Most Google Ads Budgets Leak Because of Geography — Here’s How I Fixed It Using Real User Location Data
Updated: Mar 2
Most Google Ads accounts are optimized around keywords, bids, and creatives.
Almost none are optimized around where conversions actually happen.
That’s a mistake — especially for local and service-based businesses.
In this case study, I’ll show how analyzing actual user ZIP locations (not just targeting radius) revealed a hidden demand zone that was responsible for the majority of efficient conversions — and how restructuring geo bidding around that insight dramatically improved performance.
If you’d like help optimizing, your own Google Ads account, you can learn more about how I work here.
The Hidden Problem with Flat Radius Targeting
Most local Google Ads campaigns use a simple approach:
Pick a radius (usually 10–15 miles)
Apply one bid strategy across the entire area
Let Google “optimize”
On paper, this looks reasonable.
In reality, demand is not evenly distributed.
Some distance zones generate high-intent leads efficiently.Others quietly burn budget with little return.
When everything is treated equally, high-efficiency areas subsidize low-efficiency ones — and CPA slowly creeps up.
What the Data Actually Showed
Instead of looking at targeting radius, I analyzed real user locations by distance ring:
0–3 miles
3–5 miles
5–7 miles
7–9 miles
9–12 miles
12–15 miles
15–20+ miles
Then I compared:
Cost per acquisition (CPA)
Total conversions
Here’s what the actual performance looked like:
Key findings:
9–12 miles produced the highest conversion volume
5–7 miles delivered the lowest CPA
Inner rings (0–5 miles) underperformed
Outer rings (12+ miles) showed weak efficiency
The true core demand zone was 5–12 miles from the clinic
This was surprising.
Most marketers assume the strongest demand sits closest to the business.
It didn’t.
The most profitable users were consistently coming from mid-range distances.
Why This Happens (and Why Google Doesn’t Tell You)
User behavior isn’t driven by proximity alone.
People are influenced by:
commuting patterns
residential density
competitive saturation near the clinic
perceived travel friction
search intent maturity
Google Ads doesn’t surface this clearly by default.
If you don’t explicitly analyze distance-based performance using user ZIP data, this insight stays invisible.
The Fix: Tiered Geo Bidding Instead of Flat Radius
Targeting
Once the efficiency zones were identified, I restructured bidding around real performance:
Strategy implemented:
Increased bids in 5–12 mile range (core efficiency zone)
Reduced bids in 3–5 mile range
Aggressively downweighted 12+ mile zones
Shifted budget toward high-density conversion rings
Instead of treating geography as a circle, it became a performance-weighted system.
The Result
Without changing creatives or keywords:
Budget moved toward zones that actually convert
CPA leakage was reduced
Conversion density increased
Spend became aligned with real demand, not assumptions
This is what optimization looks like when you treat Google Ads as an economic system — not just a keyword platform.
Who This Approach Is For
This framework works especially well for:
Local service businesses
Clinics, contractors, home services
Advertisers spending $3k+/month
Markets where geography affects intent
If your account uses flat radius targeting, you are almost certainly overpaying for low-efficiency zones.
You can see a related Home Services case study here with real performance breakdown.
Final Thought
Most Google Ads optimizations are surface-level.
Real performance gains come from understanding where demand lives — and reallocating spend accordingly.
Keywords tell you what people search.
Geography tells you who converts.
If you’d like a location efficiency audit for your account, you can contact me here.
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