Soft-launch, first page on HN – here are the numbers

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[1/2] Thursday evening (Mar 26) we made a soft launch for https://uidesigndaily.com (a UI website that I built for my wife) The goal was to get some feedback, fix bugs and get about 30-40 subscribers in the mailing list, to see how the newsletter performs. The launch went better than expected, and the feedback was generally positive. Below are some numbers for those interested. I posted it to 4 channels, IH, HN, Reddit and Twitter. It was best received on HN with 203 points, it made it in the top 10, and it stayed on the front page for a good while. Reddit also surprised me, I posted in r/SideProject and got 26 upvotes and only positive comments.. ? That is so not what I expected from reddit... Was very pleasantly surprised to say the least. Analytics: - 6.659 Users - 6,757 New Users - 7,906 Sessions - 19,125 Page views - 61.81% Bounce Rate - 10.1% Returning Visitors Users timeline: - Mar 24 - 0 Users - Mar 25 - 4 Users [Soft Launch] - Mar 26 - 2458 Users - Mar 27 - 3693 Users - Mar 28 - 706 Users - Mar 29 - 186 Users - Mar 30 - 190 Users As you can see, there’s been a spike and seems like it’ll stagnate around ~150, but it remains to be seen. It might dip even further. Newsletter: - 546 Subscriptions - 52.1% Open Rate - 6.7% Clicks - 7 Unsubscribes Slack Community: 40 Members. Interestingly enough, the Slack ad only received 30 clicks total. This means most users came through the welcome email, which has a slack community ad included. Ad Performance: - 35744 Impressions - 836 Clicks on Website - 8 Clicks in Newsletter

Visit product View on Hacker NewsMar 31, 2020

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Actual performance

6points

8comments

Did not reach leaderboard

Launch Intel predictions

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

82%82% 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: slack, user, new · Missing: mac, agents, macos

77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

Hacker NewsStrong engagement from HN community · Strong signals: ide, 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.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription, subscribers · Missing: arr, mrr, revenue

29%29% 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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