We

We Just Landed Our First 5 Customers

Hacker News

We Just Landed Our First 5 Customers

Hey everyone, I’m thrilled to share that my startup, Symbols, just reached a significant milestone—we’ve landed our first 5 customers! *How did we do it?* In short, after countless discovery and demo calls throughout the initial stage of development, we talked to anyone we thought would use our product. We used the pain points and aspects of our demo that wowed the most impressed type of users, and created an initial landing page and some content over social media based on these insights. Allowing us to market the platform with messaging that was different to our competitors, because of the greater level of understanding of the problems they were having. *No free plan* Instead, we offer a lifetime deal with a 14-day money-back guarantee. This approach allowed our customers to test the platform, validated it quickly with actual paying customers instead of dealing with free users who might never upgrade, and I’m proud to say that *none of them have asked for a refund!* *Just like any business, it’s vital to understand what stage you are in.* For us, the focus was on validating whether we had a product users would pay for. Later on, we plan to offer a free plan for marketing/distribution reasons, but only after ensuring we have a solid base of paying customers. Many tools fall into the trap of accumulating free users with no clear path to revenue, essentially becoming a charity. Effectively mistaking movement for achievement. We wanted to avoid that. *The key insight here?* Early-stage products don’t need to be perfect, but they need to show promise of becoming something far greater than existing tools on the market. Our customers aren’t just buying the current version of Symbols—they’re investing in our vision and trusting our team’s experience and track record to deliver. And that trust has been crucial in these initial stages. *Looking ahead,* we’re planning to evolve Symbols beyond just a product. We’re going to double down on content, aiming to become partly a media company (every company needs to) to boost our distribution. So far, warm leads generated through content have been the main driver for acquiring these initial customers, rather than cold emailing or DMs. We’ll be producing more content that resonates with our audience—addressing their pain points and creating value even outside of our product, through initiatives like “Symbols University,” where we’ll educate by building with our platform, showcasing how it can save time and money compared to traditional tools. By aligning our content strategy with the problems our product solves, we hope to build a strong community and grow quickly over the coming months. I’m excited about what’s to come and grateful for the trust our first customers have placed in us. Here’s to more milestones ahead! Would love to hear any thoughts, feedback, or questions from this SaaS community! If you want to check out our landing page, it’s here: [https://symbols-beta.framer.website]

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Actual performance

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Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
94%94% 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 · Missing: mac, agents, macos
83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users, calls · Missing: plus, intuitive, reviews
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month, users · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: excited, exist, existing · Missing: https docs, just released, lua
28%28% 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 · Missing: arr, mrr, profit
20%20% 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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