I’ve tried a wide range of strategies to distribute my SaaS.
I recently had a sudden burst of inspiration for a new project: AI-driven lead distribution. The idea is to use AI to analyze publicly available information and identify potential clients.
It used to be about handing out flyers on busy streets;
"AI distribution" gives the impression of using AI analysis to identify high-value potential customers and then targeting them with flyers.
How does everyone handle distribution, and what are some genuinely effective distribution strategies?
Clear and practical, thanks. Did anything surprise you along the way?
Interesting take. Would you still recommend this approach to someone starting today?
Good write-up. What would you do differently if you started again?
Curious how long it took before you saw the first real results?
try to post naturally on related subreddit of your niche. Don't rush else your account get banned faster. Reddit is still bigger goldmine for marketing your services.
Curious how long it took before you saw the first real results?
For me, distribution has become part of the product itself.
I’m experimenting with a SaaS where one of the main goals is to get discovered through AI search (ChatGPT, Perplexity, Google AI, etc.), so I’ve been thinking about distribution from the other direction:
Instead of only asking “how do I get people to see my product?”, ask “when someone is already looking for a solution like mine, does my product show up?”
So far, the channels I’m paying the most attention to are:
I’ve tried paid acquisition and broad promotion before, and honestly, getting traffic is much easier than getting the right traffic.
Curious what channels have actually converted into paying users for you guys.
For early-stage SaaS, I’ve found that distribution works better when you go where the problem is already being discussed rather than trying to reach everyone. Reddit, niche communities, founder groups, and targeted cold outreach have been more useful for me than broad promotion.
The key is usually finding the right audience first, then testing a few channels consistently instead of spreading yourself across too many.
Still figuring this out with Padro. We help experts monetize what they know through an AI twin their audience can pay to use. Right now I’m reaching out to people who already sell courses or coaching. I’m posting here too, though that’s been more about getting feedback than finding customers.
Your lead idea would be useful to me if it could tell me why someone might care right now. Maybe they just launched a course or mentioned wanting another way to earn from their audience. I can find a list of coaches pretty easily. The timing is the hard bit.
I’m starting to think building the product was the easy part 😄
I launched recently and suddenly discovered my new full-time job: figuring out where the people who might actually want it are hiding.
I’m testing a few very different channels right now, and my biggest lesson so far is that traffic and actual users are two completely different species.
I’m becoming much more interested in small, concentrated communities than in “reach everyone” distribution. Fewer people, but the right people.
If your AI figures out where those people are hiding before I do, please send it my way. 😄
Regarding the AI lead generation: from working with agencies, the issue usually isn't defining a lead, it's identifying which prospects actually have intent to buy anything at all. A company can look like a perfect fit on paper, and you'd expect them to reply to outreach, but often they don't. What signal would your AI use to tell intent apart from fit?
What has worked for me on distribution: test one channel at a time, with a number you have decided -> before you start, and tag every link with a UTM per channel. When I ran several at once I couldn't tell which one did anything.
Solo builder here, shipping tiny one-time-purchase web tools, and my distribution stack looks pretty different from the SaaS playbook in this thread. Three things that actually moved the needle for me:
Launch directories as a system, not a one-off. Product Hunt, BetaList, and the smaller launch calendars — I treat them as a repeatable pipeline and schedule every launch on PH a few weeks out so I can line up the assets (demo video, screenshots, the first comment). One launch won't do much; the fifth one compounds because you stop making rookie mistakes.
Marketplaces with built-in search intent. Gumroad and itch.io both have people actively browsing and searching — the tool sits next to a free demo, and the paid tier ($19 lifetime Pro) is one click away. That "try it now, pay once" loop works far better for me than any landing page could, because the demo IS the marketing.
Keep it tiny and self-serve so distribution is the product's job, not yours. No onboarding emails, no sales calls — if it needs an explanation video longer than 90 seconds, it doesn't ship.
The common thread: I don't do outreach at all. Everything is 'show, don't tell' — free interactive demo first, paywall second. It works because the tools are small enough that the demo is the whole pitch.
distribution is the hardest part of building
Nice progress. What is the next thing you are focusing on?
