On episode 334 of PPC Live The Podcast, I speak to Sophie Fell Head of Paid Media at Liberty Marketing Group about a real PPC mistake involving location targeting. The conversation focuses on how small oversights can have big consequences—and how to recover from them professionally.
Sophie accidentally launched a campaign with worldwide location targeting enabled instead of restricting it to the client’s service area. In just a couple of days, the campaign generated around 1,500 leads that looked impressive on paper but were unusable because they came from outside the target locations.
The unusually strong performance initially looked like a win, but it became a red flag. When Sophie reviewed the campaign more closely, she discovered the location setting issue. This highlights an important PPC lesson: results that look too good should always be investigated, not celebrated blindly.
The client spotted the issue around the same time Sophie did, while she was already preparing to flag it. The situation was handled with honesty—acknowledging the mistake, explaining what happened, and fixing it immediately. Transparency helped preserve trust, even though the client was understandably unhappy.
This wasn’t a lack of knowledge—it came down to moving too quickly and relying on assumed checks rather than confirmed ones. Like many experienced practitioners, Sophie thought the setting had already been reviewed. The experience reinforced how dangerous platform defaults can be.
Once corrected, the campaign went on to perform exceptionally well. The client hit their targets six weeks early and exceeded revenue expectations by £3.5 million. The initial mistake didn’t define the outcome—how it was handled did.
Sophie now checks campaign settings multiple times, both before and after launch. She reviews settings whenever performance spikes or dips and never reports results without rechecking fundamentals. The key change is recognising that post-launch reviews often reveal what pre-launch checks miss.
Sophie’s guidance is simple: pause, investigate, and be honest. Check metrics and settings immediately, take responsibility, explain what went wrong, and clearly outline how you’ll prevent it from happening again. Mistakes become serious problems only when they’re mishandled.
Sophie regularly audits accounts that haven’t been updated for years, rely heavily on brand campaigns, or misuse automation like Performance Max. She also sees poor alignment between keywords, ads, and landing pages—fundamentals that still matter, even in AI-driven campaigns.
Many PPC professionals assume industry leaders no longer make mistakes. Sophie challenges that idea. Everyone is still learning, regardless of experience level. Sharing failures helps juniors feel safer, encourages better leadership, and keeps the industry moving forward.
A strong team culture allows for testing, learning, and accountability without fear. Sophie emphasises clear testing frameworks, capped budgets, and open conversations. Teams that claim to be mistake-free rarely innovate.
Platforms change, defaults evolve, and assumptions fail. Whether performance is soaring or struggling, always verify that campaigns are doing what you think they’re doing. You can’t over-check your settings—but you can definitely under-check them.
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.
(Provided to Search Engine Land by SEOjobs.com)
(Provided to Search Engine Land by PPCjobs.com)
Sr. Performance Marketing Manager, RobertHalf (Hybrid, Miami, FL)
Senior PPC Manager / Lead Gen Onward Search (Onsite Los Angeles, CA)
Director, Paid Search, Omnicom Media Group (Hybrid, New York City Metropolitan Area)
Senior PPC Manager / Lead Gen (on-site, downtown LA, direct hire), Onward Search (Los Angeles, CA)
Senior Manager, SEO, Kennison & Associates (Hybrid, Boston, MA)
Lead Generation Manager, Mondo (Hybrid, Charlotte, NC)
Search Engine Optimization Manager, NoGood (Remote)
Search Engine Optimization Manager, Pump.co (San Francisco)
Senior Content Manager, TrustedTech (Irvine, CA)
Senior Growth Product Manager, Reku (Remote)
Note: We update this post weekly. So make sure to bookmark this page and check back.
Google is rolling out a new Performance Max beta that lets advertisers pull video assets directly from Merchant Center — a small tweak with big implications for retail and e-commerce.
How it works. Google Ads will now:
Why we care. This update removes a friction point in PMax: getting high-quality, product-relevant video into campaigns. By auto-pulling videos from Merchant Center, Google is tightening the link between inventory and creative, which typically translates to higher relevance, stronger engagement, and better performance.
