We're growing a mobile app with free web tools instead of ads. Here's the playbook so far.
We're two friends building Poker Reflex, a mobile app that trains your preflop
poker decisions. Classic problem: a paid app, no ad budget, and a niche audience.
So instead of running ads, we build free web tools around the same niche and use them as the top of the funnel. The counterintuitive part: a small free tool that solves one specific problem ranks and gets shared far better than the app itself, because people share useful tools, not ads. The tool pulls in search traffic and community shares, and the site converts a slice of that into app installs.
We've shipped three so far:
- A pot odds calculator
- A range visualizer (build and save your own preflop ranges)
- An equity calculator we just launched (hand vs hand win %), which I'm oddly
proud of: the engine is validated against exact enumeration of every possible
board, so the numbers are provably correct.
All free, no signup: https://poker-reflex.com/tools
The app: https://poker-reflex.com/get?src=indiehackers
Where we're at: early but real. The tools are starting to pull organic traffic,
we get a steady trickle of installs, and a premium subscription launches in a few
weeks. Instagram converts, Reddit is hit or miss, and YouTube age-restricts every poker video (fun).
The question I keep chewing on: how do you cleanly measure tool-to-app conversion,
and is a free-tool funnel a real long-term channel or just a slow trickle? Has
anyone grown an app this way? Would love to hear what worked.
This is a good fit for mobile because the free tool can answer the pre-download trust question, not just drive traffic.
For a food logging app I would not start with a generic calorie calculator, because that attracts people who want a number and then leave. I would test tools that map to the exact moment before app usage: barcode nutrition lookup, photo-to-meal estimate examples, or “what should I log when I ate X restaurant meal?” The tool should make the user think “I need this workflow again tomorrow,” not just “nice calculator.”
For measurement, I’d separate three numbers: tool completion rate, install CTA click after completion, and day-2 app open by campaign. If tool A has lower traffic but higher day-2 opens, that is probably the one teaching the right habit.
This is the sharpest take in the thread, and it reframes my own lineup. The "want a
number and then leave" trap is real: my pot odds and equity calculators are exactly
that, you grab the number and you're gone. The one that maps to your "I need this again
tomorrow" is the range visualizer, because it lets you save and edit your own ranges, so
it's a workflow you come back to, not a lookup. I hadn't drawn that line between my own
three tools until you said it.
And it lines up with the app itself: it's a daily trainer with streaks and an ELO, so the
tool that teaches "come back tomorrow" is the closest cousin to the actual product. The
number-grab tools pull traffic, the habit tool probably pulls the right people.
Your three-number split is also better than what I had planned. Completion rate and
install-CTA-click I had, but "day-2 app open by campaign" is the one that actually answers
it, because for a trainer the win isn't the install, it's whether they came back. Lower
traffic but higher day-2 opens equals the tool teaching the right habit. That's now the
metric I'll use to decide which tool to build next. Genuinely useful, thank you.
Love this. I'm doing a version of it for HealthOS — instead of ads, I wrote up the whole Toyota on-device AI story and put it on my product page. The bet is that content teaching something actually interesting pulls in the people who care about the problem, not just clickers.
The free-tool idea is smart for your niche. I've been toying with a free "voice stress test" web demo for the same reason — let people feel it before they commit to a download.
On attribution: have you tried a separate landing page per tool with App Store campaign tracking? That's my plan, so I can see exactly which channel actually drives installs.
"Content that teaches pulls the people who care, not just clickers" is exactly it. An
ad makes a claim, a tool or a real story lets someone feel the thing before they decide.
Same bet, different shape. The Toyota on-device story on your product page is a great
version of that.
And "let people feel it before they commit to a download" is the cleanest way I've heard
the free-tool logic put. A voice stress test demo is perfect for it, because the demo IS
the pitch. If it works on them, the download mostly sells itself.
