Distribution Playbooks
Getting a product in front of the right people — the channels founders bet on, the partnerships that scaled, and the underrated distribution plays most people skip. Each one is quoted from the founder who ran it.
266 tactics · page 7 of 9
“There's a lot of tourists in that group that start a trial or convert a trial, and a lot of people are targeting off of that — as these methods become less good, it'll force developers to actually talk to users.”
Optimising Facebook on trial conversions acquires tourists, not locals
Optimising Meta campaigns on trial starts targets the event easiest to drive, not the users who will pay for three years. High trial volume with weak long-term retention is a tourist-acquisition machine dressed up as growth. ATT degrading that signal is arguably a gift: it forces a shift toward understanding why locals convert and building acquisition around those behaviours — lower volume, far better LTV.
“Building the app has never been like the hardest part is like getting attention sustainably building a community building up a user base that's where the rubber really meets the road.”
Building was never the hard part — getting sustained attention still is
AI lowered the cost to build an app but didn't change the fundamental challenge: distribution. There were always a million apps in the store; soon there will be ten million. The apps that win will be the ones that solve the attention problem, not the ones that ship fastest. Sustainable organic reach or a genuine community moat matters far more than shipping speed.
“There's also differentiation as distribution where just being so unique and strange like distribution just kind of takes care of itself because you're the one app that can do the thing.”
Differentiation as distribution: the truly unique product gets attention by itself
The strongest distribution strategy is building something no one else can build. When your product is genuinely singular, organic coverage, word of mouth, and creator content happen without a paid media budget. Combine that with a distribution channel you're good at and you have both vectors working together.
“The two things that were scarring to Apple were the near bankruptcy. They're still thinking of themselves as underdogs who want to assert at least 51% of the power over developers — they've lost sight of the fact that they've actually got like 95% of the power.”
Apple's tight platform control traces directly to near-bankruptcy in the '90s
The three executives who control Apple's App Store relationships — Jaws, Schiller, and Eddie Q — all joined Apple in the late 1980s and lived through the company's near-collapse when developer leverage almost pulled the platform under. That existential scare became institutional memory: never let third parties hold majority power again. Understanding this history is essential context for any developer trying to read Apple's behaviour.
“They open up subscriptions to all apps — which obviously working at RevenueCat and now all my apps are subscription. That was Revolution. That was App Store 2.0 — to empower developers to better monetize apps.”
App Store 2.0 in 2016 unlocked subscriptions for all apps and powered a decade of growth
Before 2016, subscriptions were restricted to narrow app categories. Phil Schiller's App Store 2.0 overhaul opened them to every app, sped up review from 14 days to under 48 hours, introduced the 15% renewal rate, and launched Search Ads. Each change would have been meaningful on its own. Together they powered an entire decade of subscription app growth — a reminder of how much platform policy shapes the economics of every app built on top of it.
“Vision OS today is nowhere near as vibrant a third party developer ecosystem as the Mac was in 1985 or 1986. Resentment — numbers 1, 2, and 3 on the list of reasons why developer relations are strained with Apple — has to do with money.”
Developer fee resentment is the single biggest threat to Vision OS ecosystem adoption
The 1984 Mac, despite poor consumer sales, had a blossoming third-party app ecosystem driven by developer enthusiasm. Vision OS in 2025 does not — and Gruber argues this is primarily a financial resentment problem, not a technology problem. If Apple enters its next hardware platform cycle with reluctant rather than enthusiastic developers, it will lose the ecosystem advantage that made the iPhone unstoppable.
“The app store was genuinely a revolution in software. Bandwidth was expensive, working with third-party payment platforms was a hassle. On phones the only software was carrier-billed and they took 50% of everything.”
The original App Store was a genuine revolution — free distribution replaced 50% carrier cuts
In 2008, distributing software required self-hosted servers, payment infrastructure, and often carrier deals that took 50% of revenue. The App Store collapsed that to a $99/year developer account and a 70/30 split — genuinely transformative at the time. Understanding that original context matters: it explains both why Apple feels entitled to its commission and why modern developers, who have grown up with Stripe and Vercel, find that entitlement increasingly hard to justify.
“When people do have some level of affinity or understanding of the brand, when you do hit them with that performance marketing it can be way more efficient and effective because you've kind of warmed them up as a lead.”
Brand affinity pre-warms audiences so performance campaigns convert more efficiently
The hidden value of brand campaigns shows up in performance campaign CPAs, not brand metrics. Users who have been exposed to brand messaging are already partially convinced before they see a conversion ad — so performance campaigns harvest that warmth rather than trying to build trust and drive action in a single step. Brand investment is pre-paying for future performance efficiency.
