I made reverse Google Analytics at a hackathon last weekend

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I was at a hackathon last weekend and made a neat tool to help online store owners see what websites were showing up in chatbot responses. The theme was 'agentic commerce'. I realize this has nothing to do with giving an agent my credit card but I was inspired to build this because there was a lot of discussion about how people were using ChatGPT and the like to recommend stuff to buy. It's totally free to use, but I got some feedback from the judges that this was genuinely useful, so I added a sign up link at the bottom. If anyone ends up pre-ordering it, I'll build out the functionality to track prompts over time and crawl those webpages to see how often the citations link back to target domains.

Visit product View on Hacker NewsJun 25, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, agentic, google · Missing: mac, agents, macos

71%71% 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 · Missing: supports, reddit linkedin, podcasting

70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, 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

36%36% 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

34%34% 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

13%13% 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

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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