Holy cow, I opened my email today and it was nothing but comments—this post has gone viral.
Let me go through them one by one and see what everyone’s saying.
AI-driven distribution sounds promising. The key is using AI to identify genuine buying signals, not just generate more leads. Combining that with personalized outreach could make it much more effective than traditional mass marketing.
Good write-up. What would you do differently if you started again?
Nice work shipping it. What has been the biggest challenge since launch?
Nothing has worked for me except talking to people one at a time. I message people on LinkedIn myself, no script, no mass send, and have a proper conversation before I ever mention DOER. Slow but the ones who join stick. Every tool I tried to skip that step with got me nothing.
I'm trying multiple things. Most are built into a Claude plugin I made to find conversations on socials, leads and posting opportunities. I also built tools for video gen and meme making just to help produce more content, and next step is to repurpose that content by finding multiple places to post. I plan to post an update on IH if any of my efforts are effective.
one thing i have realised sometimes its all about how cool your product is like days back i shipped mybox: message yourself ios app built it in 2 days like very stupid app and i just did one post on reddit and its well unique and cool yet simple idea people liked it got around 100 upvotes 1200 users & $1.2k+ added in my bank account and reddit account got banned lol all within the same day and before it i never got even 100 downloads or $10 on my first launch. I realised sometimes its about idea and how cool product is if its user facing and if not if its b2b then you gotta grind hard the manul door to door knocking and the other case is simply look for people already using your competitive business reach out to them with better offer
A useful contrast from this week: a small batch of personalized cold emails produced no replies, while one public community thread produced a detailed critique that changed the product. The difference was that the thread asked people to challenge a concrete output, not to evaluate a pitch.
I’m now separating distribution into two loops: direct outreach for buyer conversations, and public problem posts for product learning. I track replies and completed actions per source rather than views. For your AI lead idea, I would test whether it can attach one checkable, recent reason to contact each lead. Fit alone still leaves the recipient asking, ‘why are you writing to me today?’
Interested
Distribution is the part most technical founders underinvest in until it's too late. In my experience, the honest breakdown is: channel one almost always comes from direct relationships (someone you know, or someone who knows someone, who has the problem and says yes). Channel two usually comes from content you wrote that's specific enough to rank or be shared. Channel three tends to be community — IH posts like this one, actually.
The AI lead distribution angle is interesting but I'd be cautious about leading with it as a channel before you have product-channel fit. The way I've seen it go wrong: AI identifies the right company but the wrong person, outreach goes to someone with no budget authority, and you burn the introduction. Especially in B2B, the relationship layer still matters. AI gets you to the door faster; you still have to knock.
What's your actual conversion rate looking like from the strategies you've tried so far? That'll tell you which one to double down on before layering in AI targeting.
You offer profound insights; you’ve highlighted the distinct challenges of B2B distribution and the specific risks associated with AI-driven distribution in this sector. Your points—along with tristanlefler’s comments—underscore the unique nature of B2B distribution. If I move forward with this project, I will certainly give this aspect serious consideration. Thanks for sharing.
for B2B we stopped chasing "channels" and ran one outbound motion hard for 4 weeks: tiny ICP, one real signal in line one, then email + LinkedIn on the same account.
distribution only compounds after you know why people say no. until then more channels just multiply confusion.
Thanks for the insight.
It’s actually somewhat similar to AI-driven distribution; the difference is that AI-driven distribution delegates the capture process to the AI, whereas your strategy involves capturing the information yourself. Doing it yourself likely encompasses a broader scope—such as real-world sources—rather than relying solely on publicly available online information.
I have seen a lot of products listed recently who promise some form of this idea. Like with everything else, they are just lots of nice promises until you actually prove them. Ask around and see if anyone you know has actually used one of them as a real customer. Did it work for them? What were the drawbacks?
That’s a great idea. My concept was inspired by Ben Cera’s polsia.com on X. While AI distribution is currently just one part of that product, I think it would be better to spin it off as a standalone offering; this would allow for the inclusion of a wider range of products and services—going beyond just SaaS and apps—since all products and services require distribution. As for the specific implementation details, I need to look into that further.
