Dashingly – A conversion-focused Strikingly for YouTubers

Hacker News

http://dashingly.co http://demo.dashingly.co What's good HN, just built a browser-based website builder called Dashingly. It was designed and built specifically to help YouTubers increase the number of visitors to their sales pages and online stores. I designed this to help YouTubers have a great looking, easy-updating/low-maintenance site, get more visits on their online stores, and ultimately get more online sales. Free accounts available at http://dashingly.co, and a demo of a site built with Dashingly over at http://demo.dashingly.co. I'd also love to hear your comments and am definitely open to suggestions for improvements! :)

Visit product View on Hacker NewsAug 18, 2014

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

59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: builder · Missing: plus, platform, intuitive

57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

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

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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