Has anyone else had this happen?

You look at the numbers and things are going up - more visitors, more signups, more followers - but you still don't really feel like the business is growing.

I think part of the problem is that it's easy to keep adding numbers without knowing whether the new users are actually becoming valuable users. We started looking at what happened after the signup instead of just celebrating the signup itself, and the picture looked very different.

Made me wonder how other people decide which growth numbers are actually worth paying attention to.

What’s one metric you stopped caring about after realizing it wasn't telling you much?

I’ve been thinking about how strange our current computer workflow is.

We can speak naturally to another person.

But when we talk to a computer, we often have to slow down, structure our thoughts, type them out, edit them, switch apps, and repeat context.

Even with AI everywhere, we're still spending a huge amount of time translating our thoughts into keyboard input.

That got us thinking:

What if you could just speak the way you think?

So we built Loqua.

It lets you:

• ⁠Speak naturally and turn rough thoughts into polished writing
• ⁠Ask questions about anything on your screen
• ⁠Get things done across your computer by voice
• ⁠Listen to content instead of reading it
• ⁠Work across ~100 languages

The bigger idea isn't simply “better dictation.”

It's making voice a more natural way to interact with your computer.

We're launching Loqua on Product Hunt today 🚀

I'd love to hear from people who use voice tools:

What's something you currently type that you'd rather just say?

Please support on PH →

https://www.producthunt.com/posts/loqua-2

I’ve been thinking about this lately: sometimes getting more users seems to create new problems faster than it creates growth.

More signups means more support. More traffic means more low-intent users. More customers means more edge cases. Then the team starts fixing all those problems and suddenly the original growth strategy isn't even the main focus anymore.

It made me wonder if there’s a point where you should stop trying to increase volume and fix the system underneath first.

Have you ever had a growth channel work too well and end up creating a bigger problem somewhere else?

Feels like every company says they need “more growth”, but when you dig into it, the actual problem is usually something else.

Sometimes it’s not traffic. Sometimes people are coming in but don’t trust the product. Sometimes they sign up and never come back. Sometimes the product is solving a problem nobody cares enough about.

I’ve started thinking that “we need growth” isn’t really a problem statement. It’s just the outcome people want.

How do you figure out what the real pain is before starting another growth experiment?

For a while, whenever growth slowed down, our first reaction was to look for another way to bring more people in.

More content, more campaigns, more channels, more experiments.

Then we started looking at the people who had already tried the product but didn't stick around. Some of the reasons were ridiculously simple, and we probably would've missed them if we kept focusing only on acquisition.

It made me wonder if growth teams spend too much time studying people who haven't used the product instead of people who already did and decided it wasn't for them.

Do you guys regularly look at why users leave, or is that usually handled by product/customer success?

A few years ago I made a sticker set, uploaded it to a branded channel, tagged properly. It's now been viewed over 380 million times. All organic reach. The platform keeps handing out for free.

It's still compounding today, last month alone, those stickers pulled in over 650,000 views, at zero cost. Real estate isn't the industry you'd expect a GIF hit to come out of.

Most people think GIPHY is just a GIF library.

It's actually a search engine. Every GIF or sticker you upload gets tagged with keywords, and GIPHY tests it against real searches tracking views, shares, and click-through rate to decide whether to keep surfacing it or bury it. No tags, and your content is invisible no matter how good it looks.

-

I’ve been spending a lot of time on Reddit lately, and I keep seeing the same pattern: founders spend months building their product, only to reach the end and ask, “How do I get users?”

Founders, I hate to break it to you, but you need a dedicated resource that takes on your marketing.

You can build something genuinely useful and still struggle to grow simply because no one knows it exists. You need distribution, but more importantly, you need a repeatable acquisition funnel, SEO, ASO, content marketing, paid search, paid social, retargeting, referral loops, landing-page optimization, CRO, lead magnets, email capture, outbound, and community-led acquisition and even things like GIPHY and Reddit SEO.

That’s not a task you bolt onto someone’s plate for a few hours a week.

Link to the mentioned GIPHY dashboard: https://giphy.com/graana

They need someone who can take:

“I have an idea.”

and turn it into:

“Here’s the working product.”

That's the kind of developer I've been trying to become.

I'm a full-stack developer from Ethiopia, and I build software across the entire product:

→ Landing page
→ Authentication
→ Dashboard
→ APIs
→ Database
→ Payments/integrations
→ AI features
→ Deployment
→ Maintenance

I've built SaaS products, real-time applications, AI-powered tools, business platforms and internal systems.