On your attribution question: yes, and it's basically our setup already. Each tool is its
own page, and the download links route through a single redirect that stamps a campaign
token, so Apple's App Analytics shows installs per campaign and Play Console shows them
per install referrer. Honest caveat though: it's campaign-LEVEL counts, not per-user
paths. iOS will tell you "this campaign drove N installs" but not what that person did
before the tap. For deciding which channel actually drives installs, that's plenty. For
stitching one user's full journey, it isn't, and that's where you'd need deferred deep
links or an SDK, which I've parked until it's clearly worth the work. For your stage, the
per-tool page plus campaign tokens will already answer your real question.
This "useful tool > useful app" framing is really clicking for me — solo dev here, also paid app + zero ad budget + niche audience, so I've been thinking about the exact same funnel.
Curious about the tool selection process: did you pick "pot odds calculator" etc. based on search volume/keyword research, or just "what would our target user google when they're stuck"? And roughly how long after publishing a tool did you start seeing meaningful organic traffic — weeks or months?
Following this for sure, would love to see the conversion numbers from tool → install once you have more data.
Same boat, with one correction: ours is actually free, not paid (premium is planned,
not live yet), but the zero-budget niche-audience funnel is identical, so all of this
applies to you.
On tool selection: it started as "what does a poker player google the second they're
stuck" way more than a spreadsheet. Pot odds, ranges, and hand equity are the three
things players literally look up mid-hand or right after, so the intent was obvious
before I checked a single volume number. I did sanity-check search volume after,
mostly to decide which to build first and how to name the page. But if I'd led with
volume I'd have risked building something technically searched and useless to solve,
which is the trap. Intent first, volume to prioritize.
On timing, honest answer: too early to give you a clean number from the tools. The pot
odds calc is about two weeks old and the equity calc is days old, so they haven't had
time to rank yet. What I can tell you from the blog side is that meaningful organic was
months, not weeks. A small trickle showed up in a few weeks, but the real compounding,
pages ranking and pulling steady traffic, is a 3 to 6 month game. Anyone promising
faster without budget is selling something.
And yes, I'll post the tool to install conversion numbers once I've actually
instrumented it. A few people in this thread have convinced me that's the next job.
Good luck with yours, happy to compare notes as we both figure this out.
"Intent first, volume to prioritize" — that's a clean framework,
stealing it.
My situation is a bit different: snoring is something people google
when they're frustrated at 2am, not when they're calm. So the intent
is obvious, but the window is short and emotional. Makes me think the
tool angle for me is more about "here's what's actually happening while
you sleep" rather than a calculator.
Months for organic makes sense. Appreciate the honest answer
I think the bigger opportunity here might not be the app-to-user funnel, but the tool-to-tool flywheel.
Most founders build one free tool and hope it converts. What you have done is more interesting: each new tool increases the discoverability of the others, which compounds search traffic over time. If the equity calculator, range visualizer, and pot odds calculator all rank for different intents, you're effectively building a mini search ecosystem around poker training.
For attribution, I'd be less worried about perfect tracking and more focused on whether the tools are acquiring users cheaper than any paid channel could. If organic traffic keeps growing while install costs stay near zero, that's a pretty strong signal.
Curious: have you seen users coming back to multiple tools, or is most traffic one and done?
The tool-to-tool flywheel framing is sharper than how I'd been thinking about it,
thank you. That's basically the bet without me having named it: the tools and the
blog articles all cross-link, so every new page is another entry point that also
feeds the others. The equity calc isn't just a third tool, it's a third front door.
On attribution, you and a couple of others in this thread have pushed me the same
way: stop chasing perfect tracking, ask whether CAC beats any paid channel. With
install cost near zero and organic still climbing, the honest answer is yes, and
that's the signal that actually matters.
To your question, and it bugs me that I can't answer it cleanly yet: the tools do
link to each other so the path exists, and anecdotally blog readers do land on a
tool. But the equity calc is only two days old, so the sample for real multi-tool
sessions is too thin to call one-and-done vs sticky. Instrumenting that, tool-to-tool
movement and repeat visits, is now top of my list, because if people hop between
tools it changes how I treat the whole thing. I'll report back once I have it.
At this point it feels less like a funnel problem and more like you’re building a network of entry points where discovery is the product.
Once that clicks, conversion stops being something you chase and starts happening as a side effect of reach.
