CompeteDesk

CompeteDesk

Indie Hackers

Find buyer searches competitors already win.

CompeteDesk exists because buyers now compare software in search results and AI answers before they ever talk to sales. It gives teams a concrete weekly read on the searches and competitor mentions they are losing.

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Actual performance

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
TrustMRRFits verified-revenue profile · Strong signals: answers · Missing: mobile apps, ios, personal
56%56% predicted probability of success on TrustMRR, 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 · Missing: mac, agents, macos
54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
37%37% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, io · Missing: https docs, excited, just released
35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
30%30% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

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