Ecommerce Management Advisors
Ecommerce Management Advisors
Google cites a 40% drop in invalid ad traffic from deceptive serving, helping protect budgets and keep billing clean for advertisers.
Google Ads just dropped another wave of updates to Performance Max today.
For those who’ve been asking for better audience targeting, clearer reporting on new customer acquisition, and more transparency around auto-generated assets, these updates will feel like long-overdue upgrades.
Let’s break down what’s new, why it matters, and how advertisers should respond.
Google has announced three core areas of updates for Performance Max campaigns:
Most are either rolling out now or available broadly, with some elements in beta. Let’s walk through the details.
Performance Max has long leaned on automation, sometimes at the expense of control. Google is slowly changing that, and this release continues that shift.
Advertisers can now apply negative keyword lists across Performance Max campaigns. Previously, campaign-level negatives had to be managed individually, which created friction for accounts with dozens of asset groups.
With this update, advertisers can centralize keyword exclusions. For example, excluding terms like “cheap” or “free” across multiple luxury or premium product campaigns.
Image credit: Google, August 2025You still have the option to apply unique negative keywords to individual campaigns, but this rollout makes managing brand suitability far more scalable.
Google has doubled the search theme limit from 25 to 50 per asset group. This matters for brands that want to influence where their Performance Max ads show up in Search, without leaning on historical keyword builds.
By expanding your search theme input, you’re giving Google more information to better match your ads to queries. It also helps widen your eligible inventory while staying relevant.
You can now fully control which device types your Performance Max campaigns appear on, something that was previously only partially available.
For example, a gaming company can restrict campaigns to mobile devices, or a B2B advertiser can exclude tablets entirely.
Age targeting is now also available, allowing advertisers to exclude or target specific age ranges.
Google is also testing gender-based demographic targeting in beta. These controls bring Performance Max closer in line with what’s long been possible in Search, Display, and YouTube campaigns.
One of the most frustrating parts of new customer acquisition bidding has been the vague “Unknown” label in reporting. That’s changing with today’s updates in Performance Max reporting.
In lifecycle reporting for new vs. returning customers, Google previously bucketed a portion of conversions as “Unknown”. This left advertisers with limited visibility into actual performance.
Google has now improved the backend logic that determines if a user is new or existing, meaning those “Unknown” labels should be gone moving forward.
This matters for two key reasons:
For even more precision, Google encourages advertisers to update their conversion tracking tags to include the new customer acquisition parameter. This signals to Google whether a conversion is from a new or returning customer, based on first-party data.
Alongside the reporting improvements, Google has added new diagnostics that surface goal-related issues in Performance Max.
These include broken or missing conversion tags, goal misconfigurations, or other tracking issues that could be holding back performance.
The diagnostics come with actionable recommendations to help advertisers resolve the problem. While this might not be the most glamorous update, it will save time and frustration during campaign setup and troubleshooting.
Asset transparency in Performance Max has been a long-standing pain point. While things have improved in the last year, these new changes go further.
Advertisers can now view reporting for assets generated through Final URL Expansion (FUE). This is Google’s feature that dynamically creates assets based on landing page content.
You’ll be able to see what text and visuals were created through FUE and how they performed.
Image credit: Google, August 2025More importantly, if you don’t like what Google created, you now have the ability to remove those assets from your campaign.
This is a big win for brands concerned about creative consistency, especially when it comes to legal language or brand tone. While FUE can be useful for scale, it hasn’t always produced on-brand results. So, this added visibility is a welcome change.
Performance Max will now generate image-specific recommendations to help you improve performance. These suggestions will include both what types of visuals to add and how to optimize existing ones for better performance on various channels (like YouTube vs. Discover).
Image credit: Google, August 2025Best of all, these recommendations link directly into the built-in AI-powered image editor in Google Ads, so you can make changes right inside the platform without needing to re-upload or redesign assets elsewhere.
It’s clear Google wants advertisers to take a more active role in creative strategy, even inside an automated campaign structure.
Google is clearly listening to advertisers’ calls for more transparency and control. These updates to Performance Max mark another step toward striking a better balance between scale and strategy.
While not every advertiser will need to use every new feature, the option to do so means there’s more room to tailor Performance Max campaigns to your business goals, creative preferences, and customer insights.
Whether you’re looking to fine-tune audience reach, fix tracking issues, or clean up your creative assets, there’s something in this update that’s worth your attention.
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This post was sponsored by Market Brew. The opinions expressed in this article are the sponsor’s own.
What if your client’s PPC budget could fund long-term organic growth instead?
Why do organic results dominate user clicks, but get sidelined in budget discussions?
The Short Answer: Yes!
Over the past decade, digital marketers have witnessed a dramatic shift in how search budgets are allocated.
In the past decade, companies were funding SEO teams alongside PPC teams. However, a shift towards PPC-first has dominated the inbound marketing space.
Today, more than $150 billion is spent annually on paid search in the United States alone, while only $50 billion is invested in SEO.
That’s a 3-to-1 ratio, even though 90% of search clicks go to organic results, and only 10% to ads.
It’s not because paid search is more effective. Paid search is just easier to measure.
But that’s changing with the return of attribution within predictive SEO.
What Is Attribution?
Attribution in marketing is the process of identifying which touchpoints or channels contributed to a conversion or sale.
It helps us understand the customer journey so we can allocate budget more effectively and optimize campaigns for higher ROI.
As Google’s algorithms evolved, the cause-and-effect between SEO efforts and business outcomes became harder to prove.
Ranking fluctuations seemed random. Timelines stretched.
Clients became impatient.
With Google Ads, every dollar has a direct, reportable outcome:
SEO, by contrast, has long been:
As a result, agencies and the clients that hire them followed the money, even when SEO’s results were higher.
Hard facts:
Image created by MarketBrew, August 2025As a result, many SEO professionals and agencies want a way back to organic. Now, there is one, and it’s powered by attribution.
Instead of sitting on the edge of the search engine’s black box, guessing what might happen, we can now go inside the SEO black box, to simulate how the algorithms behave, factor by factor, and observe exactly how rankings react to each change.
