GrowthEngine – 5X ROAS Through AI-Driven Ad Optimization
How we built a unified marketing analytics platform that increased return on ad spend by 400% across all channels.
5X
Average ROAS Achieved
400%
Increase in Ad Efficiency
40+
Client Campaigns Managed
$2.3M
Ad Spend Optimized Monthly
The Challenge
BrandBoost was managing ad campaigns across Meta, Google, and LinkedIn for 40+ clients but lacked a unified view of performance. Campaign optimization was manual, leading to wasted ad spend and inconsistent ROAS across channels.
Our Solution
We developed GrowthEngine — a centralized marketing analytics platform that aggregates data from all ad platforms, uses predictive ML models to forecast campaign performance, and provides automated budget reallocation recommendations based on real-time ROAS data.
The Agency Challenge
BrandBoost Agency manages digital advertising for 40+ clients across diverse industries — from D2C fashion brands to B2B SaaS companies. Their team of 12 media buyers was manually switching between Meta Ads Manager, Google Ads, and LinkedIn Campaign Manager dozens of times daily, copying data into spreadsheets to create unified reports. Campaign optimization was reactive rather than proactive, with budget adjustments happening weekly instead of in real-time. The result: inconsistent ROAS across clients, missed optimization opportunities, and account managers spending 60% of their time on reporting instead of strategy.
Building the Unified Data Layer
The foundation of GrowthEngine is its unified data layer. We built API integrations with Meta Ads (supporting Campaigns, Ad Sets, and Ads level data), Google Ads (Search, Display, Shopping, and YouTube), and LinkedIn Campaign Manager. Data is pulled every 15 minutes and normalized into a consistent schema in BigQuery. The normalization layer handles the significant differences in how each platform defines metrics — for example, 'conversions' means different things on each platform. We created a universal attribution model that provides consistent, comparable metrics regardless of the source platform.
The Predictive Engine
GrowthEngine's ML models are trained on 18 months of historical campaign data across all 40+ client accounts. The system predicts three key metrics: (1) Expected ROAS for the next 7 days given current budget allocation, (2) Optimal budget distribution across campaigns to maximize overall ROAS, (3) Creative fatigue detection — predicting when ad performance will decline before it actually does. The models are retrained weekly on fresh data, maintaining prediction accuracy above 87%. The automated budget reallocation engine shifts spend between campaigns based on these predictions, making micro-adjustments that a human media buyer simply couldn't execute at scale.
Transformative Results
Within the first quarter of deployment, GrowthEngine delivered transformative results for BrandBoost and their clients. Average ROAS across all client accounts increased from 1.2X to 5X. Client churn dropped to zero as every account saw measurable performance improvements. The media buying team reclaimed 60% of their time previously spent on reporting, redirecting it to strategy and creative development. BrandBoost's monthly managed ad spend grew from $800K to $2.3M as existing clients increased budgets and new clients were attracted by the proven results. The platform has since been white-labeled and offered to BrandBoost's clients as a value-added service.
Project Timeline
Platform Audit & API Integration
Mapped data schemas across Meta Ads, Google Ads, and LinkedIn Campaign Manager APIs. Designed the unified data model that normalizes metrics across platforms for apples-to-apples comparison.
Dashboard & Analytics Engine
Built the React dashboard with real-time data visualization using D3.js. Implemented the data pipeline that pulls from all ad platforms every 15 minutes and processes metrics in BigQuery.
Predictive ML Models
Trained Scikit-learn models on 18 months of historical campaign data to predict ROAS, CPA, and conversion rates. Built the automated budget reallocation algorithm that shifts spend toward high-performing campaigns in real-time.
Client Onboarding & Launch
Migrated 40+ client accounts to the platform, trained BrandBoost's team, and deployed the automated optimization rules. Monitored performance for 2 weeks to validate recommendations before enabling full automation.
Technology Stack
“GrowthEngine gave us superpowers. We can now predict campaign performance before spending a single dollar, and our clients are seeing record-breaking returns.”
Sneha Kapoor
CEO, BrandBoost Agency
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