Timely thread — I'm mid-way through exactly this problem. Packaged a real client project (membership/booking web app) into a generic template and put it on Gumroad. First move was posting into dev-heavy spaces (r/webdev, X, here on IH) — got some likes/engagement, but zero real traffic to the actual listing.
Lesson so far: dev communities will engage with the "how it's built" story, but they're not the buyer — the actual buyer for a productized template like this is a non-technical small-business owner (gym/league/studio manager), who isn't reading r/webdev or IH.
Now trying to find where that audience actually is — FB groups for studio/club owners, Product Hunt, etc. Curious if anyone here who's sold B2B-small-business tools (not to other devs) found a discovery channel that actually worked for reaching a non-technical buyer.
Demo + listing if useful context: https://claude.ai/artifact/1NzvyGFAKa1tC14pVUYeNd · https://arielshimmer6.gumroad.com/l/jtiei
At its core, it is really about identifying exactly who your target audience is and figuring out how to reach them. Experts in the comments section have shared some highly valuable strategies; you should take a close look at them and learn along with everyone else.
I'm just starting with my first small app: it helps people document the condition of a rented flat or car with photos and signatures. I don't know anyone who rents, so I'm trying to reach tenants through tenant unions and forums where people already ask about deposit or fuel disputes, and I answer their questions first before mentioning anything. Too early to say if it works, but replying to real problems is the only thing that hasn't felt like spam. Curious: what got you your first 10 users when you had no audience?
Based on the replies from the experts in the comments section, your approach should be very effective.
What we've leaned on is posting the specific problem in communities where people already talk about it, then replying to what comes back. It gets you in front of people who already care, which a broad list can't do.
Great idea—I've learned something new.
Glad it helped. Happy to swap notes if you're testing it out.
Small bets have worked better for me than one big channel: launch directories for search intent, 1-2 helpful founder communities, then a simple challenge or interactive hook people can share. I’m testing that with a free builder benchmark game for SaaS founders, where the top five get their SaaS link on the leaderboard: https://www.buildersbenchmark.com/
I checked out your website—it’s interesting.
It uses games to determine rankings and makes sharing easy.
However, what happens to users with low scores whose rankings aren't visible?
One pattern I've seen hold up across products: write about the problem, not the product. Problem-focused content ranks and gets shared; product announcements get ignored everywhere except launch communities. The channel honestly matters less than whether a stranger would find the content useful with the product stripped out.
This is a very astute observation: it emphasizes asking rather than telling. The essence of asking is to get others to speak, whereas the essence of telling is to get them to listen—and the real question is, why should they listen to you? This approach echoes the ancient Chinese strategic philosophy of Baihe (opening and closing/advancing and retreating). Setting the product itself aside, the core lies in whether the problem you are addressing holds value and whether your solution offers value. A truly good solution does not require aggressive promotion; it will naturally stick in the minds of your trial users.
For small products, I’d use a tight loop: (1) pick one buyer/job, (2) choose one channel where that buyer already asks questions, (3) publish 3–5 useful answers before linking anything, (4) track qualified conversations and conversions—not impressions, and (5) repeat the message that earns replies. A tiny checklist and a clear next step usually outperform a broad “AI-powered” pitch.
I’m testing this with a small, value-first sprint: $7 for a Close Kit, $12 for a discovery scorecard or keep kit, and $27 for all three. Happy to share if useful; no pressure.
Regarding this new distribution approach, my understanding is that your product solution analyzes high-value content and then provides the user with distribution recommendations—is that correct? And the idea is for the user to actually carry out the distribution based on those recommendations?
Honestly still figuring this out myself. Tried Facebook groups first —
most posts got auto-removed before anyone saw them. Reddit needs
account karma before it'll even let you post. Direct outreach (DMs,
emails to people who'd actually use the thing) has been the only
channel that doesn't have some kind of gatekeeping built in, so that's
where I've been putting most of my time lately. Curious if others
found something that worked faster.