This is SEO with attribution.
Image created by MarketBrew, August 2025With this model in place, you are no longer stuck saying “trust us.”
You can say, “Here’s what we changed. Here’s how rankings moved. Here’s the value of that movement.” Whether the change was a new internal link structure or a content improvement, it’s now visible, measurable, and attributable.
For the first time, SEO teams have a way to communicate performance in terms executives understand: cause, effect, and value.
This transparency is changing the way agencies operate. It turns SEO into a predictable system, not a gamble. And it arms client-facing teams with the evidence they need to justify the budget, or win it back.
For agencies, attribution opens the door to something much bigger than better reporting; it enables a completely new kind of offering: performance-based SEO.
Traditionally, SEO services have been sold as retainers or hourly engagements. Clients pay for effort, not outcomes. With attribution, agencies can now flip that model and say: You only pay when results happen.
Enter Market Brew’s AdShifted feature to model this value and success as shown here:
The AdShift tool starts by entering a keyword to discover up to 4* competitive URLs for the Keyword’s Top Clustered Similarities. (*including your own website plus 4 top-ranking competitors)
AdShift averages CPC and search volume across all keywords and URLs, giving you a reliable market-wide estimate and details for your brand towards a monthly PPC investment to rank #1.
AdShift then calculates YOUR percentage of replacement for PPC to fund SEO.
This allows you to model your own Performance Plan with variable discounts available to the Market Brew license fees with an always less than 50% of PPC Fee for clicks replaced by new SEO traffic.
AdShift simulates a PPC replacement plan option selected based on its keywords footprint to instantly see savings from the associated Performance Plans.
That’s the heart of the PPC replacement plan: a strategy you can use to gradually shift a clients’ paid search budgets into measurable performance-based SEO.
A PPC replacement plan is a strategy in which agencies gradually shift their clients’ paid search budgets into organic investments, with measurable outcomes and shared performance incentives.
Here’s how it works:
This is not about replacing all paid spend.
Branded queries and some high-value targets may remain in PPC. But for the large, expensive middle of the keyword funnel, agencies can now offer a smarter path: predictable, attributable organic results, at a lower cost-per-click, with better margins.
And most importantly, instead of lining Google’s pockets with PPC revenue, your investments begin to fuel both organic and LLM searches!
Agencies exploring this new attribution-powered model aren’t just intrigued … they’re energized. For many, it’s the first time in years that SEO feels like a strategic growth engine, not just a checklist of deliverables.
“We’ve pitched performance SEO to three clients this month alone,” said one digital strategy lead. “The ability to tie ranking improvements to specific tasks changed the entire conversation.”
Another partner shared,
“Instead of walking into meetings looking to justify an SEO retainer, we enter with a blueprint representing a SEO/GEO/AEO Search Engine’s ‘digital twin’ with the AI-driven tasks that show exactly what needs to be changed and the rankings it produces. Clients don’t question the value … they ask what’s next.”
– Stephen Heitz, Chief Innovation Officer, LAVIDGE
Several agencies report that new business wins are increasing simply because they offer something different. While competitors stick to vague SEO promises or expensive PPC management, partners leveraging attribution offer clarity, accountability, and control.
And when the client sees that they’re paying less and getting more, it’s not a hard sell, it’s a long-term relationship.
The traditional agency model in search has become a maze of expectations.
Managing paid search may deliver short-term wins, but it comes to a bidding war with only those with the biggest budgets winning. SEO, meanwhile, has often felt like a thankless task … necessary but underappreciated, valuable but difficult to prove.
Attribution changes that.
For agencies, this is a path back to profitability and positioning. With attribution, you’re not just selling effort … you’re selling outcomes. And because the work is modeled and measured in advance, you can confidently offer performance plans that are both client-friendly and agency-profitable.
For SEOs, this is about getting the credit they deserve. Attribution allows practitioners to demonstrate their impact in concrete terms. Rankings don’t just move, … they move because of you. Traffic increases aren’t vague, … they’re connected to your specific strategies.
Now, you can show this.
Most importantly, this approach rebuilds trust.
Clients no longer have to guess what’s working. They see it. In dashboards, in forecasts, in side-by-side comparisons of where they were and where they are now. It restores SEO to a place of clarity and control where value is obvious, and investment is earned.
The industry has been waiting for this. And now, it’s here.
Search budgets have long been upside down, pouring billions into paid clicks that capture a mere fraction of user attention, while underfunding the organic channel that delivers lasting value.
Why? Because SEO lacked attribution.
That’s no longer the case.
Today, agencies and SEO professionals have the tools to prove what works, forecast what’s next, and get paid for the real value they deliver. It’s a shift that empowers agencies to move beyond bidding-war PPC management and into a lower cost & higher ROAS, performance-based SEO.
This isn’t just a new service mode it’s a rebalancing of power in search.
Organic is back. It’s measurable. It’s profitable. And it’s ready to take center stage again.
The only question is: will you be the agency or brand that leads the shift or watch as others do it first?
Image Credits
Featured Image: Image by Market Brew. Used with permission.
In-Post Image: Images by Market Brew. Used with permission.
When Google first announced the existence of Performance Max back in 2020, to say I was skeptical of this ad unit would’ve been an understatement.
When it rolled out to everyone in 2021, I described my thoughts about it as “loud, angry, and distrusting”.
In my defense, look at it from a 2021 Jon perspective: Google gave you an ad unit that would opt you into areas you may not want to be in (Display, Partner Network, YouTube), which you couldn’t opt out of.
You also couldn’t target one network; if you didn’t add a YouTube video, it would make its own. There were no exclusions; there were no negatives. There was negligible reporting.
Additionally, it would show in all the ad placements you were already in, and potentially, cannibalize them. There was limited control over the budget.
All you knew was that you would give Google your money and hope it did right by you.
On top of it all, it was described as a supplementary function, but if you wanted to use Local Search Ads or Smart Shopping, you were forced to do this.
This was then followed by Google representatives recommending that we stop running Shopping campaigns because “PMax will handle it” (which contradicted the original descriptions).
