos68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: reviews · Missing: plus, platform, intuitive68%68% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released46%46% 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: personal · Missing: mobile apps, ios, entrepreneurs24%24% 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, revenue11%11% 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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