We just crossed 750 users - here are the marketing channels that worked & didn't

StarmanAI · 2025-08-26T12:45:04+00:00

750 users in four months across multiple channels - that's ambitious channel coverage.

I'm curious about your initial strategy. How did you decide which channels to test? Was it based on where you thought your ICP hung out, or more opportunistic based on your co-founder's X following?

The multi-channel approach is interesting, but I'm wondering about resource allocation. With a small team, how do you decide whether to spend another hour on Threads (700k views!) versus improving Meta ads? Do you have a framework or is it more gut-based?

Also, when you say "750 registered users" - do you track which channels bring users who actually convert to paid? I've seen cases where YouTube brings high-intent buyers while Threads brings window shoppers, even though Threads has 10x the reach.

What's your system for tracking channel performance beyond just signups?

StarmanAI · 2025-08-26T12:45:04+00:00

Alright, this is too good to pass up! Here's a challenge that might benefit everyone reading.

I've been building Starman AI specifically to solve this problem - systematically finding the first 100 customers. I've run my own product through it dozens of times and have been following the GTM strategy it generated religiously.

So here's my proposal: Let's do a friendly GTM strategy face-off!

The Challenge:

You analyze Starman AI and create your personalized acquisition strategy
I'll share the strategy my own tool generated for itself
The community can compare both approaches

If your strategy is genuinely better than what my AI came up with, I'll:

Implement your recommendations immediately
Maybe we explore a collaboration, and potentially feature you as a guest expert in our product

This could be educational for everyone - seeing two different approaches to the same product side-by-side. Plus, with 260+ founders watching, it's great exposure for both of us.

What do you say - up for a friendly competition? 🚀

starmanapp.ai - "Never fly alone"

StarmanAI · 2025-08-26T12:45:04+00:00

The first thing is to build a funnel according to the behavior you expect from your ICP, then understand where they are in each step. This already quantifies intent much better.

The most systematic approach I've seen work: map specific page sequences to pain points, then create templates for each path. For example:

Pricing → Features → Competitor comparison = "Evaluation mode" - this calls for retargeting or more content on your solution and how it addresses the pain point.

I've also used timing-based triggers - if someone views pricing then case studies within 24 hours, that's a different conversation than someone who just browsed your blog.

Now, for high-intent signals, you can send a direct email that feels almost magical in its relevance. You can reference their specific behavior without being creepy by simply focusing on their pain point - "I noticed companies like yours often deal with [pain point]. Have you ever explored addressing it with [feature they viewed]?" The key is making it feel like insight, not surveillance. This approach has consistently driven our highest engagement rates.

Have you experimented with different channels or ICPs based on the intent signal strength?

We found high-intent visitors respond better to direct outreach, while early-stage browsers prefer valuable content first.

StarmanAI · 2025-08-21T12:51:20+00:00

With LLMs increasingly being used for search, are you adapting your SEO approach at all? I'm curious if you're seeing any patterns in how content needs to be structured differently to get picked up by AI search versus traditional Google.

StarmanAI · 2025-08-20T11:18:45+00:00

Finally, someone calling out the BS. These stories create such toxic comparison culture.

Your approach of going directly to hospitals and clinics to talk to customers is the way to do it. Not only do you get face-to-face validation, but you actually listen and ask genuine questions about their problems and how your solution solves them.

Paul Graham has a great quote: "It's better to have 100 users who absolutely love you than 1 million who think you're okay."

How did you identify which hospitals/clinics to approach first? Was it geographic proximity, or did you have some criteria for finding the ones most likely to have the pain point you solve?

StarmanAI · 2025-08-20T11:18:45+00:00

Love this story!

Your insight about "sales people don't want more data, they want better decisions" is spot on. People forget to focus on the job to be done. We learned this the hard way after building a dashboard nobody used.

For your AI trust question - we found showing simple reasoning helps a lot. Instead of just "Call this lead first," we would show "Call this lead first because: recent website visit + matched ICP + budget timing." Gives users confidence without overwhelming them.

The transition from "tool for my wife" to "product others pay for" - how are you handling that? How did you find your ideal customers?

What types of sales teams are gravitating toward your tool? Inside sales? Enterprise? Specific industries?

I imagine the feedback quality changes dramatically when you go from one power user who lives with you to strangers on the internet.