For brands with large SKU counts, this dramatically speeds up workflow and ensures video coverage at scale — something that was previously difficult and resource-heavy to achieve.
The big picture. Google has been rapidly expanding PMax’s creative pipeline — from social video imports to this new Merchant Center integration — signaling a broader push to make PMax more plug-and-play for commerce-heavy advertisers.
First seen. This update was first spotted by senior performance marketing executive, Rakshit Shetty who shared his view of the option on LinkedIn.
The bottom line. A subtle update, but a meaningful win for brands running eCommerce at scale.
For the past two years, we’ve been living in AI’s gold rush era. To borrow from Taylor Swift, think of it as the “Lover” phase where everything is shiny, new, and full of possibility.
But we’re entering a new era now. Call it the “Reputation” phase, which is darker, edgier, and entirely focused on receipts.
A sign of this shift was in the headlines recently, blaring on about Microsoft lowering its AI sales targets. The hot takes rushed in to frame it as a disappointment, a slowdown, and even a sign that enterprise demand is cooling.
They all misread the moment. This is really a sign of the market graduating.
We’re maturing. The AI gold rush era is coming to an end. Microsoft’s recalibration is one of many signals of this shift being felt broadly across the market, as we enter AI’s Production Phase era.
Another sign is how the questions leaders are asking have started to mature:
Leaders are getting smarter and choosier. It confirms what many CMOs have suspected: We don’t need more tools. We need orchestration across the tools, so we use what we have more effectively and cohesively.
This shift comes as the broader AI market remains unsettled.
Nearly 40% of U.S. consumers have tried generative AI, but only half use it regularly, according to eMarketer. Platform loyalty is fluid. ChatGPT’s global traffic share fell from 86.6% to 72.3% in a year, while Google Gemini tripled to 13.7%.
For marketers, this volatility means orchestration is critical to future-proof against a fragmented ecosystem.
The martech landscape just crossed 15,384 solutions, up 9% from last year according to ChiefMartec. We’ve never had more capability available.
Yet Gartner shows martech utilization has dropped to just 33%. Companies are paying for the full stack but extracting value from one-third of it. Even as budgets are getting slashed everywhere.
During the gold rush, we bought point solutions to fix functional problems. A tool for copy. A tool for creative. A tool for bidding. Each team got their own set of tools. We built rooms full of brilliant soloists but never hired a conductor.
The result is something I call Pilot Theater: impressive AI demos that look innovative but can’t deliver enterprise ROI because they’re trapped in silos.
The signals exist, as does the technology.
What’s missing is the coordination. And the pressure to fix this is mounting, with 86% of CEOs expecting AI ROI within three years (eMarketer).
Flashy pilots aren’t enough anymore. The orchestration gap is now a revenue risk.
Most leaders still confuse automation with orchestration.
Automation is rigid: “If X happens, do Y.” Orchestration is adaptive: “Achieve goal Z using the best available tools and conditions.”
In this new agentic AI era, you have systems that go beyond generating content to observing, coordinating, and optimizing workflows across your entire stack.
Think of orchestration as the nervous system of your marketing operation. The connective tissue that interprets signals across channels and triggers the next best action, instantly.
I’d even call this a survival strategy. Smaller AI platforms are running out of time as VCs lose patience, according to eMarketer. The prize for winning in AI is massive, but so are the resources required.
Betting on a single vendor is risky. Building adaptive orchestration is how you stay ahead when the ecosystem reshuffles.
Much of this is happening now, with manual handoffs being replaced with intelligent feedback loops. Here are three real-world examples:
One of the most telling stats in the 2025 State of Martech report: Custom-built internal platforms jumped from 2% to 10% of core stacks.
A 5x increase in a single year.
Marketing teams are evolving into product teams. Product management tools grew from 23% to 42% penetration, the highest growth of any martech category.
The off-the-shelf ecosystem isn’t solving the coordination problem fast enough. So marketing leaders are building it themselves.