“We try to figure out what is the right level of investment on the digital upper funnel campaigns — how do these impact our performance campaign. You can actually do this very easily with a conversion lift study through Meta among other partners.”
Conversion lift studies prove how much upper-funnel brand spend boosts performance campaigns
One of the hardest questions in mixed brand/performance budgets is proving the causal link between upper-funnel spend and downstream conversions. Meta's conversion lift study (and equivalents from other platforms) shuts down specific audiences temporarily to measure the counterfactual. At Deezer, this validated assumptions at a much larger magnitude than last-click attribution ever showed.
“There's really nothing to lose with it because it doesn't cost money to be on there and try things. It's brainstorming, trying things, seeing what sticks and if it doesn't stick then try something different.”
TikTok organic costs nothing — test it before committing budget to any other channel
TikTok's zero-cost floor makes it uniquely suited as a channel for experimentation before budget commitment. Maddie Kirby frames it as a discovery process: post across content types, measure what gets traction, then double down. The risk of not trying is missing a distribution channel that has driven #1 App Store rankings for apps with zero ad spend.
“I was randomly scrolling through TikTok and a girl had made a video — it hadn't even been at one million views yet — and so I was like: I gotta do a duet right now. I just filmed a duet where I was walking through the app as she's explaining the idea.”
Duet a viral video before it hits 1M views — early responses ride the wave, late ones disappear
Timing matters more than polish on TikTok. Maddie Kirby spotted a video describing something that sounded like One Second Every Day before it went viral and immediately filmed a response — no script, no approval process. The duet surfaced One Second Every Day to everyone who later found the original 13M-view video. Late responses to viral content are invisible; early ones become part of the wave.
“It wouldn't have gone as well if we didn't have a presence on the platform too. You shouldn't be just jumping on — just imagine if they already had a presence and people would want to be posting about them more.”
Build a TikTok presence before you go viral — you cannot amplify a wave you are not on
When the viral duet opportunity appeared, One Second Every Day could respond instantly because they were already on the platform with an established account. Without that pre-built presence, a potential #1 App Store moment might have passed with no one to amplify it. Being on the platform before you need it is the prerequisite for capitalizing on any organic viral moment.
“We had over 200 applications for people to join our brand ambassador team. We narrowed it down to 26 people — they get connections with us and can have impacts within the app as well as free merch, and we get some content from them in exchange.”
Turn superfans into brand ambassadors — merch for content beats paid influencers
One Second Every Day's brand ambassador program received 200+ applications because the community was already full of people who wanted to help. The exchange — exclusive merch and early feature access for organic content creation — costs almost nothing but generates authentic, high-trust content from genuine users. This outperforms paid influencer content on cost, authenticity, and audience trust simultaneously.
“Cross promotion helps with our existing app because we already have an audience and the use case translates so we were able to target folks at night for example that's something you don't have the first time around.”
Cross-promoting to existing audience is the unfair advantage when launching a second product
When launching sleep app Rest, Siniawski tapped Podcast App's existing users — specifically those who used the app at night, a behavioral signal of sleep use-case fit. This cross-promotion blast gave the zero-to-one phase a boost unavailable to a first-time founder. Even 130K subscribers is a meaningful launch advantage when they're the right audience for what you're building next.
“I think the most important piece is first realizing this is important and then just spending a lot of time and energy to try to learn it... product alone won't do it and many times a worse product wins over a better product just because they have better distribution right.”
Distribution is a skill — product won't do it alone, and the channels keep changing
Siniawski treats distribution as a craft requiring constant re-learning: channels that worked in 2013 (Facebook virality, early ASO) are saturated or dead. His framework: allocate dedicated time to studying distribution as a discipline, not just implementing the tactic du jour. Awareness that channels mature and tactics change is itself the meta-skill — it stops founders from assuming what worked before will keep working.
“There is no point for you to try to interpret why an ad won or didn't win. What you should be interpreting is: when you get a win, or the win rate increases — the process worked. The output is irrelevant. That output is utterly random. Why that worked was utterly random.”
Stop trying to decode why a winning ad won — focus on the process that produced it
Seufert's most counterintuitive insight: with black-box platforms like Advantage+ and Pmax, the winning creative is selected by an algorithm you can't see, targeting an audience you don't know. Post-hoc rationalizations are noise. The only learnable signal is whether your creative-input process improved. Focus on raising the win rate, not reverse-engineering individual winners.
“Diversifying for the sake of diversifying is often times a bad idea. A new channel's ROAS doesn't just have to meet the ROAS of the other channels that could have absorbed that budget — it has to exceed it, because you're supporting a new channel.”
