Apple Search Ads · Facebook & Instagram · Google Ads
Lingviny plans, runs and measures paid growth for mobile apps across the three channels that drive most of it. Every decision goes back to one question: did this spend make money you wouldn’t have made anyway?
| Channel | Spend | Reported ROAS | Incremental ROAS | Next move |
|---|---|---|---|---|
| Apple | $15,000 | 2.40 | 1.60 | Shift brand to category |
| Meta | $30,000 | 1.80 | 1.20 | New creative concepts |
| $15,000 | 1.60 | 1.20 | Optimize to in-app value | |
| Total | $60,000 | 1.90 | 1.30 |
Hypothetical account. Reported ROAS is what each platform claims; incremental ROAS is what remains once you subtract sales that would have happened anyway.
They don’t compete for the same customer at the same moment, so they shouldn’t be judged by the same number. We set each one up for the job it does best.
Meet intent at the moment of download.
Create demand before anyone searches for it.
Cover the whole funnel without letting automation hide the mix.
Add up what Apple, Meta and Google each report and the total usually comes out higher than the revenue in your bank account, even before you count the people who would have bought anyway. Budget decisions made on those numbers scale the wrong things. We start by finding the gap, then manage to the real number.
What the platforms report$114,000
What the spend really added$78,000
No single tool gives you the answer. Each one answers a narrower question, and we use them together so they can check each other.
We read your accounts, tracking and unit economics, then show you where reported numbers and revenue disagree.
We agree on one source of truth: conversion definitions, attribution windows and a payback target finance would sign off on.
Changes run as experiments, with a holdout or a decision rule set in advance, so a result means something before budget moves.
Budget follows incremental return. Each week you get a plain account of what changed, what we learned and what comes next.
Worked examples of ROI and analytics problems, with the math shown. These are illustrative scenarios with hypothetical numbers, not client results.
A subscription app sees a healthy 1.90 reported ROAS. Measured against sales that would have happened anyway, the real figure is 1.30, and that changes where the budget should go.
1.90 Reported ROAS (hypothetical)
A $5 cost per install on brand terms looks like the best deal in the account. A holdout suggests the true cost is $12.50, and moving part of that budget buys 25% more incremental installs.
$5.00 Reported brand cost per install (hypothetical)
When one ad takes most of the budget, broad targeting has little to work with. More distinct concepts take this hypothetical account from $133 to about $106 per paid subscriber.
$40 to $32 Cost per trial (hypothetical)
Google is scaling ads in AI Mode to ten more countries and adding multiturn ads in the US. What controls you have, what you lack, and how to measure what you cannot see.
Ad slots, AI answers and map placements are arriving inside existing campaigns or under new controls. A budget structure that funds learning without putting core performance at risk.
Three platforms changed how results are counted or delivered this year. A payback-based method for setting CPA and ROAS targets that does not depend on last quarter's reported numbers.
No. Anyone who does is guessing. We can commit to how we’ll test, how we’ll measure and how quickly you’ll know whether something is working.
You do. We work inside your accounts, so the history, audiences and reporting stay with you.
Not necessarily. Sometimes one channel is the right place to start. The audit shows where the next dollar is most likely to earn its keep.
Read access to your ad accounts and attribution tools, your revenue data, and someone who can make decisions about budget.
They show our method using hypothetical numbers. We don’t present them as client results, because they aren’t.
Tell us what you’re spending, where, and what’s bothering you about the results. We’ll tell you what we’d look at first.