Not long ago, broad match was positioned as the future of paid search. Today, that role belongs to AI Max.

Over the last few months, I’ve heard repeated recommendations to enable AI Max on brand campaigns, even when those campaigns are already performing exactly as intended.

The problem is that many accounts still lack the foundations AI Max needs to work well. Conversion tracking is unreliable, offline conversion imports are missing, and generic campaigns remain constrained by budget or structure.

AI Max depends on strong conversion signals, sufficient volume, and enough variation for the system to learn effectively. In many accounts, brand campaigns provide most of that signal. 

But using AI Max on brand means introducing additional automation into your most predictable and efficient traffic source.

The promise and limitations of AI Max

AI Max expands search targeting beyond your existing keyword list by using keywords, landing pages, and site content as signals rather than strict targeting parameters.

Like dynamic search ads (DSA), AI Max can match to queries you didn’t explicitly target. But it goes further, reaching beyond the intent boundaries defined by your keyword set.

Google has positioned AI Max as the next step in Search automation, with DSA, automatically created assets, and campaign-level broad match settings scheduled to transition into AI Max in September.

The platform includes controls such as brand exclusions, URL exclusions, text guidelines, and location targeting. In accounts with strong conversion tracking, sufficient search volume, and reliable performance signals, AI Max may uncover incremental growth opportunities.

Many accounts haven’t reached that stage yet.

Your customers search everywhere. Make sure your brand shows up.

The SEO toolkit you know, plus the AI visibility data you need.

Start Free Trial

Get started with

Why AI surface eligibility isn’t a reason to rush into AI Max

Much of the recent interest in AI Max stems from Google’s push toward AI-powered search experiences.

AI Overviews now reach 2.5 billion monthly users, according to Google. Ads appear in 25.6% of AI Overview results, Semrush data shows.

As Google continues expanding AI-driven search experiences, advertisers are understandably focused on maintaining visibility across those surfaces.

That concern is reasonable. The problem is that AI Max is often presented as the solution before advertisers address the measurement, conversion, and account structure issues that determine whether the automation can succeed.

Google Ads representatives typically pitch AI Max for brand campaigns by claiming it’s necessary for eligibility in AI Mode and AI Overviews on brand searches. But this isn’t accurate.

Ginny Marvin, Google Ads liaison, confirmed that three campaign types are eligible to serve in AI Overviews: broad match with Smart Bidding, Performance Max (PMax), and AI Max for Search.

However, exact match keywords aren’t eligible to serve in AI Overviews at all, even when identical broad match keywords exist in the same account.

So, the eligibility picture looks like this:

PMax and AI Max do broadly the same job in terms of AI surface eligibility. So if you run PMax brand campaigns, you’re already covered. Adding AI Max won’t unlock anything new, as it’ll only add another automation layer to a setup that’s already eligible.

So, when reps position AI Max on brand as the answer to AI surface eligibility, advertisers should stop and ask why this feature takes priority over fixing the account’s foundation.

Test data doesn’t support Google’s AI Max claims

When AI Max was in beta, Google stated that advertisers who activate the feature would see 14% more conversions, and those running exact and phrase match keywords would likely see a 27% increase in conversions.

Google also indicated that advertisers who enable the full AI Max feature suite see 7% more conversions on average. Independent testing has produced more mixed results.

The evidence for AI Max remains mixed

Across 600 accounts, Smarter Ecommerce found that AI Max delivered a 35% lower return on ad spend (ROAS) than traditional match types. AI Max accounted for just 0.57% of total ad spend in those accounts, indicating that advertisers kept the budget to a minimum.

After running a four-month test, Xavier Mantica found that AI Max had the most expensive conversions. While AI Max cost $100.37 per conversion, phrase match cost $43.97 per conversion, and exact match cost $52.69 per conversion. And Ezra Sackett tested 30,000 search terms with AI Max, only to find that 99% of impressions delivered zero conversions.

After a 23-test analysis of 16 advertisers, Andy Goodwin noted improved Quality Score and ROAS when advertisers used the AI Max full feature suite. But he tested mature advertisers and used text customization in only 50% of tests and URL optimization in just 44%. This suggests advertisers were cautious about enabling every AI Max feature.

However, none of this data is brand-specific. AI Max may deliver value in the right context, but an exact match defensive brand campaign that already performs well isn’t the ideal place to test a new automation product that depends heavily on signal quality. This is especially true for accounts that haven’t solved the underlying data problems feeding the automation.

AI Max attribution gets murky on brand

AI Max doesn’t always find genuinely new search terms, according to Adalysis. In some cases, it simply takes credit for the queries that exact and phrase campaigns were already winning.

Because AI Max treats keywords as signals rather than targeting parameters, impressions that would previously have been attributed to your exact match keyword can end up attributed to AI Max instead.

This reporting issue can be significant for brand campaigns. Brand traffic is already the highest converting traffic in most accounts.

Flip on AI Max, and suddenly you see an uplift. But it’s difficult to tell if it’s incremental or if preexisting branded performance simply appears in a different automation bucket.

Brand controls don’t work consistently

Google’s pitch leans heavily on brand controls. AI Max offers inclusions, exclusions, and guardrails that supposedly keep the match type tightly focused. In practice though, these controls don’t always work well.

Adalysis notes that competitor terms occasionally slip through and brand terms sometimes match to non-brand queries. DAC reports overlap between brand and non-brand terms as well as unintended language matching. And LBBOnline finds relevance hovering around 50% in some campaigns.

Brand controls could improve over time. But the available evidence doesn’t support treating AI Max as a low-risk switch for tightly controlled defensive brand campaigns.

What to consider before testing AI Max on brand

Before expanding automation into a defensive brand campaign, ask these questions.

1. Are the conversion signals trustworthy?

Have you separated macro and micro conversions? Do offline imports work correctly? Does lead quality feed back into the platform, or does Google still optimize equally toward every form fill?

If the signal quality underneath the account is poor, AI Max will amplify it instead of fixing it.

2. Have you already explored generic growth?

In many of the accounts I audit, budget, weak landing page alignment, poor structure, and outdated query management limit generic campaigns. This is where you usually find incremental growth, not inside an already dominant brand campaign.

3. Does the account give automation enough useful learning data?

AI Max isn’t magic. It reflects the quality of the signals underneath it.

If most of the account’s meaningful conversion volume comes from brand, then turning AI Max on in a brand campaign may reinforce existing dependency on branded traffic rather than helping the account grow beyond it.

4. Are brand + modifier searches already structured properly?

“Brand + reviews,” “Brand + pricing,” “Brand + near me,” and product intent variations often deserve their own campaign strategy entirely. AI Max shouldn’t become a substitute for good account architecture.

5. Do you have a strategic reason to expand the brand campaign?

If so, test carefully using experiments. That’s a business decision, not a checkbox recommendation from a rep who hasn’t looked deeply enough at the account to understand where the real opportunities actually are.

See the complete picture of your search visibility.

Track, optimize, and win in Google and AI search from one platform.

Start Free Trial

Get started with

AI Max only works as well as the signals feeding it

AI Max may grow into something genuinely useful over time. Remember, PMax went through a similar evolution and is in a much stronger place now than it was early on.

But automation only works as well as the signals feeding it. Right now, the issue is that the foundations underneath the automation still aren’t strong enough. Better conversion frameworks, measurement, account structure, and feedback loops make automation smarter.

If brand remains the best-performing campaign in the account, the bigger question is why the rest of the account hasn’t caught up yet. 

Above all else, don’t confuse Google’s automation priorities with your account priorities.

Google is expanding experimentation capabilities in Performance Max, giving advertisers more ways to test creative assets and measure campaign performance before making large-scale changes.

What’s happening. Google is rolling out new asset experiments for Performance Max campaigns, allowing advertisers to test how different creative assets affect results.

The feature enables marketers to compare entirely new asset groups, evaluate the impact of adding individual assets, or measure the performance of seasonal creative against evergreen content.

Advertisers will also be able to test assets generated through Google’s Asset Studio.

The big picture. Performance Max has long automated campaign optimization across Google’s inventory, but advertisers have had limited visibility into the impact of creative changes.

The new experiments aim to give marketers a more controlled way to evaluate creative decisions before applying them across campaigns.

Between the lines. The addition of a second success metric could be particularly valuable for advertisers balancing competing objectives, such as maximizing conversions while maintaining efficiency targets.

Rather than declaring a winner based on a single KPI, marketers will be able to evaluate how changes affect broader campaign performance.

What else is new:

• Conversion lift studies and experiments are being brought together under one Experiments page.
• Additional experiment and measurement capabilities are planned for future releases.
• Expanded support for manager accounts (MCCs) and the Google Ads API is expected to begin rolling out in the coming weeks.

Why we care. Creative remains one of the biggest levers available to Performance Max advertisers, yet testing new assets often involves risk. The new experimentation tools provide a structured way to validate creative decisions with data before fully committing budget.

What to watch. As Google continues investing in automation and AI-generated creative, asset testing is becoming increasingly important. The ability to directly compare human-created, seasonal, evergreen, and AI-generated assets could offer advertisers deeper insight into what drives performance across Performance Max campaigns.

The bottom line. Google is giving Performance Max advertisers more sophisticated testing capabilities, making it easier to evaluate creative changes, measure results across multiple KPIs, and manage experiments from a centralized location.

First spotted. The update was first spotted by PPC News Feed.

OpenAI is expanding its advertising ambitions inside ChatGPT, beginning an early test that allows multiple advertisers to appear within a single ad placement.

What’s happening. The company is testing multi-advertiser ad units across a small subset of ChatGPT ads, according to a product update sent to advertisers.

Rather than displaying a single sponsored result, the new format will group multiple relevant ads together in one placement. Eligible ads will be sold through a second-price auction model, a common pricing mechanism used across digital advertising platforms.

OpenAI says the goal is to improve product discovery for users while creating more opportunities for advertisers to engage with users during high-intent conversations.

Meanwhile, in Ads Manager Beta. OpenAI also announced several new campaign management features for advertisers:

• Advertisers can now convert existing campaigns from lifetime budgets to daily budgets.
• CPM campaigns can be cloned and converted to CPC bidding with one click.
• Impression-based campaigns now support custom CPM max bids.
• Bulk editing is available directly within the Ads Manager interface.
• Daily budgets will transition to an average daily budget model with weekly pacing flexibility.
• Geographic targeting is expanding beyond the U.S., Canada, Australia, and New Zealand to include the U.K., Japan, South Korea, Brazil, and Mexico.

