An application to stop the barking of dogs with separation anxiety

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I created a software application that helps dogs with separation anxiety. The application creates audio log of dog's barking, so the user can find out exactly how much and when the dog has been barking. It allows to easily record sound clips that will be played back to the dog whenever barking is detected. The dog will recognize his owner's voice and calm down. The program has been in beta testing for over two years. It works surprisingly well and the feedback we have received has been very positive. We released a public version a few months back and it can be downloaded from http://www.digitaldogsitter.com. Please, tell me what you think. I'd appreciate any thoughts on the idea in general, the software itself, business model, or the web site.

Visit product View on Hacker NewsFeb 25, 2013

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

85%85% 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.

Indie HackersFits the IH revenue-focused audience · Strong signals: created, para · Missing: supports, reddit linkedin, podcasting

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

41%41% 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

32%32% 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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto

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

Incorrect prediction on native model

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