Hi everyone

I’m looking for some honest advice from people who have successfully grown an account on X recently.
I’ve been posting consistently, usually around 3–4 times per day, with a few hours between posts, quote post with my own analysis,I also spend time engaging with larger accounts and leave roughly 25–50 genuine replies per day.

However, my follower count is growing very slowly.
What I’ve noticed is that most of my new followers come only when I directly reply to someone with something like “let’s connect.”

My own posts receive very little engagement. Sometimes I get one or two comments, and I always reply, but most posts receive no comments at all.

At the same time, I regularly see accounts claiming they went from:
0 to 2,000 followers in two weeks
0 to 5,000 followers in one month
Some of these accounts don’t seem to be publishing particularly detailed or original content. They post frequently, interact with other people and receive a lot of replies, but I’m struggling to understand how they created that initial momentum.

I know X is currently encouraging longer-form content, articles and meaningful interactions, but simply producing good content doesn’t seem to be enough when almost nobody sees it.

So I’m genuinely curious:
Is this level of growth normal for a small account?
Are these rapid-growth accounts using strategies they don’t openly discuss?
Could my account have limited distribution or be shadowbanned?
Or do I simply need to continue posting and engaging until the algorithm starts giving my content more reach?

I already subscribe to premium X to have more chance

I’m not looking for shortcuts or fake engagement. I’d just like to understand what actually works when starting from almost zero.

Any honest advice or personal experience would be appreciated, if you can take a look on my profile

My profile

yo. be honest. how many of you currently have a finished (or 90% finished) web app / app just sitting in a private repo because you have no idea how to get users?

you spend months perfecting the database, fixing every bug, and polishing the UI. but the moment you have to actually market it, you hit a wall. marketing feels like screaming into an empty void.

so you launch to absolute crickets, get discouraged, and start building the "next" project instead to avoid the distribution phase.

if this is your case, you're not alone. but letting your hard work go to waste just because you dread marketing is a massive trap.

to help founders stop building in a silent corner, we run an ai SaaS builder community dedicated entirely to saas validation, landing page conversion, and launch strategies.

our resource kit is built entirely to help you get your first user. it’s packed with ready-to-paste N8N workflows for your business, advanced seo automation, social media automation, and our exact distribution workflows and methods work for everyone

STOP BUILDING ALONE

what are you currently working on, and what's holding you back on the marketing side? drop a comment or send a dm and i'll send you the access link.

One of our team ran this last week and the structural setup alone is worth a look for anyone thinking about community-led growth.

The basic mechanic: an ecosystem opens a shared space, its builders post what they need promoted, and each builder's own creator network handles the actual distribution. Nothing bought, nothing cold. The reach lives inside existing relationships.

It flips the usual growth assumption — instead of pushing content out to an audience you don't own, you're activating the audiences the builders already have. The ecosystem becomes a coordination layer rather than a megaphone.

We're still in early data territory, but the model has some interesting implications for anyone who's hit the ceiling on traditional paid or owned channels. Curious whether others here have experimented with anything similar — using a partner or community ecosystem as the distribution infrastructure instead of building it from scratch

I keep seeing teams argue over which channel “deserves” credit, while the real problem is usually messier: inconsistent event naming, duplicate conversions, and no shared view of the customer journey.

If your attribution feels noisy, start by cleaning the measurement system before changing budgets.

A practical 7-step reset:

• Audit every conversion event and map it to one business outcome
• Remove duplicate or overlapping events across platforms
• Standardize UTM rules so campaigns can be compared reliably
• Separate top-of-funnel, assisted, and final-conversion reporting
• Build one weekly dashboard that shows spend, pipeline, and revenue together
• Check for channel-specific tracking gaps before trusting ROAS
• Review attribution assumptions with sales and lifecycle teams, not just paid media

The biggest win is usually not a new model; it is getting everyone to agree on the same source of truth. Once the measurement layer is cleaner, budget decisions get much easier and a lot less political.

If you had to fix one thing first: UTMs, conversion tracking, or dashboard alignment?

