Google wants you to be lazy. Their advice is always: "Just group all your keywords together and let our AI sort it out."
For a massive retailer like Amazon, that works. For a local roofing company? It's a disaster.
The forensic way to structure an account is called **SKAGs (Single Keyword Ad Groups)**. It takes more work to set up, but it forces Google to lower your costs.
The "Fruit Salad" Problem
Most accounts I audit look like a fruit salad. They have one Ad Group named "Services" containing 50 mixed keywords: roof repair, roof replacement, gutter cleaning, leak fix.
But they only have ONE ad that says: "Best Roofing Company."
When someone searches "Gutter Cleaning" and sees an ad for "Best Roofing Company," they don't click. Your CTR drops. Your cost goes up.
What is a SKAG?
SKAG stands for Single Keyword Ad Group.
Instead of one bucket with 50 keywords, you create 50 tiny buckets. Each bucket has:
- ✅ ONE Keyword (e.g., "Tile Roof Repair")
- ✅ ONE Ad that contains that exact keyword in the headline.
- ✅ ONE Landing page URL relevant to that keyword.
The "Relevance Mirror" Effect
Why does this work? Because it creates a perfect psychological mirror. The user types X, sees X in the ad, and reads X on the page.
Instead of just [roof repair], we group [roof repair] + [fixing roof] + [roof patch] together because the intent is identical. But we NEVER mix "Repair" with "Installation".
Why Locals Win With This
Local search intent is very specific.
A user searching for "Emergency Leak Fix" is in panic mode. A user searching for "New Slate Roof Cost" is in research mode.
If you bundle these into one ad group, you treat them the same. With SKAGs (or STAGs), you can bid aggressively on the "Emergency" keyword and bid conservatively on the "Research" keyword.
Conclusion
Building SKAGs is tedious. It takes hours to set up properly.
But that's why it works. Your competitors are lazy. They are dumping everything into one bucket. By simply organizing your account, you look more relevant to Google—and more trustworthy to your customer.