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Indie Compass – A CRM built for Reddit lead gen and outreach

Hacker News

Indie Compass – A CRM built for Reddit lead gen and outreach

Hi HN, I built Indie Compass ( https://indiecompass.app ) because managing leads and conversations from Reddit using spreadsheets and scattered DMs felt inefficient and prone to error. Many potential connections were getting lost. Indie Compass aims to solve this by providing a focused CRM specifically for Reddit interactions: - Contact Tracking: Add Reddit users as contacts, tag them, add notes, and track their status. - Conversation Management: Link contacts to conversations (currently DMs, comment thread linking planned) to keep track of interactions in one place. - Simple Automations: Basic automation for welcome messages or follow-ups based on tags/status changes. (Roadmap): Keyword alerts + post monitoring for lead generation next, then outreach strategies, campaigns and goals are coming after! The goal is to provide a streamlined tool for Indie hackers, and solo founders who use Reddit for outreach, without the bloat of general-purpose CRMs. It centralizes the information needed to follow up effectively. Tech Stack: Next.js, TypeScript, Tailwind, Supabase, Clerk, Stripe. Launch Offer: As part of this launch, the first 15 sign-ups get lifetime access for a one-time $19.99 payment. The landing page checks availability. Link: https://indiecompass.app I'm looking for feedback on the concept, usability, and features. Does this solve a problem you face? What's missing for your Reddit workflow? Thanks!

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
87%87% 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: user, stripe, using · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: lifetime access, efficient, users · Missing: plus, platform, intuitive
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
26%26% 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
23%23% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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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