In the comments section, some experts have put forward several highly valuable distribution strategies.
ahora mismo estas en el canal que estabas buscando
Ha ha
For a B2B WordPress plugin (I build TurnKey Directories - it lets someone launch a business directory site), what's working at the pre-revenue stage is boringly manual. I picked the handful of communities where my exact buyers already talk - WordPress, local SEO, people trying to launch directories - and show up daily with actual help, not promos: public replies first, never cold DMs. The second leg is qualification over volume. I hand-pick maybe five real prospects a day and offer founder-assisted onboarding instead of a checkout link. A hundred targeted touches beat a thousand impressions at this stage because you learn why each no happens. On the AI-lead-distribution idea: identification is the easy half, the message that lands is the hard half - same trap as flyers. What's your plan for the outreach part once the AI hands you the list?
Right, the idea is to commit to a specific channel and maintain long-term, active engagement there to reach users—a point also highlighted in "sniper8192's" earlier comment regarding the actual effectiveness of this approach.
Once the list generated by the AI is obtained, the process could be designed so that the AI initiates contact and handles replies through a unified interface; however, I still need to further evaluate the feasibility of this plan.
That last step is where I'd be careful. AI finding the list is fine; AI sending the first touch is how you end up in spam folders with a burned domain - people smell automated outreach instantly now. I'd keep the first message and every reply human. The unified inbox for triage is the genuinely useful half of the idea. What guardrails are you weighing for the send side?
Distribution that scaled for me was never a channel I built, it was one I borrowed. Henson Group grew for almost two decades on Microsoft's field sellers, because they already had the meetings and we only had to be the partner they trusted to hand the work to. Before you build AI lead gen, ask who is already selling to your exact buyer, then figure out what you can do for them that makes introducing you worth their time.
A scoreboard from the other side of this question: solo founder, a few weeks in, small EU-accessibility scanner. X suspended my account three times and Reddit auto-removed comments from a new account, so both were dead ends before I had a single conversation. About 150 cold emails so far have produced one human reply and no payment. Search is the slow bet: five articles built from data I collected while scanning, too early to say anything.
The trust-borrowing framing in this thread matches what I saw. The one thing that got a reply was giving the recipient something checkable without asking them to trust me first. That's what I'd want an AI lead tool to prove: not "here is your list," but "here is a checkable reason this person should care." Has anyone here seen that work at scale?
Right, your core concern is whether the individuals on this list are genuinely facing this issue; the comment by "peptides13" further highlights the importance of timing, cutting straight to the heart of the matter.
What worked for me over twenty years was not finding customers, it was finding whoever already had them. At Henson Group we grew on the back of Microsoft's field sellers, because one partner who already owned the relationship beat any volume of cold outreach we could run ourselves. Before you build AI lead distribution, work out who already sells to your buyer every week and what you can hand them so they bring you along.
This is a truly unique perspective on distribution. Targeting the salespeople who are already solving this problem—rather than the people actually facing it—creates a sense of leveraging existing momentum and forming an alliance, with the option to offer commissions. Thanks for sharing; I will give serious consideration to this approach.
Your flyer metaphor is the sharpest part of your post, and I'd take it one step further. A flyer works on a busy street because the street already has the traffic, and the human vendor picked the street — the targeting was done before the flyer was printed. Most distribution failures I see are the reverse: founders build the flyer (product, landing page, outreach list) and then pick a random street.
A framework that helps me rank candidate channels: score them by how much trust they come with pre-loaded. Cold outreach borrows zero trust — you pay for every reply with effort. Communities borrow a little, via your comment history. Search borrows Google's. Referrals borrow someone else's reputation. The "AI finds the customer" idea only solves discovery; it doesn't add any trust to the channel, which is why scaled outreach still converts at ~1%. The lever isn't a better list, it's a channel where the trust is already there.
Concretely, once you pass praneetbrar's "one ugly sentence" test — who it's for, in one line — ask where those exact people already admit the problem out loud: search queries, subreddits, Slack or Discord communities, comparison threads. Pick exactly one street, and commit to 90 days of showing up there before touching another channel. Almost every indie distribution story that works is "I became a regular somewhere for three months," not "I tested twelve channels." The AI can help you find the street. It can't hand out the flyers in a way people trust.