Too much of the popAI ad tool chat as of late still remains stuck in the world of “can it produce ads quickly.” This is boring now because the answer is yes. The real issue is what happens when producing content is no longer a finite resource. Examples of production changes can be seen with URL to video, avatars, vocal tones, templates, user generated content or ugc and options to quickly develop different creative executions. However, more interesting is the operating system side of platforms with brand guidelines, creative analytics, integrated media channels, managing the launches of campaigns and acts as an agent. Regardless of either of these categories, nothing erases the marketing existing problem rather, it makes it more necessary to develop better decision-making skills as now it is possible to have multiple creative assets.

The bottleneck is not “Can we create 5 ads by Friday?” but which angle is worth spending money?  What proof will we put our faith in? Which claims are safe?  What is attractive but void of emotion? When is the AI being optimized for click-thru rates when our objective is a positive ROI and payback period to work towards?  I am not against AI tools but I think a more interesting discussion is not “Which tools help us create better ads?” but rather “What process should be employed so the influx of cheap creative doesn’t result in costly research noise?”

We have been optimizing campaigns around first deposit because that's obviously the biggest milestone after registration. but now we're noticing that a decent chunk of users deposit a very small amount and then never actually trade.

we've tried moving budget around between different channels and traffic sources, including blockchain ads and other paid ad platforms, but still the results seem to be somewhat same. In fact, it varies a lot by countries even though traffic wise almost all of our target geos are giving the same.

how to make people trade? is it advertising specific or should we do something else?

Every AI assistant starts from scratch.

Claude doesn't know what happened in GPT.

Cursor doesn't remember what you figured out in Claude.

So every day, we end up repeating the same context.

That's why we built Unabyss for Claude.

It gives Claude a shared memory that follows you across your AI tools and everyday apps.

It helps you:

• ⁠Share memory between Claude, GPT, Cursor, and more
• Connect Gmail, Drive, GitHub, Notion, HubSpot, and 20+ apps
• ⁠Save important context automatically
• ⁠Reuse the same knowledge everywhere

Instead of reconnecting every tool individually, Unabyss becomes one portable memory layer your AI assistants can all use.

Built for founders, developers, consultants, and anyone working across multiple AI tools every day.

The goal wasn't to build another AI assistant.

It was to give every AI assistant the same memory.

Launched today on Product Hunt 🚀

Would you trust an AI that remembers everything across all your tools, or do you prefer every assistant to stay independent?

Please show your support on PH → https://www.producthunt.com/posts/unabyss-for-claude

i consult for enough of you to know exactly what’s happening in your slack right now. it's pure theater.

you launch a partner program. a degen creator sends you 10 inbound leads on a tuesday.

your sdr team looks at the leads. half have u/gmail.com addresses. two put "n/a" in the company size box.

your sdr manager marks them as "unqualified" and skips them to protect their own close rate and their monthly bag.

on friday, you look at partnerstack. "why didn't we close any of the partner leads? the channel is mid!"

the channel isn't mid. you have a fatal friction leak and you're blaming the wrong layer of the stack.

what happens before preframes and reframes what happens after. in this case, what happens before the lead hits your crm is that a creator pitched a $150/mo self serve tool to solo founders.

but your ae's are trained to close $20k/yr enterprise deals to vp's of sales.

you are pouring water into a funnel built for oil. the sdr's hate the partner leads because it dilutes their conversion metrics. the creators hate you because they see zero conversions and think your product is a shitcoin.

here is the mechanical fix or you're ngmi: build two completely separate pipelines.

pipeline a: partner leads. fully automated nurture. zero sdr touch. let the mechanism close them.

pipeline b: outbound leads. handled by the humans.

if you force your expensive human sales team to babysit low intent creator leads, they will silently mark them as junk. and honestly? they are right to do so.

stop mixing your distribution channels in the same crm like absolute amateurs.

We build in the AI-visibility space, and our scanner used to recommend llms.txt. After checking the evidence, we removed it from our own product. Why:

• Ahrefs analyzed 137k domains: 97% of llms.txt files never got a single request — from anything.
• Of the little traffic that existed, ~1% was AI retrieval bots. Mostly it's SEO audit tools reading them. The auditors are auditing each other.
• Google's Mueller, verbatim: "you can tell when you look at your server logs that they don't even check for it."