Yeah, that reframe sticks. If discovery is the product, my job stops being "optimize a
funnel" and becomes "build more things genuinely worth finding," which is a much
healthier thing to wake up to.
One discipline it forces, and I want to stay honest here: reach only becomes installs if
the bridge from each tool to the app stays honest and frictionless. Discovery as the
product, sure, but the product still has to earn the tap. That's the part I won't let
myself hand-wave. Appreciate you sharpening this, genuinely.
That feels like the right constraint.
Discovery can be the engine, but the trust in that bridge is what keeps it from turning into traffic noise. If that stays clean, the compounding effect actually becomes durable instead of just spiky growth.
Appreciate the thoughtful pushback that’s the part that usually decides whether this kind of system actually holds up in practice.
Durable over spiky, that's the whole game. This was genuinely one of the sharper
threads I've had on here, so thank you for pushing on it. I'll circle back with real
numbers once the system has had time to prove whether it holds. Until then, back to
building front doors.
That’s a solid way to frame it.
Looking forward to seeing what the numbers say once it’s had time to settle. this is one of those cases where the system will probably teach more than the discussion ever could. Good luck with it.
Appreciate it, will do. And you're right, the system will teach me more than I could
guess at right now. Good luck with yours too.
Grown a product almost entirely on free tools, so a couple concrete bits on your questions.
Measuring tool→app: the web→mobile jump is where attribution dies. A ?src= param gets you to the store and then you lose the thread. What worked for me: fire an event at the tool's "aha" moment (the calc spitting out the answer), one on the install CTA click, then a deferred deep link / attribution SDK (Branch etc) so the install actually ties back to the tool that drove it. Without that last bit you're guessing.
Slow trickle vs real channel: it's a trickle that compounds, which isn't the same as slow. The tools keep ranking and pulling traffic months later for zero extra spend, so it stacks. The thing that decided whether a tool actually fed the product for me: it had to fully solve the thing someone googled. My "lite version of the paid app" tools flopped, the ones that stood on their own converted. Your equity calc being provably correct is exactly the kind that earns links and trust, btw.
Which of the three pulls the most install-intent traffic? Usually one ends up carrying it.
This is gold, thank you. You nailed exactly where we're weak: we're on ?src=
right now, so we literally lose the thread at the store like you said. The
deferred deep link / Branch layer is the obvious missing piece, firing an event
at the "aha" moment plus the install CTA click and tying it through an
attribution SDK is going on the list this week. Without it we're guessing, agreed.
The "fully solve the googled thing vs lite version of the app" point really lands.
Our weakest tool is the one that feels closest to a teaser; the standalone
calculators pull better. Good to hear that pattern held for you too.
On which of the three carries it: honestly too early and too blind (that exact
attribution gap) to say with confidence. Early read is the pot odds calc has the
most search volume, but the equity calc is two days old. Once Branch is in I'll
actually know. Really appreciate you taking the time.
Hey everyone, I’m the other friend building Poker Reflex.
We’d honestly love to get your feedback on this. We’re putting a lot of energy into the app and these free tools, and we’re trying to figure out if this “useful tools first, app second” approach can become a real growth channel.
If you have thoughts, experience with this kind of funnel, or even brutal feedback on the tools/app, we’d be really grateful.
Thanks, and have a great day.
Love this approach. Doing something similar here, but on a revenue operations' scope. Free tools as top of funnel makes a lot of sense for the unit economics.
One thing I've been curious about with this kind of model: the three tools probably look similar in GA but might convert to installs at pretty different rates. Curious if you've started tracking at the per-tool level yet, because that data could really sharpen what you build next.
Not sure if its useful but I built something similar for measuring this kind of channel breakdown. https://pipelinegrader.com/calculator/lead-source
This is the right wedge for a niche app with no budget. The part most people get wrong is treating all three tools as equal. They are not. A pot odds calculator answers one question and the user leaves, zero switching cost. The range visualizer is different because saving a custom range makes the user invest effort and build a mental model, so the app becomes continue where I left off instead of try a new thing. I would pour everything into the tools that create saved, user-generated data and let the one-shot calculators just feed SEO. One question: are you tracking 7-day retention by which tool drove the install? A tool with half the traffic but double the retention is the one to double down on, and that number usually surprises people.