This mirrors what’s happening in AI platforms. Google’s Gemini is surging thanks to deep integrations across search, browser, and mobile OS. Advantages OpenAI can’t match. The lesson for marketers is that integration wins.
Don’t fall for the hot takes touting the end of this era as a sign of the AI bubble popping. This is the end of AI tourism.
In this new era you can’t force growth with volume. You have to orchestrate it with intelligence.
Your competitive advantage will come from building the best AI nervous system. One that can sense a signal in one channel and react across the whole stack before the opportunity moves on.
Especially as AI platforms race to monetize through ads and sponsored content, orchestration layers help you measure and optimize ROI across the entire funnel.
The gold rush is over. The production era is here and it belongs to the orchestrators.
When a TV commercial makes people feel something, it doesn’t just win in the moment – it sparks curiosity, drives searches, and fuels conversions.
That’s why the “Breaking TV Ads Report,” jointly launched by Kinetiq and DAIVID, deserves a spot on every search marketer’s radar.
The monthly report ranks the top-performing new TV ads in the U.S., blending Kinetiq’s real-time TV ad detection with DAIVID’s AI-driven creative analytics to uncover which ads broke through, why they resonated, and what brands can learn from their success.
It’s a powerful reminder that search doesn’t start on Google – it starts in the mind.
As Barney Worfolk-Smith, chief growth officer at DAIVID, recently told me in an email:
The first edition of the “Breaking TV Ads Report” highlighted a commercial that checks every emotional and strategic box: Indeed’s “What If LeBron James’ Skills Were Never Seen?”
The ad traces James’s journey from his early life to his work with the LeBron James Family Foundation, connecting it to Indeed’s “skills-first” hiring message.
It resonated not only because of its star power but because it made viewers feel something authentic.
The ad generated 11% higher intense positive emotion and 7% higher attention than the average U.S. TV ad, per DAIVID’s data.
It was joined in the top 10 by campaigns from TikTok (twice), Subaru, and Taco Bell, with emotional themes centered on family, mentorship, and belonging.
These aren’t just nice stories – they’re search triggers.
When people connect emotionally with a brand message, they’re more likely to act on it – often by turning to Google or YouTube for more information, reviews, or purchase options.
Dig deeper: Brand + performance: The secret to maximizing ad ROI
Back in 2011, Google introduced the concept of “The Zero Moment of Truth.”
But the ZMOT stage in the buying journey – when consumers research a product or service online before making a purchase – was the “new” second step.
The first step remained “stimulus,” and it could be “a TV ad.”
Many search marketers focus on what happens in the second ZMOT stage, because we can measure impressions, clicks, and conversions on mobile and laptop screens.
And we ignore the stimulus step because it is sucking money out of our marketing budgets.
But several studies over the past decade have shown that the impact of TV advertising extends directly into search behavior:
Put simply: when a campaign captures attention on TV, search demand spikes – often within minutes.
For SEO and PPC professionals, this presents a clear opportunity to anticipate and capitalize on those moments.
Several major brands have already proven that when TV storytelling and search strategy work together, both channels perform better.
Apple’s product launches are masterclasses in cross-channel momentum.
Every time a new iPhone ad airs, search volume for terms like “iPhone 17 Pro Max” or “iPhone 17 release date” skyrockets.
Apple’s branded search traffic increases by up to 40% in the days following a major campaign, according to Semrush.
Apple intentionally designs its TV creative to generate questions – not answer them – encouraging viewers to seek out more details online.
That’s where Apple’s search-optimized landing pages, YouTube product videos, and paid search campaigns complete the journey.
Progressive’s long-running “Flo” campaign shows how consistent creative storytelling translates into search intent.
The insurance brand’s TV spots spark curiosity around characters, slogans, and offers – leading to measurable spikes in branded searches such as “Progressive car insurance” and “Flo from Progressive.”
The brand’s media team aligns paid search and display campaigns with national TV flighting schedules, ensuring that when interest peaks, search ads and organic results are ready to capture demand.
Coca-Cola’s “Share a Coke” campaign is another classic case of TV leading to search.
