The new reporting view will bring together three things in one place:
- The search term that triggered the ad
- The creative assets the user saw
- The landing page Google sent them to
Google describes it as a unified view of the Search ads journey, designed to give advertisers a clearer picture of AI-driven performance.
It sounds like a relatively simple reporting update.
In practice, it could be one of the more useful AI Max changes Google has made.
The Problem With Automation Has Never Only Been Performance
Google Ads has been moving steadily toward greater automation.
Smart Bidding automated bid decisions.
Performance Max automated inventory and targeting across Google’s channels.
Broad match expanded the way Google interprets intent.
And AI Max takes Search further by combining expanded query matching with automatically generated creative and landing-page selection.
The potential upside is clear.
Google can identify relevant demand that a rigid keyword structure might miss and adapt the ad experience to individual searches.
But the more decisions the platform makes, the harder it can become for advertisers to understand what actually happened.
A campaign might produce a conversion.
But what did the person search?
What message did Google show them?
Where did Google send them?
Until now, getting the full picture has often meant piecing together information from several different reports.
Google’s new AI Max reporting aims to put that journey together.
Search Term → Creative → Landing Page
This is the part of the announcement we find most interesting.
Google says advertisers will be able to see the search term that triggered the ad, the creative assets shown to that user and exactly where they landed on the website in one reporting interface.
That means advertisers should be able to look at an AI Max interaction more like this:
Search: “best waterproof work trousers”
↓
Creative: “Waterproof Workwear Built for the Toughest Conditions”
↓
Landing page: Waterproof Trousers category
That is significantly more useful than simply knowing the search term converted.
Because once you understand the entire journey, you can start asking much better questions.
Was the query relevant?
Did the creative match the intent?
Was the landing page the best possible destination?
Did Google’s AI make the same decision we would have made manually?
Those questions are going to become increasingly important as Search becomes more automated.
Query Quality Becomes Easier To Audit
AI Max can help advertisers reach queries outside the traditional boundaries of their keyword lists.
That can create incremental opportunities.
It can also create poor routing.
Imagine an e-Commerce retailer sells premium running shoes.
Google identifies a search such as: “cheap running trainers under £30”
The campaign may technically consider the query relevant because the retailer sells running shoes.
But commercially, it could be completely wrong.
With clearer reporting, advertisers should have a much better opportunity to identify these situations and decide whether they need:
- Negative keywords
- Brand exclusions
- Search term exclusions
- Campaign restructuring
- Different landing-page controls
- Page exclusions
The challenge with AI-led campaigns isn’t necessarily preventing Google from exploring.
It’s making sure that exploration stays within commercially sensible boundaries.
Landing-Page Selection Matters More Than Most Advertisers Realise
One of the more interesting aspects of AI Max is Google’s ability to decide which page on a website best matches a user’s search.
When it works properly, that can be powerful.
Someone searching: “men’s black waterproof work jacket”
should ideally land on something significantly more relevant than a generic homepage.
But there are plenty of situations where Google’s interpretation could be technically related while still being commercially poor.
For example:
A generic category instead of the most relevant subcategory.
An informational page instead of a transactional page.
A discontinued product.
A low-margin range.
A page with limited stock.
A page that doesn’t align properly with the creative shown.
Seeing the search term, creative and landing page together gives advertisers much more context for evaluating those decisions.
Creative Reporting Gets More Interesting Too
The update shouldn’t only help with query monitoring.
It should also improve how advertisers analyse Search creative.
Dynamic creative has always created an attribution challenge.
You might know that an asset performs well overall, but that doesn’t necessarily tell you why it performs.
Connecting assets back to the searches that triggered them gives advertisers another layer of insight.
For example, you may discover that customers searching around price respond strongly to one message: “Free Delivery Over £50”
while product-specific searches respond better to:
“Shop 500+ Waterproof Workwear Styles”
And searches around reliability may respond to:
“Trusted by Tradespeople Across the UK.”
The bigger opportunity is moving away from asking:
“Which headline performs best?”
towards:
“Which message works best for which type of intent?”
That’s a much more useful question.
This doesn’t make AI Max completely transparent
There is an important distinction here.
Better reporting doesn’t mean advertisers suddenly understand every decision Google’s models make.
We still won’t see the full logic behind every auction-level decision.
Google isn’t opening the algorithm.
