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Our first sales with our Alt-Text Generator SaaS

Hacker News

Our first sales with our Alt-Text Generator SaaS

Hey everyone! I wanted to share some exciting (and humbling) learnings from launching our very first SaaS product: the AI Alt-Text Generator, available as an API or WordPress plugin. When we initially launched, we didn’t get any sales in the first couple of weeks, which was pretty discouraging. But just recently, we made a breakthrough—we had three purchases and officially welcomed our first-ever customers! Sure, the revenue might still be small, but honestly, seeing those first conversions felt amazing. It’s a huge motivation boost to know that people are willing to pay for something we built. What Changed? We made quite a few adjustments to the website and pricing along the way, and it looks like one of them finally hit the mark. Originally, we only offered a “pay-as-you-go” model, dynamically charging per usage. However, we noticed that this might feel too uncertain or risky for some users. So we introduced fixed pricing packages—one-time payments for a set amount of usage. Guess what? All three of our first customers opted for those fixed packages! I’m pretty sure it’s because people generally dislike subscriptions and would rather pay a fixed amount upfront than commit to something intangible. Next Steps We’re planning to reach out to our new customers to learn how they discovered us. Interestingly, we had Google Ads running for a few weeks, but we actually turned them off the week before the purchases came through. Coincidence? Maybe. But we definitely want to dig deeper and understand what worked. Would Love Your Input Any feedback or insights on pricing strategies or customer acquisition would be super helpful. Also, if anyone has experience launching their first product and figuring out what worked (or didn’t), I’d love to hear your stories! Thanks for the support—this community is awesome!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
93%93% 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: model, google, user · Missing: mac, agents, macos
69%69% 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: ide, io · Missing: https docs, excited, just released
34%34% 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, subscription · Missing: arr, mrr, profit
31%31% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google, users, way · Missing: mobile apps, ios, personal
29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: introduce · 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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