The original “Share a Coke” campaign was launched in Australia in 2011 and involved replacing the Coca-Cola logo on bottles with hundreds of popular first names.
This personalization strategy was a global success, encouraging consumers to find bottles with their names and share them with friends and loved ones, which boosted sales and created emotional connections with the brand.
The latest “Share a Coke” campaign is a global relaunch targeting Gen Z with a focus on digital experiences and authentic, in-person connections.
It features personalized cans, a digital “Memory Maker” tool for creating shareable videos, and a partnership with McDonald’s.
Consumers can find names on bottles or use a QR code to customize bottles – a creative hook that’s sent millions to Google searching “custom Coke” or “share a Coke names.”
The campaign’s success wasn’t just creative; it was data-driven.
By tracking spikes in branded search and social mentions, Coca-Cola refined its targeting and extended the campaign’s life cycle online.
Dig deeper: Hyper-personalization in PPC: Using data to deliver tailored ad experiences
What makes the new “Breaking TV Ads” report particularly valuable is its data-driven framework for measuring creative effectiveness.
Kinetiq’s proprietary ad detection technology identifies every ad that first airs across 210 U.S. DMAs and 15 streaming apps, capturing over a million daily detections.
DAIVID’s AI then evaluates each ad’s emotional response, attention, and brand recall, creating a creative effectiveness score (CES) – a composite metric that mirrors how audiences actually experience content.
In a media landscape increasingly defined by short attention spans and fragmented screens, this data provides a rare window into why certain stories break through – and how that resonance correlates with downstream behaviors like search and site visits.
As Kinetiq CEO Kevin Kohn put it, the partnership “gives marketers a holistic view of the TV and CTV advertising landscape – not just what aired, but why it resonated.”
That’s exactly the kind of insight performance marketers need to connect the dots between creative resonance and measurable outcomes.
Dig deeper: Your ads are dying: How to spot and stop creative fatigue before it tanks performance
In February 2025, Neal Mohan, the CEO of YouTube, revealed that:
So, search marketers can apply the latest findings from the Breaking TV Ads Report in several ways:
Search has long been viewed as a response channel – the final step in a consumer journey. But that view is outdated.
Today’s most successful campaigns use search as a connective tissue between offline inspiration and online action.
Whether it’s a QR code at the end of a TV ad, a YouTube masthead following a primetime spot, or a Google Shopping ad that captures post-broadcast demand – search is the bridge between storytelling and sales.
As more brands invest in connected TV (CTV) and streaming, the line between “brand” and “performance” marketing will continue to blur.
Creative effectiveness data helps close that gap – showing which emotional and visual cues are most likely to drive measurable search and conversion behavior.
Ultimately, reports like “Breaking TV Ads” remind us that the most powerful search strategy begins long before the query.
It begins with attention and emotion, and, increasingly, on the biggest screen in the house.
Dig deeper: How connected TV advertising drives search demand
Tiiny AI, a US-based startup, has announced the Tiiny AI Pocket Lab, which it claims is the world’s smallest personal AI supercomputer. The device weighs just 300 grams, fits in one hand, and delivers up to 190 TOPS of AI compute performance. It has been officially certified by Guinness World Records as the ‘Smallest MiniPC (100B LLM Locally)’ and can run up to 120-billion-parameter large language models (LLMs) entirely on-device.
The Pocket Lab features a 12-core ARMv9.2 CPU paired with a custom-designed NPU, achieving an AI compute performance of approximately 190 TOPS. It includes 80GB of LPDDR5X memory and a 1TB SSD to support large-scale inference workloads. Tiiny AI has built the device to operate within a 30W TDP and a typical 65W system power envelope, offering high performance with reduced energy consumption.
Tiiny AI says the Pocket Lab addresses the growing concerns around cloud dependency, data privacy, and rising energy costs. The company believes local AI processing offers a more sustainable and secure alternative to cloud-based systems. The device stores all user data and model interactions locally with bank-level encryption, eliminating the need for internet access or external servers.
