Discoverability
Get found where your users decide
How to get found where SaaS users actually vet software: Reddit, Hacker News, G2 and Product Hunt. What compounds, and what gets you ignored.
Follow the places people make a decision.
What should I use?
In this article
A prospective customer may consult a discussion, a review or a comparison before visiting your site. Those pages can answer questions your own marketing leaves open: what setup involved, where a product fell short and why someone kept using it.
Your website still needs to explain the product well. Alongside it, inspect the places customers use to compare options and consider where you can contribute accurate information.
- Inspect the discussions, reviews and comparisons your customers use before choosing a product.
- Disclose your affiliation, follow the destination’s rules and contribute information that answers the question.
- Keep a small number of relevant profiles and resources accurate before expanding to more channels.
An answer can draw on more than your website.
Which product should I use?
How people actually vet software
Watch how a careful person chooses a tool and you see a pattern. They do not start at your site. They start with a question, usually phrased as a problem rather than a product. What are people using for X now. Is Y worth it or is there something lighter. How do small teams handle Z without paying for the enterprise thing.
They take that question to a place with other practitioners in it. For developers and technical founders, that is often Hacker News, a relevant subreddit, or a Slack or Discord they already trust. For a less technical operator, it might be a review site, a roundup post, or a recommendation from someone in their network. They are not looking for marketing. They are looking for someone like them who has already done the evaluation and will tell them the truth, including the parts you would not put on your pricing page.
The decision is comparative, not absolute
Almost nobody evaluates your product in isolation. They evaluate it against two or three alternatives and the option of doing nothing. This is why the most valuable place to appear is not a page about you. It is a thread comparing you to the thing they are currently using, or a list where you sit next to your closest competitors and the differences are laid out plainly. If you are absent from those comparisons, you are not in the consideration set, regardless of how good the product is.
Explain the trade-off, including when the product is unsuitable. A reader comparing tools needs that information to assess the recommendation.
Reddit and Hacker News: earn the room first
Check whether the specific discussion is relevant to the product and whether you have useful experience to contribute. Reddit communities and Hacker News have different rules and audiences; broad assumptions about either are a poor basis for a post.
The pattern they punish
Read each community’s current rules. Hacker News asks members not to use it primarily for promotion and prohibits generated or AI-edited text. Subreddit rules differ, so do not assume a universal acceptable ratio of promotional posts.
People need enough context to judge a recommendation. Disclose your connection to a product and explain why it fits the question, including relevant limitations.
What actually works
Be a participant before you are a vendor. Answer questions in your area of expertise where your product is not the answer. Write the comment that genuinely helps the person asking, even when the help is how to do this without any tool at all. When your product is honestly the best fit for a specific question someone has asked, mention it plainly, disclose that it is yours, and explain the reasoning. Disclosure is not a weakness here. It is the thing that makes the recommendation usable.
On Hacker News specifically, the Show HN format exists for exactly this. It is a sanctioned place to put your work in front of the community and ask for reactions. It works when you treat it as a conversation: post the thing, explain what it does and what it does not, and then stay in the thread and answer every hard question without getting defensive. The people who do this well treat the critical comments as the point, not the threat.
A useful public reply may continue to help people who find it through search. Keep it specific to the question and correct it if the facts change. Do not assume that publishing it will produce a particular search rank or AI citation.
Related: why competitors win the AI answer when you do not →Review sites: G2, Capterra and the directories
Review sites help people compare options using product information and customer accounts. Read the relevant category pages before investing in a listing, and check whether their audience overlaps with yours.
Correct incomplete product profiles
Inspect any existing profile for missing or outdated facts. A description that omits a supported integration or shows an old price can make a comparison less useful to a prospective customer.
Claim a profile where appropriate, correct its factual information and keep screenshots current. Invite customers to describe their actual experience, rather than selecting only the happiest users or asking for a particular rating. Follow the site’s rules on review requests and incentives.