Why we care. The updates bring OpenAI’s ad platform closer to the functionality marketers expect from mature advertising ecosystems, reducing campaign management friction while expanding targeting opportunities internationally.

What to watch. The multi-advertiser placement test could provide an early signal of how aggressively OpenAI intends to monetize ChatGPT. If successful, the format may become a larger part of the platform’s ad inventory strategy while offering advertisers more opportunities to reach users during purchase and research journeys.

The bottom line. OpenAI is steadily building out its advertising stack, but the biggest development may be its experiment with showing multiple advertisers in a single ChatGPT ad placement — a move that could reshape how sponsored content appears within AI conversations.

Google is changing the rules framework that governs Local Services Ads, updating policy language and aligning advertiser requirements with its new badge system.

What’s happening. On July 6th Google will update its Local Services Ads policies to improve readability, revise terminology, and remove requirements that no longer apply to advertisers.

As part of the update, Google will rename “Local Services platform policies” as “Local Services Ads requirements.”

The changes build on the company’s recent overhaul of the Local Services Ads badge system, including updates to Google Guarantee badges and advertiser verification standards.

Why we care. While these changes are mostly administrative, advertisers should pay attention because the new “requirements” framework could make it easier for Google to tie compliance standards directly to badge status in the future. For agencies and local businesses, it’s another indication that maintaining verification credentials and meeting platform standards will remain critical for competing in LSAs.

The big picture. Google says the policy refresh is intended to better align advertiser requirements with the new badge framework while making compliance guidance easier to understand.

The company is not positioning the update as a major policy crackdown. Instead, the focus appears to be on simplifying existing rules and modernizing the way requirements are communicated to businesses.

The bottom line. Google is refreshing the policy framework for Local Services Ads, replacing “platform policies” with “requirements” and aligning advertiser guidance with a new badge-driven approach to trust and eligibility.

People have been calling the keyword dead since at least 2010. Yet here we are in 2026, still using keywords to show ads on Google.

Advertisers weren’t wrong to equate the loss of control with the death of the keyword. The keyword simply couldn’t disappear until Google had something better to replace it.

At Google Marketing Live (GML) last month, we may have seen that replacement. AI Brief is a Gemini-powered control layer that lets you steer AI Max using prompts-first language.

At first glance, AI Brief may seem like just another AI Max feature. AI Max is still trying to gain traction among advertisers. So couldn’t advertisers simply ignore it and stick with keywords?

Probably not.

When users shifted to mobile, Google eventually pushed advertisers toward Enhanced Campaigns. The conditions may now be in place for a similar transition, this time from keywords to prompts.

Consider the other announcements from GML. AI Mode surpassed 1 billion monthly users. The search box is getting its biggest redesign in 25 years. Users in AI Mode are also submitting queries that are, on average, three times as long as traditional searches.

Whether advertisers like it or not, people are increasingly using prompts instead of keywords to find information.

With AI Brief, the replacement for the keyword finally exists. We can now target prompts with prompts. Combined with the consumer-driven shift away from keyword-based searches, that makes the keyword’s obituary much easier to believe.

The keyword is dying because users stopped using it

Most “keywords are dead” arguments over the past decade were supply-side stories. Google reduced broad match’s control, made RSAs decide the best ad variation, and let Smart Bidding set bids to help any keyword deliver on its underlying financial goals. They also stopped showing every query in search terms reports, all steps framed as Google taking the keyword away.

Now it’s different. The pressure is coming from the demand side.

People are asking Google longer, more conversational questions because Google built a search experience that invites them to. The new search box, the biggest upgrade in 25 years, dynamically expands as you type. You no longer pick a “mode” before you ask. The interface itself is telling consumers that “running shoes” is no longer the only way to ask for what they really want.

If you’re an advertiser, the question stops being “Do I want to use keywords?” It becomes “How do I show up in a query a keyword can’t possibly match?” Trying to capture a paragraph of context with three positive match types and one negative is, let’s be real, increasingly absurd.

Optmyzr’s 2026 Match Type Study shows the same pattern from the spend side. We analyzed 30,000 Google Ads accounts in February 2026 across all Search campaigns with active keyword spend. (Disclosure: I’m the cofounder and CEO of Optmyzr.)

Exact match has lost nearly 10 percentage points of spend share since 2022, while broad match has climbed steadily to become the dominant match type by budget. 

Phrase match, meanwhile, consistently punches above its weight, holding the largest share of non-branded spend and leading on conversion rate in both ecommerce and lead-gen segments. 

Advertisers are clearly growing more comfortable trusting Google’s AI with broader targeting, a shift attributed to Smart Bidding’s maturation rather than exact match losing its performance edge.

The other tell is that Google isn’t alone here. We recently started managing ads on ChatGPT, and OpenAI’s ad surface is keyword-optional from day one. 

When the company that invented keyword advertising and the company reinventing search both ship a keyword-optional product, that means something. At this point, we’re just arguing about how fast the keyword is dying.

Your customers search everywhere. Make sure your brand shows up.

The SEO toolkit you know, plus the AI visibility data you need.

Start Free Trial

Get started with

AI Brief is a technical replacement for keywords

Unsurprisingly, AI was the topic that drove nearly every announcement at GML 2026. At I/O the day before, Sundar Pichai, Google’s CEO, even said that Google’s migration to become an AI-first company was nearing completion, with AI agents providing the final push and rewriting the last remaining code. Downstream from all the talk about AI is the realization that consumers now prompt rather than search with keywords.

AI Brief is one way to operationalize the required evolution for advertisers to keep up with consumer behavior. Powered by Gemini, it lets you describe, in your own words, what your business is, what your messaging should and shouldn’t say, the searches you want to capture or avoid, and the audience you’re trying to reach. 

Google calls these messaging guidelines, matching guidelines, and audience guidelines. Internally, I think of it as: tell the model what you’d tell a new media buyer on their first day.

Then AI Brief echoes back how it understood your requests and shows preview samples of the assets and queries it thinks you meant. You push back if it’s off. You iterate. When you’re happy, you lock in the brief.

That’s a meaningfully different interaction model than a keyword list. A keyword list is a static artifact. A brief is a negotiation. It can adapt as your business changes without you reuploading hundreds of new keywords.

There’s a parallel in the world of coding, where AI has arguably had the biggest impact with agentic code writers and vibe-coding systems like Lovable.dev. The idea is that the code we write to have software achieve an outcome should be merely a temporary artifact reflecting the current abilities of the tech. 

Coders should focus on writing the prompts that describe the goals of the web page rather than the code needed to achieve those goals. The prompt instructs the software what it should do and how to do it safely. AI can then write the code that executes the task on demand, using the latest capabilities while staying grounded in the prompts that define its purpose.

This is what Sam Altman called “software on demand” at the GPT-5 launch, the idea that AI can “instantaneously create an entire piece of computer software for you.”

Google echoed the same vision at I/O 2026, where Pichai described Search using Gemini and Antigravity to build custom experiences, dynamic layouts, and persistent mini apps on the fly. Software generated in response to what each user needs, in the moment they need it.

People need to be purposeful about work. Your purpose at work isn’t to write emails and work with spreadsheets. It’s to achieve certain outcomes, and writing emails and using spreadsheets is how that gets done. Stop worrying about how and start thinking about the real goal: growing your ad revenue by 10% while maintaining similar margins.

Keywords are the “how,” not the “why.” AI Brief is actually closer to letting us manage the “why” while letting AI figure out the “how.”

How to try AI brief now

AI Brief is rolling out in English for AI Max for Search first, then Performance Max and AI Max for Shopping. Existing text guidelines will migrate into AI Brief automatically as messaging guidelines. 

So yes, this is starting as an AI Max feature, and you may not be using AI Max because several practitioners note that AI Max can pull in junk traffic on lead-gen accounts, competitor-heavy verticals, and new campaigns with thin signal. Some veteran marketers have been turning AI Max off in those situations.

The practical playbook shared during a recent PPC Town Hall is solid: start new campaigns in Phrase, promote the winners to Exact, and layer Broad and Smart Bidding on top once you have data. 

With the advent of AI Brief’s matching guidelines, advertisers can further tweak their targeting by saying, “prioritize searches for X, avoid Y.” But this strategy still requires a human who knows the account to pull that lever. So don’t unplug your keyboard just yet.

The new funnel, and why short keywords still have a job

Andrew Lolk and Kirk Williams pushed me on a real edge case in the LinkedIn discussion that led to this piece: the newborn photographer whose entire business depends on someone in their city typing “newborn photographer” and converting on the first ad that shows.

Short, transactional queries won’t disappear. So why not keep traditional search campaigns with keywords around to handle these types of queries? I think it’s reasonable to have two campaign types for different jobs. But their relationship is a funnel, not a parallel.

Here’s how I see it shaping up:

• AI prompts for discovery: “I just had a baby and I want to remember this period. What are some ideas?”
• AI prompts for research: “Compare lifestyle newborn photographers to studio newborn photographers in the Bay Area.”
• Short keyword to buy: “Newborn photographer Los Altos.”

If you only show up at the bottom of that funnel, you’re betting your entire business on being the first short-keyword click. If you’re not present in the discovery and research prompts above it, you’re not in the consideration mix when the short query happens. 

The reason a user may do that short query is that they already know more or less who they’d buy from, and they’re now looking for the best offer from a shortlisted set of options. The conversational layer feeds the transactional layer. Ignore it, and the transactional volume eventually stops coming to you.

This is also why I don’t think Google maintains two parallel systems forever. The short-keyword volume will keep shrinking relative to AI prompt volume, and at some point, the economics of supporting both stop working. 

Further, AI-first campaign types will soon be great at converting agentically, using the Universal Commerce Protocol and other new methods being developed to allow agents to transact for their humans.

What AI Brief does to the four human PPC roles

I’ve argued for years that PPC pros take on four roles in an automated world: 

• Teacher.
• Doctor.
• Pilot.
• Restaurateur. 

These roles continue to explain the PPC manager’s world quite well, but with some new nuance.

The teacher 

This role is the most direct analogy. You used to teach the machine what to target by handing it the end result: a keyword. 

The funny part is that for many of us, that keyword was already generated by feeding an LLM a prompt and cleaning up the output. 

AI Brief lets you skip the lossy translation step. Hand the machine the prompt itself, not the artifact it produced. The teaching gets richer because nothing gets lost.

The doctor

The shift is from “prescribe Drug X” to writing down, in structured language, what the patient actually needs. 

The treatment can then evolve as the patient’s condition and the available solutions change. Keywords were restrictive: one symptom, one prescription. 

