The business owner came with a clear diagnosis: "My spend has gotten out of control compared to sales. My campaigns are running at about 40% efficiency."
They weren't wrong. Grab Bar Specialists—a safety equipment distributor serving nursing homes, hospitals, contractors, and home renovation customers across the USA—had a $30K monthly ad budget producing underwhelming returns. The task was straightforward: increase revenue without raising spending.
But before optimizing anything, I discovered a deeper problem hiding in plain sight.
Before making any campaign changes, I found incorrect conversion tracking across the sales channels. This matters more than most realize: you can't optimize what you can't measure. Every bidding decision, every budget allocation, every performance assessment was based on flawed data.
Correct conversion tracking isn't a nice-to-have. It's the foundation everything else builds on.
After fixing tracking and establishing a reliable baseline, I worked through each campaign type methodically.
Search campaigns: I fine-tuned ad groups to target only successful products and segmented brand keywords into a separate campaign. This stopped brand and non-brand traffic from competing for the same budget and muddying performance signals.
Remarketing campaigns: I discovered the display remarketing was serving ads beyond just website visitors—unnecessary spend on cold audiences. I tightened targeting to reach only people who had actually visited the site.
Shopping campaigns: These received the deepest attention. I optimized product titles, descriptions, and images to improve feed quality. Then I refined bidding—starting with manual control to understand the data, then shifting to Target ROAS once I had confidence in the numbers.
The progression from manual to automated bidding isn't about laziness. It's about trust. You earn the right to use automation by first understanding what the data is telling you.
Seven months of systematic optimization delivered:
The business owner's intuition was validated. The account was indeed running at less than half its potential. But intuition alone couldn't fix it—structured diagnosis and systematic execution did.
This case illustrates a pattern I see repeatedly: business owners often know something is wrong before they know exactly what.
The owner correctly identified the symptom (40% efficiency). But the root cause—broken conversion tracking—was invisible until someone looked for it. Once the measurement problem was solved, the optimization path became clear.
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