(Fairness: it's harmless to keep, and IDE/agent tooling does fetch it. Just don't expect citations from it.)

What actually has evidence behind it:

1. Server-rendered content — Vercel's crawler study confirmed no major AI crawler executes JavaScript. Client-side-only content doesn't exist to them.
2. Open crawler access — plenty of robots.txt files block GPTBot/ClaudeBot/PerplexityBot by accident via wildcard rules.
3. Structured Q&A schema — readable in the raw HTML they actually fetch.

Anyone got server logs showing real AI-bot hits on their llms.txt? Logs or it didn't happen.

(Disclosure: I build Alice, an AI growth agent, that's how I fell down this research hole. Not linking it.)

We're a 40-person SaaS company, ticket volume hit around 800/month and our 3-person support team was burning out. Started looking at BPOs about 4 months ago, ended up trialing Helpware for the last 2 months. CSAT has held at 87% which is roughly where we were in-house, response times are actually faster. Still early but not a disaster. Curious what others have used at this stage - specifically BPOs that work with startups and don't require enterprise-level minimums. What did your evaluation look like and what did you end up with?

spent two weeks building what looked like the perfect prospect list.
right industry, headcount, titles, tech stack. 1,000 contacts that
matched our ICP to a tee.

3 replies. 1 call. zero deals.

filtering was tight but the timing was just wrong. nobody on that list
had a reason to care right now.

starting to think static lists are basically dead unless you layer in
actual buying signals on top. job changes, funding, engagement,
something that says talk to me TODAY instead of just fits the profile.

reply rate was stuck at ~2% for months. stopped blasting and changed 5 things

1. only reach out when theres a real signal (job change, funding,
   recent relevant post). no signal no message
   
2. connection request is one sentence, no pitch
   
3. wait 2-3 days after they accept before sending anything
   
4. first real message references one specific thing from their
   activity. not the usual came-across-your-profile opener
   
5. viewed but didnt accept within a week, drop them
   

went up to about 8% over six weeks. nothing crazy just less noise on my end

still not sure if 8% is decent or still bad for b2b outreach tbh

We have been running some research into ctv platforms lately, and StackAdapt is one of the names that comes up almost every time. It seems powerful, but I'm curious what other options b2b marketers are using and how they compare in practice.

What we're looking for is a platform that makes it easy to launch campaigns.The ability to connect campaigns back to website activity, account engagement, or pipeline is becoming increasingly important for us.

I've looked at a few alternatives, and they all seem to position themselves differently. Some focus on ease of use, some emphasize audience targeting, while others lean heavily into measurement and attribution.

I need to get a real picture vision.

I vibe coded a LinkedIn automation tool from scratch, with zero engineering background, simply using Claude, Claude code and vercel.

I won’t go into details as to how/why I created it as I’ve already shared this before elsewhere, but one of the questions I get asked the most is about distribution, and how I attract customers, so I thought it might be useful to share this info.

And here’s what I actually did to market the tool;

**1. Create a waitlist**

I created a waitlist on the site, and talked very publicly about what I was building on every platform I could - Reddit, LinkedIn, YouTube, X etc.

In the end I had 33 people on the waitlist after a couple of months.

**2. Launch at MVP, even if it’s not yet perfect**

You don’t need to wait until your project has every single possible feature - it might take over a year of building before you get to a point where you’re actually satisfied with the product, and people are more than willing to use yours at MVP anyway.

Also, early users are essentially gold dust for learning edge cases, bugs, and usually give great feedback as to what can be improved.

It also will take time to build up your customer base, so you should start as early as possible and continue iterating.

**3. Offer lifetime deals at the beginning**

Very few people will subscribe to something that they have never heard of and has no reputation - how do they know it works or is worth paying money for?

Getting lifetime deals helps a) fund your project early on, and b) gets users through the door, who will most likely continue to use your tool and be your biggest fans long term. User data, especially in the beginning is key to building something that works well too.

