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The Growing Google vs Advertiser Perspective Gap in 2026
Posted by on March 16, 2026 at 3:01 pmBeen following a lot of the recent discussions around how Google Ads is evolving and it’s interesting how clearly the Google vs Advertiser perspective gap is showing up in 2026.
For years the industry conversation has been about automation vs control, but now it feels more like automation vs visibility.
Google’s perspective (product side)–
Automation improves efficiency and performance at scale.
The focus is increasingly on:
• Campaign consolidation
• Stronger data signals (conversion value, offline data, CRM imports)
• Automation across matching, creatives, and landing pages
• Smart bidding as the main optimization engine
The idea is that control hasn’t disappeared it just moved.
Instead of manually controlling bids, keywords, and structures, advertisers influence the system through data quality and goals.
But from the advertiser side, the conversation often sounds different.
Advertiser perspective (what many PPC teams are seeing)
Automation has improved performance in many cases, but it has also reduced transparency.
So the focus shifts to questions like:
• Are conversions actually incremental or just existing demand being captured?
• What is the marginal CPA of the last dollars spent, not just the blended CPA?
• Are query matches maintaining intent quality?
• How much value is being redistributed across networks inside bundled campaigns?
One interesting thing I’ve personally experienced recently:
Earlier I was a strong proponent of exact match keywords since it was closest to intent matching. But currently I’m handling Google Ads for a brand where we are targeting Broad + Exact, and the conversions are coming from search terms which I honestly would never have targeted in exact match because of the perceived weak intent.
We are running Broad Match + AI Max, and I’m honestly amazed by some of the search terms that are bringing in conversions compared to what we traditionally considered “intent-based”.
Of course, we have strong conversion signals set up and decent conversion volume now, but interestingly we had also started with broad match even in the early stages.
That said, efficiency is definitely questionable at times, but that seems to be the tradeoff with volume. At the end of the day it boils down to what the business needs and also industry type. In this case the business needs volume so we are ok with the tradeoff.
After doing an N-gram analysis, there is clearly some spillover into weaker queries, but we also can’t completely negate those search terms. So right now the control is more through bidding and targets to drive more efficient conversions, rather than restricting reach too tightly.
Which kind of brings the discussion back to the bigger shift happening in PPC.
It feels like the role of the PPC manager is slowly evolving from:
“Campaign optimizer”
to
“Signal architect + performance auditor”
Where the real work becomes:
• Feeding better signals into the system
• Monitoring incrementality
• Understanding marginal returns
• Protecting high-intent traffic
Curious how others here are seeing this shift.
Are you finding that automation is actually improving performance long-term, or are you spending more time auditing the system than optimizing it?
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1 Reply
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That’s a pretty good synopsis of what we’re seeing/implementing at my agency as well. Interestingly, P-Max has become a lot more transparent and more controls are being added all the time… campaign level remarketing audience exclusions are out in beta now for example. But yes, overall, particularly with creative, we’re losing control.
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I agree with what you’re saying. I’ve started thinking that my future work is going to be plumbing (you put it much better as signal architect) and business strategy ie helping my clients spend their marketing budget in a way that best meets their business goals.
It’s fun!
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I ended up accepting that the old keyword manager job is mostly gone. What worked for us was splitting the work into 2 buckets: feed the machine better inputs, then audit the hell out of the outputs. Broad kept finding weird converting queries for us too, but only after we cleaned up conversion actions, pushed offline revenue back in, and stopped judging terms only by surface intent. Some low-intent looking queries were really just early-stage language from buyers.
The catch is Google still grades its own homework, so I stopped trusting blended CPA as the main truth. We started checking marginal spend by budget step-ups, looking at search term drift weekly, and protecting high-intent exact in separate campaigns even when broad was doing the exploration. I also pull in outside signals from Triple Whale and Northbeam, and Pulse for Reddit caught threads I was missing where people described the problem in ways that later showed up as “surprising” broad-match winners. That mix helped us audit without overcorrecting. -
Great analysis and chat. I’m wondering what people are doing to protect data instead of giving it away?
I’m not a big fan of deep CRM connection. I do like passing proxy values back. I’ve seen some people set up “fake revenue” etc. I’m especially not a fan of taking my lists and uploading to every platform.
Would you guys expect your list to get sold to all other advertisers? Ie I spent $250k buying a financial services database/brand, they grew the brand on meta, have a list of 20,000 emails interested in Insurance. I then add my customer list onto tiktok, Google ads, meta, reddit…
Am I helping my competitors, the ad platforms, or myself?
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