The Pocket Lab supports one-click deployment of several open-source LLMs and agent frameworks. These include GPT-OSS, Llama, Mistral, DeepSeek, Qwen, and Phi, along with automation tools like ComfyUI, SillyTavern, and Flowise. The system runs entirely offline and enables use cases like multi-step reasoning, content generation, deep context understanding, and secure personal memory.
The company plans to showcase the Tiiny AI Pocket Lab at CES 2026. It has positioned the product for developers, researchers, professionals, and students who require portable and private AI capabilities. The device aims to serve real-world use cases in the 10B to 100B parameter range, which the company says accounts for over 80% of practical AI demands.
In related news, Xiaomi is reportedly developing a new AI assistant called Mi Chat, and reports indicate that GPUs are no longer the main barrier to AI progress, with other system-level constraints now becoming the limiting factor.
For more daily updates, please visit our News Section.
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The post Tiiny AI unveils a pocket-sized Mini PC that runs 120B LLMs locally appeared first on Gizmochina.
Search Engine Land turns 19 today.
Nineteen years. Almost two decades of analyzing, explaining, questioning, challenging, obsessing over, and occasionally shaking our heads at whatever Google and the search industry throw our way.
And this past year? The pace of change has made it one of the most transformative since we launched in 2006.
Through all of it, our mission is the same as Day 1: help you make sense of search with clear news, smart analysis, and practical guidance.
Before we look ahead, I want to say thank you — and take a moment to reflect on the past year at Search Engine Land.
Seriously, thank you.
Every day, we start with you: what you need to know, what actually matters, and what changes could shape your work today or your strategy six months from now.
We aim to:
If you haven’t yet, subscribe to our daily newsletter for a curated wrap-up of everything happening in search. It’s still the easiest way to stay informed without feeling overwhelmed.
Search Engine Land has always punched above its weight for one reason: the people.
A small team can do big, meaningful work when everyone is aligned, mission-driven, and a little obsessed with search.
A huge thank-you to:
And to the entire Third Door Media team within Semrush — thank you. Whether or not your name appears here, your work matters and is appreciated.
In a year defined by uncertainty, it was encouraging to see so many people continue to rely on Search Engine Land as a trusted community resource. And Search Engine Land had a strong 2025.
This was the standout moment of the year. Bringing SMX Advanced back in person after six years felt overdue and incredibly energizing.
Attendance exceeded expectations, sessions were packed, and hallway conversations felt like a reunion of the search marketing community. You could feel how much people missed connecting face-to-face — debating AI’s impact on search, swapping tactics, comparing notes on Google’s latest changes, and simply enjoying each other’s company.
It reaffirmed what we’ve always believed: great things happen when smart marketers share a room. We’re already looking forward to doing it again in Boston, June 3-5.
This past year brought one of the most dramatic shifts in search since Search Engine Land launched in 2006. Whatever we end up calling this emerging practice, we focused on giving the industry the clarity, context, and reporting it needed.
Readers have told us again and again that Search Engine Land is their go-to source for cutting through the noise during a confusing and often chaotic time. We’re proud that our reporting, explainers, and expert analysis are helping shape the industry’s understanding of where search is headed next.
This year brought a surge of new readers and renewed engagement from long-time practitioners. With so many shifts reshaping SEO and PPC – from AI to SERP experiments to advertiser updates – and the continued emergence of GEO, marketers turned to Search Engine Land in record numbers to stay informed.
Our contributors played a significant role in our growth. A huge thank you to all of our excellent SMEs for all the great content and insights you shared in 2025.
As we enter our 19th year, our commitment remains unchanged: provide the most trusted, useful coverage of search anywhere.
This year you can expect:
Save the dates:
There’s much more to come – and as always, our goal is to give you the insight and intelligence you need to do your best work.
On Dec. 11, 2006, Search Engine Land officially launched with a simple idea: search was becoming not just a tool, but a place. A world. A community. A discipline shaping how people find information and how businesses connect with customers.
Nineteen years later, that world has grown in ways none of us could have imagined. But the core idea still holds:
Search Engine Land is a place to stay informed, to learn, to connect, and to understand the engines driving the modern web.