Diversifying UA channels for its own sake destroys performance — use the waterfall method instead
Seufert's waterfall model: max out the biggest channel until it hits your ROAS threshold, then move to channel two, then three. Adding a second channel before saturating the first adds overhead without proportional return. Diversify only when you've hit true saturation or when a brand-oriented channel lifts blended performance across the portfolio.
“On Android you have the benefit of actually serving your ads in the Play Store — that's super high intent. You cannot get that inventory anywhere else. It doesn't exist. You can't buy it. I always liken Play Store traffic to branded search: you're reaching people at the highest intent moment possible, when they're actively searching for something they want.”
Android Play Store placement = the highest-intent UA inventory that exists anywhere
Ashley Black spent 6 years leading Google's App Ads team and calls Play Store placement the defining advantage of UAC on Android. Unlike Meta (Facebook + Instagram) or TikTok, Google uniquely controls intent-level search inventory: Play Store browse, Google.com search, and YouTube. No other network can replicate someone actively querying 'fitness app' while staring at the Play Store.
“The engineers at Google are always like '20% — no more than 20% in any given day on bids and budgets up or down.' I got burned pushing it more, and what happens is the system goes crazy. I only adjust by 20% every two to three days, not every single day, otherwise it keeps kicking back into learning mode at too great a frequency.”
Scale UAC budget max 20% every 2-3 days — not daily — or the algorithm goes rogue
Google's UAC algorithm treats large budget jumps as a signal to re-explore the entire inventory landscape, throwing it back into learning phase and tanking short-term performance. The 20% rule is an internal Google engineering guideline that Black could share only after leaving. Two-to-three day spacing between changes further stabilizes cohort comparisons.
“I always encourage people to build out multiple ad groups and I theme them around use cases or features. Build out maybe five ad groups per campaign, get traction, see what's resonating. A really common mistake: the first ad group you create is the one Google runs with, even if another one performs better.”
Run 5 themed ad groups per campaign — Google favorites its first child regardless of later performance
Google doesn't give budget control at the ad group level — the algorithm decides how to distribute spend. But you can influence creative testing by segmenting into themed groups. Five groups gives enough surface area to find a resonant angle without splitting signal too thin. Knowing the 'first child' bias helps: your original ad group often stays dominant regardless of later entrants.
“A lot of times cheaper CPMs mean worse traffic — not always, but a lot of times. If there's a big decline in performance, I check if there was also a decline in CPM. Google's algorithm can blend high-quality and low-quality inventory and average it out. People are like 'I don't want the crap' — but you have to actively manage it.”
Cheaper CPMs in UAC are a warning sign — low cost usually means low-quality display traffic
UAC blends Play Store, Search, YouTube, Admob, and Display Network traffic into a single averaged performance number. If CPMs suddenly drop, the algorithm has shifted spend toward cheaper Display Network inventory. Black monitors CPMs as a leading indicator of traffic quality — a counterintuitive practice since most UA managers optimize for CPI. She also audits specific sites serving ads and excludes spammy placements.
“The best consumer subscription companies, almost without exception, have really robust organic acquisition strategies as their primary growth lever, and they only use paid ads as a supplement. They're either growing through word of mouth, or through content — like Quizlet through longtail SEO with user-generated flashcard content, or AllTrails through hyper-local search.”
Best subscription companies treat organic acquisition as primary and paid as a supplement
Carter distills the pattern across Quizlet, AllTrails, Duolingo, Strava, and Life360: each built a flywheel of organic acquisition before scaling paid ads. Companies whose first and primary growth loop is paid UA hit a ceiling because LTV/CAC degrades as they exhaust their highest-intent audiences. The moat is always the organic engine.
“Consumers flock to best of breed and they learn and decide what best of breed is because other consumers tell them. Word of mouth is such a dominating channel. Flo is really special — they get over 50% of their users are organic. Moms now are telling their daughters, friends, girls in school tell each other about it.”
Category killers win on organic word-of-mouth — over 50% of Flo's users are organic
In consumer, word-of-mouth is the dominant channel — not paid UA. The apps that become category leaders reach a self-reinforcing flywheel where organic referral dwarfs all paid channels. Crowley's framing: 'category killers' emerge in every vertical (female health, youth sports, family management) and they compound on the organic advantage until paid acquisition becomes almost irrelevant. Building for that scale is the highest-value strategic goal.
“It was all focused on the content to start, not on any sort of acquisition or monetization. It was all on: can we create great content that is providing value? And if you nail those, then they're willing to learn more and purchase from you. If you're not nailing that before spending a dollar on paid marketing, you're going to give up pretty quickly.”
