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My first SaaS venture. Feedback welcome

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My first SaaS venture. Feedback welcome

My friend and I left our jobs a month ago to get our side project, Cloud Cannon, ready for launch. Cloud Cannon makes it easy to get a simple website with a CMS online and launched. It does this by: 1. Syncing with Dropbox. You drag your files into Dropbox, Cloud Cannon then syncs them to our server and makes them live on the internet under the domain you've provided. 2. Integrated CMS. Have your clients update their own website using our simple CMS. Add a class of "editable" to any div you want your clients to edit. All changes your client's make will be pushed live and saved back to your Dropbox. 3. Website Optimization. Cloud Cannon periodically optimizes websites. It minifies Javascript and CSS and pushes all website assets to a fast CDN. This is our first business venture so any feedback is more than welcome. I hope you find Cloud Cannon useful. http://cloudcannon.com

Visit productView on Hacker NewsJun 21, 2013
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
80%80% 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: using · Missing: mac, agents, macos
62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
47%47% 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
46%46% 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 · Strong signals: saas · Missing: arr, mrr, revenue
25%25% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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