Briefs and prompts allow freedom and evolution. That’s what good medicine looks like, and that’s what good targeting looks like now.

The pilot

We need a new instrument panel. If we’re not aiming at keywords anymore, the search query report stops being the right gauge of how well Google is matching intent. 

We’ll probably see more search themes (buckets of intent that AI Brief is mapping into) replacing the line-by-line query list.

The restaurateur 

You write the menu and the concept brief so the chef (the AI) cooks. AI Brief is almost literally the concept brief. 

You define the cuisine, the values, the things the chef must never serve, and the kind of guest you’re cooking for. Then you taste, correct, and iterate. The kitchen runs.

If you want the longer-form version of where I think digital marketing automation is heading, I wrote it up earlier this year as AI skills, the next layer of marketing automation.

See the complete picture of your search visibility.

Track, optimize, and win in Google and AI search from one platform.

Start Free Trial

Get started with

Why AI Brief feels different

The keyword isn’t dying because Google decided to kill it. It’s dying because consumers stopped phrasing their needs in a couple of words.

AI Brief is the first structural replacement that seems to allow advertisers to express their intent in as rich a manner as consumers can now express theirs to a chatbot. That’s why this GML announcement felt like a more serious nail in the coffin of the keyword than the last several.

Control was about dictating keywords to Google. Leverage is about feeding the engine the right brief and letting the auction execute at a scale no human team can match.

We don’t have to escape automation. We have to coexist with it on better terms. AI Brief is a great eventual replacement for the keyword. Hand it your prompt. Watch what it does. 

Push back. Lock it in. Then you can move on to the parts of the job a machine can’t do, like knowing your customers and working on the goals that move their business in the direction they want.

Most PPC budget discussions focus on finding the right split between brand awareness and conversion-focused campaigns. That’s usually the wrong goal.

The optimal balance changes constantly based on business stage, market saturation, seasonality, competitive pressure, and revenue objectives.

Yet many teams still treat the funnel split as a fixed decision: 40% upper funnel, 60% lower funnel, set it and forget it. That might be the right ratio today and completely wrong in six months.

Every budget conversation eventually comes down to the same argument. Someone wants to cut brand awareness spend because it doesn’t convert directly. Someone else warns that if you only chase conversions, the pipeline dries up in 12 months.

Both are right, which is what makes this so difficult.

The lower-funnel case is easy to make

When most PPC managers talk about the lower funnel, they mean Shopping, Performance Max, and high-intent Search. 

Someone typing “buy running shoes new york” has already decided they want the product. Shopping shows the right SKU at the right price. PMax chases the conversion signal across every Google surface. The attribution is clean, the ROAS is visible, and the CFO is happy.

The problem is that this demand already exists. These campaign types harvest intent. They don’t create it. Every conversion you get from a high-intent search term or a Shopping click is the result of awareness that was built somewhere else: 

• A YouTube pre-roll.
• A friend’s recommendation.
• A social post.
• Years of brand presence in the market. 

You’re collecting fruit from a tree you didn’t plant.

Search is worth treating separately here because it doesn’t sit neatly at the bottom of the funnel. A query like “best running shoes for marathon training” is informational. 

The person is researching, not buying. AI Max and broad match expansion in Google Ads are pushing Search campaigns further into this territory, meaning Search can serve both ends of the funnel depending on how it’s configured and which queries it actually captures. 

It’s worth auditing your Search terms regularly through this lens: How much of your Search spend is closing existing demand versus reaching people earlier in their decision-making process?

This works until it stops working. And the signal that it’s stopping usually arrives too late. 

When branded search volume flatlines, CPCs on your core terms keep climbing because the same pool of high-intent users is getting more expensive to reach, and new customer acquisition starts to plateau while retention holds steady. These are the symptoms of a brand that’s been living off existing demand without replenishing it.

Lower-funnel efficiency is real. But it’s also borrowing against the future.

Dig deeper: PPC budget planning: Aligning business goals, ad spend, and performance

Your customers search everywhere. Make sure your brand shows up.

The SEO toolkit you know, plus the AI visibility data you need.

Start Free Trial

Get started with

The reseller trap: When your lower funnel depends on someone else’s brand

There is a version of this problem that’s specific to resellers and multi-brand ecommerce, and it doesn’t get discussed enough.

If you sell branded products you don’t own, your lower funnel can work extremely well in the short term. 

Shopping and Search campaigns for established brands convert efficiently because the brand owner has already done the awareness work. You’re harvesting demand that Nike, Adidas, or whoever else has spent years and significant budgets building.

The structural risk is that you have no control over that demand. If the brand owner reduces its marketing investment, pulls out of a market, or simply fades in relevance, your Shopping and Search volume follows. 

You can’t counter it with your own PPC spend because the underlying interest isn’t there to harvest. The tree stops producing fruit, and you never owned it.

This creates two strategic imperatives that are easy to deprioritize when the lower funnel is performing well. 

• Own-brand development: products or lines that you control, where you own the brand equity and can invest in awareness independently. 
• Reseller brand building: investing in the upper funnel to make your own name well known, so customers think of you as the destination regardless of which brands you carry. A consumer who searches for your store name rather than a specific brand is much more resilient than one who only finds you through a branded product query.

Both require some form of upper-funnel investment. Own-brand development needs awareness campaigns to build product recognition from scratch. Reseller brand building needs a consistent presence across Demand Gen, YouTube, and Display to make your name synonymous with the category, not just the brands within it. That’s only within Google’s ecosystem. 

To complete the picture, you might also include SEO, word of mouth, pop-up events, local advertising, and more. Brand building has no limits.

Neither of these investments shows up in this month’s ROAS report. Both show up in next year’s business resilience.

Upper funnel is inventory management

Brand awareness spend is often framed as the soft, hard-to-measure part of the budget. The part you do when you have money left over. That framing gets it exactly backward.

Upper-funnel investment is how you build the pool of future converters. Every person who sees a Demand Gen ad on YouTube or Google Display today and doesn’t click isn’t a failed impression. They’re a potential high-intent searcher in three weeks. You’re filling the top of the pipeline that your Shopping and Search campaigns will harvest later.

Google’s Demand Gen campaigns make this dynamic particularly visible within a single platform. You can run Demand Gen to reach in-market audiences who don’t yet know your brand, then watch Search impression share and branded query volume respond over the following weeks. The lag is real and measurable. 

Upper-funnel spend today shows up in lower-funnel performance next month, not this week. That delay is why it gets cut first when budgets tighten, and why cutting it tends to hurt six to eight weeks later rather than immediately.

Teams that manage this well think of Demand Gen not as brand spend, but as pipeline investment. The question isn’t “What is the ROAS on this campaign?” It’s “How much qualified demand am I creating for my Shopping and Search campaigns to close?”

Dig deeper: Paid media efficiency: How to cut waste and improve ROAS

Why a fixed split is the wrong answer

The 70/30 or 60/40 rules you read about are averages across many businesses in many contexts. They’re useful as a starting point and useless as a long-term policy.

Consider what changes the optimal split.

• A new product launch needs heavy upper-funnel investment upfront because awareness is zero. 
• A mature product in a saturated category needs it, too, because every competitor is also harvesting the same pool of high-intent searchers, and the only way to grow is to expand the pool. 
• A seasonal business approaching peak needs to have already done its upper-funnel work before the peak hits because awareness doesn’t respond fast enough to be built in-season.

Equally, a business in financial distress or facing a short-term revenue target can’t afford to wait eight weeks for upper-funnel investment to mature. The right answer in that moment is to focus on the lower funnel, accept the trade-off consciously, and plan to reinvest in awareness as soon as the pressure lifts.

The point is that both of these decisions are correct in context. A fixed split ignores context entirely.

Building a dynamic split logic

Rather than a fixed ratio, the most useful framework is a set of conditions that trigger a shift in either direction.

Shift budget toward upper funnel when:

• Branded search volume is flat or declining quarter over quarter.
• New customer acquisition cost is rising while retention metrics hold.
• You’re entering a new market or launching a new product.
• Competitors are visibly increasing their brand presence.
• You’re approaching a peak season with at least six to eight weeks of runway.
• You’re a reseller whose top brands are showing declining search interest or reduced marketing activity.

Shift budget toward lower funnel when:

• You have a short-term revenue target that can’t wait.
• Upper-funnel campaigns have been running long enough to build measurable awareness, and the conversion window is now.
• Cost per acquisition on Shopping or Search is below target, and scaling makes sense.
• Audience saturation on Demand Gen is high, meaning you’re reaching the same people repeatedly without expanding reach.

Within Google Ads, the data to monitor this is available without external tools. Branded query volume in Search Terms, impression share trends on non-branded terms, Demand Gen reach and frequency metrics, and new versus returning customer segmentation in conversion data together give you a reasonable picture of where the funnel is healthy and where it isn’t.

The review cadence matters as much as the metrics. Monthly is the minimum for a funnel split review. Quarterly is too slow. By the time a quarterly review catches a declining branded search trend, you’ve already lost several weeks of pipeline-building time.

See the complete picture of your search visibility.

Track, optimize, and win in Google and AI search from one platform.

Start Free Trial

Get started with

The conversation nobody wants to have

The reason funnel balance stays broken in most organizations isn’t analytical. It’s political.

Lower-funnel spend is easy to defend in a meeting. The ROAS is there, the conversion numbers are there, and the CFO can see a direct line between spend and revenue. 

Upper-funnel spend requires a different kind of argument: “This investment will make our Shopping and Search campaigns work better in six weeks.” That argument is harder to make, easier to cut, and almost impossible to defend when someone asks for a quick win.

The answer isn’t to stop making the argument. It’s to change the evidence you bring to it. 

• Track branded search volume as a leading indicator. 
• Build a view that shows Demand Gen reach in month one and Search conversion volume in month two alongside each other. 
• Make the lag visible and the relationship concrete. Once the data tells the story, the conversation gets easier.

Budget allocation isn’t a one-time decision. It’s an ongoing signal about what kind of growth you’re building. 

Optimizing purely for this month’s ROAS is a choice. So is investing in the demand that will drive next quarter’s revenue. 

And if you’re a reseller, it’s also a decision about whether your business is built on a foundation you control or one you’re renting from brand owners who have their own priorities.

The best PPC teams do both, and they know when to lean in each direction.

Dig deeper: How to optimize B2B PPC spend when budgets and confidence are low

Here’s something worth sitting with for a moment.

