Distribution Beats Product: Lessons from 40+ Apps Before the AI Wave
Distribution beats product because a product nobody finds has zero users, no matter how well it's built. After growing 40+ mobile apps and games through App Store Optimization and paid acquisition, the pattern I saw over and over was simple: the apps that won were the ones designed around how people discover them. Today that discovery channel is shifting to AI engines, which is why GEO is the new ASO.
What did 40+ apps teach me about winning?
Before Torch99, before GEO, there was the App Store.
At Appskilled, the studio I co-founded, we grew more than 40 apps and games through organic marketing, App Store Optimization (ASO), and later Apple Search Ads. Some were utilities. Some were games. Later, a wave of them were AI apps. Different categories, same lesson.
The uncomfortable truth: polish was never the deciding factor. Discovery was.
Builders hate hearing this. I get it. I'm a builder too. We like to believe that if the product is good enough, people will come. But "good enough" is invisible until someone finds it. The market doesn't grade your code. It grades whether you showed up when someone was looking.
If you want the longer version of that journey, I wrote it up in From 40+ Apps to AI Strategy.
Why do great products fail without distribution?
Because the order of events is fixed. A user has to find you before they can judge you.
Think about what happens in an app store. Someone types a search. They see a short list of results. They look at an icon, a title, a few screenshots, and a star rating. They decide in seconds. The app that's not on that list doesn't get judged as worse. It doesn't get judged at all.
Builders keep making the same mistake for three reasons:
- Building feels like progress. Shipping a feature is visible and satisfying. Distribution work is slow, uncertain, and full of rejection.
- Quality is what we control. Distribution depends on channels, algorithms, and other people. So we polish what we can control and hope.
- Marketing comes "after launch." By then the product's positioning, naming, and core promise are locked in, often around how the team thinks about it, not how buyers search for it.
The result is a graveyard of well-built products with no audience. Every founder has walked past it.
What did ASO actually teach me about distribution?
ASO looks like a technical discipline: titles, keywords, screenshots. Underneath, it's a full distribution system with a feedback loop. Here's what it drilled into me.
- Demand comes before the product. Every app launch started with keyword research. What are people searching for? Where is search demand outpacing the supply of decent apps? We picked the gap first, then built to fill it.
- The listing is the product, at first. Before anyone opens your app, your title, subtitle, icon, and screenshots are the entire experience. We tested every one of those elements.
- Ratings are a distribution asset. Ratings shape both whether people install and how the store treats you. An app that earns good ratings early has a structural edge over a better app that doesn't.
- Discovery and retention feed each other. Good retention signals help visibility. Better visibility brings more users to retain. Break either side and the loop slows down.
- Treat apps like a portfolio. Not every launch wins. Double down on the ones that show pull, cut the ones that don't, and move fast.
None of these lessons are about code. All of them decided which apps grew.
What does a distribution-first build loop look like?
Most teams run the loop in one direction: build, then market. A distribution-first team runs it backwards.
| Step | Build-first | Distribution-first |
|---|---|---|
| 1 | Idea from the team's head | Find where demand is outpacing supply |
| 2 | Build the full product | Pick the channel where that demand lives |
| 3 | Polish for months | Build the smallest version that fits how that channel discovers products |
| 4 | Launch and "do marketing" | Ship fast, measure pull in days |
| 5 | Wonder why nobody came | Double down on pull, kill what has none |
The distribution-first loop is not anti-quality. You still need a product that delivers. It just refuses to spend months on quality before proving anyone can find you.
Did distribution-first actually work in practice?
The clearest proof came in early 2023.
ChatGPT had launched on desktop a few months earlier and there was no official OpenAI mobile app yet. ChatGPT-related searches were exploding on mobile, and the supply side was thin. We had the ASO playbook, so we read the signal and shipped an AI chatbot app in days, not months.
It crossed four figures in subscription revenue within its first five days.
We didn't build the best AI chatbot in the world. We built a credible one, optimized for discovery from day one, at the moment demand peaked. Timing plus distribution beat perfection. That's the whole lesson in one launch.
What do acquirers actually buy?
Code is replaceable. Attention isn't.
Polyfy, one of the projects I worked on, was a virtual experience in Decentraland that reconstructed New York City and hosted brands and celebrities in virtual events. The platform was acquired. My read, as someone who worked on it rather than someone who negotiated the deal: what made it valuable wasn't only the 3D build. It was the audience and brand relationships the build attracted.
That's the general rule. A buyer can rebuild your software. Rebuilding your distribution (your rankings, your audience, your place in the channels where customers look) takes years. Reach is the expensive part.
Why is GEO the new ASO?
Because the discovery channel moved.
For a decade, discovery meant app store search and Google. Now a growing share of buyers ask ChatGPT, Perplexity, Google AI, or Claude what to use, and get a shortlist back. Those engines are the new storefront. The same mechanics I learned in ASO map almost one to one.
| ASO lever | GEO equivalent |
|---|---|
| Keyword research | The questions buyers ask AI about your category |
| App listing (title, screenshots) | How AI engines describe your brand in one paragraph |
| Ratings and reviews | Citations and mentions on sources AI engines trust |
| Search ranking | Share of Model: how often you're named vs competitors |
| Update, test, re-measure | Audit, fix, re-measure across engines |
If you're not in the AI's answer, you're in the same spot as an app that doesn't rank: invisible, regardless of quality. I break down which old habits still work in GEO vs SEO: what changes, what stays, what dies.
This is exactly why I built 99Visibility. It audits how AI engines describe a brand, flags what's missing or wrong, and shows what to fix, at $49 to $149 a month. Most tools in the category stop at tracking and charge $300 to $500+ a month. I wanted the ASO feedback loop, rebuilt for AI search.
And if you're earlier than that, still deciding what to build and where your buyers will find it, that's the work we do in AI strategy and automation consulting.
FAQ
Does distribution really matter more than product quality?
In the early stage, yes. A product has to be found before it can be judged, so distribution decides whether quality ever gets a chance to matter. Over time, quality keeps the users you win. You need both, but distribution comes first in the sequence.
What is a distribution-first strategy?
It means choosing the channel and the demand before building. You research where buyers are already searching, build the smallest product that fits how that channel surfaces products, ship fast, and invest further only where you see real pull.
How is GEO similar to App Store Optimization?
Both are about being found inside a closed discovery system. ASO optimizes for app store search, ratings, and listings. GEO optimizes for how AI engines like ChatGPT and Perplexity describe and recommend a brand: the questions buyers ask, the facts engines repeat, and the sources they cite.
Can a small or bootstrapped company compete on distribution?
Yes, and it's often the best edge a small team has. Big players move slowly in new channels. When a channel shifts, like app stores in the last decade or AI engines now, a small team that reads the demand early can take positions before incumbents notice.
Building something and worried nobody will find it? Start with a GEO audit on 99Visibility, or talk strategy with me.
About the Author
Liwaa Beaini is the founder of Torch99 and co-founder of Virtual Minds, an AI product studio registered under ADGM (Abu Dhabi Global Market), UAE. He is an AI strategist and product builder operating from Lebanon, specialising in GEO (Generative Engine Optimization), mobile app growth, and AI-first systems. He has grown 40+ mobile apps, advised enterprise clients across MENA, and built products across AI visibility, local intelligence, and digital transformation.
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Founder, Torch99 · Co-Founder, Virtual Minds (ADGM, UAE)
AI strategist and product builder operating from Lebanon. Founder of Torch99 and co-founder of Virtual Minds. Founder of 99Visibility — the live GEO audit platform for the AI search era.