Nail organic before spending a dollar — profitable paid TikTok requires a proven organic playbook first
Stewart's TikTok formula was explicit: first spend months testing organic content at zero cost to find repeatable million-view hooks, then put paid dollars behind proven creative. Ladder reached 250K followers on a new coach account in 45 days with no new video shot, just repurposed existing content. The organic signal is the selection filter for ad spend; without it, paid TikTok burns cash on creative guesses.
“We learned Spark, which is just whitelisting on TikTok but taking the coach's organic content and turning that into an ad and pointing that in a direction that we set. That was explosive very quickly for us.”
Spark Ads — whitelisting organic coach content as an ad — was explosive for Ladder
TikTok's Spark Ads let you take an organic post from a creator's account, boost it with paid budget, and control the CTA destination. For Ladder, this bridged the organic-to-paid gap: proven organic content became the ad creative, so social proof (real follower counts, organic engagement) was visible to paid audiences. This hybrid format outperformed brand-produced ads because TikTok's algorithm treats Spark Ads like organic posts.
“More and more AI products are using hybrid monetization models where you've got a subscription but then you also have to purchase additional AI credits. That leads to an opportunity around incentivizing referral programs where now if I invite a friend or colleague I get additional AI credits.”
PLG loops and AEO are the cheapest acquisition as paid channels get more crowded and expensive
As Meta and Google CPMs rise, product-led growth loops become the highest-leverage acquisition channel. Carter identifies four loop types: personal viral (invite friends), social viral (shareables like Tolen's personality infographic), financial viral (AI credits for referrals), and content-driven (SEO and AEO from crawlable output). AI apps have a structural advantage — their outputs are inherently shareable. He also highlights Reddit as an early AEO tactic: products with a Reddit community show up more often in LLM prompt responses.
“A lot of people despise Google's products for that reason but as we were kind of pointing out it's like it's all trade-offs. You trade off some of that control for reach for the high intent things like that.”
UAC trades targeting control for scale — accepting that trade-off is the key mindset shift
Google UAC's biggest drawback is its black-box nature: advertisers cannot force video ads to run in specific placements, and traffic distribution across Play Store search, YouTube, AdMob (in-app network), and mobile web display is opaque. Ashley Black reframes this not as a flaw but as a designed trade-off — you sacrifice placement-level control in exchange for Google's algorithm optimizing across massive scale inventory. Fighting the algorithm by manipulating bids to force traffic to specific placements usually backfires.
“Google Search is mostly done in a browser — it's not like in an app. YouTube — there's still quite a bit that happens in a browser. MGDN is mobile Google Display Network — ads in browsers on websites. A lot more of Google's mobile traffic is served in-browser in comparison to these other app-native platforms like Meta or TikTok.”
Google UAC serves more traffic in-browser than any other mobile network — critical for iOS measurement
A material portion of Google UAC traffic reaches users through mobile browsers rather than apps — which was historically invisible to SKAdNetwork on iOS. Ashley Black had clients where 99% of Google traffic came from search and zero conversions registered in attribution before SKAN 4.0. Even with SKAN 4.0, iOS Google campaigns require careful measurement configuration that Meta or TikTok campaigns simply don't need. This unique in-browser traffic mix is the most underappreciated difference between Google UAC and every other major mobile ad platform.
“Nobody knows — this is the other reason why people don't like this. You have really limited visibility into where your ads are showing. If you have a really good Google rep they do have the ability to see the breakout but in the frontend you're making a lot of assumptions and you're a little bit blind to what's actually at play.”
Limited placement visibility makes UAC optimization inference-heavy — get a rep with backend access
In the Google Ads UI, placements are bucketed into just four groups — Search, Search Partners, YouTube, and Display Network — each hiding sub-placements. Play Store search and google.com search are lumped together; AdMob and Play Browse are both inside Display Network. Without a Google rep who has backend access, advertisers are largely blind to whether poor performance comes from low-intent AdMob traffic or high-quality Play Store search. Ashley Black's advice: build a relationship with a dedicated Google rep who can pull the placement breakdown and treat the algorithm as an optimization partner rather than an adversary.
“I hired an influencer for $1,500. Professional video, beautiful footage on a real golf course, edited perfectly. My $0 screen recording from my basement — literally just me talking over a screen capture — doubled its install rate. I would never have known without testing both.”
The basement screen-recording ad outperformed the $1,500 influencer video — iterate on raw content first
Duffett's experience echoes a pattern across consumer subscription apps: raw, authentic content — especially in acquisition contexts — outperforms polished production. The influencer video looked like an ad; the screen recording felt like advice from a fellow golfer. In a high-trust niche like golf, the latter framing converts better because it matches the context (someone sharing a tool they use) rather than advertising.