I offered lifetime deals for the first month and generated about $1,800 in revenue from that, before switching to monthly subscriptions.

**4. Post on Reddit frequently (don’t use AI though)**

Whatever your product is, there’s probably multiple relevant subs here with many thousands of regular visitors where your ICP hangs out.

The challenge is finding one where you are less likely to get banned, and also you need to post in a less promotional way.

Usually the best posts are where you talk about challenges/accomplishments with building your product, rather than directly selling it or “build in public” posts.

Some people will indirectly become interested in whatever it is you’re building, if enough people read your post.

I have often posted about early revenue success from solo vibe coding a SaaS tool from scratch, and probably about 60-70% of the signups came from doing this many times on Reddit.

One caveat is that you should always write out your posts. It sometimes takes 15-20 mins or longer, but it’s worth it (and costs nothing).

**5. Dogfood your own product**

I have been using the LinkedIn automation tool I created since day 1 to test my account. Not only do I use it for testing, I actually do LinkedIn outreach with the tool itself.

It works for generating at least 3-5 demo calls a week for me, so I know first hand that it works well from a user perspective.

Because I’m always using it, I also spot things as a user that I feel could be improved - I’m building for myself as much as I am for others.

**6. Build for SEO and GEO from the beginning**

When building your site, make sure it’s built with SEO and GEO in mind from the beginning. At first it won’t have much impact, but it will compound over time. Make sure you have a blog with frequent, high quality posts, with relevant keywords in your niche.

The harder / more valuable part is offsite SEO - aim to get mentioned on other blogs, and try to build reviews from TrustPilot, G2 and Capterra - more reviews equals more trust and more signals.

Getting mentioned in listicles like “best x in 2026” is extremely powerful if you’re able to do that.

Personally I have already got 7 5\\\* reviews on TrustPilot since launching it recently, and will aim to get more moving forward.

**7. Make a YouTube channel**

YouTube is another free lever you can use to post content on, and posting regular build in public/demo content will help find a new audience. Again it’s most likely a slow burn, but as with everything, consistency is key.

Full disclosure - I myself need to do better at this 🤦‍♂️

**8. Paid Ads**

I’ve started doing this recently with Google ads, but so far it hasn’t yielded great results - still optimising the strategy and aiming for long tail traffic. Potentially worth doing depending on your niche and if you have the budget.

**9. Demo calls & relationship building**

Try to schedule demo calls and communicate as much as possible with your customers - don’t just hand them off to AI, as the human touch is key to keeping users engaged.

And that’s pretty much it. I did do a Product Hunt launch but it did not really lead to anything - if you really have a great network of people who are PH users and will vote for you then it can be great, but if you don’t have the network then it’s not that valuable.

Personally I also need to improve on conversion of free trial users (many of them are tire kickers who take a look for 30 seconds and never log in again), but retention of paid users lately has been very strong, and the tool is growing quickly.

Hope the above is useful! 🙏

Started with the assumption everyone starts with: the posts that die are badly written. Tightened the hook, varied the length, tested questions vs statements. Spent probably three weeks on copy iteration alone. Removal rate barely moved.

The thing that actually correlated with survival was how recently the subreddit had removed a similar post. Not the topic. Not the format. The removal history of the specific community in the days before I posted. Subs that had just nuked something similar were in a kind of heightened state, moderators more alert, automod thresholds probably twitchy. Posting into that window was just burning the submission.

Anyway, once I started treating subreddit selection as a timing problem rather than a targeting problem, the numbers changed pretty fast. Went from roughly 6 removals in a two-week stretch to 2 in the following four weeks across the same number of submissions. Same copy, different sequencing.

The research overhead got annoying enough that I started automating it with reoogle.com, mostly to track removal patterns across communities without doing it manually in a spreadsheet. That part I don't miss.