Needless to say, I wasn’t thrilled about it. Then, when Bing (because I refuse to call them Microsoft Ads) announced it was going to be rolling out PMax back in 2024, I almost lost it.
My loyal, consistent, trustworthy little buddy, Bing, was going down the evil rabbit hole of non-transparent advertising, and I was angry. That was all then (I know that was just over a year ago, but give me credit).
Fast forward to June 2025 Jon, (maybe it is the early summer heat in New England), I am no longer that belligerently angry at PMax for existing (still angry about a lot of other things, though).
Now, for different reasons, I am afraid to say it: I am a Performance Max loyalist. Not just in Google, either, but also in Bing – I love the PMax function in both of them.
A little bit of background: I’ve been in the digital space for over 20 years. I’ve seen the evolution of search platforms many times over. Some changes were good. Several were terrible (a la “Enhanced Campaigns” or mandatory “MSAN”).
So, needless to say, I am a firm believer of: “If it ain’t broke, don’t fix it.” But, PMax was a fix for something that wasn’t broken (at least, at the time, I believed it).
More importantly, this ad unit went against a lot of Google’s claims of “trust and transparency.” This ad unit provided, at the time, almost no transparency whatsoever, so it sure didn’t give us a reason to trust it.
A little awkward (Screenshot from Google Transparency Center, July 2025)This was essentially having the fox watch the hen house.
What if I didn’t want to trigger for a specific search? What if I didn’t have video assets and I couldn’t let Google create them? What do you mean I can’t get a full placement report of where my ad was showing?
Not to mention, initial data and results yielded little to no noticeable growth in a positive direction. But, there was a lot of burning cash somewhere.
But that was just Google. When Bing rolled out its PMax, the Audience Network had just become mandatory for search. The search syndication network was producing garbage, there was no video ad unit, and the documentation on the Bing PMax capability was negligible and hidden (shout out to Milton for helping me find it).
Why was this so hard to find?! (Screenshot from Microsoft Advertising, July 2025)Why should anyone have been in a pro-PMax mindset at all?
And if you scroll through the old X (Twitter) hashtag of #PPCCHAT (which by the way is the best global paid search community there is), you will realize that few – if any – were, in fact, pro-PMax.
I should first clarify that I now heavily use Performance Max. It is a necessity (think a necessary evil) in most direct response/performance-driven paid media initiatives.
I maintain several reservations about it. However, other reservations have eroded away over time.
When I first tested out Performance Max, it was a test effort for a consumer packaged goods (CPG) ecommerce company and a couple of quick service restaurant (QSR) brands.
For CPG, we were testing it as a supplement to shopping, and we were honestly ignorant of what it was doing.
For the QSR brands, we tested it out as an alternative to local search campaigns, as those were being “sunsetted” by Google.
If we wanted to continue our digital marketing push to hundreds of brick-and-mortar locations on maps, then our only option was to do PMax (net-net, we were forced to).
In both cases, the initial results were “dog water” (a phrase my 10-year-old son keeps using when describing the Jets’ season).
Why were they bad? There are multiple reasons, including but not limited to: lack of education, probably a poor setup on our part, multiple technical flaws on it via Google, and what seemed like a rush to market/incomplete system.
The CPG ecommerce brand abandoned the effort within a few months (at my recommendation, I should note). But the QSR brands – that was different. We started seeing the data.
For both brands, we had been using local search, YouTube, Search, Discovery (may it rest in peace), and every now and then, GDN – all for different needs.
So, getting them to work together for a single function made sense on paper, but was a novel concept to us.
The QSR brands were optimizing for conversions (we had six types), but one of the six types was more valuable than the others (Store Visits).
Once we moved to a conversion value strategy on PMax, we were off to the races. More so, we started seeing deliveries that exceeded prior deliveries in regular search or local search.
I miss local search (Screenshot from author, July 2025)This shift in performance forced me to accept that I could compromise my lack of transparency for strong performance.
Something that was eating at me, though, was the impact on search.
For those who remember, briefly, PMax search was only on mobile. Then, it expanded to all devices. We did a study to prove it was cannibalizing regular search.
But ultimately, the study made me realize something: I may not be in control of the target and the function, but if the performance was there, my argument against it was going to have to diminish as quickly and quietly as Google Glass.
My perception of Bing PMax changed for a different reason than Google’s.
If you’ve read my past articles, you know I am very much pro-Bing, but in very specific categories, such as healthcare. I am not huge on it in other categories.
So, entering into Bing PMax was going to have to be done either by force or because I heard a rumor.
Needless to say, I got backed into a corner that forced my hand on it (twice), and the first instance happened to coincide with a rumor.
First, note this: I am adamantly against the forced usage of the Bing audience network (MSAN) in search, and not being able to opt out of it, completely infuriates me.
Now, cue the rumor: I had been informed by a former Bing employee that if I wanted greater control of the audience network, I needed to go one of two routes:
I elected the PMax route (which, by the way, the rumor about that part was not, in fact, accurate).
I went this route because, at the same time, I had a health insurance brand that was crushing it in efficiency in Bing search, but we couldn’t really scale it anymore.
But, we had a test budget earmarked for direct response/performance tactics, and time was running out to use it (or I would lose it).
So, I threw out the idea of trying PMax in Bing. It had been negligibly attempted within the agency in various verticals with underwhelming performance.
We said, “Why not, let’s give it the old college try and prove that this was not going to work for us,” and we tested it against search.
Well … needless to say, I was wrong. It was beating out search. The only thing it couldn’t do – that Google could – was drive click-to-call leads.
A number of things:
Don’t take this come around thought train as total acceptance. There are still several things that grind my gears, and tips I recommend for dealing with them:
Performance Max, whether it is on Google or Bing, is an ad unit that makes you feel somewhat powerless, but honestly, that isn’t a bad thing.
There are a few verticals/scenarios where PMax isn’t usable (specifically, if it is “remarketing only” audiences or legal compliance restrictions).
You will likely be comfortable with the results, but uncomfortable with the method. You aren’t alone; this is a continuously evolving ad unit.
While you’re at it, especially in Google, don’t sleep on Demand Gen; it’s basically a PMax “lite.”