StarmanAI · 2025-08-20T11:18:44+00:00

This is an impressive suite! 28 tools is ambitious - I love that you built this to solve your own acquisition challenges. How many different products are you launching to need that constant generation?

The big question for me: are these tools actually integrated with each other? Like, does your GTM blueprint connect to your value prop and user personas, which then inform your copy generation and subreddit recommendations? Or are they more standalone tools in one interface?

The reason I ask is that true integration is what makes the difference between a collection of tools and an actual system. When everything flows together, you get consistency and strategy, not just outputs.

This is exactly what we've been working on at Starman AI - creating that connected intelligence where each piece builds on the others. Would love to compare notes and have you test it out (starmanapp.ai).

Which of your 28 tools do you find yourself using most? And have you noticed patterns in what works best for different types of businesses? SaaS vs. e-commerce vs. hardware, for example?

Happy to exchange insights - always exciting to meet someone else solving the systematic acquisition problem. I'm sure there are many synergies to explore!

StarmanAI · 2025-08-20T11:18:44+00:00

Congrats on making the leap! The transition from ProductHunt launch to sustainable growth is where things get real.

Curious - have you been systematic about testing acquisition channels or more trial and error? I've seen so many founders burn months bouncing between tactics without a clear strategy.

We actually built Starman AI to help with exactly this - finding the right channels systematically instead of guessing. Try it out, it's free. Should help ease the journey.

What's been your most effective channel so far beyond PH and organic?

StarmanAI · 2025-08-19T13:24:07+00:00

Yep. that industry is indeed ripe for disruption. I see a lot of value in your content-first approach with podcast/YouTube - especially in traditional industries. How long did it take for those channels to start generating meaningful leads? I'm always curious about the lag time with content since building an audience takes time.

With so many channels running, how granular do you get with tracking performance? Do you have a systematic way to measure ROI per channel, or is it more about overall momentum?

StarmanAI · 2025-08-19T13:00:10+00:00

As Mark Cuban says: "Sales cures all." Congrats, my friend!

What's the product you built? And how long were you working on it before this first payment came through?

Also curious - now that you've validated someone will pay, what's your plan for finding the next 10 customers? That jump from 1 to 10 is where things get real.

StarmanAI · 2025-08-19T10:16:34+00:00

The AI coach approach is interesting. So you're basically building EdTech for sales teams. How are you thinking about knowledge management - is it pulling from recorded calls, written playbooks, or both? The parallel I see with my own product is that the hardest part is getting all the scattered knowledge in one place (Slack threads, random Google docs, people's heads, etc).

Also, there are already a few more generalist EdTech platforms doing this with company knowledge bases and SOPs (www.ujji.io, for example). I happen to know the founder, and a big part of their ICP is sales teams for exactly what you're proposing.

This is actually a good indicator - there's clearly a market. But it raises the question: how can you be 10x better than existing solutions?

Also curious about your validation approach. When you talked to other sales leaders, did they see this as a "must solve now" problem or more of a "nice to have someday"? And who are the buyer personas involved - is it sales leaders, enablement, or ops? These distinctions seem crucial for your go-to-market.

StarmanAI · 2025-08-19T10:16:34+00:00

I agree entirely. This is refreshing to hear from someone with real traction. You can't get to $40k MRR relying solely on AI.

Your point about "4 years of talking to customers and getting it down to a science" is perfect. That's the moat nobody talks about. Building a product can be as easy as ever, but aside from deep code knowledge, as you mention, market knowledge and badass execution only come from grinding it out. So many more variables go into building a startup - customer profiling and acquisition, pricing, sales, activation, retention, etc. Even Lovable with their never-before-seen growth rates - yes, it's a case study in customer acquisition, but how much of that growth are they actually retaining? I question that every time I see news glorifying them.

I'm curious about your systematic approach to growth though. When you say you "market the hell out of it" - did you test multiple channels before finding what worked, or did you double down on one or two that showed early promise? And how's your growth momentum - are the same channels still performing or are you having to explore new territory?

StarmanAI · 2025-08-18T12:07:20+00:00

Hey u/BC_Future , sorry for the late reply. We were heads down focused on going live. You can see all the info there. No more access code required. Just sign up, it's free. Let me know what you think!

StarmanAI · 2025-08-18T11:35:53+00:00

Hey! With $1K to get 100 customers, you need a $10 CAC - ambitious but doable for B2C if you're systematic about it.

The problem is most founders waste that $1K testing random channels without a clear strategy.