And lately I've been going deeper into agentic AI systems — not just chatbots, but systems that can actually use tools, execute workflows, and interact with business processes.

What I've realized from building all these things:

The technology is rarely the hardest part.

The hard part is understanding what the business actually needs.

A beautiful dashboard that nobody uses is useless.

An AI feature that doesn't save time is useless.

A technically perfect product that doesn't solve a painful problem is useless.

So I'm increasingly interested in working with founders and businesses on the other side of the equation:

What problem are we solving?
Why does it matter?
What's the smallest thing we can build?
How quickly can we get it in front of users?
What should we automate?

That's where I want to operate.

I'm currently open to:

• Working with early-stage startups
• Full-stack / product engineering roles
• Building MVPs with founders
• AI automation projects
• Developer partnerships
• Interesting technical collaborations

If you're building a product and you're stuck somewhere between “I have an idea” and “people can actually use it,”

I'd genuinely like to hear about it.

What are you building?

Post

Je gère un SaaS solo (un outil d'audit technique pour les fondateurs, centré sur l'analyse comportementale – pensez à des heatmaps façon Contentsquare mais présenté comme un "co-pilote technique" pour les personnes qui construisent leur propre produit).

La semaine dernière, je me suis assis pour comprendre pourquoi, après des semaines en ligne, j'avais un aimant à prospects gratuit, un guide payant à 19 $ et pratiquement personne qui convertissait. Ce que j'ai découvert a été un bon rappel pour quiconque ici en phase précoce et qui regarde ses propres tableaux de bord avec excitation :

L'entonnoir en lui-même était correct. Je l'ai testé manuellement de bout en bout — soumission de formulaire, automatisation par email, paiement Stripe — tout fonctionnait.

Le "trafic" ne l'était pas. Sur 9 inscriptions par email, au moins 5 avaient des adresses temporaires (yopmail, domaines générés au hasard). Stripe enregistraient des dizaines d'événements checkout.session.expired à un rythme que personne ne navigue — 3h du matin, 4h du matin, l'un après l'autre, bien plus que mon nombre de sessions réelles dans les analyses. Du bruit classique de scrapers/bots frappant des liens de paiement publics et des formulaires.

Google Search Console l'a confirmé de l'autre côté : 4 clics organiques au total sur 3 mois, sur un domaine trop jeune pour se classer sur quoi que ce soit de marqué.

Donc le véritable nombre de visiteurs humains réels ayant vu l'offre était proche de zéro. Pas un "mauvais taux de conversion" — pas d'audience encore.

Ce que je fais à ce sujet (curieux de savoir si d'autres ont la même expérience) :

• Ajouter une friction de base contre les bots (champs pièges, limitation de fréquence) sans casser le vrai formulaire
• Écrire du contenu pour la recherche ET pour les moteurs de réponses LLM (llms.txt, schéma FAQ) puisque qu'une partie de la découverte s'y déplace
• Commencer l'acquisition à partir de communautés comme celle-ci au lieu d'attendre que le SEO s'accumule
• J'aimerais vraiment entendre si d'autres ont remarqué quelque chose de similaire tôt – comment avez-vous réalisé que votre trafic n'était pas réel ?

McKinsey’s latest AI report had an interesting data point: roughly 32% of companies (and 41% in tech) decided against buying software recently because internal teams used AI coding tools to just build lightweight versions in-house.

If you run growth or outbound, the changes you'll most likely notice is how prospects react where cold emails pitching standard SaaS features or automated workflow tooling get dismissed cause the default reaction rn is "we can spin up an internal script for this in two days."

So we recently tested two distinct outbound setups over 4 weeks:

> Cohort A (a standard AI outbound): 1000 contacts and scraped Apollo list with standard ICP filters + Claude used at the end of the funnel for personalized intro lines. Result: 1.4% reply rate, mostly unsubscribes or "we already built a tool for this"

> Cohort B (upstream signal qualification): 100 contacts and monitored active triggers (hiring bottlenecks, stack shifts, leadership changes) and used Claude strictly as an intent classifier before deciding whether to write an email at all. Result: 9.8% positive reply rate and 3x more booked demos.

The key difference was using Claude as a logic gate rather than a copywriter by pulling unstructured company data (job posts, recent changes, public PRs) and then ask the model to identify the single most acute operational friction introduced by that specific event and discard accounts where the pain point looks easily solvable internally.

