FOR APPS BETWEEN 100K AND 500K MAU

The specialists your team is missing. Already in the system.

At your size the team exists — and every person on it is covering two specialist jobs they never trained for. AppDNA doesn't add another tool to the twelve you already run. It adds the specialists: agents that watch every module around the clock, diagnose, and draft. Your team approves; the SDK ships.

AppDNA is the App Growth OS for subscription apps. For mid-size apps — 100K to 500K monthly active users, typically run by a growth team of two or three — it fills the specialist roles the team hasn't hired: ASO, lifecycle, and monetization exist as agents in the system that watch the funnel, diagnose problems, and draft fixes for the team to approve. One SDK ships approved changes without an App Store release, collapsing the typical 3–6 week experiment cycle toward 1–2 weeks with a single owner.

Free · ~2 minutes · No credit card
01

What growth looks like at 100K–500K MAU

Big enough to have a team. Not big enough to have specialists.

01
Every experiment takes the whole team.

The typical industry cycle is 3–6 weeks and 4–6 people per experiment — a designer, an engineer, an analyst, a release slot. At your size, that means the growth team's throughput is set by everyone else's calendar.

02
Generalists are doing specialist work.

Two or three people covering ASO, lifecycle, paid, monetization, and analytics. Each of those is a full-time craft at bigger apps. The gap doesn't show up as failure — it shows up as levers nobody has time to pull.

03
The cross-funnel question costs a week.

"Did the onboarding change move revenue?" With data split across 8–12 tools, that answer is a week of SQL and exports — so mostly it goes unanswered, and decisions run on the metric each tool happens to show.

04
The learning doesn't compound.

8 out of 10 teams can't tell you what they tested last year; the other 2 send 50 Excel files — our founder's observation from a decade of agency work, and mid-size teams are its center of gravity: enough experiments to matter, no system that remembers them.

02

The six things AppDNA changes at your size

One system, six differences — sized for a 2–3 person growth team.

01
The specialists your team is missing.

ASO, lifecycle, monetization, onboarding — they exist as agents in the system, each one watching its module's data around the clock, diagnosing, and drafting fixes. Your team stops covering six crafts with three people and starts reviewing the work of nine specialists. Every change waits for your approval before it ships.

02
Collapse the experiment cycle.

The industry's typical 3–6 weeks with 4–6 people becomes a system designed for 1–2 weeks with one owner — because the design, the build, and the release step disappear. Approved changes go live on devices in minutes, no App Store release, no engineering ticket.

03
"Did onboarding move revenue?" in one view.

One event pipeline owns the whole chain, so cross-module cause-and-effect — the onboarding change that moved paywall conversion — is a view, not a week of SQL. The question your tools structurally can't answer is the one this system is built around.

04
Your approvals, your traffic caps, your stop-losses.

The team keeps control of everything that ships: approval gates on every change, rollouts starting at 10% of traffic, stop-losses on the metrics you guard, full audit trail. You can also encode your own playbook — how your team does growth — and the agents work your process rather than a generic one. That is included, not an upgrade.

05
Benchmarks where you're blind. Memory where you learn.

Category benchmarks fill the gaps where you have no specialist to ask; every experiment your team runs compounds in Growth Memory, so the learning survives quarters, reorgs, and departures. Anonymized market patterns flow in; your data never flows out.

06
Zero migration.

AppDNA reads your existing stack — RevenueCat, Adapty, Firebase, AppsFlyer and the rest — from day one. Nothing to rip out, nothing to re-instrument. And because the meter counts only paying subscribers, better instrumentation never costs you more.

03

Your plan & path

What this costs at your size.

One plan, Autopilot: $149/mo plus $1.49 per monthly tracked paying user above the first 100. It carries all nine modules, the full zero-deploy SDK, the experiments engine, your own process encoded, and five named seats (additional seats $49/mo). Nothing is held back for a higher tier, and there are no MAU bands to cross.