Your competitors are running ads on ChatGPT. You can’t see them. You don’t know which prompts they’re bidding on, what creative they’re running, or how their presence compares to yours. And unlike Google Ads (where Auction Insights at least gives you a rear-view mirror), there’s currently no native way to get any of that picture on ChatGPT.

That’s the blind spot. And it’s bigger than most search teams realize.

OpenAI launched advertising inside AI-generated responses earlier this year. Brands moved fast, all in within weeks. The minimum spend dropped, the Ads Manager launched, and a genuinely new ad channel was born. With ChatGPT advertising expected to expand to U.K. markets soon, the window for early-mover advantage is closing faster than it looks.

We’ve been watching since day one. Here’s what we’ve found.

What does ChatGPT Ads actually look like right now?

We analyzed nearly 1 million query indexes across 20 industries and five markets (the U.S., U.K., Australia, New Zealand, and Canada) between March 2026 and May 2026. The data tells a clear story.

It’s a U.S.-first channel. Everywhere else is still warming up.

In the U.S., ChatGPT served ads on 4.5% of queries. Across roughly 170,000 U.K. indexes in the same period? We found zero ads. The U.S. accounts for around 90% of all ChatGPT ad placements in our dataset. Canada and New Zealand are active. Australia’s at 1.6%. The U.K. hasn’t flipped yet, but it will.

For U.K. search teams, that’s a two-sided finding. The channel isn’t live here yet. But your U.S. competitors have had months to figure out which prompts convert, what creative works, and where the real opportunity sits. When U.K. advertising opens up, they won’t be starting from scratch. You might be.

There’s only one ad per response the majority of cases

In the U.S., ChatGPT averages just 1.06 ad items per ad-bearing answer. That means in the vast majority of responses, there’s a single sponsored slot. Not three. Not a carousel. One.

That changes the stakes completely. In Google Ads you can hold position two or three and still get clicks. On ChatGPT, you’re either in the answer or you’re not. Share of voice here is binary in a way paid search has never quite been before.

Some industries are blocked for now

Four categories returned zero ChatGPT ads across the entire dataset: Legal, Pharma, Banking, and Nonprofit. Healthcare was near-zero at 0.45%. This looks like deliberate OpenAI policy rather than lack of demand. These restrictions will evolve. When they do, the teams that are already watching will have a head start.

The hottest categories aren’t the ones you’d expect

Logistics tops the chart at 12.4% ad frequency, followed by Home & Garden at 12% and Beauty & Cosmetics at 10%. These are categories building serious ground on ChatGPT right now, well above a platform average of around 3.3%. Media & Entertainment (8%), Insurance (7.2%), and Energy & Utilities (6.4%) aren’t far behind.

Retail is where the real money is flowing

Retail & Fashion makes up 24% of U.S. query volume but accounts for 39% of all U.S. ad items. That’s not a scrape artifact. It’s genuine advertiser demand. With an ad frequency of 6.55% against a U.S. average of 4.5%, retail brands are competing hard for ChatGPT presence. The category accounts for more than a third of all ad placements in our full dataset.

So what’s the actual problem?

Here’s where it gets frustrating. And we’ll be straight with you about it.

Every serious search practitioner lives and dies by competitive intelligence: auction Insights, competitor ad copy, impression share trends. You know this stuff because running campaigns without it isn’t a strategy. It’s guesswork.

None of those tools exist for ChatGPT Ads.

OpenAI’s native Ads Manager shows you your own data. Your spend, and basic performance metrics such as impressions, clicks, CPC, and CTR, and that’s it. What you can’t see: which competitors are showing up alongside you, which prompts are triggering their ads, what creative they’re running, or how your share of voice stacks up across the market.

You’re spending real budget on a channel where you can only see yourself. In a format where there’s one winner per response. That’s a problem worth taking seriously.

What does full visibility actually look like?

That’s the gap we built ChatGPT Ads Intelligence to close.

We monitor 300,000+ prompts daily across the markets where ChatGPT Ads are live, giving you the whole-market view that’s been missing from this channel since day one. It’s the same competitive intelligence approach that’s made Adthena essential for Google paid search, now fully applied to ChatGPT.

You can see which competitors are bidding on your prompts, track share of voice week on week, and find the greenfield prompts (the high-intent queries where no one’s advertising yet) before someone else does.

That last part matters more than it might sound. In a new channel where positions aren’t entrenched yet, first-mover advantage is still genuinely available. It won’t be forever.

Try ChatGPT Ads Intelligence free for 21 days and see the full picture.

Why does this matter beyond ChatGPT?

Let’s zoom out for a second.

Search isn’t one place anymore. It hasn’t been for a while. Users are turning to AI-native interfaces like ChatGPT and Perplexity for exactly the kind of high-intent queries paid search was built around: product recommendations, service comparisons, purchase decisions. The intent is there. The ads are starting to follow.

For search practitioners, the job description is expanding whether you signed up for it or not. The same rigor you apply to Google Ads (competitive monitoring and share of voice tracking) needs to extend to wherever high-intent search is actually happening.

The brands paying attention to ChatGPT Ads now are the ones who’ll be hardest to displace when the channel fully matures. We’ve seen this movie before. The early Google Ads practitioners who understood the platform first built advantages that took years to close.

That window is open right now. Our data shows it clearly.

Ready to see what’s happening on ChatGPT Ads? Start your free 21-day trial of Adthena’s ChatGPT Ads Intelligence.

Google updated its personalized advertising policy documentation to clarify how restricted targeting rules apply to Demand Gen and Discovery campaigns, particularly when advertisers promote products or services tied to sensitive interest categories.

The big picture. The update appears in Google’s “Restricted targeting in Personalized Advertising” policy documentation and focuses on explaining potential ad serving limitations rather than introducing new policy restrictions.

What’s changing. Google updated its help documentation in June to provide additional guidance on how Demand Gen and Discovery campaigns interact with personalized advertising restrictions.

The changes specifically address campaigns that target products and services associated with sensitive interest categories.

The fine print. The update is a clarification to existing policy guidance, not a new policy announcement.

Google says the revised documentation includes additional information about potential serving implications when advertisers use audience targeting for products or services that fall into restricted categories.

Sensitive interest categories can include areas such as:

• Health conditions
• Financial hardship
• Personal difficulties
• Other topics that Google considers sensitive under its personalized advertising policies

Between the lines. Demand Gen campaigns rely heavily on audience signals and personalized targeting to reach users across YouTube, Discover and Gmail.

As adoption of Demand Gen continues to grow, advertisers have increasingly sought clarity around how Google’s sensitive interest policies affect audience eligibility, reach and campaign delivery.

The documentation update suggests Google is responding to those questions by providing more explicit guidance on when targeting restrictions may limit campaign performance.

Why now. The clarification comes as Demand Gen becomes a larger part of Google’s advertising ecosystem and more advertisers shift budgets from Discovery campaigns into Google’s AI-powered audience products.

Why we care. For advertisers operating in regulated or sensitive industries, understanding these restrictions is becoming increasingly important to campaign planning and audience strategy.

What to watch. Advertisers running Demand Gen campaigns in healthcare, financial services or other potentially sensitive verticals may want to review the updated guidance to understand whether targeting choices could affect reach or ad delivery.

Microsoft is widening advertising opportunities for cryptocurrency exchanges by allowing them to run Audience Ads in all markets where crypto advertising is already permitted.

The big picture: The update extends cryptocurrency advertising beyond traditional search placements, giving eligible exchanges access to Microsoft’s Audience Ads inventory across its broader network.

What’s changing. Microsoft has updated its advertising policies to allow cryptocurrency exchanges to use Audience Ads in all approved crypto advertising markets.

The expansion applies only to advertisers that comply with Microsoft’s Cryptocurrency and Related Products policies and any applicable local regulations.

Why we care. Audience Ads allow advertisers to reach users across Microsoft’s native advertising network, which includes placements on content, news and partner sites.

For cryptocurrency exchanges, the change creates additional opportunities to build awareness and engage potential customers beyond search-driven intent.

The fine print. The policy update does not represent a relaxation of Microsoft’s cryptocurrency advertising requirements.

Advertisers must still meet all eligibility requirements and comply with the company’s Cryptocurrency and Related Products policies, which vary by market and regulatory environment.

What to watch. Advertisers will be watching to see whether the expanded inventory leads to increased adoption of Audience Ads among cryptocurrency exchanges and whether Microsoft further broadens crypto advertising opportunities in additional markets.

The best TV ads don’t just generate awareness. They generate searches.

When a high-impact campaign airs, viewers immediately turn to Google, YouTube, and other platforms to learn more, find products, or continue engaging with a brand. The challenge isn’t generating that interest. It’s being ready to capture it.

A recent World Cup campaign from Fox Sports shows exactly how this process works — and why SEO and PPC planning need to start long before an ad goes live.

A World Cup ad that created more than awareness

On May 13, creative intelligence platform DAIVID published new data ranking the most emotionally engaging World Cup ads released so far, and Fox Sports’ promo “Miracle” led the field by a clear margin.

DAIVID tested 31 World Cup ads released online and ranked them by the intensity of positive emotions they generated, the measure most closely linked to long-term brand impact. Here’s how the top five shook out:

Adidas’ “Backyard Legends” and Pepsi’s “Football Nation Is Here” narrowly missed making the top five. DAIVID will update the rankings throughout the tournament, meaning the creative competition is far from over.

But that table shouldn’t just be an advertising scorecard. It also represents a demand map. Every brand in the top five is generating search interest right now, weeks before the World Cup kicks off on June 11. The question isn’t whether their branded terms are seeing spikes in traffic, but whether their search teams are ready for it.

Now, let’s talk about that Fox spot in a bit more detail. Created by Fox Sports Marketing and Special US, and directed by Lance Acord, “Miracle” imagines Team USA doing the unthinkable: winning the World Cup, including a dramatic 3-2 victory over five-time champion Brazil in the 97th minute. 

U.S. soccer star Christian Pulisic sends in a corner kick, the ball is headed home in the dying seconds, and the country erupts. Soccer players end up on currency. Times Square is taken over by revelers.

Then, just as reality starts to reassert itself, in walks Mike Eruzione, captain of the legendary 1980 U.S. Olympic hockey team that miraculously beat the Soviet Union against all odds, with the only line the ad needed: “What? You don’t believe in miracles?”

The spot is set to Elvis Presley’s “The Impossible Dream.” Yes, really. They lean hard into Americana. And it works.

When DAIVID ran it through its AI-powered creative testing platform, trained on tens of millions of human responses, “Miracle” earned a creative effectiveness score (CES) of 6.99 out of 10, placing it in the top 14% of all ads ever tested by the platform, well above the industry average of 5.8. 