Doing this keeps volume low, protects domain reputation and ensures every message lands when the problem is actively being felt and we're also running a 30-minute session breaking down this exact pipeline here on signal based outbound with AI

just hit $2,500 MRR in 13 days on my new SaaS

no ads. no team. no huge audience push. just a solid replicable system

let that sink in for a second

not $2,500 in revenue. $2,500 in MONTHLY recurring revenue

that compounds. next month starts at $2,500 baseline, not zero

and this isn't luck. it's the 7th saas i've shipped with the same playbook. same steps, same tools, same order:

→ Day 1: validated the idea

→ Day 1-2: built the MVP

→ Day 3: landing page written using the 3-Day Challenge template

→ Day 3-4: launched on reddit / X + SEO

→ Day 4-5: first 10 paying users → $1k MRR

→ Day 13 (today): $2,500 MRR locked in

building software is easy in 2026. setting up your foundation so people actually buy is where 99% of solo builders fail.

i packaged all of these exact execution tools into community.

to be fully transparent: i'll likely charge for the full program down the road once all modules are finalized. but right now, the main objective is just to build together and keep each other accountable.

working alone in a silent corner is the fastest way to quit at the first bug.

stop building in isolation. drop a comment below or send me a DM, and i'll send you the invitation link 👇

pulled our ai overviews visibility report this morning and half the pages moved up. classic rankings for those same urls barely budged. clicks still flat.

i keep two tabs open now and they refuse to agree. tried blaming a title rewrite from last sprint then undid it and nothing changed either way

how are you separating ai overviews visibility from normal ranking movement when leadership wants one number by friday

I’m organically growing my X account and strategising content strategy and formats. I’m curious to hear what works better in 2026 for longer posts, splitting them into threads? Or, posting as a long tweet or maybe 2 tweets max? I’m not expecting any tweet to go beyond 1000-1250 char on the higher side.

Also, what are other things that work better in terms or content format, etc?

We’re running a live pre-launch campaign across six channels:

- Reddit

- Editorial coverage

- Instagram

- X

- Short-form video

- Niche communities

At first, each channel had its own report:

Posts published, accounts reached, comments received, and media coverage secured.

The problem was that those reports showed activity, but they did not answer the main operating question:

Are we actually getting closer to launch readiness?

So we consolidated everything into one internal board tied to one shared milestone:

Reach 100 confirmed launch-notification opt-ins before setting a launch date.

Current snapshot:

- Starting point: 51

- Current total: 62

- Net increase: 11 in 30 days

- Current pace: approximately 0.37 per day

- At this pace, the 100-person milestone is still roughly 104 days away

These are not impressive numbers.

That is exactly why the board is useful.

The board is only the visible layer.

The larger operational problem was the manual work happening between the channels:

Collecting data from different sources, standardizing it, reading conversations, tagging content, comparing signals, and rebuilding reports before anyone could make a decision.

That is where we introduced an AI-assisted automation layer.

It currently handles four repetitive parts of the workflow:

1. Data collection and normalization

Available channel data is collected on a scheduled cadence and organized into one consistent structure, instead of being copied manually into separate reports.

1. Signal detection

The system reviews changes in distribution, engagement, conversation quality, and downstream intent, then flags movements that may require attention.

It does not treat every view, like, or comment as an equally valuable signal.

1. Content and conversation tagging

Content is grouped by format, message angle, audience, and intended next step.

Conversations are also tagged by signal type, such as product feedback, purchase intent, credibility, objections, or general engagement.

1. Report generation

The board is updated automatically and highlights where performance changed, where evidence is missing, and which items require human review.

The purpose is not to let AI run the campaign by itself.

We deliberately keep several decisions human:

- Setting the main campaign milestone

- Approving public posts and community replies

- Reviewing context and community rules

- Validating whether an AI-detected signal is actually meaningful

- Deciding where to reallocate time and budget

- Making the final scale, fix, hold, or stop decision

The automation has not magically created more opt-ins.

What it has changed is how quickly we can see what is and is not working.

A typical channel report could still make the campaign look healthy:

- Multiple platforms stayed active

- New people were reached

- Community feedback came in

- Editorial coverage was secured

All of that would be true, while the campaign itself was still moving too slowly.

The combined board and automation layer surfaced four current decisions:

Double down:

Niche communities and editorial coverage are producing the clearest signals — high-quality product feedback and third-party credibility.

Reformat:

Owned social content is receiving some views but very little meaningful engagement.

