Guide · Updated August 2026

How to Find Your First 100 Customersin online communities

The first hundred are not a growth problem. They are a hundred conversations, most of them started by somebody else, in five places where people are already asking for exactly what you built. This is how to find those conversations and be useful in them without turning into the thing everyone mutes.

Updated 15 min readBy the ParseStream team
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Five platform cards — Reddit, Hacker News, Quora, X and LinkedIn — routing down into one inbox, where an r/SaaS post asking “Any tool that watches Reddit for keywords?” is tagged buy-intent above a quieter pain-point mention from Hacker News, beside a counter reading “#14 of your first 100” in week 3, over a Suggested Reply draft to edit and post yourself.
The short answer

How do you find your first 100 customers?

You find your first 100 customers by going to the communities where your buyers already ask questions — Reddit, Hacker News, Quora, X (Twitter) and LinkedIn — monitoring the phrases people use when they have the problem you solve, and answering those posts one at a time. ParseStream watches those phrases across all five platforms, alerts you when one appears, and — whenever Lead Detection or an AI Filter is running on that keyword — tags each mention's intent, so a buying question is easy to tell from a rant.

Expect weeks, not days. The first hundred are recruited by hand, in public, one conversation at a time, and every reply is one you edit and post yourself.

83%

of B2B decision-makers research on their own before ever speaking to a salesperson.

Source: SurveyMonkey with Reddit
2 in 3

buyers now prefer to talk to a vendor's salespeople only in the later stages — up 17 percentage points in a year.

Source: G2 (2025 Buyer Behavior Report)
10%

or less of your posting and conversation should link to your own content, by Reddit's own rule of thumb.

Source: Reddit self-promotion guide
01

Why do the first 100 customers come from communities?

Because there is nowhere else for them to come from yet. You have no brand, no backlinks, no referrals and no budget that survives a paid experiment. What you do have is the ability to go where people are already discussing your problem and be conspicuously useful about it — a channel open to a company of one precisely because it does not scale.

The first users get recruited, not acquired

Paul Graham's essay on the subject remains the clearest statement of it. “The most common unscalable thing founders have to do at the start is to recruit users manually,” he wrote in 2013. “Nearly all startups have to. You can't wait for users to come to you. You have to go out and get them.” The line before it is the one that stings: “Actually startups take off because the founders make them take off.”

His best example is what Y Combinator calls the “Collison installation”. Where most founders would email a link and hope, Stripe's founders “weren't going to wait” — when anyone agreed to try it they would say “Right then, give me your laptop” and set them up on the spot. That is the register the first hundred are won in: not a funnel, but a hundred separate people deciding you were worth the risk because you were useful to them first.

Your buyers are already asking, in public, before they buy

This is not a hunch about how software gets bought. A study SurveyMonkey ran with Reddit among 1,202 US business decision-makers found 83% self-research before ever speaking to sales, and that peer recommendations are the most trusted channel they have: 73% trust peer insights, ahead of vendor websites (55%), search engines (54%), review sites (46%) and AI chatbots (39%).

G2's 2025 Buyer Behavior Report, from 1,169 B2B decision-makers, found nearly two out of three now prefer to engage a vendor's salespeople only in the later stages — up 17 percentage points in a year. So the part of the buying process you are allowed into happens in public, among peers, long before anyone fills in a form. There is also a standing supply of dissatisfaction: Forrester, surveying more than 16,000 global business buyers, found 81% express dissatisfaction with the provider they chose at the end of a purchase everyone would call successful.

What this is not

It is not a launch. A launch is one day with a spike and a long tail of nothing; this is a habit with a slope, and the two are easy to confuse until the spike is over.

It is not astroturfing, and the distinction is not subtle. One real account, disclosed affiliation, replies you would stand behind if the reader knew everything — that is participation. Multiple accounts, invented enthusiasm, friends brought in to upvote — that is what these communities are built to detect, and getting caught costs you the only place your buyers gather.

And it is not a substitute for the product being good: if the first ten people you help try it and quietly do not come back, the monitoring is doing its job.

02

Which communities should you be in, and what is each one good for?

The five platforms ParseStream monitors behave nothing like each other. Picking two to do properly beats spreading yourself across all five badly — but you need to know what each is for before you can pick.

The honest test for any of them: search it for the problem you solve, in a customer's words, and read what comes back. If there are threads, there is a channel. If there are three results from 2019, there is not, and no tool changes that.

