Less coordinating tools. More shipped experiments.
Your title says growth. Your calendar says integration manager: briefing the agency, queueing engineering, exporting CSVs to answer one question, and assembling Friday's deck from six tools. AppDNA takes the coordination off your plate and gives you back the only metric that matters in your job — experiments shipped per month.
AppDNA for growth leads is the execution layer that replaces tool coordination with shipped experiments: one system that sees the whole funnel across nine modules, proposes prioritized experiments in the Insight Inbox, ships approved changes to devices without a release, and keeps every learning in Growth Memory — built to turn the typical 3–6 week, 4–6 person cycle into 1–2 weeks with one person.
Five things that eat your week — and how they collapse into an approval.
Owning the metric you can't touch
Maya owns trial→paid. Standup: engineering can slot her paywall test "early next sprint, maybe." The agency's report is due Thursday. Amplitude says activation dipped; RevenueCat disagrees; the truth is in a CSV she hasn't exported yet. Her one experiment this month is waiting on three other teams.
One growth lead. Nine tools. Everyone's schedule but hers.
Maya opens the Insight Inbox: the activation dip, diagnosed across the whole chain, with a proposed fix — prioritized above the paywall test because the data says so. She approves both. Both are live this week, at 10% of traffic, stop-loss armed. Engineering wasn't in the meeting. There wasn't a meeting.
Same growth lead. One system. Shipping on her schedule.
The team your headcount plan keeps deferring.
You don't have a tooling gap — you have a specialist gap wearing a tooling costume. These are the seats AppDNA fills.
The experiment PM — Insight Inbox + the experiments engine.
A standing queue of prioritized, ready-to-run experiments — each with hypothesis, projected impact, and guardrails pre-set. Approve like email. The engine handles staged rollout (10% → 50% → 100%), SRM detection, and calling the winner. Full-lifecycle experiments across the whole funnel, not just the paywall.
The lifecycle manager — Retention.
Journeys, push, in-app messages, and email in one orchestra — targeted from the same event pipeline as everything else, so your win-back campaign knows what the paywall knows. The CRM specialist role, minus the six-month ramp.
The analyst who sees everything — cross-module intelligence.
The engine underneath the modules: because one pipeline owns ad → onboarding → paywall → revenue, it surfaces the correlations point tools structurally cannot see. This is the "your onboarding change moved paywall conversion" answer — the one that used to cost a week of SQL.
The performance marketer — Paid UA.
Campaigns across 9 ad platforms with creative management, read next to funnel outcomes — so "spend more on TikTok" is a decision backed by trial→paid data, not by installs. Your paid generalist hours go to strategy; the coordination goes away.
Why not just add another tool? Or hand it to the agency?
Both are rational moves — you've probably made both. Point tools are genuinely best-in-class at their slice; a good agency brings real expertise and accountable humans. Here's where each ends.
| Another point tool | The agency | AppDNA | |
|---|---|---|---|
| Sees the whole funnel | One slice, by design — and you become the integration layer between slices | Sees what you export to them, weeks late | Nine modules, one event pipeline, one source of truth |
| Ships the fix | Shows you data; the ticket queue ships the fix | Recommends; your engineering ships — 2–4 week cycles | Live on devices in minutes, no release, guardrails on |
| Keeps the learning | Logs its own results, blind to the rest | Knowledge leaves with the account manager | Growth Memory compounds in your workspace — and it never resigns |
| Cost & speed | Another subscription, another tab, another Monday | $10–50K/mo typical, on their calendar | One system, your team, software speed |
Adding tools is how you got here. AppDNA is expert like the agency, yours like a hire, instant like a tool — and it ships like none of them.
Complete on its own. Compatible with everything you already run.
RevenueCat · Adapty · Firebase · AppsFlyer · Adjust · Amplitude · Mixpanel · Braze · OneSignal
Zero migration. AppDNA reads your existing stack from day one — it doesn't ask your team to abandon anything on week one. Over time, you'll simply need fewer of them.
A note from the founder
Walk into Monday's standup with the plan already prioritized.
Paste your App Store or Google Play link. The audit scores all nine modules, finds your biggest funnel leak, and produces a 90-day plan — the internal ammunition doc your CEO conversation has been missing. Free, and yours either way.
Book a discovery call — no pitch, we listen; you leave with a Growth Conception — a real plan for your app — in 2 days. Free, whether or not you buy.
FAQ
Eight questions Heads of Growth ask us on demo calls — usually in this order.
01Will this tank trial starts before I even see it happening?
It can't move faster than your guardrails. You designate trial starts (or any KPI) as a guarded metric; every experiment launches at 10% of traffic with a stop-loss on it — if the metric degrades, the experiment is halted and withdrawn automatically, and you see exactly what happened in the audit log. That's tighter control than your current release process gives you.
02Do we replace Amplitude and RevenueCat? My team just finished setting them up.
No — AppDNA reads from them on day one, zero migration. The point isn't ripping out your stack; it's that today none of those tools can answer "did the onboarding change move revenue?" because each sees one slice. AppDNA sits across the whole chain. Over time you may need fewer subscriptions — that's your budget line to optimize, not our requirement.
03Engineering already said no to more experiment tickets this quarter.
This is the ticket that ends the tickets: one SDK, about an hour of engineering, once. After that, paywall, onboarding, and messaging experiments ship from your console with zero releases — the 3–6 week, 4–6 person cycle becomes 1–2 weeks with you alone. Your roadmap negotiation with engineering is over.
04Does our funnel data end up informing our competitors' recommendations?
No — isolation is enforced in code, not policy. Your experiments and results live in your workspace only; the cross-market patterns you benefit from are anonymized, and nothing identifiable flows the other way.
05Is this another tool my 3-person team has to learn?
It's the opposite trade: it removes work rather than adding a surface. Your team already knows how to use it — the Insight Inbox works like email: proposed experiment, evidence, approve or decline. What it replaces is the week of SQL, the ticket queue, and the specialist skills (ASO, lifecycle, monetization) you don't have headcount for.
06If I champion this internally and it flops, that's my credibility spent.
So spend nothing first: run the free audit and take the report to your CEO — it's a real diagnostic with your Growth Score and biggest leak, useful ammunition even if you never buy. Then the system commits to a first experiment live within 14 days of SDK install — you'll have a shipped, measured result to show before anyone asks how the new tool is going. And everything is exportable if you walk.
07How rigorous are the experiment statistics? I've been burned by peeking and broken splits.
The engine is built for the failure modes you've seen: SRM detection flags broken randomization before you trust a result, rollouts are staged (10% → 50% → 100%), guardrail metrics are monitored alongside the target metric, and winners are called by the engine's criteria rather than by whoever checked the graph most optimistically. Every decision is logged with its data, so you can defend any result in front of anyone.
08How do I prove ROI internally before committing budget?
Start with the two free artifacts. The audit gives you a scored, benchmarked analysis of all nine modules and a 90-day plan — a document you can put in front of your CEO whether or not you buy. Then the math is transparent: 10% improvement at each of four funnel stages compounds to ≈46% MRR (1.1⁴ ≈ 1.46) — and the system's job is making those 10% improvements continuous. From there, your own experiment log becomes the ROI report: every shipped test carries its measured impact. Missing your question? Ask us directly — a human replies within one business day.
Missing your question? Ask us directly — a human replies within one business day.
See your biggest leak — free, in about 2 minutes.
Everything your app needs to grow. In one system.