What it is doing is giving advertisers better visibility into the outputs.
That’s valuable because those outputs are the things advertisers can actually act on.
We can evaluate:
- The queries Google is finding
- The messages Google is serving
- The pages Google is choosing
- The conversions those combinations generate
That provides much stronger feedback for campaign optimisation.
AI Max Still Needs Guardrails
More transparency doesn’t mean AI Max becomes a campaign you switch on and leave alone.
In our view, the opposite is true.
As Google gives its systems more freedom, advertisers need stronger governance around what those systems are allowed to do.
That means continuing to think carefully about:
- Negative keyword strategy
- Brand controls
- Page exclusions
- Search term monitoring
- Conversion quality
- New vs existing customer performance
- Product profitability
- Landing-page relevance
- Creative messaging
Automation can make millions of decisions faster than a person ever could.
But it still needs to optimise toward the right objective.
If the inputs, constraints or conversion signals are poor, automation can simply make the wrong decisions faster.
AI Brief Is Expanding Too
Google also announced that AI Brief is expanding into more languages.
The closed beta will now support Dutch, French, German, Italian, Japanese, Portuguese and Spanish.
AI Brief allows advertisers to give AI Max additional context using natural language, including information about:
- The business
- The audience
- Key messaging
This is another sign of where Google Search is heading.
Campaign management is gradually shifting from configuring every individual decision toward giving Google’s AI better instructions, data and boundaries.
That doesn’t remove the role of the advertiser.
It changes it.
The Role Of The PPC Manager Is Changing
Ten years ago, a large part of PPC management involved making manual decisions at keyword level.
Adjust bids.
Add keywords.
Pause keywords.
Change match types.
Analyse average position.
That world has already changed considerably.
Increasingly, the role is becoming about guiding automated systems.
That means deciding:
What should the campaign optimise toward?
What demand do we actually want?
Which signals can we trust?
Where should automation be restricted?
Which queries are incremental?
Which customers are valuable?
Which landing pages should Google use?
Which messages should be associated with which intent?
And most importantly:
Is Google’s automation actually helping the business grow?
Better reporting makes those decisions easier.
This Is Why Query Routing Matters
As Search becomes more dynamic, the traditional keyword-to-ad-group model matters less.
The relationship between intent, message and destination matters more.
We think of this as query routing.
A search enters the account.
The first question is whether that query is relevant.
If it is, where should it be routed?
Which campaign?
Which product category?
Which landing page?
Which message?
If it isn’t relevant, should it be excluded?
AI Max can increasingly make those decisions automatically.
The advertiser’s job becomes monitoring whether it’s making them correctly.
That’s why this new reporting could be particularly valuable.
It gives marketers a clearer way of comparing what Google’s AI decided against what the business would actually want to happen.
What Should Advertisers Do Now?
There’s nothing advertisers need to radically change today.
Google says additional details and availability for the new reporting will be shared later this year.
But the announcement is another good reason to start thinking beyond traditional keyword reporting.
For retailers running AI Max, we’d increasingly look at Search performance through three connected dimensions:
1. Intent
What was the customer actually looking for?
2. Message
What did we say to them?
3. Destination
Where did we send them?
When all three align, AI Max has the potential to create a highly relevant Search experience at a scale that would be difficult to build manually.
When they don’t align, performance can deteriorate very quickly.
AI Max Is Becoming Easier To Audit
Google isn’t reversing the direction of travel.
Search is going to become more automated, more dynamic and more AI-led.
The interesting part of this announcement is that Google appears to recognise that advertisers still need visibility into what its systems are doing.
The winning approach won’t be trying to manually control every decision Google’s AI makes.
Nor will it be handing everything over to automation and hoping for the best.
It will sit somewhere between the two.
Give the system room to find opportunities.
Give it strong data and clear guardrails.
Then audit the decisions it makes.
Google’s new AI Max reporting should make that last part considerably easier.
At 360 OM, we’re already building our Search approach around this model — using automation to find incremental demand while continually auditing query routing, landing-page relevance and the quality of the traffic being generated.
As Google’s reporting improves, that process should become even more powerful.
Need a fresh perspective? Let’s talk.
At 360 OM, we specialise in helping businesses take their marketing efforts to the next level. Our team stays on top of industry trends, uses data-informed decisions to maximise your ROI, and provides full transparency through comprehensive reports.
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