More Resources:
Featured Image: Master1305/Shutterstock
Marketers tend to prioritize top-of-funnel awareness and bottom-funnel conversion efforts.
Yet, the mid-funnel stage is where prospects actively weigh options and is crucial for sustained growth and profitability.
Overlooking this critical stage can reduce revenue potential. Using AI-driven paid media for nurturing and retargeting can bridge this gap, converting high-quality leads into profitable customers.
Prospects in the mid-funnel have already expressed interest and are ready to move to action.
They are conducting detailed comparisons, attending webinars, downloading whitepapers, and critically evaluating their choices.
Despite this intense engagement, advertisers often overlook this critical phase, causing leads to drop off.
Common challenges at this stage include generic content that fails to resonate and intrusive retargeting campaigns.
The lack of personalized campaigns and ad copy further undermines mid-funnel marketing. It’s important now for marketers to reassess their strategies to better engage prospects.
To effectively target prospects, we have to understand their journey through the marketing funnel.
As we explore AI’s impact on the mid-funnel, let’s first look at how prospect behaviors evolve from awareness to conversion.
For PPC strategists and chief marketing officers, aligning paid media tactics with each funnel stage is key to maximizing AI’s potential in campaigns.
To illustrate how PPC strategies should evolve with the prospect’s mindset, consider the following breakdown of PPC tactics for each funnel stage.
| Funnel Stage | Prospect Mindset & Goal (PPC Lens) | Common PPC Keyword/Query Types | Key PPC Ad Focus | Core PPC Tactics & Ad Formats |
| Top-Funnel (Awareness) | “I have a problem or need.”
|
Informational keywords:
|
|
|
| Mid-Funnel (Consideration/ Evaluation) | “I understand my problem and am looking for solutions.”
|
Comparison keywords:
|
|
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| Bottom-Funnel (Decision/ Purchase) | “I’m ready to buy, need to choose who from.”
|
Transactional keywords:
|
|
|
In the “consideration” phase, advertisers now have new ways to engage, segment, and nurture mid-funnel audiences with AI and innovative PPC targeting tactics.
Here are three AI-powered mid-funnel tactics to integrate into the paid search plan.
This tactic uses AI to analyze huge amounts of user data signals to identify which specific prospects are most likely to take action (convert) at mid-funnel.
The ad platforms may look at past website interactions to demographic signals to predict who are the most qualified new customers.
Smart Bidding and targeting tools allow advertisers to focus ad budget and messaging on the most effective, hot leads.
In one example, Google Ads segments out new customers, calling it the “New customer acquisition goal.” This lifecycle goal prioritizes bidding to reach and acquire new customers.
AI automation can generate personalized ad creatives in real-time, enhancing relevance and engagement.
This means prospects see ads that are custom for their specific interests and previous interactions, in real-time, making the ads feel more relevant and personal.
Shift your focus from conversion volume to conversion value with AI-powered bidding strategies that prioritize high-value leads.
Advertisers can assign a higher monetary value to actions that signify greater intent or higher potential lifetime value, like a demo request vs. a download.
The AI then prioritizes bids and focuses the budget on acquiring more valuable leads.
Rethink your approach to the mid-funnel, where valuable engagement opportunities often go untapped.
By using AI-driven strategies like those discussed, you can reconnect with high-intent prospects and guide them toward conversion.
For CMOs and senior marketers, optimizing the mid-funnel is a strategic opportunity to grow the customer acquisition pipeline.
More Resources:
Featured Image: N Universe/Shutterstock
Performance Max has become one of the most talked-about campaign types in PPC for a number of reasons.
Some advertisers swear by it, while others remain skeptical, and opinions are increasingly polarized.
In reality, PMax is neither flawless nor fundamentally flawed. It is a campaign type with both advantages and drawbacks, and deciding whether to use it requires nuance.
Before taking a “for or against” stance, consider how PMax evolved, why the industry is divided, and when this campaign type makes strategic sense.
Starting at the beginning, let’s look into where this evolved from.
Google officially launched Performance Max in late 2021, a milestone in terms of automation in Google Ads.
By 2022, it had effectively absorbed Smart Shopping and Local campaigns, consolidating multiple ad networks and formats into one unified solution.
The reason this change marked a major shift in PPC strategy was that advertisers no longer had to manage separate campaigns for each channel (in theory).
Adoption of PMax was rapid, in part because Google’s transition forced the issue.
Smart Shopping campaigns were auto-upgraded to PMax, so many advertisers found themselves using PMax whether they planned to or not.
By mid-2024, PMax accounted for ~82% of Google advertising spend within retail alone, and the simplicity of PMax began making waves with smaller advertisers.
In a relatively short space of time, this momentum signaled that PMax was not a niche experiment or small change by Google, but a mainstream part of the ecosystem that signified the direction in which Google Ads is going.
Back when PMax launched, there were expected growing pains. The lack of transparency and many controls advertisers were used to over decades of managing PPC were essentially removed, and the term “black box” became widely used for this campaign type.
Was this fair? In my opinion, at launch, yes.
Campaign management went from having complete control over search queries, ad networks, auctions, etc, to a five-step process:
Then, where the real grunt work with optimization sets in post-launch, advertisers were simply told to leave the campaign to gather data, not knowing where their ads served, how their budget was apportioned, and more.
Advertisers essentially handed the keys to Google’s AI without the usual levers to guide it. For years, PPC professionals had built careers on meticulous campaign control, and it was gone.
However, over the past three years, PMax has changed considerably, with Google addressing some key concerns raised by advertisers.
Google added a selection of reports and control features that didn’t exist in 2022, including features like search term insights, asset group reporting, and brand exclusions.
Some of these updates feel like genuine concessions to give advertisers more transparency and control, but within the world of PPC, it’s felt that it’s still not enough.
Despite these improvements, opinions remain split, largely because the fundamental trade-off of PMax (automation vs. control) still exists.
To understand the divide, let’s look at both sides of the argument.
Instead of siloed Search, Display, Shopping, and YouTube campaigns, PMax’s machine learning decides where to show ads to best meet your goals (in the words of Google).
