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What do your customers "really" think?

Hacker News

What do your customers "really" think?

We have just launched an MVP for business to business customer satisfaction monitoring. http://www.clientheartbeat.com Our product helps identify at-risk customers and indicate trends with your individual customers that may need attention. You can then anonymously compare your scores against others in your industry. Awards in different areas of business can be earned to share with current and potential customers, or circulate among your team. We've demo'd the app to our group of alpha testers and now we'd love to get your feedback. Thanks in advance, The Team at projuce.com

Visit product View on Hacker NewsSep 6, 2012

Actual performance

14points

8comments

Made the leaderboard

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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.

best fitHighest predicted score across all platforms for this description.

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

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

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

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

27%27% 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

17%17% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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