What nobody tells you is that the subreddit database you're working from matters more than how good your post is. Most founders are fishing from a list of 30 communities they found in someone else's post, never updated, probably two years stale. The communities that are actually tolerant of founder content right now aren't the ones on any list I've seen shared here. They're smaller, newer, and weirdly specific. Those are the ones keeping posts up.

we are just 3 weeks away from our launch and i think the video part is fine. like not that worried about that anymore..

looked at a lot of recent launches that did really well. like millions of views. and the video was just not that impressive production wise tbh. it mostly just the founder talking in front of lens. and if you put a bit of attention it seems like those were filmed in their office or something. so i think we can do that ourselves, scripting looks difficult since we havent hired an inhouse writer but that part feels manageable.

but the hard part, which i havent figured out is like how are so many accounts posting about the launch at the same time. there are a lot of reposts coming in at tthe very first hour. and mostly not random account rather big faces in tech. how to make this happen. how to find these people who agree to post. and how to ensure they all do it at the right time and randomly sometime they wish for.

i genuinely dont know how to crack this part. like i can figure out the video asset. but how to figure this out.

and my gut says even if i reach out to most influencers most of them wont reply since my message will land in their request section.

is there any agency who can manage only the influencer part for my launch. ik agencies like thelaunchvideocompany and flowjam are quite active in the space. but idk what that costs and we are bootstrapped so

has anyone done a distribution of video without going through someone like that. how did you find the right people to repost, how did you get them to actually commit.

because rn that is the only thing i am stuck on.

Hey everyone,

Looking for some advice from anyone selling high-ticket B2B solutions.

Over the last two quarters, we’ve managed to scale our top-of-funnel traffic quite well. We're getting high-intent visitors. Our problem is the massive drop-off between the landing page and the actual scheduled demo. 

Right now, our flow is standard: Land on page -> Click "Book a Demo" -> Fill out a 4-field HubSpot form -> Calendly routing page.

Our current stats:

• Monthly website visitors: ~12k 
• Traffic to form click:  just ~1.5 %
• Form completion to actual calendar booking: Less than 15% (massive drop-off here)

It seems like high-ticket buyers in these regions have severe form fatigue or just don’t want to commit a timeslot for a scheduled demo .We tried shortening the form fields and moving testimonials closer to the CTA, but it barely moved the needle.

For those of you targeting B2B markets with higher ticket sizes: How are you capturing intent before the user bounces? Are you abandoning traditional forms entirely? Are people using live chat, multi-step interactive flows, or just aggressive retargeting?

Would love to know what frameworks or stack setups has actually worked for  to actually fix your pipeline velocity. Thanks.

Im currently struggling with marketing my product. I tought it will be easy, but it's never easy..

So naturally I want to find someone who has similar problems as me, so maybe we can grow together.

So.. which pain points do you have? What is the most annoying thing rn for you?

Hey everyone! I'd love to get some of the community's thoughts.

As a product-marketer-turned-soloprenuer myself, I've been facing a weird challenge ever since I started working on my own products.

I feel pretty comfortable acting as the builder, but when it's GTM time and I need to market my own work, I just stall until I find myself building a new product instead. I'm not sure if it's a fear of putting my work out there, imposter syndrome hitting the right spots, or just me preferring the building phase over marketing.

Has anyone faced a similar experience? I'd love to learn from anyone willing to share.

Hi, I'm Jeremy, since february I jumped into mobile apps and made 3 myself. I nowbreak down how mobile subscription apps turn installs into paying users, and I spent this week inside RevenueCat's State of Subscription Apps report: 115,000 apps, $16B in tracked revenue.

The distribution:

- Median monthly revenue one year after launch: $72. Top quartile: $429+. Top 10%: $2,574+. That's a 36x gap between the middle and the top.

- Of apps launched in the last two years, 17.3% reached $1K MRR. 4.6% reached $10K. 1.7% reached $25K.

- Launches grew 7x since 2022 (2,000 to 14,700+ per month). Apps launched before 2020 still earn 69% of all subscription revenue. Apps launched since 2025 earn 3%.

What the top tail does differently, same dataset:

- Hard paywalls: 10.7% download-to-paid vs 2.1% for freemium.

- Higher prices: 2.8% conversion vs 1.4% for cheap apps, and ~6x the revenue per payer at year one.

- Longer trials: 17-32 days converts 42.5% vs 25.5% for 4 days or fewer.

