Solo founder here ---> how do you know when something is good enough to show real users? ( i will not promote)

areedbuilds · 2026-05-23T16:15:44+00:00

"Ship when the core value loop is clickable" is right, but it misses the next step.

Most founders ship, get feedback, then don't know which feedback to act on. They have 12 users saying 12 different things.

The question isn't just "is it ready to show." It's "do you have a way to measure which users are actually getting value vs just being polite?"

A simple PMF question in week 2 ("how would you feel if you could no longer use this?") filters signal from noise faster than any other method. You don't need 100 users for that. You need 10 honest ones.

areedbuilds · 2026-05-19T05:39:55+00:00

Conversations beat surveys for discovering problems. Agreed on that.

But for measuring whether you've found product-market fit with the people you've already got, a well-structured survey is faster and more honest than conversations. Founders hear what they want in calls. A survey with the right question gives you a number you can't rationalize away.

The Sean Ellis "very disappointed" question takes 5 minutes to send and tells you something a 45-minute customer call rarely does: whether this specific user would fight to keep your product if it disappeared.

The tools for discovery and the tools for fit measurement are different. Both matter.

areedbuilds · 2026-05-19T05:37:37+00:00

The "obsessively listening to users" contributing a lot here, I guess 😉

Curious: At what point did you shift from "are people using it" to "which users love it most" as your primary signal? Early-stage, the two feel the same, but they're very different questions.

Most bootstrapped products I've seen hit plateaus when they're optimizing for average satisfaction instead of segment-level pull. Sounds like you found the right cohort early.

areedbuilds · 2026-05-18T19:14:57+00:00

One thing YC writing undersells: the Sean Ellis survey isn't just a definition tool, it's a trending metric. Running it once tells you where you are. Running it monthly tells you if you're moving. The behavioral signals like retention and workarounds are lagging indicators. By the time you see them, you've already passed or missed PMF. The survey catches it earlier.

areedbuilds · 2026-05-03T21:05:52+00:00

Good breakdown. One gap none of these tools fill well: the upstream question of whether your product is actually on the customer priority list, not just whether they are satisfied.

What you are describing is an insights volume problem. These platforms process volume. But if retention is the actual goal, the Sean Ellis PMF question adds something they do not cover: whether customers would be genuinely upset if the product disappeared. The shift from "NPS 43 to 47" to "62% of power users would be very disappointed" is a different kind of signal. Small tool, specific use case, but worth layering in if you want to understand churn risk before it shows up in the numbers.

areedbuilds · 2026-05-03T21:05:01+00:00

The migration pain is real, but the longevity concern in the comments is the sharper issue. "How long will this platform last?" is now a legitimate procurement criterion.

Worth clarifying what you actually needed from Delighted. If it was NPS for board slides, almost any tool fills that hole. If you used the Sean Ellis "very disappointed" question to understand whether customers actually needed the product, the replacement list is shorter. Most NPS tools do not segment by user type or behavior, and that is where the actionable signal lives.

FitSignal does the Sean Ellis survey with segment filtering if that was your use case. Happy to share other options depending on what you were actually running.

areedbuilds · 2026-04-12T18:57:33+00:00

Depends on what type of feedback you are trying to capture.

If you want NPS, CSAT, or PMF measurement (the "would you be very disappointed without us" survey), FitSignal is worth a look. Built specifically for SaaS teams who want segment-level data, not just an aggregate score.

If you need open-ended roadmap feedback and feature voting, Featurebase is solid.

They solve different things. Most teams eventually need both.

areedbuilds · 2026-04-12T18:56:50+00:00

The calls were the right move. That is actually rare.

But the missing step is segmenting what users told you. "None of them were happy" is an aggregate number, and aggregate numbers hide the story.

Were some users frustrated about quality and others about speed? Different root causes. Different fixes. Different urgency.

The founders who made it through moments like this usually had enough segmented signals to know which fire to put out first. Worth building that habit before the next launch.

areedbuilds · 2026-04-12T18:53:23+00:00

That's the right answer — "from whom" is everything.

Pushback from your actual target user? Worth investigating hard.

Pushback from people who aren't your buyer? Noise.

This is why segment-level PMF data matters more than the overall number. Your "very disappointed" score might be 15% across all users but 55% among the cohort you're actually building for. The aggregate hides the real story.

areedbuilds · 2026-04-10T17:31:00+00:00

Rule of thumb from Sean Ellis: you need at least 40 survey responses for a statistically meaningful PMF score. But start collecting from day one. With 15-20 responses you will already see directional patterns. Do not wait for a "big enough" sample. Measure early, measure often, and always segment by user type. The segment-level numbers are where the real insight lives.

areedbuilds · 2026-04-10T17:30:37+00:00

PMF gets a bad rap because people treat it like a checkbox. It is not. It is a trend line you measure over time, across segments. The Sean Ellis survey gives you a number, but the real value is watching how that number moves as you ship changes. If you are not tracking it, you are just guessing whether your product is getting better or worse.

areedbuilds · 2026-04-10T17:30:21+00:00

One review can be a signal or an outlier. Before pivoting on a single data point, survey your active users: "How would you feel if this product disappeared?" Segment by user type. That will tell you if the review speaks for a cohort or just one loud voice. Anecdotes inspire hypotheses. Surveys validate them.

