Questions founders ask, answered.

A waitlist helps when you're weeks from something usable and can reach people. When it's worth setting up, when to skip it and launch, and what to do either way.

"Everyone who needs X" isn't a customer. How to find the specific group that uses and pays, from your own signups, users and payments, and write it down in one sentence.

Signups and likes don't prove anyone will pay. Ask for money or a commitment before you build, and learn which people and channels are behind the yes.

Daily checks make noise look like news; never checking is flying blind. A weekly half-hour routine: which numbers, in what order, and one decision each time.

150 signups and no payments doesn't answer the question by itself. Three checks that tell you whether to keep going, change the offer, or move on.

Launch day is over and the visits dropped back to zero. What to do in the first month after a launch, in order, so the next post is better than the first.

Earlier than feels comfortable. Why charging from the start tells you more than free users do, how to price the first version, and what to watch after.

Some browsers delete everything when they close, so each visit looks like a new person. What you can still learn about them, and what you shouldn't try.

Every user asks for something different. How to choose the next feature by who is asking, what they're trying to do, and whether they pay, not by how loud they are.

Compare what paying customers did before they paid with what everyone else did. How to set it up with a few named events, and how to read it with small numbers.

The first ten customers come from people you reach one by one, not from ads. Where to find them, how to ask, and what to record so customer eleven is easier.

A sponsorship is one payment for one send, and most of its effect arrives later. How to tag it, what to count, and how long to wait before judging it.

Upvotes and traffic spikes feel like success. Whether a launch worked shows in who signed up, from where, and who paid in the weeks after. What to measure and when.

Knowing the path to a signup tells you which pages do the convincing. Three ways to see it: a funnel, goals by page, and one person's visit history.

Reddit often sends visits with no clear referrer, and two posts look the same. Tag each link, record the tag on the signup, and match signups to payments.

Visitors decide in a few seconds whether a page is for them. How to write a headline that names their problem or the result they want, and test it with real traffic.

A small ad test only answers a question if you decide the budget, the time and the number that counts as success before you start. How to size it and read it.

There is no single figure: it depends on your audience and your tool. Which blockers stop which scripts, what one measurement found, and how to check your own site.

Signups who never come back didn't reach the moment the product is for. How to find where they stop, fix that step, and reach out to the ones who left.

A launch site brings a day of visitors. Whether it's worth it depends on who reads it and whether you can tell its signups from the rest. How to decide.

A lifetime deal brings cash now and customers who never pay again. When it makes sense for a first product, what it costs you later, and how to limit the damage.

Cloudflare counts requests at its edge or through a small beacon; Google Analytics counts sessions and users from a script. Why they differ, and how to compare.

People who log in with Google or Discord, or pay on Stripe Checkout, come back from that site, and many analytics tools count it as a new visit from there.

Customers who cancel in the first month or two usually share a reason. How to find yours: when they leave, where they came from, and what they said before.

A redirect that rebuilds the address without the query string throws your UTM tags away before analytics sees them. Where it happens, and how to test for it.

Direct usually means the browser didn't say where the visitor came from, not that they typed your address. The common causes, and how to get the source back.

Safari caps cookies set by scripts at seven days, so most analytics tools forget a Safari visitor a week after their first visit. What that does to your numbers.

Stripe's MRR counts only active and past-due subscriptions. Trials, one-off payments, metered prices and taxes stay out. A checklist to find the gap.

Payment Links accept utm_ tags and pass them to your redirect URL. They don't tie a payment to the visit that brought the buyer unless you store them.

Netlify Analytics is built from server logs: page views, visitors by IP, pages and sources. It has no custom events or campaign report. What to add, and how.

It depends on where your visitors are and what your analytics does. What the EU, UK and French regulators say about analytics cookies, and the choices that follow.

Cloudflare Web Analytics logs no query strings and has no custom events, so campaigns and signups stay invisible. What it does count, and the workarounds.

First touch credits the channel that found the customer, last touch the one they clicked before paying. What each gets wrong, and why small products start with first.

A feedback button in the app beats a survey link in an email. Where to put it, what to ask, how to tie each message to the person, and what to do with it.

AI assistants now link to sites in their answers. How to spot those visits in your analytics, why some look direct, and how to tell whether they sign up and pay.

Recommendations happen in chats and conversations no tool can see. The signals that show word of mouth anyway, and how to give it a trackable path.

Price from the value to the customer, not from your costs or the cheapest competitor. A simple way to set a first price, how many plans to offer, and how to test it.

Letting your whole waitlist in on day one wastes it. How to invite a beta in small batches, what to watch in each one, and when to let the next group in.

Export Stripe's itemized balance report with the card and customer country columns, then group it. Why card country and billing country disagree.

Where your visitors are and where your paying customers are often differ. How to see both, and what the difference tells you about pricing, ads and timing.

A tweet reaches followers, not users. How to tell the people who use your app about a new feature: where they'll see it, what to write, and who to tell first.

Visit analytics stops at the signup. How to follow a user after it: name the few actions that matter, tie them to the person, and see who reached each one.

There's no magic number. What matters is who signed up, where they came from, and whether a few will tell you why. How to judge your waitlist before launch day.

Too often and people unsubscribe; too rarely and they forget why they joined. A simple rhythm for waitlist emails, what to say, and the one email that matters most.

BetaList features new tech startups for early adopters, and every submission is now paid. Who it suits, what its own pages say, and how to tell what it sent you.

MRR is recurring revenue per month, ARR the same per year (MRR × 12). What belongs in each, a worked example, and which a small product should watch.

Credit the first payment, or every payment for as long as they stay? How to choose an attribution window and what to count, for a small subscription product.

A free plan lets people stay; a trial asks them to decide. How to choose between them for an early product, and what to measure either way.

A soft launch finds what breaks; a hard launch finds who wants it. Why a small SaaS usually needs both, in that order, and what to measure in each one.

"Any feedback?" gets silence or politeness. The questions that get useful answers from early users, when to ask them, and what to do with what you hear.

Your app knows who signed up; your analytics knows where visitors came from. How to join them with one call after signup, and what to store so a payment finds it.

Show HN is for things people can try, not for landing pages. What the rules say, how to write the title and first comment, and how to tell what the post brought you.

Building took a weekend; finding users takes longer. Where to post a vibe-coded app, how to tell its story, and how to know which post worked.

Three numbers every analytics tool shows and few explain. What each one counts, why they differ, and which to use for which question.

Three analyses of Hacker News data disagree on the best hour, but agree that quieter times help a little and the post itself matters more. What each one measured.

Payments worked in the sandbox and fail on the real site. The usual causes, in the order to check them: keys, prices, webhooks and environment variables.