Paid Media · Service 12
Installs that
become customers.
Mobile app acquisition done with serious post-install economics. Apple Search Ads, Google App Campaigns, MMP integration, SKAN modelling, and the post-iOS 14 attribution rigour app marketing actually requires.
Most app marketing optimises for installs. The wrong metric. Installs are the cost — not the outcome. The right metric is day-7 retention × LTV ÷ blended CAC. The brands winning mobile UA in 2026 measure post-install economics at the cohort level, optimise creative against retention curves and reject the install-volume games iOS 14 tried to teach the industry.
Where post-install
economics decide everything.
The mobile UA industry built itself on cost-per-install metrics. iOS 14 and SKAN broke deterministic install attribution forever — and the smart industry response was to shift focus to post-install economics: day-7 retention, day-30 ARPU, predicted LTV, blended CAC across cohorts. Most agencies didn't shift. They're still optimising for the cheapest installs they can buy, regardless of whether those users open the app twice.
We optimise mobile programmes for cohort-level commercial outcomes, not install volumes. That requires MMP integration (Adjust, AppsFlyer, Singular), SKAN configuration sophistication, retention curve modelling, and LTV-weighted creative testing. The campaigns we run buy fewer installs at higher costs — and produce dramatically better business outcomes.
What's included.
Every App Install Campaigns engagement covers four pillars. Each pillar is a deep dive — not a checklist tick.
Channel Mix & Attribution
Apple Search Ads (highest-intent installs), Google App Campaigns (volume + retargeting), Meta App Install (creative-led), TikTok (younger demographics). The right mix depends on app category, target audience, and post-install economics.
MMP Integration
Adjust, AppsFlyer, Singular, Branch — the mobile measurement partner setup that connects ad spend to in-app behaviour. SKAN configuration, post-install event taxonomy, attribution window calibration, deduplication across networks.
LTV & Cohort Analysis
Predicted LTV models from early in-app behaviour, cohort retention curves, ARPU forecasting by source, blended CAC analysis. The economic intelligence that lets you bid against actual business value rather than blind install volume.
Creative Production for App
Vertical video for Meta and TikTok, App Store screenshots and previews, Apple Search Ads creative sets, Google App Campaign asset libraries. Creative tested at scale with retention-weighted kill decisions.
How an App Install Campaigns engagement unfolds.
Post-install economics review
Two-week diagnostic of current cohort economics. Day-7 retention by source, day-30 ARPU, predicted LTV by channel, blended CAC, MMP attribution accuracy. Most accounts have either retention or LTV math fundamentally wrong.
MMP & SKAN setup
Proper MMP integration, SKAN 4 configuration, post-install event taxonomy, conversion value mapping. The measurement layer that makes everything else possible.
LTV-weighted UA
Channel mix optimised against post-install LTV, creative testing weighted by retention not just CTR, bid strategies tied to predicted user value. The execution layer where most agencies still run install-volume strategy from 2018.
Cohort intelligence
Monthly cohort reviews, quarterly LTV model recalibration, semi-annual channel mix review. Mobile UA compounds with cohort-level intelligence — and stagnates without it.
Where cheap installs
destroy unit economics.
A mobile gaming brand drives 100,000 installs per month at €1.20 cost-per-install via volume-driven Meta campaigns. Day-7 retention: 8%. Day-30 ARPU: €0.40. The unit economics are structurally negative — they're losing money on every install they buy. Same brand shifts spend toward Apple Search Ads at €4.80 cost-per-install. Day-7 retention: 32%. Day-30 ARPU: €4.20. The day-30 ARPU:CPI ratio improved from 0.33 to 0.88 — still short of covering acquisition by day 30, with payback carried by the retention curve beyond it. The cheap installs were where the economics leaked.
Most agencies optimise for the wrong metric because the wrong metric is easier to report. Cost-per-install is what marketing teams show executives. Cohort LTV ÷ blended CAC is what determines whether the business actually works. The agencies still selling cost-per-install optimisation are selling a discipline that's been obsolete since 2020.
A B2B SaaS company's mobile app was buying installs at €0.80 each — and burning money. Cohort-driven UA strategy made the unit economics work.
A B2B SaaS platform's mobile companion app was running a €40K monthly UA programme buying installs at €0.80 each — but day-30 ARPU was €0.18 and day-7 retention was below 5%. We restructured the programme around Apple Search Ads with high-intent keyword targeting, integrated their MMP properly with SKAN 4, and shifted creative testing toward retention-weighted decisions rather than install volume. Six months later: cost-per-install rose to €3.20, but day-30 ARPU rose to €13.40 — a day-30 ARPU-to-CPI ratio of 4.2, against 0.2 before the shift.
For two years our mobile UA looked like it was working — installs were cheap and growing. The CFO asked one question and we couldn't answer it: are these installs worth more than they cost? Revolutionize rebuilt the programme around that question. We bought fewer, more expensive installs — and turned mobile from a cost centre into a profitable channel.
Questions worth asking.
Pairs beautifully with.
App Install Campaigns is most powerful when followed by these complementary services.
Google Ads
Google App Campaigns run through the Google Ads ecosystem with shared conversion infrastructure. We typically integrate ACi management with broader Google Ads programmes for compounded measurement.
Explore →Meta Ads
Meta App Install Ads share creative pipelines with broader Meta engagements. For B2C apps, Meta typically forms 30-50% of total UA spend alongside Apple Search Ads.
Explore →TikTok Ads
TikTok For App Marketing has matured significantly. For consumer apps targeting younger demographics, TikTok increasingly delivers better post-install retention than Meta on equivalent spend.
Explore →Make UA economics work
Ready to optimise
for what matters?
Book a 30-minute scoping call. We'll review your post-install economics, audit your MMP and SKAN setup, and quote a possible engagement that targets actual unit economics rather than vanity install volumes.