This is the sharpest version of a point a few people in this thread have circled, and it matches the conclusion I'd been reaching myself. The range visualizer lets you save and tweak your own ranges, so it's the one that makes you invest effort and come back, continue where I left off, while the pot odds and equity calculators are one-shot, grab the number and leave. So yeah, the saved-data tools are the ones to pour into, and the calculators mostly earn their keep as SEO front doors. On your question: I'm not tracking 7-day retention by which tool drove the install yet, the attribution isn't wired, but that's exactly the metric I want, because a tool with half the traffic and double the retention is the one to double down on. I'd bet it's the visualizer. I'll know once it's instrumented.
This is the sharpest version of a point a few people in this thread have circled, and it matches the conclusion I'd been reaching myself. The range visualizer lets you save and tweak your own ranges, so it's the one that makes you invest effort and come back, continue where I left off, while the pot odds and equity calculators are one-shot, grab the number and leave. So yeah, the saved-data tools are the ones to pour into, and the calculators mostly earn their keep as SEO front doors. On your question: I'm not tracking 7-day retention by which tool drove the install yet, the attribution isn't wired, but that's exactly the metric I want, because a tool with half the traffic and double the retention is the one to double down on. I'd bet it's the visualizer. I'll know once it's instrumented.
The free-tool funnel works especially well here because poker players are already used to paying for edge. The ICP for a serious poker training app has two clear segments: recreational players who want to improve socially, and grinders who are treating this as income. The latter group has a completely different relationship to tools — they'll pay for anything that demonstrably improves their EV, and they talk to each other in forums and Discord servers about what works.
That grinder segment is worth finding specifically. They're low volume but high lifetime value, and they're extremely influential in their communities. One grinder who uses your app consistently and mentions it in a strategy discussion is worth more than 50 casual installs.
The free web tools are doing good top-of-funnel work for general traffic. But if you want to find the grinders specifically, I'd look at where they already argue about ranges and equity — 2+2 forums, specific poker Discords, study groups. Those places have much lower traffic than Google but much higher intent from the exact user who pays and refers.
What does your current paid conversion rate look like between the two types of user?
The two-segment split is the most useful reframe I've gotten on who this is for. Recreational players who improve socially, and grinders who treat it as income with a totally different relationship to tools. And you're right that one grinder who uses the app and mentions it in a strategy thread is worth more than 50 casual installs, for revenue and for influence both. One honest correction on your question: I can't give you a paid conversion rate yet, because the app is 100% free right now. Premium is planned but not live. So today there's no paid number to compare between segments. But your point reshapes who I build premium for and where I hunt: the free web tools pull general, mostly recreational traffic, while finding grinders is a different motion, the 2+2 forums and poker Discords where they already argue about ranges and equity. Lower traffic, far higher intent. That's a separate playbook I need to run on purpose. Thanks for drawing the line so clearly.
Interesting distribution strategy — it feels like you’re building acquisition loops through utility rather than persuasion.
The real question is whether each tool strengthens a shared user journey or creates fragmented entry points that don’t compound.
"Acquisition loops through utility rather than persuasion" is a better description of it than I had. And you've put your finger on the exact thing I can't yet prove. By design it's a shared journey: the tools and the blog all cross-link, so each one is a door into the same house. But whether they actually compound or just fragment into separate one-and-done entries comes down to whether users move between them, and that's the one number I don't have yet. Instrumenting tool-to-tool movement and repeat visits is next. If people hop between tools, it compounds. If every visit dead-ends in one tool, you're right that it fragments. I'd rather measure it than assume it compounds.
I think the answer depends on whether the value compounds for the user.
If each tool solves a one-off problem, then it's fragmentation. If each interaction adds context that makes the next interaction more valuable, then it becomes a network of products rather than a collection of products.
That's the behavior I'm trying to validate now.
This makes a lot of sense. People are way more likely to share a useful tool than an app they're being asked to download.