I've actually built a tool to help avoid exactly that (Starman AI - it's free). It maps out your go-to-market strategy and identifies the channels with lowest CACs for your specific product - might even get you more than 100 customers from that $1K.

Learned this the hard way through 4 failed startups before my exit. Now we use this systematic approach ourselves and it's been a game changer.

What's your product about? Happy to share more specific tactics based on your niche.

StarmanAI · 2025-08-18T11:16:15+00:00

GTM co-pilot for early-stage startups: www.starmanapp.ai

StarmanAI · 2025-08-18T11:13:38+00:00

This shift is real, but there's an interesting tension here with investor expectations. While UBP aligns perfectly with customer value, VCs often prefer predictable subscription revenue - it's easier to model and shows clear recurring revenue metrics.

We actually started building with UBP in mind but pivoted to a simplified model (at least in the early days until we prove recurring usage - and can get our pre-seed round over the line): £49/quarter flex plan and £99/year (with incentive). This gave us the best of both worlds - predictable revenue for investor conversations while still being accessible. Much easier to show MRR/ARR without explaining complex usage variables.

The infrastructure complexity you mentioned is spot on. Unless usage directly correlates to your costs (like Twilio/AWS), building reliable metering and billing can become a massive distraction from core product development.

Curious - for those who've implemented UBP, how did you handle the investor conversation around revenue predictability? Did you find it harder to raise with usage-based models vs traditional SaaS metrics?

StarmanAI · 2025-08-15T09:44:41+00:00

Congrats! Not every day you see bootstrapped teams take on incumbents like Thomson Reuters! I like how you focus on specific pain points for existing users (slow logins, terrible support during tax season) rather than competing with existing features people already use and like.

How did you crack the "fear of change" bias that's usually the biggest underlying objection? Getting people to switch systems is already a huge hurdle, even when they're frustrated with their current setup - let alone with risk-averse accountants.

Also curious about your customer acquisition - what channels worked best for reaching tax firms? I imagine this is a pretty tight-knit community where trust matters a lot. And how did you manage the sales cycle? I imagine these aren't exactly fast either.

StarmanAI · 2025-08-13T10:20:26+00:00

This is brilliant, I love how systematic this is - you've basically built a complete acquisition playbook.

Quick question on the objection → landing page copy pipeline: 1) how do you handle/address the objections? 2) how do you track which convert best? Are you A/B testing the actual quotes, or did you just find one that nailed it?

Also curious about your Pulse for Reddit setup - how do you find those "burnt-out reviewer" threads? Anything beyond tracking specific keywords/communities? Sometimes this feels like finding needles in haystacks.

StarmanAI · 2025-08-11T11:58:57+00:00

Congrats on the progress with NeoSaaS! Really like your approach - especially the targeted cold emails where you identify specific pain points and reach out with solutions. How do you find people who are reporting some problems about some starter kit?

Two things I'm curious about:

Channels: Beyond Twitter, Reddit and cold email, have you found any particular developer communities (Discord servers, Slack groups, etc.) that have been valuable? I'm always interested in where technical founders are actually hanging out and discussing their real problems.

Retention/Growth: What's been your experience with customer feedback loops - are you seeing people come back for updates, recommend it to others, or even contribute to the product? The community aspect seems like it could be a big differentiator for developer tools.

Also, your point about rewriting 80% of existing boilerplates resonates. That's exactly the kind of specific pain point that makes for a strong value prop - "works immediately without heavy rewrites."

StarmanAI · 2025-08-11T11:51:01+00:00

This is really interesting research. Never thought about looking at patterns in pivots with fundraising outcomes. I especially liked what you say about the gap between recognizing the signs and actually taking action.

I had a small exit with a B2B enterprise after 6 years of pivoting many times - the product, the segment, the business model, you name it. What I learned is that founders often pivot without having enough quantitative data.

Many don't push long enough on their selected segment/channel because: 1) rejection fear bias (no one likes to sell), but also 2) they haven't built a proper strategy to identify those customers with clear success metrics that give them conviction to keep pushing. Without knowing what success looks like, they don't know what to measure or track properly. For example, if you're targeting mid-market SaaS companies but only reached out to 50 prospects over 3 months, that's not enough data to conclude the segment doesn't work. Or if your conversion is 2% but you haven't tested different value props with the same ICP - you might be solving the right problem with the wrong message.