What each community is worth at the first-100 stage, and what to expect from it.
CommunityWhat it is good for at this stageRealistic expectation
Reddit“What do you use for X?” threads inside subreddits organised around your buyer's job, plus complaints about the incumbent.The highest volume of genuine buying questions of the five, and the strictest etiquette. Expect to answer for a while before you ever name your product.
Hacker NewsTechnical founders and early adopters. A Show HN puts a working thing in front of them; the comments surface objections you have not heard yet.Bursty. One thread can outproduce a month of everything else, then nothing for weeks. Not a channel you can schedule.
QuoraBuying questions asked in public and answered more or less forever — “best tool for X”, “X vs Y”. Answers keep working after you write them.Slow to start and compounding afterwards. Judge it on months, not on the first fortnight.
X (Twitter)People complaining about a tool in real time and asking their timeline what to switch to. Fast, informal, low friction to reply.Reach depends on who already follows you. Early on almost all of your value comes from replying to other people, not from posting.
LinkedInWhere a switch gets announced after it has been decided, and where operations, HR and marketing buyers name vendors in public.The slowest of the five for live buying questions, the best for a warm follow-up with someone who already knows who you are.
What each community is worth at the first-100 stage, and what to expect from it. Developer and technical products usually find Reddit and Hacker News carry the load. Products bought by operations, HR or marketing teams tend to find LinkedIn and Quora do. Almost nobody finds all five worth the same effort.

Reddit: the highest volume, and the strictest rules

Reddit is where the recommendation thread lives, and its users are unusually willing to describe what broke and what they moved to — in the SurveyMonkey study, 23% of decision-makers had used it to research a business purchase, rising to 32% of software buyers. It is also the platform most likely to eject you for getting the ratio wrong. Reddit's own self-promotion guide puts a number on it: “a general rule of thumb is that 10% or less of your posting and conversation should link to your own content”. Individual subreddits layer stricter vendor rules on top, and those are the ones enforced, so read the sidebar first.

Hacker News: high ceiling, no schedule

Hacker News rewards a working thing and punishes a pitch faster than anywhere else here. The Show HN guidelines are explicit: “Show HN is for something you've made that other people can play with,” and “Off topic: blog posts, sign-up pages, newsletters, lists, and other reading material. Those can't be tried out, so can't be Show HNs.” The rest of the time the value is in comment threads, where answering well as someone who has obviously built the thing is worth more than the Show HN most weeks.

Quora: slow, then permanent

Quora is the only one of the five where the question is designed to be permanent. “Best tool for X” gets asked once and read for years, so an answer written in month one can still be sending you people in month eighteen. The cost is patience: nothing feels like it is working early, and the answers that eventually do the work are the long, specific ones that took forty minutes. Write fewer of them, and disclose what you build in the answer rather than leaving it to your profile.

X (Twitter): the fastest, and the most forgettable

X is where somebody announces at 11am that a tool has broken again and asks what everyone else is using. The window is short and the barrier to replying is almost nothing, which makes it the easiest of the five to build a daily habit around. The catch is that your own posts reach nobody early on — so the first hundred come from your replies, in other people's threads, where the audience already exists.

LinkedIn: late, warm, and useful for the follow-up

LinkedIn rarely hosts the live “what should I buy” conversation. It hosts the announcement afterwards, and the comment threads under a vendor's own marketing where honest objections surface. Its value here is continuity: someone you helped in a Reddit thread is on LinkedIn under a real name and job title, which is how a helpful stranger becomes a person your next release is relevant to. That is a follow-up, not a cold pitch — the difference being that they replied to you first.

03

The loop, step by step

Every founder who has done this by hand describes the same failure: it works for eight days and then a bad week eats it. The point of running it as a monitored loop is not that the loop finds better threads than you would. It is that it is still running in week six.

The ParseStream workflow, in five stepsA left-to-right flow: add your brand, add keywords, get alerted by email or Slack, qualify the mention with AI Filter, Lead Detection and Intent Detection, then edit and post the reply yourself.1Add branddomain + context2Add keywordswhat buyers type3Get alertedemail or Slack4QualifyAI Filter ·Lead Detection ·Intent Detection5Reply manuallyyou edit and post
How a keyword becomes a posted reply. ParseStream drafts the Suggested Reply; you edit it and post it yourself.

  1. Step 1 — Pick two communities, not five

    Count the threads from the last ninety days on each platform. Two with real activity beat five with a trickle: the habit depends on there being something worth opening most days.

    Add your brand to ParseStream at the same time — the website, a short description of what you sell and who buys it, and the competitors you keep losing to. Everything downstream reads from that description, so a vague one produces vague qualification later.

  2. Step 2 — Write the phrases people use before they know you exist

    The keyword mistake at this stage is tracking your own product name. Nobody is typing it yet. They are typing the problem, in their words, and the shape of question they ask when they want a recommendation — and each keyword can be scoped to the platforms where that question gets asked.

    • The problem in the customer's words: “our changelog is a Google Doc nobody reads”, not “release communication platform”.
    • Recommendation shapes: “any tool for”, “what do you use for”, “best way to”, “recommendations for”.
    • Competitor names, and the language of leaving them: “alternative to”, “switching from”, “migrating off”.
    • The workaround people use instead: “spreadsheet for”, “Zapier for”, “script that”.

  3. Step 3 — Get alerted while the thread is still open

    Matches arrive by email, in Slack, or both. Timing does most of the work here: a recommendation thread collects its useful answers within hours, and on X the window is shorter still. Being third to answer well beats being twentieth with the better answer.