For resource-strapped teams, the convenience of an all-in-one campaign is attractive as it significantly reduces the complexity of managing multiple campaigns.
Here are a couple of cases:
Data signals and algorithms adjust bids in real time and find the right audience for your ads across channels.
This isn’t new (think automated bidding). However, PMax is advertising across multiple ad networks.
There are plenty of case studies out there showing how automation improved performance, one in particular where Google highlighted a case where a Latin American travel company, AssistCard, saw a 15x higher conversion rate and 40% lower CPA in PMax vs. similar campaigns without it.
When set up properly, PMax’s automation can efficiently drive performance in ways manual tweaks might miss by building out each campaign in silo, and as ever, it depends on the case at hand.
Because PMax has wide latitude to find conversions anywhere on Google, it can rapidly scale campaigns that are doing well.
If your offer and creative are effective, PMax will seek out all available inventory to get in front of relevant users.
It’s also a useful way to test new channels, e.g., if you’ve never tried YouTube or Display, PMax will allocate some spend there and let you see how those channels perform as part of a blended campaign.
You can then review performance via the channel performance report or one of the many scripts available online.
The hands-off nature of PMax appeals to advertisers who want to uncover new opportunities without heavy lifting on their part.
The simplicity of PMax can lower the barrier to entry for advertisers without dedicated PPC teams or external support.
Instead of learning the ins and outs of feeds, keywords, bids, and multiple campaign types, a business can input its goals and creative assets, then hand off to Google to do the rest.
In essence, PMax offers plug-and-play advertising that aligns with limited time and expertise, whilst boasting strong results for brands of all sizes.
Google is heavily invested in PMax. Just look at the journey advertisers have been on over the last three years with PMax and where we are now with regards to features, reporting, and optimization.
Google’s SVP & Chief Business Officer Philipp Schindler states in 2022 that “we’re very, very committed to helping Performance Max deliver for our advertisers and have been very open to advertiser feedback how we can do this.”
Over the last decade, there has not been a campaign type/feature that has received this level of investment. This commitment is part of the reason why PMax now accounts for nearly 82% of all retail Google Ads spend in 2025.
So, where does the scepticism come from if it’s such a key part of advertising strategies? Let’s get into that.
Handing over targeting and bidding decisions to Google is a bitter pill for seasoned PPC professionals.
With PMax, you can’t choose specific keywords or placements; Google’s AI decides when and where your ads show.
Advertisers effectively relinquish the levers they normally use to steer campaigns, and there are two ways to look at this:
As much as PMax now has features to see performance down to a certain level of detail, it’s still not enough to grasp control of media spend and make actionable changes based on the queries and audiences the ads are being served to.
Data is the heart of PPC and has been from the start.
Take search terms, visibility through PMax is still limited with broad “search category” insights rather than the exact queries users searched.
Cross-network reporting also lacks depth. Combined results from Search, Display, YouTube, etc., make it hard to break out performance by channel or asset in a meaningful narrative that can be translated into short-term optimizations and long-term strategy.
Although Google has added some reporting improvements, advertisers still don’t get the full picture, which can be frustrating when sharing performance updates to teams, management, or clients.
PMax decides how budget is allocated across channels and audiences, with advertisers having only a snapshot view of where the budget is going.
For example, a retail PMax campaign might be spending heavily on dynamic retargeting or branded searches (which can be negated using the request form, but, in my experience is not always a guarantee that brand will stop serving in ad auctions). It raises the question: Is PMax really driving new incremental customers or just capturing easy wins?
Alongside this, advertisers have auto-generated assets, enhanced images, AI-suggested copy, and more to deal with when managing their campaigns.
Features like this add layers of complexity when deciding whether or not to use PMax. Sectors, such as luxury fashion with strict brand guidelines, simply cannot give creative freedom to Google when advertising on networks as vast as GDN.
Running PMax alongside traditional campaigns has historically been tricky.
When PMax first launched, it was a bit of a blurred area with which campaigns would take priority when factoring in standard Search or Shopping campaigns for the same products/audiences.
Google has now shared the details on this, stating that PMax and standard Shopping can compete more evenly based on ad rank and that PMax will not override shopping; both will enter auctions that are eligible for, and the ad rank will determine which shows.
Aside from the auction, there are other factors involved in running a portfolio of campaign types, such as search query overlap, where advertisers have to define queries between campaigns.
This isn’t anything new, but the process of negating queries for PMax is more convoluted than adding negative keywords to search or shopping.
If you’ve followed the narrative surrounding PMax, you’ll have read that it works great for some advertisers and is diabolical for others.
Post launch, some advertisers simply found that their carefully optimized standard campaigns outperformed PMax.
For instance, one industry analysis noted that PMax conversion rates in late 2024 were slightly lower (about 2%) than those of standard Shopping campaigns.
Others found that moving to a fully automated solution actually delivered uplifts in performance, with Google stating an average increase in revenue of 27% vs. non-PMax.
This uncertainty makes risk-averse advertisers inclined to stick with what they know. Others, who are more open to experimentation, treat PMax as a testing ground and embrace automation when it proves its value.
In reality, the truth about Performance Max lies somewhere in the middle.
Rather than asking, “Should we use PMax or not?” a better question is, “In what scenarios does PMax make sense for us?” Framing it as simply good or bad is too simplistic.
As with most marketing strategies, whether PMax is right for you depends on context, your business, goals, and resources.
What are you trying to achieve? If your goal is broad reach and top-line conversion growth, PMax’s all-channel approach could align well.
It could efficiently drive online sales or leads when you aren’t as concerned with a specific channel mix.
On the other hand, if your goals require tight control (e.g., a precise cost per acquisition target for a niche B2B product or a brand that can only serve on very specific ad auctions), you might favor more hands-on campaigns.
Ensure PMax’s optimization style matches your KPIs and tolerance for how those results are achieved.
Do you have a team that can manage campaigns or a portfolio of campaigns, or do you need an automated solution without heavy lifting?
A lean organization with limited PPC staff may benefit from PMax handling the heavy lifting across channels.
Conversely, a large team or agency with deep expertise might squeeze more performance from manual control in Search or Shopping campaigns.
