Tried a Google Ad campaign and failed

Hacker News

Hi all! I tried Google ad for my SaaS (MediaFa.st), but ended up loosing $50 over 4 days. Today I made my second attempt and I can recommend to all - research or ask someone who knows first, may save you tons of time and money… For example I only today learned that there are 2 types, and I used maximum spread one (shows everywhere, YT, apps, websites etc) and it didn’t work, but there is a search focused one and this one may generate real traffic!

Visit product View on Hacker NewsMay 25, 2025

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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

91%91% 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 · Missing: https docs, excited, just released

65%65% 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

60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

26%26% 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

15%15% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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