I've seen this work in other niches too. Once a tool starts getting mentioned in forum discussions, Reddit threads, and search results, it keeps bringing in new people without you having to push it constantly. I'm curious to see how the equity calculator performs compared to the others.
Exactly, a useful tool is something people will share, an app download is something you have to ask for. That difference is the whole bet. On the equity calculator specifically: it's only days old, so it's too early to tell, and honestly I expect it to behave more like the pot odds calculator (one-shot, grab the number, leave) than the range visualizer, which is the one people actually come back to. So my guess is the equity calc earns its keep as an SEO front door more than a retention driver. But that's a guess until I've got per-tool tracking in. I'll report back.
This is the playbook I believe in too — I'm growing something with free content instead of ad spend, so I've been living this. The hard part nobody warns you about: free-tool/content-led growth is slower to show signal, so it's easy to panic and abandon it right before it compounds. What's your read on the lag? Curious how long you gave each tool before deciding it was working or not — that patience threshold is the part I find hardest to hold.
You named the hardest part exactly: the signal lags, so the temptation to kill it right before it compounds is real. Honest answer on how long I've given each tool: not long enough to judge yet. The pot odds calc is about two weeks old, the equity calc is days. So I haven't hit a real "is this working" checkpoint on any single tool. My read on the lag, mostly from the blog side, is that meaningful organic is months not weeks, with a small trickle in the first few weeks. The way I try to hold patience is to set the evaluation window up front (3 to 6 months for anything SEO-driven) and judge on leading indicators in the meantime, rankings climbing, backlinks showing up, people moving between tools, rather than on installs early. If I judged on week-two installs I'd kill everything. How long are you giving yours before you call it?
The "slow trickle vs real channel" question is the right one to pressure-test, and I think the answer depends on something most people overlook: backlinks. Beyond direct install conversions, are your tool pages picking up links from poker communities, strategy forums like 2+2, or Discord servers? If yes, that's what eventually turns a trickle into a compounding channel — each backlink raises domain authority and helps future content rank faster. A free tool that converts 0.5% of visitors directly but generates 150 quality backlinks in a year can be wildly worth it even if the direct conversion looks disappointing.
The range visualizer seems especially shareable because people naturally want to show others the ranges they've built — that's organic seeding. Curious whether you're actively posting the tool link in poker communities or waiting for organic discovery?
Backlinks is the piece I think people underrate, and you framed the math perfectly: a tool that converts 0.5% directly but earns 150 quality links a year can be the best thing you build, because every link makes the next piece of content rank faster. Honest state: the tools are too new to have meaningful links yet, so I can't claim that flywheel is spinning, only that it's the outcome I'm building for. On active posting vs waiting: I've tried active, and it's harder than it sounds. Poker communities and tool subreddits are protective, so straight link posts get caught by spam filters or sit in mod queues, especially from an account that reads as promotional. So right now it's a mix: lean into making the tools naturally shareable (the range visualizer is the obvious one, people want to show the ranges they built), build in public like this, and earn the community links the slow way instead of forcing them. How are you seeding yours, active or organic?
Mostly organic for now — posting in subreddits where the problem is real, not where the tool fits. For AI Bridge I found r/HowToMen works better than r/SideProject because people there actually want to compare AI answers, not just upvote indie products. Same lesson as you: accounts that read as promotional get filtered fast, so I'm trying to show up where the conversation is already happening. The waitlist is small (handful of people) but they found it themselves which feels like a better signal than forced traffic. Curious what your range visualizer conversion looks like when people share it — does the sharer bring back traffic or does it just go viral and disappear?
the tool to app conversion measurement problem is solvable but requires accepting that attribution will always be fuzzy. the cleanest approach is UTM parameters on every CTA from the tool pages to the app store, combined with a post-install survey asking how they found the app. neither is perfect but together they give you directional confidence. the bigger signal is usually cohort behavior: users who came from tools tend to have different retention than users from social because they arrived with more specific intent. that quality difference is worth tracking separately from volume
Agreed on all of it, and the post-install survey is the piece I hadn't given enough weight. A single "how did you find us" question in the app is cheap to add and covers exactly the iOS gap where UTMs go dark, so the UTM-plus-survey combo is a smarter stack than either alone. I'm partway there: I tag the download links with a source param today, but no survey and no cohort view yet. Your last point is the one I most want to get to: tracking the quality difference, not just the volume. Tool visitors arrive with a specific problem in mind, so I'd expect their retention to look nothing like a social-driven install, and that deserves its own column. Wiring both is next.