Also, consider the tools at your disposal. If you have sophisticated in-house data and optimization systems, you might not want to relinquish control to Google’s black box.
Advertisers with strict data requirements (for example, those who need to see every search query for compliance or want to segment performance by niche audiences) will struggle with PMax’s opacity.
If full transparency is non-negotiable, PMax may not be a fit for those campaigns.
However, if you can work with modeled and aggregate data, and you measure success on bottom-line results, PMax’s data limitations might be acceptable.
Companies vary in how they adopt new technology. Some are innovators or early adopters who eagerly try new Google features; others are late adopters or even laggards who resist change.
This human factor shapes PMax opinions.
If your organization values being on the cutting edge (and can tolerate some volatility), you may have leaned toward giving PMax a shot early.
If your culture is very risk-averse, you might have held off until there’s more industry-wide proof and Google has ironed out the kinks.
Neither approach is “wrong,” but it should be a conscious strategic choice rather than a knee-jerk stance.
In some cases, the optimal approach could be a hybrid.
For example, some advertisers run Performance Max alongside standard Search or Shopping campaigns and find a balance that works.
You might use PMax to cover certain areas (like display retargeting, non-brand terms with controlled exclusions, etc.) while still running dedicated campaigns for core products or certain keywords where you need more control.
Google has been listening to advertisers and agencies, with ongoing updates allowing PMax and traditional campaigns to coexist more harmoniously (no more automatic overriding of standard campaigns).
This opens the door to a nuanced account strategy that leverages PMax where it excels and uses other tactics where they’re stronger.
A mix-and-match strategy could outperform an all-or-nothing approach, or it might be one over the other; it’s just something you wouldn’t know without testing.
PMax today is more flexible than PMax three years ago.
As Google continues to refine the platform, some of the early drawbacks are being mitigated.
Advertisers who were against PMax due to a specific missing feature may find that the issue has since been addressed.
This is why it’s worth continuously re-evaluating your stance and testing on a case-by-case basis.
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Featured Image: Roman Samborskyi/Shutterstock
Budget increase, performance drops, budget decrease. Almost every marketer knows that short-sighted game, where decisions are made on a daily basis and campaign performance fluctuates to extremes, without a clear goal.
I’ve seen this pattern destroy more campaigns than I can count. The problem isn’t bad ads or wrong keywords – it’s “actionism.”
That’s when you’re constantly changing things without a plan, reacting to yesterday’s numbers instead of building for tomorrow.
PPC scaling isn’t about doing more. It’s about doing the right things in the right order, which is why I highly recommend a sustainable growth framework to companies working on their long-term goals.
The following framework has consistently delivered three to five times growth while keeping campaigns profitable.
Here’s what I see marketers doing wrong every single day:
Sound familiar? These create a mess.
Bad results make you or your leadership panic and change more stuff. More changes mess up your data. Messy data means you can’t tell what’s actually working.
Your campaigns end up stuck between “meh” and “disaster,” never really growing.
Here’s the system I use to scale campaigns without the guesswork:
You can’t scale chaos. Before adding budget anywhere, fix what you have first.
Start with a reality check. Look at your campaigns and find what’s actually working. Which ad groups bring in customers? Which keywords convert? Which ads get clicked and actually lead to sales?
Write this stuff down – these are your money-makers.
Track your key numbers: How much it costs to get a customer, how much money you make per dollar spent, conversion rates, and average order size. These become your benchmarks for everything else.
Next, cut the dead weight. This sounds backwards, but scaling often starts with doing less. Pause campaigns that have been losing money for X+ days with no signs of life.
Remove ad groups that overlap and compete with each other. Stop throwing good money after bad.
Here’s the key: Take 80% of your budget and put it on your top 20% best performers. This gives you cleaner data and better results faster.
Make everything consistent. Create naming systems that make sense. Set up tracking that actually works. Build templates for ads and landing pages you can copy later.
Most importantly, set rules for when campaigns get more budget, like they need to hit your target cost per customer and keep it there before getting more money.
Analyze deeper. Don’t just look at surface numbers. Watch how your budget gets spent throughout the day.
Those Google Ads notifications about limited budgets? They’re garbage. They show up late, stick around for days after you’ve fixed things, and waste your time.
Instead, build a proper budget monitor. I use Google Ads scripts that loads data into Google Sheets so I can see exactly how fast money is burning in real time.
If you want something quicker to set up, Google has a budget depletion report in Looker Studio that works decently enough to start with.
Once your campaigns are stable, it’s time to understand what’s happening in your market and where you stand against competitors.
Know your competition. Use auction insights to see who you’re really fighting against. Look at your products manually or use merchant center data to see how your pricing stacks up.
Find out what you’re good at and where you’re getting crushed. Maybe certain product categories just don’t work, or your margins are too thin.
Here’s the thing: Google wants you to dump everything into Performance Max and call it a day. That works for basic campaigns, but in my opinion, it won’t scale.
Real growth comes from understanding why some products sell and others don’t. Sometimes a small tweak fixes everything.
Other times, a product is just dead in the water. You need to know the difference if you want to grow consistently without wild swings in performance.
Track search trends and volume. Google Keyword Planner shows you search volume, plus three-month and year-over-year trends – perfect for spotting seasonal patterns.
Google Trends helps you see what’s hot and what’s dying.
Stay on top of market news by checking Google News regularly. Set up Google Alerts for your brand names and key industry terms so you don’t miss anything important.
If you’re in the EU and work with a CSS partner, ask for CSS Insights reports. They show you market data on clicks, impressions, and how deep other advertisers are bidding.
CSS Insights sample report (Image from author, June 2025)These insights give you a clear picture of industry click volume, impression volume, and how tough your competition really is.
Always back your decisions with real data. Otherwise, you’re just guessing. But when you have solid data, you can make moves with confidence.
This analysis shows you how much room your current campaigns have to grow and where new opportunities are hiding.
Now, you take your winners and make them bigger. This isn’t just throwing more money at campaigns. It’s a smart expansion based on what the data tells you.