It generated intense positive emotions in 56.1% of viewers, 15.2% higher than the average ad. It held attention all the way to the end, with 66.9% still watching in the final three seconds versus an industry norm of 58.2%. Viewers were also 35% more likely to remember Fox as the brand behind it.

Three emotions drove its success: excitement (+85%), hope (+72%), and pride (+61%), all significantly above industry averages.

Ian Forrester, CEO and founder of DAIVID, puts it plainly: 

• “The conventional wisdom in advertising is that you make people laugh, or you make them cry. These are the reliable emotional levers. Hope is harder. It asks the audience to believe in something, which is a big ask in this time of economic and political turmoil. Fox Sports didn’t just clear that bar, they set a new one.”

That’s a masterclass in emotional advertising. It highlights a direct business problem that needs solving — fast.

Your customers search everywhere. Make sure your brand shows up.

The SEO toolkit you know, plus the AI visibility data you need.

Start Free Trial

Get started with

Why this is a search marketing problem, not just an advertising one

Here’s what happens the moment that Fox spot airs during a major broadcast window: millions of viewers grab their phones. They search “U.S. World Cup 2026,” “Christian Pulisic,” “Fox World Cup schedule,” “Mike Eruzione 1980,” “The Impossible Dream Elvis,” and dozens of other queries the Fox search team may or may not have prepared for.

According to a white paper called “TV Ads and Search Spikes: Toward a Deeper Understanding,” 75% of incremental search activity occurs within the first two minutes of an ad airing. Not the first hour. The first two minutes.

If your search campaign isn’t already live, optimized, and fully funded at that moment, you won’t just miss the opportunity, you’ll actively route warm, brand-interested traffic to your competitors.

This is the fundamental strategic failure that still plagues most organizations: Search marketing is treated as a last-click discipline, siloed from the creative and media teams that generate demand upstream. Search is the digital bridge for video-driven interest. Far too many brands let that bridge wash out every time a high-impact ad airs.

4 query types TV ads generate (and how to prepare for them)

The “Miracle” spot is instructive because it generates not one type of search query, but four distinct categories, each requiring a different strategic response.

Branded queries 

These are the most obvious searches you’ll see after an ad airs: “Fox Sports,” “Fox World Cup.” Basically, they’re your brand terms. If you’re Fox, you’re already winning these. But are you capturing 100% of impressions? 

Budget should surge the moment an ad goes live to absorb the volume spike, with established brands expecting up to a 20% lift in branded search volume during a major campaign.

Campaign queries 

These searches emerge from the creative itself, such as “U.S. wins World Cup,” “Miracle ad,” or “Impossible Dream commercial.”

They only exist because the ad aired. If Fox’s search team didn’t prebuild landing pages and keyword groups around these terms before the first broadcast, they left money on the table.

Asset queries 

Viewers often search for memorable elements featured in the creative, including songs, athletes, celebrities, or story references.

For the Fox ad, these might look like “song in Fox World Cup ad,” “who is Mike Eruzione,” “Christian Pulisic World Cup commercial.”

Viewers searching for the Elvis track or the 1980 hockey captain are highly engaged, highly curious, and highly convertible. These queries need to be anticipated in keyword planning sessions — not discovered two weeks after launch.

Category queries 

Some viewers skip the brand entirely and search for solutions, products, or viewing options related to the campaign’s broader theme.

For the Fox ad these might look like “how to watch World Cup 2026,” “World Cup streaming options,” “where to watch U.S. soccer.” 

A viewer, emotionally moved by “Miracle,” who then searches for one of these terms and lands on a competitor’s streaming service would be a direct cost of poor planning. 

Bidding only on brand terms during a TV flight while ignoring category-level terms is, bluntly, strategic negligence.

Dig deeper: AI for video advertising: 5 best practices for PPC campaigns

The 10/90 rule: Technology is the easy part

The good news is that search platforms now offer automated tools to sync bidding with broadcast schedules, detect search spikes, and adjust budgets in real time.

The bad news is that these tools may do about 10% of the actual work. The other 90% is human, and it has to happen before the ad airs.

That means you need to be in the room when the creative is being storyboarded to:

• Flag searchable hooks, such as songs, athletes, and visual gags, that will need keyword coverage.
• Prebuild landing pages that maintain visual and verbal continuity with the broadcast creative.
• Align search, video, and content teams around the questions viewers are likely to ask after seeing the ad.

Getting that alignment right matters. A viewer who searches “Fox Miracle ad” and lands on a generic programming grid will bounce immediately. The cognitive dissonance alone kills the conversion.

Viewers are also increasingly asking conversational questions triggered by video content.  Using our example, these might include “how does the Fox streaming app work,” “who plays in the World Cup this summer,” or “is Christian Pulisic injured.”

YouTube descriptions, structured metadata, and FAQ content need to be optimized for these queries before a campaign launches, not after.

Measuring what matters

While traditional TV metrics measure exposure, branded search volume measures intent. These are not the same thing, and confusing them is one of the most expensive mistakes in modern marketing.

The right framework is a Branded Search Lift Model (BSLM):

• Establish a rigorous baseline using 90 to 120 days of historical data (not the standard four weeks, which is too short to control for seasonality).
• Apply a time-series forecasting model to project expected volume without advertising.
• Measure the gap between expected and observed searches during and after the campaign.

That gap, incremental search lift, is your most honest signal of whether the creative is working. It can also serve as a diagnostic tool to identify where the funnel is leaking.

For “Miracle,” the emotional data suggests the spot will generate significant search activity across all four query categories, particularly for asset and category queries. 

The hope-and-pride emotional signature that DAIVID identified tends to drive social sharing, which in turn drives a fourth conversion pathway: 

• TV → Social → Search → Conversion. 

That means hashtag volume and social mentions should be tracked alongside search lift as correlated signals of a campaign that’s genuinely breaking through.

Dig deeper: The SEO shift you can’t ignore: Video is becoming source material

The feedback loop that changes everything

Here’s where this gets genuinely exciting: The relationship between TV creative and search data is reciprocal.

Search lift data is a low-cost, real-time proof of concept for your most expensive media investments. By running small-scale tests on YouTube or CTV and monitoring branded search lift for each creative variant, teams can identify which ads actually trigger digital action before committing massive budgets to traditional broadcast.

Conversely, TV performance data can and should inform search strategy. If “Miracle” generates a 60%+ spike in branded search, as emotionally resonant ads have been shown to do, that’s not just a media win. 

It’s a creative brief for the next campaign, a signal about which emotional levers to pull again, and evidence that should be sitting in front of every senior marketer and media planner in the organization.

The brands winning this game aren’t treating search and video as separate disciplines. They’re running them as a single, integrated demand engine. Video creates curiosity, search captures it, and data from both channels sharpens the creative for whatever comes next.

Barney Worfolk-Smith, chief growth officer at DAIVID, frames the opportunity well: 

• “For tentpole events like the World Cup, it’s a smart move to think more strategically about the relationship between TV and SEM. When effectiveness testing shows you’ve got a genuine firecracker of a TVC on your hands, that’s the moment to tighten the connection even further. This highly emotive Fox Sports campaign is a powerful reminder of the link between emotionally resonant advertising and uplifts in next-step intent.”

See the complete picture of your search visibility.

Track, optimize, and win in Google and AI search from one platform.

Start Free Trial

Get started with

Search belongs in the creative brief

Fox’s “Miracle” spot works because it dares viewers to feel something unfashionable. Hope. Possibility. The audacity of imagining a different outcome.

Search marketers should take the same lesson to heart when approaching their counterparts in TV and video. Stop waiting to be invited to the post-launch debrief. Walk into the creative brief. Ask what’s searchable. Plan the SERP with the same rigor applied to the media buy.

The dance has already started. The question is whether you’re going to watch from the bleachers while your competitors capture every lead you paid to generate, or whether you’re going to join in.

You wouldn’t dream of running your Google Ads campaigns without conversion tracking. So why are you still running Google Ads without uploading your customer list?

As third-party cookies phase out and privacy regulations tighten, you lose some of the traditional tracking capabilities that you (and Google Ads) rely on. Because of this, your own first-party data is the strongest lever you have left to steer Google’s automation.

Think about it: When every one of your competitors has access to the exact same Smart Bidding and AI targeting algorithms, you can’t win by relying on the same Google-owned data as everyone else. You win by feeding the system data that only you possess: your customer list.

The $50,000 threshold myth for Customer Match

Let’s address the primary hurdle first. To use Customer Match for direct campaign targeting or exclusions, Google requires that your account be in good standing, have at least 90 days of spend history, and have accumulated at least US$50,000 in lifetime spend.

If you’re managing a smaller account that hasn’t hit that milestone yet, or perhaps will never hit that milestone, that doesn’t mean that Customer Match isn’t for you! You should still upload your customer list to Google Ads immediately.

Why? Even without direct targeting eligibility, your uploaded customer list acts as a key AI signal. Google Ads uses it to train your Smart Bidding and optimized targeting (including Performance Max); the algorithm looks at the traits of your customers to find similar high-converting prospects.

Additionally, uploading your list opens up Audience Insights inside Audience Manager. You can review the demographic breakdowns and see which Google audience segments your customers belong to, completely free of charge. This is a great way to get ideas for new Demand Gen audience targeting, or different kinds of ad creative / landing pages.

Customer match campaign compatibility

Once your account crosses the lifetime spend threshold, Customer Match becomes compatible with campaigns running ads across Search, Shopping, Gmail, YouTube, and Display. You can apply your customer list on targeting or exclusion in Search, Shopping, Display, Demand Gen or Video campaigns. And although Performance Max doesn’t allow audience targeting, you can exclude Your data segments (including a customer list) and you can achieve a similar effect via Customer Lifecycle goals.

Customer Match unlocks customer lifecycle goals

Customer Lifecycle Goals are a feature of Search, Shopping, and Performance Max that let you tell the system how to value or prioritize different user segments within a single campaign.

For example, in “New Customer Only” mode, your customer list is treated as a hard exclusion so that the campaign only targets new customers. In “Customer Retention” mode, it does the opposite, focusing exclusively on your customer list to encourage repeat purchase behavior. There’s also New Customer Value, High Value Customers, New Prospect Mode, and more – and none of it works without Customer Match.

So when should you use this vs. direct targeting or exclusion?

I developed my “1% Rule” for customer lifecycle goals: unless your active customer list represents at least 1% of your target geographic location’s population, you probably don’t need to use customer lifecycle goals. For instance, targeting the United States (population 340 million) requires a list of roughly 3.4 million users, according to my 1% rule, to make customer lifecycle goals effective.