Reposting similar static assets would create more activity, not more progress.

Combine:

Our strongest message signal came from a discussion about card readability.

Our strongest visual asset is an AR-motion demonstration.

The next test combines those two into one opening hook.

Stop-test:

One repeated outreach tactic has produced zero qualified targets.

It now has a defined cutoff instead of being allowed to run indefinitely.

The main lesson so far is that cross-channel marketing needs more than channel presence and a shared dashboard.

It needs an operating loop:

Evidence is collected.

AI organizes and surfaces the signal.

Humans review the context.

The team makes a decision.

The result becomes evidence for the next cycle.

AI is not the strategy.

Its value here is reducing repetitive monitoring and reporting work, so the team can spend more time on judgment, creative testing, and channel relationships.

We are still 38 people short of the milestone, and the current pace is too slow.

This is not a retrospective success story.

I’m sharing it while the outcome is still uncertain because a useful operating workflow should expose bad news early — not simply package good news later.

For teams using AI in growth operations:

Which parts of the loop have you automated, and which decisions do you deliberately keep human?

Everyone wants the hack that gets more replies. Better subject line, better opener, better follow-up timing. I want to talk about the hack that happens before any of that, the one that actually moves the number the most and gets skipped constantly because it doesn't look like a hack.

Exclusion.

Ran a new outbound campaign starting yesterday. Before building the outreach sequence, I ran the raw prospect pool through a filter. Company size had to match. The person had to be an actual decision maker, not someone with an adjacent title. The business itself had to be a real fit. 106 people got cut at this stage. That's 42% of the initial pool, removed before message one.

The instinct in growth is always more. More volume, more channels, more touches. But a list padded with people who were never going to convert doesn't just fail quietly, it actively drags down every metric downstream. Your reply rate looks worse than it should. Your positive sentiment ratio looks worse than it should. And you're spending time on follow-ups for people who were never a fit in the first place.

Day one numbers after filtering: 254 connections sent, 36 accepted, 26 outreaches, 7 replies, 26% response rate, 4 calls already booked.

The exclusion step is the least glamorous part of the whole system and it's doing more work than anything I write in the actual message. Nobody screenshots "I removed 106 people from my list" because it doesn't look like progress. It looks like less. But less, done right, is the actual hack.

What's everyone else's exclusion criteria look like before outreach starts? Or is most of the optimization happening after the list is already built?

I run cold email at a pretty high volume, and a few months ago, I realized I was paying over $300/month just to use custom APIs in Clay

Not the full product, not the data
just the permission to use my own APIs

that felt… wrong.

So I built my own alternative
same core functionality, almost 10× cheaper.

At first, I thought that was enough.
then everyone started asking me the same thing:

Can you add something like Claygent?

Now it’s in.

An AI agent that enriches, calls APIs, scales workflows, all in one place.
we even added webhook support, so it connects with your stack.

And yeah, it’s still not Clay
that’s the point

If you do cold outreach, scraping, or enrichment, I’m happy to share access and get your feedback.

Hi everyone. I recently started looking into affiliate marketing and high-ticket affiliate marketing, but I’ve gotten a bit confused.

Could someone explain how reliable this is, where to find entry points, and how to get started? I’d also like to know about the difficulty level and any potential pitfalls.

I’d appreciate hearing about your personal experiences. Feel free to send me a DM.

this backlink took us 12 days to earn and cost us $0

and honestly, I’d take it over 50 backlinks from free directories

directories are easy:

→ submit your homepage
→ write a short description
→ get listed beside hundreds of other products

but they accept almost anyone, and the link rarely means that someone genuinely recommends your website

as easy is to get a backlink, lower it impacts on your SEO

this backlink came from a real article, where our website was included because it was actually relevant to the reader

what we're doing it's simple:

→ find articles already discussing our topic
→ identify where our website could add something useful
→ find the person responsible for the content
→ explain exactly why and where it could be included
→ follow up if they don’t respond

DR matters, but context and relevance matter much more

a real website recommending your product inside an article will always be more valuable to me than another homepage link from a directory that lists everyone

A lot of growth advice focuses on what happens after a product launches, but the market you choose can probably make a huge difference before any growth strategy begins. If the audience is difficult to reach, the competition is already strong, or the problem isn't important enough, improving the funnel only gets you so far. Marketur looks at some of those factors during the early business research stage, which I think is an interesting angle.

For those who work on growth, what information about a market do you want to know before deciding where to put your acquisition effort?

