Founder Growth
How a new SaaS gets its first 100 users
An honest playbook for the first 100 users with no audience: where people actually look, how discoverability compounds, and why consistency beats launches.
Follow the places people make a decision.
What should I use?
In this article
If you launched without an audience, the first hundred users will require a way to reach people who have the problem your product solves. Start by defining “user”: a signup, a completed first task and a paying customer are different milestones.
For a small team, the useful early record is simple: where a person found you, what they wanted to do, whether they completed it and why they returned or left. That record helps you choose the next conversation or page to work on.
This guide covers ways to make the product easier to discover while you learn from the people trying it. The channels are options to investigate, rather than a promise that every product needs the same marketing plan.
- Define the milestone: signups, activated users and paying customers are different counts.
- Start with a reachable audience and a task the product can help them complete.
- Keep the source of each arrival alongside activation and retention, so traffic does not become the only success measure.
An answer can draw on more than your website.
Which product should I use?
Why the launch myth fails you
A successful launch story may omit the audience, partnerships or earlier work behind it. Use it for ideas, but build your plan around the people you can reach and the problem you can demonstrate today.
A launch concentrates attention in a short window. Plan what an interested person should do next: try a working example, import a small dataset or complete a task. Check where that path breaks before seeking another burst of traffic.
The follow-up matters. Read support requests, ask new users what they expected and look for the task that brought them back. Those details can improve both the product and the explanation you use to attract the next person.
Where your first users actually look
Ask the people already using the product where they looked for help and which alternatives they considered. When there are no users yet, study the public questions asked by the intended audience.
When someone has a problem your product solves, they do some combination of the following, often in the same afternoon, without thinking of it as research.
They ask an AI assistant
An assistant may be one place a prospective customer asks for options. Check a few realistic questions, save the returned recommendations and inspect their sources. An omission tells you about those answers; it does not establish that the product is absent from every customer’s research.
Keep answer checks beside conventional search data. They describe different routes to discovery, and a high result in one does not guarantee inclusion in the other.
They still search, but differently
People also search for instructions, comparisons and alternatives. A clear page answering a specific question can introduce the product while helping the reader make progress. Track the queries that bring relevant visitors and what those visitors do next.
They read communities and ask peers
Choose communities based on the audience you actually need to reach. A developer tool and a clinic scheduling product are unlikely to belong in the same discussions. Read the rules and contribute where your experience is useful.
They check directories and review sites
A relevant directory or review site can give customers another way to inspect the product. Check where comparable products appear, then decide whether a maintained listing would help the people you want to serve.
These routes can overlap. A customer might read a discussion, search the product name and visit the documentation before signing up. Ask about that sequence when you can; the last referral alone may miss most of it.
The discoverability flywheel
One useful resource can serve several purposes. A setup guide may answer a support question, attract a search visitor and give someone a page to share with a colleague. Plan around those uses rather than an assumed growth curve.
For example, a tool for importing spreadsheets could publish a worked guide using a small sample file. The guide helps a prospective user judge the process and gives support staff something to share. If readers link to it or an assistant cites it, record that as an observed result.
The resource has a reason to exist before it earns a backlink or citation. That makes it easier to judge: can someone use it to complete the task, and where do they get stuck?
Some resources continue attracting relevant visitors; others receive little attention or become outdated. Review both the traffic and the usefulness of the material before assuming that more publishing will compound.
For the deeper mechanics of how AI engines decide who to name, see the new playbook for the AI search era. →Why consistency beats launches
A recurring review helps you notice changes and follow up with users. Choose a cadence you can maintain without crowding out product work.
Consistency is valuable when it produces learning or useful material. Publishing on a fixed schedule is not, by itself, evidence that a search engine or assistant will give you more visibility.
Set a review point before trying a channel. Decide what would make it worth continuing: relevant conversations, successful trials or retained users. A quiet fortnight may be too little evidence, but indefinite effort without learning is not a plan either.
A realistic cadence for one person
You cannot be everywhere. You can be somewhere, reliably. A workable weekly rhythm for a solo founder looks roughly like this: publish one honest, specific piece of writing that answers a real question in your category. Spend genuine time being useful in one or two communities where your ICP already gathers, with no pitch attached. Make sure your product is listed and current on the two or three directories that matter for your niche. Check, every so often, whether AI assistants name you when asked what to use for your problem, and whether they describe you correctly.
Keep the routine small enough to review properly. You can expand it once you know which activity brings useful conversations or customers.
Measure the right thing
Early numbers can be small and noisy. Pair counts with what individual users did: a useful conversation and a completed task can explain more than a week-to-week percentage change.
Watch whether the surfaces themselves are filling in. Are AI assistants starting to name you when asked about your category, and getting your description right. Is a community thread you contributed to now ranking and sending the occasional visitor. Are your published pages accumulating impressions in Search Console even before the clicks arrive, which is the unmistakable signal that you are being seen upstream of the click. Are you appearing on the directories and roundups your customers check.
Impressions, replies and mentions can help you investigate whether a channel reaches the right people. They do not guarantee later signups. Use them with activation and retention evidence when deciding whether to continue.
If you want to know specifically why a competitor keeps getting named in AI answers and you do not, this breaks down the mechanism. →The honest version of the first 100 users playbook
There is no single route to a hundred users. A launch, a partner, a community or direct customer conversations may contribute very different shares depending on the product. Keep enough context to understand which route brought people who stayed.
Choose one reachable audience and one useful next step. For an import tool, that might be trying a sample dataset; for a team product, it may be inviting a colleague. Make that step clear in the resource or conversation that introduces the product.
AfterLaunch monitors discoverability and prepares growth work with supporting evidence and a draft. The free scan can help establish where to investigate. Keep the product’s own activation and retention data alongside that view.
At the next review, be able to explain where the recent users came from, what they completed and what you learned. That is a more useful basis for the next week’s work than a larger publishing target.
My launch traffic disappeared. What should I check?
Look at what the people who arrived actually did. Check signup, first-task completion and return use before deciding that another launch is the next priority.
Which channel should I try first?
Start where you can reach people with the relevant problem and learn from their response. Customer conversations and existing referral patterns are more useful than a universal channel ranking.
How long should I give it?
Set a review point and a meaningful observation before starting. The time needed depends on the activity; a conversation and an indexed resource provide feedback on different schedules.
Are repeated launches useful?
They can introduce the product to a different audience or support a significant release. Give each a clear purpose and a working path for interested people to try the product.
What should I measure?
Track relevant arrivals, successful first use and whether people return. Record the questions and obstacles behind those counts so you can improve the product and its introduction.
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