Comparison and alternative pages
Review sites generate pages like X versus Y and alternatives to Z automatically, and those pages capture people at the exact moment they are switching. You cannot fully control them, but you can make sure the underlying data is accurate, that your profile is complete enough to render well in the comparison, and that the reviews present give a fair picture. When a person is reading alternatives to the tool they are frustrated with, you want to be a complete, credible entry on that list rather than a blank one.
Work through it: the SaaS directory checklist →Product Hunt: the launch is the smaller half
A Product Hunt listing remains available after launch day. Make the description and replies useful to someone who finds it later, and check whether the listing produces relevant visits before deciding how much ongoing attention it needs.
Treat it as a permanent page, not a one-day event
Because the page persists, the things that age well are worth more than the things that spike. A clear, honest first comment from the founder explaining what the product is and who it is for. A tagline that describes the product rather than reaching for cleverness. Replies to the questions people asked, left intact for the next reader. Someone who finds your page in eight months will not see your upvote count climbing in real time. They will see whether you showed up as a real person and explained your work.
Plan a clear demonstration and be available to answer product questions. The discussion can reveal unclear positioning or onboarding problems even when the traffic volume is modest.
What that upkeep looks like in practice: your Product Hunt page after launch day →A mention and a citation tell you different things.
Which product fits my team?
A recommendation names a product and may point to a source page ↗.
- Mention
- Who was named?
- Citation
- What page was linked?
What compounds and what evaporates
Look for contributions that remain useful after publication: a specific answer, an accurate comparison or a maintained profile. Their continued value needs checking, especially when the product changes.
A good answer can be found again, and a maintained review profile can help the next person comparing options. Neither outcome is automatic. Revisit important material and use referral data or customer feedback to judge whether it is helping.
Help a reader judge the fit
A useful contribution explains the fit and the limits of a product. Write it so that someone can make a different choice without needing to discover an omitted constraint later.
Making it manageable as a team of one
A solo founder cannot follow every discussion. Choose a small set of relevant places, keep a record of the questions that recur and set aside time to review them.
AfterLaunch monitors public signals and prepares growth work with evidence and a draft. You remain responsible for deciding whether a contribution is appropriate and whether the destination permits that kind of assistance.
The free scan offers an initial view of discoverability. Use it alongside conversations with customers about where they looked for advice and what information they found missing.
Related: the new playbook for getting found in the AI search era →Should I post about my own product on Reddit or Hacker News?
You can, but only after you have a track record of contributing usefully without selling. Both communities are quick to flag accounts that only ever surface to promote, and a poorly judged post can do more reputational damage than the visibility is worth. The safer path is to be genuinely helpful in the relevant subreddits or threads, answer questions in your area, and mention your product only when it directly answers what someone asked.
Are review sites like G2 and Capterra worth it for an early-stage product?
They are worth seeding early, because the listings compound. A handful of honest reviews from real users gives you a presence that keeps surfacing in comparison searches and increasingly in AI answers long after you stop actively working on it. The slow part is gathering reviews without incentivising them in ways the platforms prohibit, so build a simple, repeatable ask into your onboarding or post-support touchpoints rather than chasing reviews in bursts.
Is a Product Hunt launch still worth doing?
It can be, but treat the launch day as the smaller half of the work. The lasting value tends to come from the listing itself, the reviews and comments it gathers, and the relationships you build around it, not the spike of traffic on the day. Plan for what happens the day after: where the interested people go, what they read next, and how you stay in the rooms they came from.
How do I keep up with all these communities as a solo founder?
You do not try to be everywhere. Pick the two or three rooms where your specific users actually make decisions, and ignore the rest until you have evidence they matter. Consistency in a few places beats a thin presence across many, and it is far more sustainable when you are the only person doing it.
What is the difference between visibility that compounds and visibility that evaporates?
Compounding visibility is something that keeps working after you stop: an indexed review listing, an answer in a thread that ranks, a directory entry that gets cited. Evaporating visibility is a one-day spike that leaves nothing behind once the attention passes. The practical test is whether a piece of work is still findable and useful six months later.
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