This is really useful.
I’m currently validating a habit/accountability app before building the MVP, and I’ve been thinking about a similar problem: people don’t usually share “apps,” but they do share small tools or concepts that solve one clear pain.
For your tool-to-app conversion, I’d probably separate each tool as its own acquisition channel:
Then track each one with separate UTMs or deep links, instead of treating “tools” as one funnel.
The part I’d be most curious about is not just installs, but downstream quality:
My instinct is that the free-tool funnel can be a real long-term channel if the tools match high-intent search behavior. But if the tools only attract casual users, it might stay a slow trickle.
Curious: are you tracking each tool separately, or just total site → app installs right now?
To answer your direct question first: right now it's basically total site to installs, with only a coarse source tag, not clean per-tool tracking. So I can't yet answer your four downstream questions, and they're the right four to ask. One honest note on number two: there's no trial or subscription conversion to measure yet, because the app is 100% free today and premium is planned but not live. Number four is the one I'd bet the whole thesis on though: do people who save or create something in a tool convert better than people who calculate once. The range visualizer lets you build and save your own ranges, the calculators are one-shot, so if save-and-return behavior converts better, that tells me exactly what to build next. I just need the per-tool instrumentation in to prove it. Good luck with the habit app, the same sharing dynamic applies: people share a streak or a tool, not "download my app."
the free tool as top of funnel strategy is underrated — people share useful things, not products. that insight alone is worth stealing for almost any niche.
for tool-to-app conversion tracking, the cleanest approach i've seen is a unique UTM parameter on every CTA inside each tool page. then you know exactly which tool drives installs, not just aggregate traffic.
curious whether the range visualizer or the pot odds calculator pulls more return visits — that would tell you which problem your audience cares about most before you double down on more tools.
Unique UTM per CTA per tool is exactly the plan. Aggregate traffic hides the only thing I care about. On your return-visits question: I don't have the numbers yet, but my bet is the range visualizer pulls far more return visits than the pot odds calculator, because it lets you save and tweak your own ranges, so there's a reason to come back, while pot odds is grab the number and leave. If that holds, it tells me my audience cares more about studying ranges than running quick math, and that's where the next tools should go. Measuring it is the next job.
Free-tools-as-distribution is criminally underused for early-stage products. The piece most founders miss: the tool itself doesn't need to be tightly related to the paid product — it just needs to serve the SAME ICP at the SAME stage of awareness. A free Lighthouse-score widget pulls in performance-conscious devs; a free meta-tag generator pulls in SEO-conscious site owners. If your paid mobile app serves either of those personas, both tools route traffic to you for years even when you stop maintaining them.
Two operational tips from doing this at scale: (1) make each free tool a STATIC page with its own unique <h1> mapped to the highest-volume keyword you can defend (not a generic "/tools/x" route — those don't rank). (2) Add programmatic schema (FAQPage + HowTo) on every tool page; that's worth ~20% extra organic CTR in 2026 because AI Overviews source from rich snippets first.
The dwell-time signal on a working free tool is the strongest organic-rank moat I've seen in years.
This is the most actionable comment in the thread, thank you. On your first tip, I'm partway there: the tools are already separate static routes (/tools/pot-odds-calculator, /tools/range-visualizer, /tools/equity-calculator), each with its own metadata, not a generic catch-all. What I haven't done rigorously is map each H1 to the single highest-volume keyword I can actually defend, so that's a concrete audit I'm taking. The schema tip is the one I'm acting on fastest: I already have FAQPage on the tool pages, but adding HowTo is an easy win, and your read on AI Overviews sourcing rich snippets first in 2026 is the kind of thing I'd rather build for now than retrofit later. The dwell-time-as-moat point matches what I'm seeing reasoned all over this thread. Appreciate the operator-level detail.
