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Civic – Online Hub for Causes

Hacker News

Civic – Online Hub for Causes

Hi HN! Matias and Jessica here, we're the founders of Civic (https://civicapp.co/), an online platform that connects people to causes in their area. That could mean everything from volunteering opportunities to activism and politics. Every year, over 180M Americans contribute to social causes, yet doing so takes a significant amount of time and energy — information on how to get involved or take action often spreads through disconnected pages, newsletters, and word of mouth. Civic plans to solve this by creating a hub for people to find and organize events, connect, and donate to causes around them. We just launched our MVP in NYC, focusing exclusively on events. I (Matias) started working on Civic while still in college, where I also spent a lot of my time in politics, having worked with ActBlue and a presidential campaign. I also served as a hyper-local elected official in DC, where I represented about 2k constituents to the city. Jessica is a full-stack software engineer and spent 5 years working at Google before joining us. She's fully responsible for our tech and is the reason why we're able to build this at all. During my time in DC, one of the most interesting things I observed was how the causes that were most likely to get people engaged were the local/neighborhood issues that affected them directly. Yet, because of their local nature, those causes were also the ones least likely to get publicity. That plus the general lack of a true online hub for civic engagement led us to start Civic. The MVP is rough around the edges and we're definitely looking for ideas and feedback on how we can improve! Some of the features in our dev pipeline include an onboarding process to customize the content seen by each user (causes are very broad); easy and streamlined, no-fee donations to organizations; social "spaces" based on location and interests where users can meet and discuss issues with others; and much more! For those curious about revenue, we plan to monetize by introducing donations. Right now, over $300B are donated by individuals to non-profits in the United States each year, much of which goes through outdated platforms that charge high fees. We'd target smaller, local organizations that aren't well served by existing platforms, and would follow the same model as GoFundMe and a few other companies, allowing users to add an optional "tip" to Civic after each donation. From our research, this tends to lead to tips of about 6-8% per transaction. You can check out our MVP here: https://civicapp.co/ We'd really appreciate any and all feedback (especially related to features, new and existing), please let us know what you think! :)

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, organizations · 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: model, google, user · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
49%49% 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: plus, platform, exclusive · Missing: intuitive, reviews, host
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google, users · Missing: mobile apps, ios, personal
33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue, profit · Missing: arr, mrr, saas
15%15% 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.

Incorrect prediction on native model

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