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Engage – Fun and Approachable Sticky Note Surveys

Hacker News

Engage – Fun and Approachable Sticky Note Surveys

Hello everyone, I'm Josh, one of the creators of Engage. I work in architecture and do a lot of community outreach. I've noticed that people really love to do activities like sticky notes to gather feedback. Unfortunately, sticky notes can get lost, be hard to read, or don't make it into any type of data analysis tool. We created Engage to bring these popular and familiar physical activities to the digital world. It functions like google forms but allows for the creation of sticky note surveys where people can place digital sticky notes anywhere on an image to leave their feedback. We've already used this to gather community input from thousands of project stakeholders and are now opening it up to users from around the world. Here is a short video about Engage: https://www.youtube.com/watch?v=OQJUKcVG_mQ Engage is free to sign up. Thanks for taking a look!

Visit productView on Hacker NewsMar 22, 2024
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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
94%94% 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, user, physical · Missing: mac, agents, macos
74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: video, google, users · Missing: mobile apps, ios, personal
67%67% 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
48%48% 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 · Strong signals: users · Missing: plus, platform, intuitive
41%41% 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 · 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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