Practical CM Reporting & Analytics

Practical CM Reporting & Analytics

Indie Hackers

community management, health metrics, reporting

Any team working on a community needs to report the progress monthly. It takes at least one full day to prepare such reports. Our app allows one to get all needed reports without any action from the end user.

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Actual performance

1followers
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
TrustMRRFits verified-revenue profile · Strong signals: month, monthly · Missing: mobile apps, ios, personal
62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: user · Missing: mac, agents, macos
54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
26%26% 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
24%24% 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
8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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