These are profound insights; let me summarize them:
Incorporating "praneetbrar's" comment, an AI-driven distribution system could be designed to handle the process: after AI analysis, the system initiates the first contact, follows up if there is no reply, and so on. Once a response is received, a unified interface allows for human follow-up to engage the customer. AI could even analyze performance to further refine the analysis phase. While the concept is compelling, I am unsure of its practical feasibility and need to conduct further research.
Regarding the trust associated with distribution channels, I believe it depends largely on the nature of the problem the product addresses and the level of competition. If you offer a solution to a problem that represents an extreme, absolute necessity and faces no competition, users are highly likely to give it a try.
Seen this problem now with many founders. Distribution is honestly where a lot of them seem to get stuck after building the product.
I think the first question is less “what channel should I use?” and more of 'where are the people who already have this problem looking for answers?' That could be search, Reddit, communities, comparison sites, reviews, etc. Once you know that, you can work backwards and figure out what would actually get the product in front of them. AI can help with the research, but I don't think it replaces the actual understanding of the customer.
Yes, distribution is essentially about finding people facing the same problem and getting them to try your solution. There are many distribution channels, each with varying levels of effectiveness. AI-driven distribution is simply one such channel; its purpose is to leverage public data to identify the most valuable potential customers—though, as you rightly pointed out, there is a risk that it might not truly understand your customers. Ultimately, the actual results will depend on the product's launch and market validation; you have raised a very valid point regarding this risk. Personally, however, I lean towards embracing AI.
I’ve had better luck treating distribution as a set of small experiments rather than one AI-powered list. For each channel I log who I contacted, the problem they mentioned, and whether a real conversation happened. One reply with a specific pain is more useful than a large batch of prospects. I’d keep the first outreach manual and narrow enough that a recipient can tell why they were selected. How are you thinking about consent and relevance when using public data?
Here is how I envision it: the process you described would actually be carried out through AI analysis rather than by manually searching for public information. AI allows us to generate a precise list of potential clients—far faster than a human could—and then contact them. It’s similar to distributing flyers, but with an added layer of AI-driven relevance analysis, so you don't waste time handing them out to random people on the street who aren't interested. If you receive a reply, that establishes the connection you mentioned.
The gap in the AI distribution idea is that public information tells you fit and almost never tells you timing, and outreach is mostly a timing problem. A company can be a perfect match for two years and only be buying in one particular week. What does carry timing is change rather than state: somebody just posted a complaint about the tool you would replace, a job ad appeared for the role that owns this, a pricing page moved. If the AI watched for what changed this week instead of scoring companies on how well they fit, you would get a much shorter list with a reason to write today attached to each name.
That’s an insightful point—timing is crucial. Regarding timing, it requires specific attention to how AI prompts are structured; if I launch this new project later on, I will certainly keep that in mind. Thank you for the observation—it’s very helpful.
Honestly the flyer picture is the useful bit. The AI part is just a faster way to pick the wrong street. What actually worked for me was one place I could sit in the same week and answer, not a pile of potential clients. If I cannot say who it is for in one ugly sentence, more targeting just burns the morning faster. Are you stuck distributing the old SaaS, or is this lead thing already the product?
That’s a great idea. My initial concept was to use AI to analyze public data, identify the most valuable prospects, and obtain their contact information. You are proposing taking it a step further by centralizing all communications—whether via email, X, or various social media platforms—into a single interface for responding. I had considered this, but I’m not sure if integrating that many social media channels is feasible for the first version; I’ll need to look into it further.
I forgot to mention the content of the flyer earlier. You can easily use AI to generate content that aligns with publicly available information while incorporating the unique selling points of your product; it is a straightforward task that AI excels at.
Distribution is the moat. We spent €150 on Google Ads and got 0 installs. Pivot to organic: reply to growing conversations on Threads, build in public, cold DMs. Personal > paid every time.
I view distribution as occurring in stages: the cold-start phase and the expansion phase. The cold-start phase involves early market validation and rapid product iteration, whereas the expansion phase represents a period of rapid growth once the product has stabilized.
This comment was deleted 2 hours ago