Calibrate Rapid. A SaaS Evaluation Service

Hacker News

I've just launched a band new productised service called Calibrate Rapid. Calibrate Rapid is an in-depth actionable report that evaluates your SaaS and tells you exactly where you should be focusing your attention. It's delivered in 1 week and will help you find and implement the biggest wins to improve your business. It's an extensive written report that is accompanied by a video walkthrough and a suggested alternative layout for the screen of your choice. If you're a SaaS founder and are struggling to increase trial conversions, reduce churn or attract more customers then Calibrate Rapid is for you. You can find more information here: http://nathanpowell.me/ And of course I'm only too happy to get a conversation going here too. Good luck! Nathan ps. You can download a sample report on my website. I'd love to hear any feedback from SaaS folks. Thanks

Visit product View on Hacker NewsJul 9, 2014

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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

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Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, io · Missing: https docs, excited, just released

46%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.

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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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Acquire.comPre-revenue stage for this audience · Strong signals: saas · 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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