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Hi guys, Noticed recently that one of my products had started getting a huge amount of traffic coming from ChatGPT and Perplexity, while another one had been getting zero. Went down a very deep rabbit hole trying to work out why the second wasn't being recommended, and found a bunch of things you can do to increase your chances (with some decent results after a week or two). So this website does a free scan of your website (no signup), creates a bunch of questions buyers could ask if looking for a product like yours, checks whether AI recommends your product or not, compares your results to your competitors and, most importantly, gives you a checklist of things you need to do to get recommended more often. You can then rescan and see whether your recommendation rate has increased or not. As I say, it's free to scan without signup. This has been pretty useful to me for my 5 products so far, so I hope it will be for you too. Any questions, issues or suggestions, please let me know. I'll respond in comments and to chris@plauditlabs.com. Thanks, Chris

Visit product View on Hacker NewsJun 24, 2026

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Did not reach leaderboard

Launch Intel predictions

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

73%73% 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.

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

61%61% 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 HuntOn track for Day 1 leaderboard · Strong signals: perplexity, chatgpt · Missing: mac, agents, macos

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

46%46% 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

28%28% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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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