We solved our own problem and pivoted to the solution w Google API

Hacker News

Hey HN, 2 months ago I was cold calling to launch a startup idea. The problem was I was spending 2 hours every day manually putting together a list of businesses to call. I figured there’s got to be a better way. So my co-founder and I got started on an app that rendered a map for us to select a location, a slider to change the radius of the area selected, an input for us to type in a keyword and a button to click to pull a list of results from the Google Places API. We clicked the button. Results loading. Less than a minute later we had the same amount of data that it was taking me 2 hours to put together previously. We just saved 10+ hours per week. Then it dawned on us that this software would be valuable to others as well, so we polished it up and packaged it into LeadSnappr. It was a super fun project. Really happy how it turned out. Unfortunately the API credits cost money each search so I can’t let you try it out for free but if you or anybody you know is spending time manually putting lists together to cold call for their startup, let them know about LeadSnappr.

Visit product View on Hacker NewsMay 11, 2024

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

90%90% 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.

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

71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

43%43% 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

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

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.

Correct prediction on native model

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