At 100K–500K MAU with around 3% of actives paying, that lands between $4,500 and $22,500 a month. The useful comparison isn't another tool — it's the specialists you'd otherwise hire. A 6–10 person growth team runs $900K–$1.5M a year, fixed from the day the offers are signed. At your size AppDNA costs between a third of one growth hire and under two — for the output this page describes. And because the meter follows paying subscribers, the bill moves with your business in both directions: a quarter where the subscriber base shrinks is a quarter where the cost shrinks with it. Salaries don't do that.

one honest note on fit: because the fee is a flat amount per paying subscriber rather than a share of revenue, it is a larger slice of a low-ARPU app than a high-ARPU one. If your revenue per paying user is under about $10, monetization is probably your real constraint — the free audit will say so, and that's the thing to fix first.

teams at this size get the most from pairing the platform with implementation — the rollout is where systems succeed or stall. Guided — 8 weeks, weekly 1:1 with an App Growth Architect, your hands on the keyboard — is $6,900. Done-for-you — we configure the workspace, integrate the stack, ship the first experiments with your team, and hand over a working rhythm — is from $15,000.

04

We already know where your team is losing the most.

Across our audits, 85% of apps share the same biggest revenue leak: onboarding that fails to create the aha moment — costing at least a third of potential conversion. At 100K–500K MAU that's not a rounding error; it's the difference between a flat quarter and the one where the trial-to-paid line finally moved.

"Ten years and roughly 300 apps in, the mid-size pattern is always the same: a smart, overloaded team that knows its top three problems and hasn't shipped a fix for any of them this quarter. The audit names the leak; the system gives your three people the throughput of ten."
Michael Synowiec — Founder, AppDNA AI
05

Get the audit your team would run if it had a spare week.

Paste your App Store or Google Play link. Get your Growth Score, your biggest funnel leak, and a 90-day plan — free. It doubles as the internal doc that gets your roadmap unblocked.

Free · ~2 minutes · No credit card · Yours to keep
06

Frequently asked questions

Six questions growth teams at 100K–500K MAU ask us before connecting their app.

What if it ships something bad to 300K users?+
It can't ship anything on its own — every change is approval-gated by your team. When you approve, the rollout starts at 10% of traffic with a stop-loss on the metrics you guard; anything that degrades a guarded metric is withdrawn automatically and logged. That's a stricter safety model than your current one: build → submit → hope the release train was right.
We already run RevenueCat, Amplitude, and Braze. Is this a rip-and-replace?+
No. AppDNA reads your existing stack from day one — zero migration. It's complete on its own, so over the following quarters you'll likely find you need fewer of the twelve subscriptions — but that's consolidation at your pace, not a migration project we require up front.
Our engineers already say no to growth tickets. What are we asking of them?+
One SDK, under an hour, once. After that, the entire point is that growth stops filing tickets: paywalls, onboarding, prices, and messages ship from the console with zero App Store releases. Engineering's roadmap gets growth off it.
Does our funnel data feed a model our competitors benefit from?+
No. Workspace isolation is enforced in code, not policy; your data never trains a shared model and is never visible to another customer. The benchmarks you see are anonymized market patterns — nothing identifiable ever flows the other way.
We have a growth PM and two marketers. Doesn't this overlap with their jobs?+
It fills the jobs they're covering, not the ones they hold. Your PM keeps strategy and approval; the agents do the watching, diagnosing, and drafting across the modules nobody owns — ASO, lifecycle, monetization. The honest framing: we give 2–3 people the output of a 6–10 person growth team. It removes work from your team's week; it doesn't add a tool to learn.
If we roll this out and it stalls, what has the team lost?+
Less than a failed agency month — and structurally less than a bad hire. The free audit shows the plan before any spend; the plan is month-to-month; and everything the team builds — strategies, experiment history, results — is yours and exportable. Because the meter follows paying subscribers, a quarter where the app shrinks is a quarter where the bill shrinks with it; a salary does not do that. If you take the done-for-you path, it carries the Service Continuity guarantee — your scope gets delivered, period: if the system ever falls short of the agreed standards, we deliver the same work by hand, at the same price, until it doesn't have to.

Missing your question? Ask us directly — a human replies within one business day.

07

When you outgrow this page

At 500K+ MAU, the conversation changes — deployment, compliance, your own Growth OS configuration: that's the enterprise page. See AppDNA for enterprise →

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