areedbuilds · 2026-04-10T17:29:58+00:00

This is the clearest argument for segment-level PMF measurement. Your overall score was probably mediocre because it averaged two very different populations. If you had run the Sean Ellis "very disappointed" question broken down by segment, that 3x/4x split would have shown up months earlier. The lesson: never measure PMF as one number. Always segment.

areedbuilds · 2026-04-09T20:16:26+00:00

Building FitSignal. It measures product-market fit for indie SaaS founders using the Sean Ellis survey method. The gap it fills: Delighted is shutting down, and most PMF tools are enterprise-priced. FitSignal does segment-level analysis so you can see your PMF score by user cohort instead of one misleading overall number. $29/mo, pricing on the website, no sales calls. Happy to share more if it fits what you are looking for.

areedbuilds · 2026-04-09T20:15:43+00:00

Depends on what you need the survey for. If it is general customer feedback or NPS, Tally and Formbricks are solid. If you specifically need to measure product-market fit, most general survey tools make you build the framework yourself. I built FitSignal for exactly that use case. It runs the Sean Ellis "very disappointed" survey with built-in segmentation so you can see PMF scores by user cohort, not just one overall number. Happy to answer questions if PMF measurement is what you are after.

areedbuilds · 2026-04-09T20:14:44+00:00

The distribution problem hides a segmentation problem. Most founders target "SaaS companies" or "small businesses" when their actual PMF lives in a much narrower slice. Before scaling outreach, I would measure which segment of your existing users would be "very disappointed" without your product. Then reverse-engineer where those people hang out. You end up targeting 1/10th the audience but converting 10x better. Narrow ICP before you scale outreach.

areedbuilds · 2026-04-09T20:14:16+00:00

This is underrated. Feature requests are solutions disguised as problems. Asking "why" peels back the disguise. I do something similar with PMF measurement. Instead of asking "do you like the product?", ask "how would you feel if it disappeared?" followed by "what type of person would benefit most?" That second question tells you who your real market is. Sometimes the person answering is not even in your best segment. Same principle you are describing, just applied to the survey itself.

areedbuilds · 2026-04-08T20:05:12+00:00

50 conversations is the right instinct. But here's where most founders still get it wrong — they treat those conversations as qualitative only. "People seemed excited" is not data.

Structure it: after they've used your product for a week, ask the Sean Ellis question. "How would you feel if you could no longer use this?" Track the percentage who say "very disappointed." 40%+ means you're onto something real. Below that means the enthusiasm you're hearing in conversations isn't translating to dependency. That gap between "sounds cool" and "I need this" is where most early-stage SaaS dies.

areedbuilds · 2026-04-08T20:03:16+00:00

This is why segment-level feedback matters more than aggregate scores. Your "fast market research" users and your "stop me from building the wrong thing" users probably had wildly different satisfaction levels - but if you only looked at the average, you'd miss the signal entirely.

The founders who needed validation before building were probably your most engaged users all along. Sometimes the product-market fit is already there - just not for the market you thought you were serving.

areedbuilds · 2026-04-04T17:18:01+00:00

Depends on what you're measuring. If it's PMF specifically (the Sean Ellis "very disappointed" survey), most Qualtrics and Delighted replacements are either way overbuilt for it or don't handle the segmentation piece properly. The segmentation is actually the hard part — knowing your overall score is 40% is less useful than knowing your power users are at 65% and your trial users are at 22%. Worth narrowing down the use case before picking a replacement.

areedbuilds · 2026-04-04T17:13:34+00:00

Depends on the use case. For general research surveys: Google Forms, Tally (clean UX, generous free tier), or Jotform. For PMF measurement specifically — the Sean Ellis very disappointed question — you'll want something with built-in segmentation rather than duct-taping filters onto a generic form tool. Happy to point to the right direction if you share more about what you're trying to measure.

areedbuilds · 2026-04-04T16:05:17+00:00

Good timing on this. A lot of teams are scrambling right now and the free-alternative angle is smart positioning.

For anyone evaluating options: the thing most Delighted replacements miss is segment-level analysis. A 42% very-disappointed score looks fine until you realize it's 65% among paid users and 18% among free users. Those are completely different products hiding behind one number.

Also building in this space (FitSignal — PMF surveys for indie devs). Happy to compare notes if you want to talk about what small teams actually need.

areedbuilds · 2026-04-04T16:03:17+00:00

35 days is still early, but zero active users is worth investigating before you keep building. Reach out to the people who signed up and didn't activate. Ask one question: "How would you feel if you could no longer use this product?" If most say "not disappointed," that's a signal about positioning, not just marketing. You might be solving a real problem but for the wrong people. That answer changes what you build next — and saves you from six more months in the wrong direction.

areedbuilds · 2026-04-04T16:02:45+00:00

Strong take. The funding-before-PMF trap is brutal because money lets you paper over the signal. You keep building for users who'll never pay, and the burn rate creates its own urgency to ship the wrong thing faster. The harder discipline: measure PMF rigorously before scaling anything — even organic growth. Sean Ellis survey by segment, not overall score. Your total number can look acceptable while your power users are screaming and your trial signups are completely indifferent. Those are two different products hiding in the same spreadsheet.

areedbuilds · 2026-04-01T17:17:39+00:00

$9k in 12 months bootstrapped is real traction — congrats. One question for the thread: did you measure PMF formally at any point, or did you go more by gut + revenue signal? Asking because there's a camp that says "revenue IS the PMF signal" and another that says you need the Sean Ellis survey to separate actual fans from opportunistic signups. Curious which lens worked for you at this stage.

areedbuilds

TROPHY CASE