Printavo v3, listening to customers and growing

Hacker News

Been going for about three years now on the side, learned to code in Rails from Michael Hartl's book, got help from friends and have been getting tons of feedback. I find using Uservoice's idea generation tool was the best along with emailing all customers a few days after they register to get feedback. I also found that a good amount of people will sign up and abandon the site quickly and I'm going to put in a JQ tour to help guide people around the app. Also been testing out Olark to gauge converting users. Anywho, I just launched the latest, responsive Printavo update with has a ton of cool things screen printers need and use on a daily basis. Any tips on converting more users are more than appreciated.

Visit product View on Hacker NewsOct 25, 2012

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

95%95% 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, email, using · Missing: mac, agents, macos

56%56% 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

56%56% 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

42%42% 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: users · Missing: plus, platform, intuitive

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

21%21% 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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