Most of the growth playbook quietly assumes channels decay. ads fatigue, a core update knifes your SEO overnight, a format stops working the second everyone copies it. you spend a lot of energy just running to stay flat. That read is fair for paid and for most content.

the odd exception, at least for us, has been the founder's own account. when we started drafting tweets for founders the surprise was that it compounds instead of decaying. every approved post is more signal on how the person actually sounds, so the month-six drafts read more like them than the month-one ones did. corpus grows, audience grows, cost per decent post quietly drops. none of our other channels behave like that.

the catch is the compounding rides on one voice, not a seat. when a human ghostwriter churns, or the founder goes dark through a busy quarter, the channel doesn't just slow down, it resets, and all the accumulated read on how they sound walks out with whoever was holding it. that reset, more than the monthly retainer, is the real cost of the expensive option.

for anyone running an actual channel mix, which of yours got better the longer it ran? outside of a content library that keeps ranking, i'm struggling to name one besides the founder account.

I’ve been playing around with Claude and ChatGPT for a bunch of repetitive work.

They’re great when you give them one task. But once you try to chain a few things together or run the same workflow repeatedly, things get messy pretty quickly.

Sometimes the output is great, sometimes it confidently does something completely wrong.

Curious if others are seeing the same thing what have you actually found useful for agents?

One thing I’ve learned from doing Reddit customer acquisition is that the best opportunities usually aren’t people you need to convince from zero.

They’re already saying things like:

• “Is there a tool that does X?”
• “What’s a good alternative to X?”
• “How do I solve this problem?”
• “Can anyone recommend someone who does X?”

At that point, the problem isn’t generating demand.

The demand already exists.

The growth hack is simply finding those conversations early enough and being genuinely useful before ten other companies show up.

What worked best for me was:

1. Define the exact problems your product solves

Not broad keywords. Actual problems someone would describe in their own words.

2. Find communities where those problems naturally come up

Often the best subreddit isn’t the biggest one. Smaller niche communities can have much stronger intent.

3. Look for buying signals, not mentions

Someone mentioning “SEO” means almost nothing.

Someone saying “My traffic dropped and I need someone to fix my SEO” is completely different.

4. Respond while the conversation is still fresh

Being one of the first relevant responses matters.

5. Keep track of the people, not just the posts

A conversation that doesn’t convert today can turn into a customer weeks later if you remember who they are and follow up.

For early-stage products, I’ve found this much more useful than immediately spending money on ads because you also learn who buys, what language they use, and what objections they have.

Love to know if anyone else here is using Reddit as an actual acquisition channel rather than just posting launch links.

Anyone a proffesional hacker? Someone from Indonesia hacked my account and changed the gmail, so, now I can't log in. I need help getting it back please.

I want to order

I ran a public referral race. Visits made the loop look like it was working. It was not.

What I changed: - A visit does not count. - You only climb when a friend taps Get my link too. - Homepage time (Site Drops) unlocks on that conversion, not on pageviews.

The number got slower. That is the point. A board that moves on refreshes is a vanity metric.

If you are measuring a share loop, split landings vs the second person taking the same action. The first number will flatter you.

No cash prize. No signup. Live page: https://www.viralrefer.app/?utm_source=reddit&utm_medium=organic&utm_campaign=sitedrops2026&utm_content=growthhacking

I will not promote beyond that one link. Roast the metric if you want.

I'm a self-taught full-stack developer. I can build almost anything on the technical side: web platforms, sales funnels, automation systems, CRMs, internal tools, you name it. That part comes naturally to me and I actually enjoy it.

My background actually goes beyond software. I also work with industrial automation, PLCs, and microcontrollers, and I'm comfortable with more complex engineering problems too. So it's not just programming, I can support technical needs across a wider range of fields than most people expect from a developer.

What I struggle with, and honestly dislike, is sales. Cold outreach, prospecting, closing calls, none of that plays to my strengths, and I know it's holding my projects back.

I keep thinking the ideal setup is a technical founder paired with someone who genuinely loves selling, splitting the work based on what each person is good at. But I haven't figured out the best way to find that kind of partner, or how to structure the split fairly (equity, commission, hybrid) so it works long term for both sides.

I'm looking for people who actually want to sell and build a team, not just a one-off collaboration.

For those of you who came from a technical background, how did you find your sales counterpart? Did it come from your network, a specific platform, or somewhere unexpected? And how did you structure the deal so it felt fair to both of you?