Local PMax
Augurian paid media | a local Performance max success story$1,167 in Ad Spend. 550,000 Map-Pack Impressions.
We tested a local-only Performance Max campaign for two clients with physical locations. By limiting what Google was allowed to optimize for, we turned PMax into a map-pack visibility engine.
Ready to talk? Request a Local PMax Audit
WHY IT MATTERsYour Customers Are Searching Nearby. Your PMax Budget Is Somewhere Else.
Performance Max is built to find conversions anywhere Google can show an ad:
YouTube
Display
Gmail
Discover
Search & Maps
For a business with locations, most of those placements don't Get people through the door.
"The biggest unlock wasn't launching PMax.
It was narrowing what PMax was allowed to optimize toward."
the experimentOne Rule: Only Local Actions Count.
We ran a local-only PMax campaign for two separate clients who’s businesses are entirely location dependent; where local visibility is the name of the game.
Here are the three decisions that shaped our experiment.
Local-only
structure
Separate campaigns for primary and specialty services, built around nearby intent instead of general traffic.
Constrained
Conversion Goals
Store visits and contacts were the only primary conversions. Everything else was secondary, so the algorithm couldn't chase soft wins.
Validated
Measurement
We combined PMax reporting with Google Business Profile data pulled through the API, then checked it against analytics.
Is Your Business Ready for Local PMax? Get The Readiness Scorecard >
the resultsVisibility at Scale. Actions at Pennies.
+550K
map-pack impressions
+600%
Google Business Profile impressions
+300%
website clicks from the profile
$0.49
per phone call
Also: 4.4K map-pack interactions, +50% direction requests, +17% calls, $0.05 per interaction and $0.17 per direction request.
Room For ImprovementWhat we’d do differently
The Results Were Strong. Our Measurement Could Be Better.
We'd rather tell you what we couldn't prove than hand you a number you can't trust.
Three Rules We’d Follow Again
Constrain the signal. Local-only primary conversions keep the campaign focused on real-world actions.
-
Some calls and direction requests would have come through organic Maps listings anyway. We didn't set a clean baseline before launch.
-
Most of the comparison data isn't available in the Google Ads interface. We pulled it through the Business Profile API.
-
We know what worked. Google doesn't let anyone see exactly why.
Baseline before launch. Benchmark Business Profile performance and organic contribution before you start.
Report conservatively. Pair big results with cautious estimates and a clear way to repeat the test.
UNIVERSAL FINDINGSFocus On Fixing This First
These four signals were evaluated on every page in the index. They aren’t included in the scored 8 because virtually no chain passes them. That’s precisely why they matter, and why the brands that fix them first will pull away from the field.
0% - LOCAL SCHEMA MARKUP
Schema markup is structured data embedded in a page’s code that tells AI systems and search engines exactly what a page is about. Things like, the business name, address, phone number, hours, and more. But, this needs to be in a format machines can read without guessing. Without it, an AI assistant has to infer these details from the visible text, which introduces ambiguity and errors. With it, your store becomes an unambiguous entity that can be cited with confidence. Not a single chain in this index had it implemented on their location pages.
0% - FRESH REVIEWS ON PAGE
Reviews aren’t just social proof for humans — they’re freshness signals for AI systems. A page with recent, dated customer reviews tells an AI that this location is active, open, and worth recommending. A static page with no reviews (or reviews buried in a third-party widget) gives an AI no signal that anything has happened at this store in the last year. Zero chains in the index surface fresh reviews directly on their location pages.
0% - DETECTABLE UPDATE DATE
AI systems weight recency. A page with a visible or metadata-level “last updated” date tells crawlers that the information is current. A page with no date could be from 2019 and an AI has no way to know. Given that store hours, services, and local offerings change regularly, the absence of any update signal is a trust gap that costs you citations. No chain in the index publishes a detectable update date on their location pages.
2% - REAL LOCATION PHOTOS
A photo of the actual storefront, interior, or local team does two things: it signals to AI systems that this page is specific to a real place, and it gives human visitors a reason to trust what they’re reading. Stock photography and generic brand imagery don’t count, they’re the visual equivalent of templated copy. Only one chain in the index uses real, location-specific photography on their store pages.
These aren’t advanced optimizations. They’re basics that nearly every grocery chain in America has left undone.
The bar is low. The opportunity is real.
FULL DATASETGet the Complete
Scoring Spreadsheet.
This summary is free. The full dataset includes every scored question, the reasoning behind each answer, and raw scores for all 24 brands across all 8 criteria.
Free downloadThe Store Page Index
Full Dataset
Enter your work email and we will send the spreadsheet directly to your inbox.
What you get:
All 24 brands scored across 8 criteria
Per-question breakdown with reasoning
Universal findings data
Category-level scores for benchmarking
FREE TOOLHow Does your store location
page score?
Paste in two location page URLs from your site. We will run them through the same scoring system used to build this index and send back your score, your grade, and a ranked list of what to fix first.
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