Conversion-based customer lists: Another Customer Match feature

Customer Match, when paired with Enhanced Conversions, unlocks another audience targeting feature: Conversion-Based Customer Lists. This bridges the gap between a single conversion action and long-term user data segments.

While a conversion is a single point-in-time event (like a form fill or a purchase), a data segment is an ongoing list of users (like a customer list or website remarketing list). A conversion-based customer list creates a list of users who have completed your conversion actions, like a list of Purchasers or a list of Form Fillers – all automatically generated and updated for you.

Technical execution: How to upload your customer list

To get your customer data into Google Ads securely, navigate to Tools > Data Manager to check for direct integrations. Platforms like Shopify, HubSpot, and Salesforce can link directly to Google Ads to sync your data automatically. If you do not use a major CRM, you can perform a manual upload via CSV file in Tools > Shared Library > Audience Manager. 

Just remember to keep uploading that data so your list doesn’t go stale! This is one of the top mistakes I see when I audit Google Ads accounts; a customer list that was created two years ago and never touched again. If you receive multiple leads or transactions daily, update your lists every 24 hours. If you only pick up a handful of customers each month, a bi-weekly or monthly calendar reminder is sufficient to keep your data fresh.

Remember, you must have user consent to upload customer data to Google Ads. Buying a list from a third party and uploading it violates Google Ads policy and potentially local privacy laws. Also, your website’s privacy policy must explicitly state that you share user data with third-party platforms like Google for advertising purposes.

The exception: Who shouldn’t use Customer Match

If your business falls under sensitive verticals such as healthcare, religion, personal hardships, or financial distress, I’m sorry to say that you cannot use Customer Match at all. Google blocks all “your data segments” in these industries to prevent exploitation of personal situations, illegal behaviour, etc.

But as long as you’re advertising in a “regular” industry, Customer Match is a non-negotiable. Your first-party data – a customer list – is one of the best competitive advantages you have. By providing Google’s AI with your own proprietary training data, you’re giving it the exact parameters it needs to find your next best customer.

This article is part of our ongoing Search Engine Land series, Everything you need to know about Google Ads in less than 3 minutes. In each edition, Jyll highlights a different Google Ads feature, and what you need to know to get the best results from it – all in a quick 3-minute read.

A Shopify service disruption on Tuesday affected core commerce functions, potentially preventing merchants from managing stores and customers from completing purchases.

The big picture. Shopify confirmed that some merchants and customers experienced issues across multiple services, including storefronts, checkouts, the Shopify admin dashboard and Retail POS.

Access to Shopify Support was also impacted.

What happened. Shopify first acknowledged the issue at 9:27 a.m. EDT, saying merchants may experience problems accessing:

• Shopify Admin
• Retail POS

At the same time, customers could encounter issues with:

• Storefronts
• Checkouts

The outage also affected access to Shopify Support.

Why we care. If Shopify storefronts or checkouts are unavailable, paid traffic can’t convert into sales, potentially wasting ad spend and skewing campaign performance data. Brands running Google, Meta, TikTok or other paid campaigns should monitor results during the outage and account for any disruptions when evaluating campaign performance.

Latest status. At 10:37 a.m. EDT, Shopify said it had identified the root cause and was seeing recovery following mitigation efforts.

“We’ve identified the problem and are seeing recovery from our mitigation efforts,” the company said in a status update. “We will continue to monitor and update.”

Earlier, at 9:45 a.m. EDT, Shopify said it was actively investigating the incident.

Between the lines. Because Shopify powers millions of online stores, even short disruptions can have immediate revenue implications for merchants, particularly when checkout functionality is affected.

For brands running promotions, product launches or high-traffic campaigns, any interruption to storefront access or payment processing can translate into lost sales and customer frustration.

What to watch. Shopify said services were recovering following mitigation efforts, but merchants will likely continue monitoring performance and order activity until the company confirms the incident has been fully resolved.

The outage also serves as a reminder of how dependent many ecommerce businesses have become on a small number of platform providers for critical commerce infrastructure.

First spotted. This alert was spotted by Senior Paid Media Manager Ayisha Yousef who shared the error message she came across on LinkedIn.

The old PPC skill set was built around control: define the keywords, choose the match types, set bids, write tightly aligned ad copy, and structure campaigns so the algorithm behaved the way you wanted.

The best ad managers of the past were great at Excel and pivot tables. Execution was the product and the differentiator for agencies and PPC experts. The more precisely you could control the variables, the better you were at the job, and that approach worked for the first decade of PPC.

Google Marketing Live (GML) 2026 made the next phase of PPC much harder to ignore. The biggest updates point to a shift from tactical control to system optimization, from keyword management to signal design, and from campaign setup to machine-aligned strategy.

The skills AI-driven Google Ads rewards

AI Max for Search is now out of beta. Smart Bidding Exploration is expanding into Shopping. Demand-led budget pacing will automate when your budget gets deployed. Business agent for leads can now qualify prospects directly inside a search conversation before anyone clicks your ad. Ads are showing up inside AI Mode conversations, matched not to keywords, but to conversational context Google’s AI interprets in real time.

The execution layer is being replaced outright. Selin Song, president of Google Customer Solutions, stated it directly during the keynote:

• “But things are changing. Execution is becoming a commodity and will no longer be a competitive advantage.”

Here’s what the new skill set looks like.

Your customers search everywhere. Make sure your brand shows up.

The SEO toolkit you know, plus the AI visibility data you need.

Start Free Trial

Get started with

Input design: The new keyword research

You need to know what inputs to give the system so it can find the right people on your behalf.

AI Max for Search, now out of beta and rolling out broadly, is a new Google Ads feature that uses a combination of broad match, keywordless targeting, text customization, and final URL expansion to find queries your keyword list never would’ve surfaced.

According to Google’s internal data, accounts using AI Max with text customization and final URL expansion see an average of 7% more conversions or conversion value at a similar CPA/ROAS.

That number is easy to wave away. What’s harder to ignore is the underlying mechanic: AI Max is finding converting queries your keyword list missed. The system has more access to user context than any keyword list you build, and it’ll keep getting better at using that access.

That means the skill is no longer “What keyword should I target?” It’s “What inputs do I need to give this system so it reaches the right people?”

That includes:

• Your conversion data: Smart Bidding can only optimize toward what you tell it matters. If your conversion actions are wrong, incomplete, or proxy metrics that don’t reflect business outcomes, the system is solving the wrong problem, and that’s the ad manager’s fault.
• Your product and feed data: For Shopping and ecommerce, Conversational Attributes — new Merchant Center feed attributes announced at GML for AI Mode surfaces — let you supply Q&A pairs, related products, and popularity signals. The AI uses that data to represent your products inside AI-generated responses. Thin feeds generate thin results. Rich feeds give the system something to work with, and as an ad manager, you need to optimize your feed with those questions at the center of the strategy.
• Your audience signals: New Customer Acquisition modes, also updated at GML, now include a “new prospects mode” that uses automated exclusions to reach brand-unaware users by filtering out people who’ve visited your site, searched your brand, or engaged with your content. This kind of upstream decision — who are we trying to reach? — shapes how the system operates. That’s not a campaign setting. It’s a strategic decision that now falls within the ad manager’s role.

If you’re still clinging to keyword lists as your main targeting strategy, you’re operating in a world that no longer exists. Today’s systems force you to think through business decisions, signal design, and the inputs steering automation.

Dig deeper: 10 keys to a successful PPC career in the AI age

Value signal architecture: The new bid management

The old version of bid management was about moving numbers. Then came automated bidding that factored in signals we couldn’t see. The job became deciding when a maximize strategy made sense versus when a target-based strategy was the better lever for the business.

That work isn’t gone, but the responsibility has expanded. Now it’s about how well you feed the system signals like first-party data, audience quality, and conversion value accuracy.

As Smart Bidding optimizes toward conversion values, you need to factor in a new layer of considerations.

Demand-led budget pacing, announced at GML and coming globally soon, will automate when your budget gets deployed throughout the day based on predicted demand signals. The system captures more on peak days, reduces spend on slower days, all within your monthly limits. You don’t control the pacing. You set the parameters the pacing operates within.

That means you also need to think through the economics of the offer. For example, if your store sells both electronics (10% margin) and home décor (55% margin), and you don’t model margin into your conversion values, Google may pace aggressively on days when electronics sell well even though those sales barely break even.

Product value adjustments, currently in global pilot, push this even further. You can now tell Google’s AI that a specific product, brand, or category should be weighted higher or lower in the auction. 

That helps nudge Smart Bidding toward actual business priorities instead of raw conversion value. You can optimize toward profit, seasonal sell-through, and best-sellers across Performance Max and Shopping campaigns without changing campaign structure.

The skill here is knowing what to signal, not how to set a bid. That requires clarity about:

• Margins: Which products can you afford to be aggressive on? Which low-margin items make aggressive bidding too expensive?
• Inventory position: What needs to move in the next 30-60 days?
• Lifetime value: Which products bring in repeat buyers? Which attract one-time purchasers?
• Cash flow timing: Where do you need revenue now versus where can you afford to be patient?

Journey-aware bidding, also newly out of beta, extends this to lead gen. You can now feed Google’s AI your full conversion journey, not just the final conversion event, and Smart Bidding will optimize across every stage of the funnel.

But to use it effectively, you need a fully instrumented conversion journey and a way to connect customer value back to the ad platform.

System prompting: The new copywriting

Here’s the skill with no real historical analog in PPC, and one of the most underestimated announcements from GML.

AI Brief, powered by Gemini, lets you guide AI Max for Search, Performance Max, and AI Max for Shopping using plain language. You write a brief describing your brand, your customer, your tone, and what to avoid. Google’s AI uses that brief in real time to shape how your campaigns find and represent you.

This isn’t copywriting or keyword strategy. It’s something closer to system prompting: the skill of giving AI enough context to act on your behalf without over-constraining it or leaving it to invent who you are.

Learning to prompt AI seems straightforward on the surface, but it isn’t. It requires attention, iteration, and a willingness to refine your thinking as you go.

Writing a brief that steers the system requires paid ads managers to understand things many advertisers haven’t had to articulate before:

• What makes this brand sound wrong?
• What searches are technically relevant but strategically damaging?
• What does the ideal customer look like in language specific enough to be useful?