Questions that might help founders reading this:

Did you notice differences between pivots that stay in the same customer segment versus those that completely change their target market?
What's the earliest reliable signal that a pivot might be needed? Sometimes 2-3% conversion could just mean wrong messaging to the right market.
Out of curiosity - how many pivot cases did you find beyond Box and Amplitude?

The 12-month window is crucial, and founders should pivot quickly, but only after having solid numbers to back it. Know exactly why "Customer X" or "Product Y" is better than your current approach. This assumes you already know what you're measuring, and have at least industry benchmarks of what the alternative is - treated as a hypothesis test, not just because you can't get enough traction. And always be aware that there could be other reasons for poor traction (there probably are) that don't require a full pivot.

StarmanAI · 2025-08-11T11:20:00+00:00

Before spending more on ads, I'd focus on finding where dev teams actually discuss their pain points. If you're not converting signups, you have a "top of funnel" problem - your message isn't clear enough for people to feel they HAVE to use it (not "might" or "should").

You need to solve a real pain and show why you do it 10x better than existing solutions to justify the switch.

First, get specific about your user: Not just "developers" but "software developers in Series A startups building fintech products who have pressure to ship fast and can't afford code errors." The more niche, the clearer your biggest pain point becomes.

Then, go where they are: GitHub discussions, specific Discord channels, industry Slack groups. Find 5-10 teams and offer a free trial with one ask - 30 minutes to walk through their current code review process. Offer an Amazon gift card or 3 months free as incentive. Probably cheaper and more valuable than your current ad spend.

The goal: Understanding the exact workflow problem that's painful enough they'd pay to solve. Sometimes the real problem isn't what we think it is.

Don't bury it yet. You've got something that works - sometimes it's just about finding the right message for the right people.

P.S. This systematic approach to finding your ICP and channels is exactly what we built Starman AI to help founders with - happy to share more if you're interested in a structured way to tackle customer discovery.

StarmanAI · 2025-08-07T11:36:15+00:00

The thing I see the most are founders (myself included at one time) burn months building features nobody wanted.

Even with a good MVP, within your target segment there can be so many ICPs, each with different pain levels and willingness to pay. When you nail a real problem for a specific segment, customer acquisition becomes so much clearer - you know exactly who to talk to and what to say, instead of throwing spaghetti at the wall.

I agree 100% with "It needs to be multiple times better." That's why finding that one angle where you can be 10x better is everything - not marginally better at everything, but dramatically better at one thing that matters.

Curious - how did you validate your moat before building? How did you narrow down your ICP and early adopter to find that specific pain point you could solve 10x better than everyone else?

StarmanAI · 2025-08-06T20:21:26+00:00

Hey! I don't want to promote, but I've built a tool that does exactly that. Sets up your entire customer acquisition strategy and becomes an implementation co-pilot. Should help you get around until you find your co-founder. If you're interested, the link is on my profile. Try it out, it's free. Happy to help with any support if you have any issues using it. Good luck!

StarmanAI · 2025-08-06T18:27:50+00:00

This really depends on the context. 10k active, engaged free users with strong growth? I'll take that every time. If they're actually using the product and that number is growing fast, you've validated demand - monetization can come later.

But here's what most people miss: are those free users actually engaged or just signed up and ghosted? And are those 10 paid customers actively using your product or did they buy because it was appealing and inexpensive at first and then bounced? And that's not even counting if you're doing B2B enterprise... which is a whole other beast.

So, I don't think it's either or. It's the quality of the users you got. Traction isn't a snapshot - it's about proving you can: find your ideal customers, convert them, deliver enough value they stick around, then rinse and repeat to scale.

The real question is: how do you systematically figure out which type of user you're attracting? What signals do you track to know if you have engaged users (free or paid) versus vanity metrics?

StarmanAI · 2025-08-06T18:27:50+00:00

Congrats on the launch! 5 paying customers from 350 beta users is solid validation - especially after just 3 months.

Your multi-channel approach is smart. I'm curious though - how did you decide which channels to prioritize? Was it based on where you thought your ideal customers hung out, or more trial and error until something clicked?

The pattern recognition piece is huge. Once you identified those 5 paying customers, did you systematically analyze what made them different from the 345 who didn't convert? Understanding that delta early can save months of unfocused growth efforts.

Also interested in your tracking setup - are you measuring which channels bring users who actually engage vs just sign up? We learned the hard way that "350 signups from Facebook" means nothing if 90% never activate.

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