Case Study
Maximizing ROAS with AI-Driven Bid Strategies in Google Ads
Problem Statement
A mid-sized D2C skincare brand was spending heavily on Google Ads but experiencing inconsistent returns. Manual bidding strategies led to wasted budget, high CPA (Cost Per Acquisition), and limited visibility into real-time performance adjustments. The marketing team wanted to improve ad efficiency by adopting AI-driven bidding strategies that optimize campaigns based on user behavior, intent signals, and conversion likelihood.
Challenge
High CPA & Low ROAS: Campaigns struggled to maintain profitability despite increased ad spend.
Limited Automation: Manual bid adjustments couldn’t react fast enough to changes in competition or user intent.
Ineffective Keyword Strategy: Broad keywords generated traffic but low conversions.
Lack of Signal Integration: Audience data wasn’t being used effectively to inform bid decisions.
Solution Provided
The brand transitioned to Google’s Smart Bidding strategies, combining Target ROAS (tROAS) and Performance Max campaigns, powered by AI and machine learning. Key optimizations included:
Conversion Tracking Enhancement: Implemented enhanced conversion tracking via Google Tag Manager to feed better data into machine learning.
Audience Signal Integration: Leveraged first-party data (email lists, site visitors) and GA4 predictive audiences.
Automated Bid Strategy: Switched from manual CPC to Target ROAS bidding on search and shopping campaigns.
Development Steps
Baseline Performance Analysis
Assessed pre-optimization ROAS (1.7), average CPA, and conversion data to set benchmarks.
Conversion Tracking Setup
Set up enhanced conversions, server-side tagging, and micro-conversion tracking for deeper attribution.
Campaign Restructure
Grouped products into high-margin and low-margin segments to tailor bid strategies based on profitability.
AI-Driven Bidding Activation
Implemented Target ROAS bidding with an initial target of 300% and later refined based on performance.
PMax Deployment & Asset Grouping
Launched Performance Max campaigns with optimized product feeds, ad assets, and audience signals.
Monitoring & Iteration
Weekly A/B tests on creatives, location-based bid adjustments, and dynamic remarketing strategy refinement.
Results
ROAS Increased by 85%
Overall ROAS jumped from 1.7 to 3.15 within 60 days of strategy implementation.
CPA Reduced by 40%
Smarter bidding led to a significant drop in acquisition cost, especially for high-converting audiences.
Conversion Volume Increased by 60%
The improved campaign efficiency attracted more qualified traffic and purchases.
Ad Spend Efficiency Improved
The same budget delivered nearly double the revenue with AI-optimized campaigns.
Time Saved on Management
Campaign automation reduced manual effort by over 50%, allowing the team to focus on creative testing and analytics.