Scale budgets the right way. For campaigns hitting your targets, increase budgets gradually. I mean gradually – max 20-30% every couple of days. Go faster and you’ll trigger Google’s learning phase or blow through cash before you know what hit you.
Watch your numbers like a hawk when scaling.
If your cost-per-customer jumps more than 20% or your return on ad spend (ROAS) drops below your limit, stop the increases immediately.
Fix what’s broken first. Also, remember that conversions take time. Don’t panic and make changes if performance wobbles for a day or two.
Segment everything by performance. Here’s where most people screw up scaling. They lump all their products together – bestsellers mixed with money burners. That’s a recipe for disaster.
Label your products by profit margins or performance, for example, with data-driven product segmentation.
Create scores or labels that make sense. Then, split your campaigns by these scores so similar products are grouped together. Your top performers get their own campaigns, your problem products get theirs.
Why? Because Google’s algorithm isn’t perfect. It might hit your average return target, but it’s doing it by letting your bestsellers carry the dead weight.
From the outside, everything looks fine, but you’re wasting tons of money on products that will never work while starving your winners of budget.
This is the biggest scaling blocker I see. Everything looks okay at the top level, but dig deeper and you’ll find massive waste.
Separate your winners from your losers, and suddenly you have way more budget to put where it actually makes money.
Your home market is working. Now, it’s time to take those winning campaigns and spread them to new countries and platforms. But here’s the key: Don’t just copy and paste everything, hoping it works.
Go international the smart way. Start with countries that are similar to your home market. The same language is easiest, but similar buying behavior and economic conditions matter more.
If you’re crushing it in Germany, try Austria or Switzerland before jumping to Brazil.
Check your current data first. Look at your Google Analytics – you’re probably already getting some international traffic.
Start with countries that already convert for you organically. These are your low-hanging fruit.
Set up separate campaigns for each country. Don’t just translate your ads, localize them.
Different countries care about different things. Price might be everything in one market, while quality and service matter more in another.
Your checkout process, shipping costs, and customer service all need to work in the local language and culture.
Start small. Take your best-performing campaign and recreate it for one new country. Get that profitable first, then expand to more markets. Don’t spread yourself thin trying to launch everywhere at once.
Expand to new platforms carefully. Once you’ve maxed out Google Ads in your main markets, look at other platforms. But here’s what most people get wrong: They think Facebook works like Google, or TikTok works like Facebook. They don’t.
Each platform has its own game. Google captures people already looking to buy. Facebook interrupts people scrolling. TikTok is all about entertainment first.
Your ads, targeting, and strategy need to match how people actually use each platform.
Start with one new platform and master it before moving to the next. Take your winning products and test them, but expect to rebuild your ad creative from scratch. What works on Google Search probably won’t work on Facebook Feeds.
The mistake I see all the time? People launch on three platforms simultaneously, spread their budget too thin, and conclude none of them work.
Pick one, give it proper attention and budget, and make it profitable before adding more.
Scaling isn’t a one-time thing. Markets change, competitors adapt, and platforms update their algorithms. You need systems that keep you ahead of the curve and focused on what actually matters, long-term growth.
Think long-term, not daily panic. Here’s where most marketers lose their minds. They check performance every day and freak out over weekly fluctuations. Stop it.
Focus on your North Star metrics, the big picture numbers that actually matter for your business over months and quarters, not days.
Set up proper attribution that shows the real customer journey. People no longer just click an ad and buy.
They see your Google ad, check you out on Facebook, read reviews, and then come back through organic search to purchase.
If you’re only looking at last-click attribution, you’re making decisions with half the story.
Marketing Mix Models (MMMs) help you understand how all your channels work together. They show you the true impact of each platform and how they influence each other. This is crucial when you’re running campaigns across multiple platforms and countries.
Let automation handle the boring stuff. Once you have enough conversion data, smart bidding strategies like Target CPA and Target ROAS can actually work well.
But they need proper setup and constant monitoring. Don’t just turn them on and hope for the best.
Build custom scripts or use third-party tools to automate the routine stuff, bid adjustments, budget pacing, and performance alerts. This frees you up to focus on strategy instead of daily maintenance.
Test everything, but do it right. Create a systematic approach to testing new ad copy, extensions, and landing pages. But only test one thing at a time, or you’ll never know what actually made the difference.
Watch for trouble before it hits. Set up early warning systems that alert you when performance starts shifting before it becomes a real problem.
Track things like impression share drops, quality score changes, and competitive pressure increases.
The goal isn’t to react to every small change, but to spot the big trends early so you can adapt your strategy before your competition does.
Sustainable PPC scaling isn’t about revolutionary tactics or secret strategies. It’s about disciplined execution of proven principles, systematic testing, and patient optimization.
The SCALE framework provides the structure to move beyond actionism toward strategic growth.
By stabilizing performance first, capturing market intelligence, amplifying what works, layering new opportunities systematically, and continuously evolving your approach, you create a foundation for sustained success.
Remember: Scaling PPC campaigns is not about doing everything at once. It’s about doing the right things in the right order, with the discipline to stick to the process even when the temptation to “optimize” everything at once becomes overwhelming.
The companies that achieve sustainable PPC growth aren’t the ones with the most sophisticated tactics. They’re the ones with the most disciplined systems.
Build your system, trust your process, and let compound growth work in your favor.
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Featured Image: Roman Samborskyi/Shutterstock
Return on ad spend (ROAS) is a common metric or key performance indicator for paid search campaigns. PPC managers and digital marketing executives have been using it for a long time.
In fact, it isn’t even novel to just digital marketing.
While calculating and connecting the dots with attribution for full end-to-end digital marketing is ideal, using ROAS within PPC and SEM specifically can be powerful as a quality metric that scales.
ROAS is a pretty straightforward equation to calculate on the surface.
Return on ad spend = total revenue generated by ads, divided by the cost of ad spend
However, it seems that no metric, KPI, or outcome is as easy to configure and measure nowadays, given the volume of changes in Google Ads, reporting software, and measurement platforms alone.
Beyond that, there’s no one-size-fits-all benchmark or result you’re looking for. A “good” ROAS is different for every business, and what defines good or successful is up to the business to determine.