Free-tool funnels work long-term, but they compound slowly and most people undercount what they actually cost. The traffic looks free because there is no ad spend, but the engineering and maintenance time to keep three calculators accurate, fast, and ranking is real. Worth tracking your effective cost-per-install including dev hours, not just the zero in the ads column.
On measurement: UTM parameters on the app-store link from each tool get you click attribution, but the harder number is what happens after install. If you can tag the install source (even just a query param on a deep link or a "how did you find us" screen), you can compare 7-day retention by tool. That is the number that matters. A tool with half the traffic but double the retention is the one to double down on.
One pattern I have seen work well in SaaS (different from mobile, but the principle transfers): the best free tools teach a workflow that the paid product automates. Your range visualizer does this. Someone who builds and saves custom ranges on the web tool has already invested effort and built a mental model. The app becomes "continue where I left off" rather than "try a new thing." The calculators, by contrast, give a one-shot answer. They build zero switching cost.
If you are choosing where to invest next, I would pick the tool that creates the most user-generated data (saved ranges, tracked sessions, custom configs) over the one that answers the most searches. Data creates return visits. Return visits create installs.
This is a great idea. I often feel that a useful tool, quiz, or even a simple game can be a much stronger acquisition hook than a direct ad because it delivers value before asking for anything in return.
We just launched a music discovery app and are exploring different user acquisition channels ourselves. Your approach resonates because it creates a natural path from solving a specific problem to discovering the broader product.
I'd be curious to see how the funnel performs over time. My intuition is that if the tools continue to rank and provide genuine value, they can become a durable acquisition channel rather than just a trickle.
Keep up the great work, and thanks for sharing the playbook :)
Thank you, that genuinely means a lot. And you said the core better than my whole post did: it delivers value before asking for anything in return. That's the whole difference between a tool and an ad.
Congrats on the music discovery launch. If I were in your shoes I'd lean into how playful music is: a 30-second "find your sound" taste-match or a shareable result quiz maps to the exact pre-download moment, and the result is something people actually post, which an ad never is. Different domain, same bet.
On durability, my honest read matches your intuition: a trickle that keeps ranking and compounding stops being a trickle. The catch is the two conditions you already named, keep ranking and keep being genuinely useful. Lose either and it's back to noise. I'll circle back and post how the funnel actually performs once it's had time to settle. Good luck with yours, and thanks for the kind words :)
good
I'd be careful treating this as a measurement question too quickly.
The interesting question may not be whether tool traffic converts.
It may be what conclusion deserves confidence if it does.
Those sound similar, but they can lead to very different decisions about whether the tools are acquisition assets, standalone products, or something else entirely.
That's not a call I'd make casually from the current signals.
That's a sharper framing than mine, thank you. You're right that I jumped to "does
it convert" when the real fork is what these tools even are: an acquisition
funnel, standalone products, or both. And you're right that I can't honestly make
that call from two weeks of thin data.
If I'm honest, the equity calc could probably stand on its own, while the others
feel more funnel-shaped, which already hints they're not all the same kind of
asset.
Genuine question back: what signal would you want to see before making that call
with confidence? Retention on the tools themselves, repeat visits, something else?
I'd rather know what I'm looking for than collect numbers blindly.
The reason I'd hesitate to answer that directly is that I don't think the interesting part is any individual signal.
I think it's the decision that signal is being used to support.
That's where I'd be careful.
The same metric can look incredibly persuasive while pointing people toward completely different conclusions.
I wouldn't try to unpack that properly in a thread.
If you're curious, drop your email and I'll put together the tighter version.
Fair, and the underlying point is real: the same metric can be used to justify opposite
decisions, so the risk lives in the conclusion, not the number. Worth keeping in front of me.
On the tighter version, I'd honestly rather keep it here. Half the value of this thread has
been that it's public, other people building the same way are reading it, and a rough
version helps them too. If it's easier, IH DMs work fine. I'd just rather not drop an email
into a public thread. Genuinely curious what you'd land on, though.
Fair.
The reason I stopped short is that I don't think the useful part is the answer itself.
It's the decision sitting underneath it.
Feel free to email me directly: [email protected]