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Unwaffle – SaaS Trial Conversion Steroids

Hacker News

Unwaffle – SaaS Trial Conversion Steroids

Unwaffle is a tool that helps SaaS businesses with Free Trials make more money. It tracks every action that your trialers take, and finds out what sort of things make those trialers convert to paid subscribers. And it gives you tools to act on that information and boost your Trial Conversion Rate. Unwaffle started as an admin feature of S3stat, but it was so apparent after a few days that it could be useful for other businesses that I separated it out with an API and stuck it at a different URL, in case it turned out (which it did) that I wanted to polish it into a product of its own. I use it on a daily basis, and it has actually added enough revenue that I'm no longer worried that it would have been a waste of time to build it, should it turn out not to be commercially viable. It lives in the same sort of space as Mixpanel, but rather than being All Things For All People, It's opinionated and focused on shaking the churn out of your Trial Funnel. It's Onboarding Things for SaaS People, so if you're not one o' those or you don't care about that, it's not going to be useful. But if you are and you do, I've found that it leaves those general purpose analytics tools in the dust. Give it a try and let me know what you think! https://unwaffle.com/ Invite Code: ShowHN

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, para · Missing: supports, reddit linkedin, podcasting
66%66% 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.
TrustMRRFits verified-revenue profile · Strong signals: para · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: code · Missing: mac, agents, macos
44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
35%35% 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: revenue, saas, subscribers · Missing: arr, mrr, profit
31%31% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
22%22% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · 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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