Whether you’re confident calculating ROAS, need help with knowing how to use it, or fall somewhere in between, I encourage you to dive into the ways to use it in your own PPC efforts.
PPC is a great channel for getting quick results and to impact a business.
However, even with the best research on the front end, it can often lead to missed expectations.
PPC expectations can vary wildly and be subjective. ROAS provides the opportunity to set a benchmark for what success looks like.
An effective PPC manager can pull different levers to drive more traffic, spend more budget, or try to find a sweet spot in between.
By establishing a ROAS goal tied to profitability, the PPC team can utilize that metric as a key in their decisions and performance overall.
And, profitability needs to factor in the cost of software, people, and things that go beyond just the cost of an ad or media budget – but that’s for another article.
ROAS can serve as a great tool in factoring budget decisions.
Like setting expectations, ROAS can serve as a benchmark, helping teams go beyond just looking at bid, budget, click, and conversion ceilings. It is a quality metric.
Use ROAS to determine where the law of diminishing returns applies and ensure it is included in projections. When looking at real past performance, it can be used to help determine ideal budgets and ranges that are acceptable.
In most cases, I have found clients are okay with not capping the budget and looking at the ROAS number solely to determine how much to spend.
If the spend can be increased and still exceed the target ROAS, then keep spending all day, every day, as we know we’re in profitable territory, assuming we’re not creating inventory, fulfillment, sales capacity, or other operational issues.
I love this type of thinking and decision-making, as it is linked to ROI versus budget or a mindset that marketing and ad dollars are an “expense.”
Getting more granular, bid decisions can also be made based on ROAS.
The ROAS can be calculated at a detailed level and not just at a high level for aggregate or total spend.
When we break down our campaigns into categories like campaign, ad group, ad type, topic, etc., we can get more granular control and insight.
For example, If we’re running Google Shopping Ads which appear on Google Shopping search results pages, we can treat those as a distinct advertising format. This allows us to measure their performance separately and calculate the return on ad spend (ROAS) they generate.
Going even deeper, we can drill down to the individual product level to see how different products produce ROAS.
By knowing what the ROAS is at different levels, we can advise and optimize our bid strategies and have more control over what is driving the overall ROAS and positively impact the whole.
The ability to roll up performance drill down to the product detail level allows for measuring toward broader business goals while also providing an opportunity to test and get things dialed in over time when launching and optimizing new campaigns and ads within an account.
One of the first types of businesses that comes to mind when thinking about ROAS and its use is ecommerce.
With a lot of the great tools and integrations available, many shopping cart platforms automatically feed revenue data back into Google Ads and Google Analytics.
By using these metrics, we can quickly arrive at our ROAS by taking total revenue divided by total spend.
Note that getting ROAS is likely the easiest part. Determining what an acceptable ROAS overall takes more time and work.
That part includes determining profit margins for products, calculating overhead, and determining the full aspect of ROI to back out what the ROAS needs to be.
A trickier business goal type for calculating ROAS is lead generation. ROAS might be tougher to back out and measure itself.
However, in most cases, lead generation campaigns have more attention to detail on the ROI side of things and know their sales cycles and overhead.
This makes arriving at ROAS goals easier, while ROAS itself might take more time to calculate based on the length of time from conversion to final sale, if that’s how ROAS is truly calculated.
When you want to look at ROAS as a meaningful metric for lead generation, you need to have a solid definition of what a lead is.
By default, if a conversion action in Google Ads (or other platforms) is what you use to calculate this metric, you might end up off-track from what your sales team or broader effort cares about.
ROAS matters, but if the “lead” isn’t right or something you can track, you can run into trouble with the definitions of “return,” “leads,” and your overall attribution.
In most cases, the deepest you can track and attribute a lead to a sale and actual revenue is best. If you can’t get that deep, ask questions and probe. The dots should be connected from impression to customer/client.
ROAS can be measured in other business goals and applications as well.
Whether it is awareness generation, page views, or other secondary goals, it can still apply.
Although, it might take more work to define the return for awareness campaigns and would need measurement through attribution modeling. But, it can still be achieved with the right work to back out the sales metric.
As a note, in B2B lead gen, attribution windows can be long, and offline conversion tracking is needed for accuracy.
An example of ROAS for an awareness campaign can look very different from one for ecommerce or lead generation.
If your goal is to create awareness for a topic, brand, or other subject matter, then you’re not as focused on direct sales or leads. You may want to cast as wide of a net as possible for your target or potential audience (even if the broader general public).
In that sense, you have to find a key metric to tie ROI to. You have the most open-ended challenge here – you have to determine the ROI for your organization. What does awareness contribute directly to ROI? How do you define it, measure it, and attribute it?
While ROAS is a great benchmark and quality guide for paid media, it isn’t the end of the story. In some cases, it is just the start.
With customer retention, recency, frequency, monetary value (RFM), and lifetime value metrics that are known in businesses, we can take it even further.
Tying ROAS to other metrics beyond the sale can lead to incredible insights for use outside of media spend management.
Again, I know that ROAS might seem like a basic metric and be something reported on by default in so many dashboards and reports.
While in some cases, it may be simple to calculate, but using it as a metric takes more work.
Getting the foundation right, knowing what a good target ROAS is, how it scales, and that the “return” you’re getting is profitable, is the key to seeing it be a key benchmark and goal-focused KPI in your set of digital marketing metrics that ultimately map out to your business outcome results.
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Featured Image: voronaman/Shutterstock
Most brands don’t know they’re wasting money on branded ads. Are you one of them?
What if your Google Ads strategy is quietly draining your budget? Many advertisers are paying high CPCs even when there’s no real competition. It’s often because they’re unknowingly bidding against themselves.
Join BrandPilot AI on July 17, 2025 for a live session with Jenn Paterson and John Beresford, as they explain The Uncontested Paid Search Problem and how to stop it before it eats into your performance.
Brands are overspending on Google Ads without knowing the real reason. If you’re running branded search campaigns, this session will show you how to identify and fix what’s costing you the most.
Register today to protect your spend and improve performance. If you can’t attend live, sign up anyway and we’ll send you the full recording after the event.