  4. Step 4 — Cut the noise with an AI Filter and Lead Detection

    Raw keyword matching is blunt, and blunt is what kills the habit. An AI Filter is a rule you write in plain English and attach to a keyword — “only keep posts where someone is asking for a tool recommendation or describing a problem we solve”.

    Lead Detection is the second pass: it checks each mention against your brand context and decides whether it is a genuine lead opportunity for you specifically. That matters more when you have no customers than when you have a thousand, because you have no pattern to recognise yet and every match looks plausible.

  5. Step 5 — Triage by intent, then open the thread

    Whenever Lead Detection or an AI Filter runs, ParseStream also tags what each mention is — buy intent, product question, competitor complaint, pain point, testimonial or promotional — at no extra credit cost. That single tag is what lets you work a queue without opening everything in it.

    Take buy intent and product questions first: those people have already decided they want something. Pain point is the slower, better queue — someone describing the problem without knowing a category exists is the least contested conversation you will find, and often the customer who stays.

  6. Step 6 — Reply, disclose, and follow through

    ParseStream drafts a Suggested Reply from your brand context and the thread it appeared in. Treat it as a first draft — cut anything that reads like marketing, add the one detail only someone who built the thing would know, and say plainly that you build it before you name it.

    ParseStream does not post anything. Automatic posting is disabled at the server level by design, so every comment under your name is one you read, edited and sent yourself.

    Then do the unscalable part: answer the follow-up, offer to set it up with them, and ask the ones who did not convert what stopped them. That is where the hundred actually comes from.

04

What should you reply to, and what should you leave alone?

Most mentions do not need you in them. The commonest way founders burn a community is answering everything, because volume of replies feels like effort — while the people reading are counting how often your comment was worth reading.

The test that works is to delete every mention of your company from the draft. If what remains still answers the question, post it. If the comment collapses without the plug, you have written an advertisement and it will be read as one.

  • Reply when you can answer properly, including the parts that have nothing to do with your product.
  • Reply when the honest answer is a competitor. It costs a thread you were never winning and buys the credibility that makes the next one land.
  • Reply when you have a specific, checkable detail — a number, a limitation, a thing that broke for you — that nobody else has.
  • Skip anything you would answer only in order to appear, and skip the pile-on — agreeing that a competitor is terrible reads as marketing however true it is.
  • Never DM someone who posted publicly without being asked, and never run a second account or ask anyone to vote for you. Either one ends the channel.
  • If a moderator pushes back, stop. Winning that argument costs more than the thread was worth.
05

How long does this actually take?

Weeks to months, and the honest version has arithmetic in it. Find three relevant threads a day across two platforms, reply well to two, and let one in five of those replies produce someone who tries the product: that is roughly two trials a day in a good week. At a conversion rate you would be pleased with, a hundred paying customers is a quarter of work, not a fortnight.

The ramp has a predictable shape. Week one is keyword tuning — you will drop phrases that match constantly and mean nothing, and add three you had not thought of. By week two the queue stabilises into a ten-minute pass each morning. Around week four you start recognising usernames, which is when it compounds: people who have seen you be useful twice behave differently the third time.

Two things reliably distort expectations. A hundred customers is not a hundred signups — the same SurveyMonkey study found 65% of buyers spend a week or less researching but 31% spend several weeks or more, so a share of this month's good conversations closes in a month you have stopped counting. And one Hacker News thread can deliver twenty of the hundred in a day and never repeat, which makes any early weekly average fictional.

The failure mode is not that this does not work, but that it works slowly enough to be abandoned at week three — exactly when the compounding would have started. Count conversations rather than customers until there are enough customers to count.

Frequently Asked Questions

How long does it take to get your first 100 customers this way?

Which platform should I start with?

Is mentioning my own product in a community against the rules?

Can I just search these platforms manually instead?

Does ParseStream post the replies for me?

What does it cost to try this?

Related reading

Where to go next once the habit exists and you want more out of the same setup.

How to find leads on Reddit

The same loop with a sharper qualification layer, once you have enough volume to need one.

Track competitors on Reddit

Pointing the same keywords at your rivals' names and the people quietly leaving them.

Reddit keyword monitoring

What ParseStream monitors on Reddit, and how subreddit filtering keeps the queue small.

Hacker News keyword monitoring

Catching the comment threads that matter more than the Show HN most weeks.

Quora keyword monitoring

The buying questions that get asked once and read for years afterwards.

X (Twitter) keyword monitoring

Where someone asks their timeline what to switch to, and the window is hours.

LinkedIn keyword monitoring

Where the switch gets announced, and where a helpful stranger becomes a warm follow-up.

Sources

Every statistic on this page comes from the published research below and was last checked in August 2026. Search and AI-citation data moves quickly, so treat the figures as a snapshot of 2026 rather than a permanent state of affairs.

Find the first hundred conversations

Add the problem your customers describe, in their words, across the communities where they describe it. ParseStream surfaces the mentions, tags what each person actually wants, and drafts a reply for you to edit and post yourself.

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