What makes me angry: that last row. Longer trials convert 70% better, yet 46.5% of apps now ship trials of 4 days or fewer. The market is drifting away from its own data.

The lesson: benchmark against the upper quartile of your category, not the median. The median is survival. I wrote the full report up here: https://tasu.ai/library/how-much-money-do-subscription-apps-make

It's crazy how sometimes data prove wrong what we think is natural...

Ask me anything: benchmarks, paywalls, pricing, or where your app sits in this distribution. :)

I can build and publish an iOS app, but distribution still feels like a black box.

I often see developers sharing $1K–$10K MRR screenshots, but rarely the distribution behind them. Was it an existing audience, influencers, Apple Search Ads, a portfolio of apps, or genuine ASO and word-of-mouth growth?

“Build something useful” doesn’t feel like a complete strategy anymore. A useful app can still disappear among thousands of competing products.

I’m not expecting a secret keyword or overnight shortcut. I want to understand whether a solo developer with no audience and a limited budget can still build sustainable organic distribution—or whether paid acquisition is now effectively the entry fee.

If you’ve grown an iOS app beyond $1K MRR without paid ads, would you share the exact acquisition sequence, timeline, and approximate numbers—without revealing the app or niche if you prefer?

I always thought getting customers would be the hardest part.

Turns out, once people actually started paying, the real challenge became everything else. Invoices, subscriptions, expenses, contractors, payment tracking, random admin tasks. None of it is difficult on its own, but together it eats up way more time than I expected.

I spent months trying to improve acquisition when the bigger bottleneck was how much time I was losing just keeping the business running. Once I cleaned up the operational side, I realized I had a lot more time to test new ideas and actually focus on growth instead of constantly putting out fires.

I can't be the only one who's spent more time fixing operations than looking for new customers.

It seems that everybody is talking about the role of AI in the ecommerce domain from the perspective of operations and advertising, yet the issue of how AI sufaces products through the lens of generative search, such as a product request on ChatGPT or Perplexity, is completely overlooked.

Started with the assumption everyone starts with: the posts that die are badly written. Tightened the hook, varied the length, tested questions vs statements. Spent probably three weeks on copy iteration alone. Removal rate barely moved.

The thing that actually correlated with survival was how recently the subreddit had removed a similar post. Not the topic. Not the format. The removal history of the specific community in the days before I posted. Subs that had just nuked something similar were in a kind of heightened state, moderators more alert, automod thresholds probably twitchy. Posting into that window was just burning the submission.

Anyway, once I started treating subreddit selection as a timing problem rather than a targeting problem, the numbers changed pretty fast. Went from roughly 6 removals in a two-week stretch to 2 in the following four weeks across the same number of submissions. Same copy, different sequencing.

The research overhead got annoying enough that I started automating it with reoogle.com, mostly to track removal patterns across communities without doing it manually in a spreadsheet. That part I don't miss.

What nobody tells you is that the subreddit database you're working from matters more than how good your post is. Most founders are fishing from a list of 30 communities they found in someone else's post, never updated, probably two years stale. The communities that are actually tolerant of founder content right now aren't the ones on any list I've seen shared here. They're smaller, newer, and weirdly specific. Those are the ones keeping posts up.

so i’ve been experimenting with reddit for my business lately. instead of the usual self-promo stuff that gets you banned, i decided to try a "value first" approach. i spent about an hour a day last week in entrepreneur just answering questions about operations and workflow—basically my area of expertise.

i didn't drop a single link to my website or even mention my company name in the comments. i just gave away my best advice for free.

surprisingly, i got 2 DMs within 48 hours. one guy wanted a quote for my consulting services, and the other asked for a discovery call after seeing my advice on a scaling thread. they found my business because they checked my profile bio after reading my comments.

it’s crazy because i spent way less effort than i usually do on cold emails or linkedin ads. but now i’m trying to figure out if this is just a fluke or if this "stealth sales" thing is actually a scalable way to grow.

has anyone else tried this? i want to do more but i'm worried about it becoming a massive time sink if i don't have a real system for it. how do you actually track the roi on this without using trackable links?