AI Performance Acquisition

AI Media Buying: Maximise ROAS Across Every Acquisition Channel Simultaneously

Running paid acquisition across Google, Meta, LinkedIn, and TikTok simultaneously — while optimising budget allocation in real time — is beyond human capacity. We deploy AI media buying infrastructure that does this automatically, 24 hours a day.

2.8×

Average ROAS improvement across all channels

−38%

Wasted spend eliminated via AI allocation

24/7

Continuous bid and budget optimisation

Trusted by growth teams at

Definition

What is AI media buying?

AI media buying is the use of machine learning algorithms and automated bidding systems to manage cross-platform advertising spend in real time — allocating budget to the highest-performing channels, campaigns, and creative based on continuous performance data. Unlike manual media buying (which optimises weekly or monthly), AI media buying systems adjust bid strategies, budget distribution, and audience targeting in real time based on conversion probability, ROAS trends, and competitive dynamics. Aroluxa implements AI media buying across Google, Meta, LinkedIn, TikTok, and programmatic channels using tools including Triple Whale, Northbeam, and custom n8n automation layers.

AI media buyingprogrammatic advertisingcross-channel attributionautomated biddingbudget optimisationROAS maximisationTriple WhaleNorthbeammulti-channelGoogleMetaLinkedIn AdsTikTok Adsreal-time bidding

The Problem

Why most companies struggle without AI

The same patterns limit every revenue team. Here's what we fix first.

01

Manual budget management can't keep pace with real-time performance shifts

Ad performance shifts hourly. Manual weekly or monthly budget reviews mean you're always optimising based on stale data — scaling losing campaigns and starving winners.

02

Cross-channel attribution is broken for most advertisers

Google claims credit. Meta claims credit. LinkedIn claims credit. The real customer journey touches all three. Without unified cross-platform attribution, you can't know where budget actually produces revenue.

03

Your media mix is based on gut feel, not data

Most advertisers stick with channels that feel comfortable rather than channels where their ICP is most responsive. AI media buying lets performance data determine media mix — not familiarity.

04

Channel-specific management creates strategic fragmentation

Separate agencies or in-house managers for Google, Meta, and LinkedIn optimise their channel in isolation. A winning strategy sees all channels as a unified system — awareness, consideration, and conversion working together.

Full System Scope

Everything we build, end to end

Every component is custom-built for your stack, ICP, and business model — not templated.

Cross-Platform Management

  • Google Ads automated bidding
  • Meta Advantage+ integration
  • LinkedIn Campaign Manager
  • TikTok Ads optimisation

AI Budget Allocation

  • Real-time cross-channel budget shifting
  • ROAS-weighted allocation model
  • Dayparting and seasonal automation
  • Budget pacing algorithms

Attribution Intelligence

  • Multi-touch attribution model
  • Data-driven attribution setup
  • Cross-platform data warehouse
  • Incrementality testing

Reporting Infrastructure

  • Unified performance dashboard
  • Channel ROAS comparison
  • Budget vs. pipeline reports
  • Weekly strategy recommendations

Deployment Process

How we build and launch your system

01

Week 1

Channel Audit

Audit all active channels: account structures, attribution models, spend efficiency, and cross-channel overlap analysis.

02

Week 2

Unified Strategy Design

Cross-channel funnel mapping, AI bidding strategy, attribution model design, and reporting infrastructure blueprint.

03

Week 2–5

Integration & Automation

Attribution stack integrated, AI bidding rules deployed, budget automation activated, unified dashboard built.

04

Ongoing

Optimise & Compound

AI systems run continuously. Human strategists review weekly, adjusting strategy based on cross-channel attribution data.

Live and producing results in 6 weeks.

Book a strategy call

Side-by-Side

AI Media Buying vs. Manual Cross-Channel Management

Factor
AI Media Buying
Manual Management
Budget optimisation
Real-time, automated
Weekly or monthly, manual
Attribution
Unified cross-platform model
Platform-siloed, conflicting
Media mix decisions
Data-driven, continuous
Experience-based, quarterly
Optimisation speed
Hours
Weeks
Scale capacity
Unlimited channels simultaneously
Limited by human bandwidth

Built on

Triple WhaleNorthbeamGoogle AdsMeta AdsLinkedIn AdsTikTok AdsGoogle Analytics 4Looker Studion8nBigQuery

Results

From the field

B2C SaaSConsumer Software Brand

2.8×

blended ROAS improvement in 90 days

Cross-PlatformBudget AutomationMulti-Touch AttributionROAS Optimisation

We unified 4 previously siloed channel teams under a single AI media buying system with cross-platform attribution. Real-time budget shifting moved $18K/month from underperforming Meta campaigns to LinkedIn sequences that showed 4× better attributed pipeline. Blended ROAS improved from 1.9× to 5.3× in 90 days.

Read full case study

Investment

Build your AI Media Buying system

Fixed-scope builds. Clear deliverables. No hourly billing surprises.

AI Media Buying Starter

$3,500

per month + ad spend

  • 2 channels managed
  • Cross-channel reporting
  • Monthly allocation review
  • Attribution model setup
Get Started
Most Popular

AI Media Buying Growth

$6,500

per month + ad spend

  • Up to 4 channels
  • Automated budget shifting
  • Multi-touch attribution
  • Unified performance dashboard
  • Weekly optimisation
Get Started

AI Media Buying Enterprise

$12,000

per month + ad spend

  • Unlimited channels
  • Real-time AI allocation
  • Custom attribution model
  • Data warehouse setup
  • Dedicated media buying strategist
Book a Call

Need a custom enterprise scope? Talk to us

FAQ

Questions, answered.

Everything you need to know about how we build AI Media Buying systems.

Still have questions? Talk to us

Core channels: Google Ads (Search, PMax, Display), Meta (Facebook + Instagram), LinkedIn Campaign Manager, and TikTok Ads. Additional channels — Pinterest, YouTube, programmatic display, Reddit — available on Enterprise plans.

We build a unified data pipeline that pulls conversion data from all channels into a single attribution model — typically using Triple Whale or Northbeam for ecommerce, or custom data warehousing for B2B. This shows the actual multi-touch path from first ad impression to closed deal, attributing credit across all channels using data-driven or position-based models.

We configure automation rules with human-defined guardrails — minimum and maximum budget thresholds, ROAS floors, and manual approval requirements for decisions above defined thresholds. The AI operates autonomously within these parameters; humans review and approve strategic shifts.

AI media buying infrastructure is most valuable at $15,000+ total monthly ad spend across channels. Below this level, manual optimisation is equally effective. Our Starter plan covers clients at $5,000+/month who want unified reporting and semi-automated allocation.

Each platform's automatic bidding optimises for that platform's metrics — which are not the same as your business metrics. Cross-channel AI media buying looks across all platforms simultaneously and shifts budget to wherever your dollar produces the most pipeline — something no individual platform's algorithm can do.

Initial implementation — attribution stack, reporting dashboard, and automation rules — typically takes 3–4 weeks. Full AI media buying capability (real-time allocation, incrementality testing) is live by week 5–6.

Ready to automate?

Let's build your AI Media Buying system

Book a free 30-minute strategy call. Walk away with a system architecture, deployment timeline, and cost estimate. No commitment, no pressure.

Book Intro Call

Free 30-min call · No obligation · System live in 6 weeks