Google’s example at GML was Cedar Pantry, a wellness grocery delivery brand. Its brief specified a tone that had to be “warm, calm, and confident, and never promotional,” while explicitly excluding price-driven language like “cheap,” “deal,” “fast,” and “bulk.”

One paragraph. Specific. Defensible. That brief shapes every impression the AI serves.

The practitioners who’ll be good at this aren’t necessarily the best keyword builders. They’re the ones who can distill brand strategy into operating instructions for a system that doesn’t already know the client.

And the strongest PPC experts will do that while maintaining confidence in the expertise they’ve spent years developing.

Dig deeper: The new PPC playbook: From media buyer to profit engineer

Budget architecture: The new budget management

Daily budget management used to be a significant part of the job. Watch pacing. Adjust if you’re under-delivering. Cap spend if you’re burning too fast. Build rules. Check in daily, all while managing the low-level stress of targeting that’s either limiting or overexposing your ad budget.

That’s compressing fast. Campaign total budgets, now generally available globally, let you set a fixed total spend with a defined start and end date. Google’s internal data says advertisers using it saw a 66% average reduction in manual budget adjustments compared to daily budgets.

The manual work has been automated. But a feature that looks great on paper raises a real question: How does a campaign using campaign total budgets perform compared to one using a daily budget?

That’s the part no GML announcement slide answers. Based on what I know about the ad auction, campaign total budgets likely work by forecasting demand across the entire flight and dynamically pacing spend based on predicted value, not daily ceilings.

It’s a prediction-led pacing model. From my experience, campaign total budget campaigns will almost always serve more aggressively on predicted high-value days, while daily budget campaigns will serve more consistently across all days.

That shifts the skill set toward interpreting auction behavior in a predictive system. It’s no longer “this is how the auction works.” It becomes “this is how the auction reacts” when pacing, budgets, and signals shift.

Demand-led budget pacing removes the daily pacing question entirely. The AI decides when to spend based on demand signals. You don’t control the daily rhythm, but you do set the ceiling and the objective.

What you still control is the architecture: how many campaigns share a budget, which budget parameters align with which objectives, and when to give the system room to operate versus when to constrain it.

Missed opportunity reporting, now generally available, provides visual insights into where bid and budget constraints are limiting growth opportunities. The data is there. The question is whether you can interpret it and make structural decisions from it.

Budget architecture is now the skill, not spreadsheet management and daily budget adjustments.

Measurement literacy: The new quality score management

Quality Score used to be the proxy for account health. CTR, ad relevance, and landing page experience were the three signals that told you whether your ads aligned with what users were searching for.

That proxy still matters today. But the upstream measurement question has become bigger and more complex.

Journey-aware Bidding requires conversion imports that reflect your actual funnel, not just the bottom of it.

Smart Bidding Exploration, which now shows 27% more unique converting users on average, only finds those users because it pulls signals from a broader range of performance data. The system’s ability to expand reach depends entirely on the quality of the signals you feed it.

Business Agent for Leads, also announced at GML, pushes this even further. An AI agent can now qualify leads directly inside a search conversation before anyone ever touches a landing page.

The leads those agents capture need to feed back into your bidding system for Smart Bidding to learn from them. That feedback loop doesn’t happen automatically. It requires integration, instrumentation, and someone who understands how conversion data shapes bidding behavior.

The skill is no longer optimizing toward Quality Score. It’s asking:

• What data does this system need upstream to make good decisions downstream?
• Do we have that data?
• How do we work with business partners to align that data with the ad account?

Dig deeper: In Google Ads automation, everything is a signal in 2026

A few things that still hold

The skill set is shifting. The fundamentals haven’t changed.

Conversion tracking is still nonnegotiable

Everything above — including AI Brief, Journey-aware Bidding, Smart Bidding Exploration, and Product Value Adjustments — operates on conversion data. If your tracking is broken or measuring the wrong thing, you’re giving the system a bad problem to optimize. Fix the measurement before touching the strategy.

Campaign structure still communicates intent

AI Max, Performance Max, and Smart Bidding Exploration have more room to operate in consolidated account structures with enough data to learn. Fragmented campaign architecture that made sense for manual bidding often works against AI learning now.

The brief you write is only as good as the thinking behind it

AI Brief doesn’t replace brand strategy. It amplifies it. If you don’t know what the client’s brand stands for or what searches would damage it, the brief will be vague, and the AI will behave vaguely.

Human oversight isn’t optional

The new skill set doesn’t remove you from the loop. It moves you to different points in the loop — upstream in the inputs, midcampaign in the signals, and downstream in the measurement. The job of the PPC practitioner is still to be the person who knows what the system should be doing and whether it’s doing it.

Skills that matter even more now

Asking better questions is now a core technical skill.

Predictive systems behave like mirrors. They reflect the clarity, structure, and intent of the questions you ask. If your questions are vague, the system’s behavior will be vague. If your questions are diagnostic and grounded in business reality, the system has something meaningful to optimize toward.

You need to know how to interrogate the system:

• What signal is it prioritizing? 
• What changed in the environment? 
• What does it believe is high‑value right now?

The quality of your questions shapes the quality of the system’s decisions.

Communicating system behavior to stakeholders is now part of the job

As execution becomes automated, the practitioner’s value shifts toward interpretation: explaining why the system behaved the way it did, what inputs shaped that behavior, and what adjustments come next. Stakeholders don’t see the signals, the pacing model, or the predictive logic. They see outcomes.

The role of the PPC expert is to translate volatility into meaning, model decisions into strategy, and system behavior into business language.

This isn’t a soft skill. It’s a survival skill in an environment where the work is increasingly invisible.

See the complete picture of your search visibility.

Track, optimize, and win in Google and AI search from one platform.

Start Free Trial

Get started with

The shift is already here

GML 2026 didn’t preview a future version of Google Ads. It confirmed the version we’re already operating in.

The practitioners who thrive now aren’t the ones who can recite how Google Ads used to work. They’re the ones who understand what the system needs to make good decisions and can provide those inputs clearly, consistently, and strategically to meet business goals.

The job has already shifted from keyword manager to system optimizer.

Dig deeper: What’s next for PPC: AI, visual creative and new ad surfaces

Google Display Network (GDN) placement exclusions have long been treated as basic account hygiene. You block spammy, inappropriate, or low-conversion placements to protect brand safety and avoid wasting budget on junk traffic.

That often meant maintaining massive lists of junk URLs and mobile app categories to keep ads off clickbait blogs, kids’ mobile games, and other low-quality inventory.

But GDN exclusions don’t just block bad placements anymore. They also influence the signals Google uses to optimize automated campaigns.

Here’s how to use placement exclusions to steer campaigns away from low-quality traffic and bad conversion signals.

The legacy blueprint: Hygiene and budget conservation

To understand the strategic shift, you first need to understand why blocking placements mattered in traditional PPC. Placement exclusions historically served two purposes: brand integrity and cost control.

You don’t want your high-end B2B software or consumer brand appearing next to extreme political rants, adult content, or clickbait farms.

GDN spans millions of sites and apps. A massive share of that inventory consists of high-click, zero-conversion black holes, like flashlight apps or mobile puzzle games where users accidentally click banner ads.

Legacy strategies also recognized that even high-quality sites like The New York Times or CNN could become budget killers. For direct-response advertisers focused on immediate ROI rather than broad brand awareness, a single premium placement could consume thousands of dollars with little to no conversion intent behind it.

The traditional fix was straightforward. Build massive static lists of 70,000-plus excluded URLs, block all mobile apps, and review the “Where Ads Showed” report monthly to eliminate outliers.

While those tactics remain necessary foundational steps, they only scratch the surface of how data operates in AI-driven advertising.

Your customers search everywhere. Make sure your brand shows up.

The SEO toolkit you know, plus the AI visibility data you need.

Start Free Trial

Get started with

How AI changed the rules of the GDN

In modern Google Ads setups, Smart Bidding algorithms like Target CPA and Target ROAS acquire customers at a predictable cost, serving ads only to searchers who fit those parameters. Combined with broad or optimized targeting, Google’s AI doesn’t just passively serve ads where you tell it to. It actively hunts for signals.

The AI analyzes who clicks, who converts, and where those actions happen. It then builds predictive models to find more placements like them. That creates a dangerous cycle when bad data enters the system.

If your campaigns lack strategic exclusions, Google’s AI will naturally gravitate toward the cheapest, highest-volume inventory available for testing. A flood of accidental clicks from mobile apps or low-quality click-fraud sites can initially appear to be a positive signal due to high CTRs.

The algorithm may then double down on those placements, burning through your budget before recognizing the traffic produces zero conversions. By the time the system learns the placements are unqualified, your monthly budget is already gone.

Dig deeper: Google Ads placements: Your guide to targeting websites, apps, and YouTube

Moving from hygiene to strategy: Guardrails for the algorithm

Strategic exclusions aren’t just about saying, “I don’t want my ad there.” They help direct the algorithm away from low-quality inventory and toward better signals.

By shaping where AI can and can’t operate, you inject human intent back into automated systems. 

Campaign intent mapping

Instead of applying one blanket exclusion list across your account, use exclusions to shape campaign psychology.

• For top-of-funnel brand awareness campaigns: Keep premium placements, such as major news outlets and industry blogs, active. Exclude niche, low-quality directories so your budget pushes the AI toward high-visibility, reputable sites.
• For bottom-of-funnel direct-response campaigns: Do the opposite. Exclude costly, broad-reach premium websites and force Google’s machine learning to focus on specific, content-rich, long-tail blogs where users actively research niche topics with high conversion intent.

Preempting Smart Bidding exhaustion

AI models need data to learn, but learning costs money. If you launch an automated campaign fully open to the Google Display Network, the AI will spend the first 14 to 30 days testing random placements. 

Applying robust, prebuilt exclusion lists at launch helps you skip that expensive trial-and-error phase and gives Google’s AI a head start on higher-quality inventory.

Fighting ‘signal poisoning’ in lead gen

Click bots and spam form fills are an AI nightmare. When a bot scrapes a GDN site, clicks your ad, and submits a fake form on your landing page, Google’s AI interprets it as a successful conversion.

The algorithm then optimizes toward more users and sites like it, contaminating your entire data pool. Strategic placement exclusions at the account level act as a firewall, cutting off low-quality inventory where these bots thrive and helping your AI optimize around clean, human traffic.

Advanced tactics for managing exclusions

To move beyond manual audits, adopt a more sophisticated framework.

Leverage automated scripts

Don’t wait for monthly reviews to catch budget drains. Deploy Google Ads scripts that monitor placement data daily.

