Scaling Google Ads with AI: A Practical Guide

When people talk about AI in advertising, they usually mean creative generation or audience targeting. But the real leverage comes from systematic automation of the tedious parts.

The Feed Rewriting Problem

Most ecommerce brands have product feeds that look like this:

• Generic titles copied from the manufacturer
• Descriptions that don't match search intent
• Missing attributes that could improve ad relevance

Manually rewriting thousands of products isn't feasible. But AI can process your entire catalog in hours, not months.

Our Approach

We use a combination of Claude and custom scripts to:

1. Analyze top-performing products - What makes your winners different?
2. Extract patterns - Title structures, keyword density, attribute usage
3. Generate variations - Multiple angles for A/B testing
4. Validate quality - Automated checks before pushing to feeds

Multi-Angle Shopping Testing

Instead of running one version of your feed, we create parallel experiments:

• Benefit-focused titles: "Lightweight Running Shoes - Cloud-Like Comfort"
• Spec-focused titles: "Running Shoes - 8oz, 10mm Drop, Mesh Upper"
• Problem-focused titles: "Running Shoes for Knee Pain Relief"

Each angle attracts different search intent. AI helps us generate these systematically.

Search Campaign Automation

For search campaigns, we use AI to:

• Generate ad copy variations that match landing page content
• Create responsive search ad combinations at scale
• Identify negative keyword opportunities from search term reports

The key is treating AI as a production system, not a creative toy.

Results

With this approach, our clients typically see:

• 30-50% improvement in click-through rates
• 20-40% reduction in cost per acquisition
• 3x faster campaign launch times

The real competitive advantage isn't having AI—it's having systematic processes that use AI effectively.