For example, you could set a trigger to automatically exclude any placement that spends more than 1.5 times your target CPA within seven days without generating a conversion.

Block mobile apps

Unless your KPI is mobile app downloads, block mobile app categories at the account level. 

Google’s AI favors app placements because they generate high click volume and low CPCs, but those clicks rarely translate into meaningful business revenue. 

Use content suitability settings

Google’s advanced content suitability settings align placements with broader trends, cultural shifts, and legal sensitivities, especially if you run campaigns internationally.

Dig deeper: Google Ads Display Keywords: Everything you need to know

Taking back the reins

AI-driven campaigns perform better when strategic guardrails shape how Google’s algorithm learns and optimizes.

Basic account hygiene keeps your campaigns clean, but strategic placement exclusions also shape campaign performance. By removing low-quality inventory, limiting bad data, and steering Google’s Smart Bidding toward higher-intent leads, you can turn a simple blocklist into a meaningful performance advantage.

You can start with this comprehensive website exclusion list.

Looking to take the next step in your search marketing career?

Below, you will find the latest SEO, PPC, and digital marketing jobs at brands and agencies. We also include positions from previous weeks that are still open.

Newest SEO Jobs

(Provided to Search Engine Land by SEOjobs.com)

• SEO and PPC job at Hiyield (B Corp)
  June 4, 2026
  Hiyield is a climate-conscious digital product studio that’s proudly B Corp and 80% employee owned – and one of Cornwall’s best places to work in 2026, according to Business Cornwall magazine. We help purpose-driven organisations do more good in the world – and we’re looking for someone brilliant to take this SEO and PPC job, to help us do even more of it. […]
• SEO Specialist (Contract)
  June 4, 2026
  Company Overview: VEA Technologies is a forward-thinking Digital Marketing Agency with roots in Missouri and Colorado. We are currently seeking an experienced and skilled SEO Specialist to collaborate with our team as a contractor at approximately 50 hrs/mo. As a contractor, you’ll enjoy the flexibility to work from anywhere and set your own schedule while […]
• SEO Specialist
  June 3, 2026
  Remote opportunity. U.S. applicants only. If you’re looking for a place where you can sharpen your SEO skills, push your expertise to the next level, and work alongside a team that genuinely loves testing, learning, and winning, we’d love to meet you. Honest Digital is one of the fastest-growing digital marketing agencies in the automotive […]
• SEO Specialist
  June 3, 2026
  Please Note: Internal Employees, please access the Jobs Hub in Workday to apply for the position. ABOUT US University of Massachusetts Global is a private, nonprofit affiliate of the University of Massachusetts, created to help working adults change their lives through flexible, high-quality education built for real life. Regionally accredited by the WASC Senior College and […]
• Manager, SEO
  June 2, 2026
  Who we are: Tinuiti is the largest independent full-funnel marketing agency in the U.S. across the media that matters most, with $4 billion in digital media under management and more than 1,200 employees. Built for marketers who demand growth and accountability, Tinuiti unites media and measurement under one roof to eliminate waste—the biggest growth killer […]
• SEO / WordPress Analyst (LATAM)
  June 1, 2026
  SEO/AEO Analyst with strong technical experience (WordPress) Fully Remote in Latam Do you get excited when your site shows up in position 1? Are you comfortable with WordPress? This is a WordPress Developer/SEO hybrid position. We are looking for a very detailed focus person who can optimize our sites for organic conversions. You’ll work with […]
• Senior Associate, SEO
  May 31, 2026
  Job Description: At dentsu, we help leading brands build visibility across a search landscape that is rapidly evolving. We’re looking for a Senior Associate, SEO to support a major client and drive performance across both traditional SEO, local SEO, and emerging AI‑powered discovery experiences.  This role is ideal for someone with a strong foundation who is ready to […]
• Associate, SEO Strategy
  May 31, 2026
  WHY DEPT®? We are a Growth Invention company built to help the world’s most ambitious brands grow faster. Operating at the intersection of technology and marketing, we create what is next by pioneering ideas, acting fast, and moving further because standing still just is not in our DNA. We are drawn to people who stay […]
• Senior Lead, SEO & Answer Engine Optimization (AEO)
  May 31, 2026
  Job Description Welcome to AMN Healthcare — Where Talent Meets Purpose Ever wondered what it takes to build one of the largest and most respected healthcare staffing and total talent solutions companies? It takes trailblazers, innovators, and exceptional people like you. At AMN Healthcare, we don’t just offer jobs — we build careers that make […]
• Senior SEO Strategist
  May 30, 2026
  Location: Remote, North America Job Type: Full-Time Reports To: SEO Director Growth Track: SEO Director About Break The Web Break The Web is a boutique SEO agency built for in-house marketing teams at ambitious eCommerce and DTC brands. We help make SEO less annoying by bringing strategic thinking, clear communication, measurable progress, and real partnership […]

Newest PPC and paid media jobs

(Provided to Search Engine Land by PPCjobs.com)

• In-House Growth Marketing Specialist
  June 8, 2026
  A leading hospitality company is seeking an In-House Marketing Agent at its Myrtle Beach Sales Office. The role involves inviting guests to owner updates and sales presentations, assisting with on-site needs, and ensuring a smooth check-in experience. Candidates should have a high school diploma, strong communication skills, and a positive attitude. Experience in OPC or […]
• Remote Paid Media Specialist – Flexible PTO & 401K
  June 8, 2026
  HigherVisibility, located in Memphis, TN, is seeking a fully remote Paid Media Specialist. The role involves executing and optimizing paid advertising campaigns for a diverse clientele across Google Ads and Meta Ads. The ideal candidate will have 1-3 years of experience in paid media management, strong organizational skills, and expertise with Google Ads and Meta […]
• Growth-Focused PPC Marketing Manager
  June 8, 2026
  Fullsteam in Birmingham, Alabama is looking for a Digital Marketing Specialist to lead and optimize PPC campaigns across Google Ads and Meta for both internal brands and client accounts. This role involves managing multiple client accounts, ensuring high performance and client satisfaction. The ideal candidate should have 2-5 years of experience in digital marketing, proficient […]
• Franchise Growth Marketing Specialist
  June 8, 2026
  6AM City, LLC in Michigan is seeking a Franchise Marketing Specialist who will act as a liaison between the Michigan Support Center marketing team and the franchisee. This role involves promoting local franchise marketing solutions and supporting marketing initiatives. The ideal candidate should possess a Bachelor’s degree in marketing or a related field, along with […]
• Growth Marketing Specialist
  June 8, 2026
  Overview Growth Marketing Specialist CooperSurgical Inc On site: Trumbull, CT. We are looking for a detail-oriented, collaborative, and proactive Specialist, Growth Marketing to support the execution of integrated marketing initiatives across CooperSurgical business units. This role is ideal for someone who enjoys working across teams, managing multiple priorities, and contributing to impactful marketing programs that […]

Other roles you may be interested in

Senior Manager SEO/Gen AI (FTC), Jellyfish (Hybrid, New York, US)

• Salary: $90,000 – $115,000
• Act as the lead interpreter of search performance and visibility quality across both traditional and AI-led discovery experiences
• Maintain a broad expertise across the evolving landscape of LLMs and generative engines, including Google Gemini, OpenAI GPT, Anthropic Claude, and other leading frontier models

Lead Marketing Manager, SEO, Care.com (Hybrid, Dallas, TX)

• Salary: $125,000 – $135,000
• Organic Growth: Build and execute the SEO roadmap across technical, content, and off-page. Own the numbers: traffic, rankings, conversions. No handoffs, no excuses.
• AI-Optimized Search (AIO): Define and drive CARE.com’s strategy for visibility in AI-generated results — Google AI Overviews, ChatGPT, Perplexity, and whatever comes next. Optimize entity coverage, content structure, and schema to ensure we’re the answer, not just a result.

SEO Marketing Manager (phone accessories), Velvet Caviar ($100,000 – $120,000)

• Salary: $100,000 – $120,000
• Own and execute the SEO strategy for a high-growth e-commerce business, driving organic traffic, revenue, and conversion improvements.
• Conduct keyword research, competitive analysis, and SEO audits to identify and prioritize high-impact growth opportunities.

Sr. Content Marketing Manager, Dayforce (Remote)

• Salary: $82,700 – $147,000
• Write and publish high-quality, search-optimized content on a consistent cadence, including (but not limited to) blogs, thought leadership, comparison pages, FAQs, infographics, and other digital content assets.
• Create structured, answer-first content designed to be surfaced in AI-generated responses and LLM-driven experiences.

Paid Media Manager, Clients Blackbox, Inc. (Remote)

• Salary: $90,000 – $125,000
• Build, launch, and optimize Meta advertising campaigns focused on lead generation and appointment booking
• Manage campaign budgets, audience targeting, bid strategies, and creative testing

Senior Manager, Paid Search, Talkiatry (Hybrid, New York, NY)

• Salary: $150,000 – $180,000
• Own and scale Talkiatry’s paid search program end-to-end, including forecasting, budgeting, pacing, bidding strategies, account structure, and creative testing for Google, Bing, and ZocDoc.
• Develop and execute a rigorous testing roadmap, including ad copy, keyword strategy, landing page variants, and automation/algorithmic controls; quantify impact using sound experimental design.

Paid Digital Marketing Manager, Pei Wei (Irving, Texas)

• Salary: $75,000 – $110,000
• Develop and manage paid digital marketing strategies across multiple channels, including: Paid Search, Performance Max (PMAX), Meta Ads (Facebook & Instagram)
• Monitor, optimize, and scale campaigns based on performance KPIs including ROAS,CPA, conversions, traffic, impressions, engagement, and sales.

Marketing, Social Media & PR Manager, PARTNERS Staffing (Fort Myers, FL)

• Salary: $75,000 – $85,000
• Develop and execute integrated marketing campaigns for shows, content releases, events, and brand initiatives
• Identify target audiences and create strategies to grow reach and engagement

Senior Paid Media Manager, Brightly Media Lab (Remote)

• Salary: $70,000 – $100,000
• Directly build, manage, and optimize campaigns within Google Ads, Microsoft Ads, and Facebook Ads (Meta).
• Serve as the lead point of contact for your book of clients, taking full ownership of their success and growth.

Paid Search Specialist, Maui Jim Sunglasses (Peoria, IL)

• Salary: $65,000 – $70,000
• Plan, set up, and manage paid search, display, and shopping campaigns on Google Ads.
• Manage and optimize advertising budgets to achieve revenue and efficiency targets.

Note: We update this post weekly. So make sure to bookmark this page and check back.