On behalf of everyone at Search Engine Land and Semrush, thank you for reading, for sharing our stories, for asking hard questions, for supporting our mission, and for caring so deeply about all things search.
Here’s to the rest of 2025 – and to a successful, healthy, and insightful 2026.
Microsoft is now testing a Google-like redesign of search ads in Bing, grouping multiple sponsored links under a single “Sponsored results” label and adding a “Hide” button that collapses the entire ad block.
Driving the news. Sachin Patel spotted the Bing test in the wild and shared screenshots and video showing the new layout. In the test, only the first sponsored result carries an ad label, while subsequent ads appear unlabelled underneath it. Users can tap “Hide” to collapse the entire set of ads, then “Show” to reveal them again.
How it works. The structure groups ad units in a way that can blur the distinction between organic and paid content. By collapsing ad labeling into a single header, the design makes individual ads look more like regular results.
Catch up. Google rolled out a nearly identical treatment two months ago — and it’s already sparked complaints of accidental ad clicks. Barry Schwartz did a poll on X that showed 63% of responders saying they had unintentionally clicked on a Google Ads Results because of the new grouping.
Bing adopting the same pattern signals a potential industrywide shift in how search ads are labeled and displayed.
Why we care. Bing’s new grouped “Sponsored results” format could increase ad visibility — and potentially boost click-through rates — by making ads appear more blended with organic results. The addition of a “Hide” button introduces a new user-control dynamic, but the single-label grouping may also lead to more accidental clicks, similar to what advertisers have seen with Google’s recent redesign, meaning higher bounce rates.
If Microsoft rolls this out broadly, it could meaningfully affect campaign performance, attribution and spend efficiency across Bing search.
First seen. Sachin Patel shared his view of this grouping on X.
The takeaway: If rolled out widely, Bing’s new format could drive more engagement — intentional or not — and reignite concerns about the clarity of search ad disclosures. For now, the experiment appears limited, and not everyone can replicate it.
What Microsoft are saying. Microsoft Ads Liaison Navahreached out to say that this was a test that they have opted not to continue.
Samsung’s new Galaxy Z TriFold is a unique foldable phone, but it’s more than just a smartphone. With a big 10-inch screen when unfolded, it can act like a tablet. Now, the Galaxy Z TriFold can also work as a second monitor for your Windows PC, which makes it a handy tool for multitasking or working.
The Galaxy Z TriFold supports Samsung’s “Second Screen” feature, which lets you extend your PC screen to the phone wirelessly using Miracast. This means no cables are needed.
To connect, just open the Second Screen page on the TriFold and press Windows + K on your PC. You can also connect by going to Settings >> System >> Display >> Connect to a wireless display.
Image via Android Authority
In addition to this, Samsung also offers a Second Screen app for PCs. It lets you adjust the screen ratio, sync power, and even reconnect the phone automatically. This app allows the Galaxy Z TriFold to be used as a second display smoothly and hassle-free.
When folded, the Samsung Galaxy TriFold looks like a normal 6.5-inch phone. Open it up, and you get a huge 10-inch display that feels more like a tablet. It can run Samsung DeX on its own, giving a desktop-like experience without a PC. And now, it can even work as a second monitor for you
For anyone who travels, works remotely, or just wants more screen space, the Samsung Galaxy Z TriFold is a powerful, flexible, and perfect tool. Samsung is going to make it available in South Korea on December 12, 2025. Stay tuned.
The post Samsung Galaxy Z TriFold can be your PC’s second screen appeared first on Sammy Fans.
I expected the dark-themed landing page to lose.
Everything I knew about conversion optimization said the light background should win.
Light themes are standard for B2B lead generation pages because they offer better readability, cleaner visual hierarchy, and align with accessibility standards.
Unbounce’s analysis of 41,000 landing pages establishes baseline patterns favoring light backgrounds. It seemed like a safe bet.
But after splitting paid traffic 50/50 between a dark landing page and a light landing page for our industrial fleet repair SaaS, the light variant achieved a 16.62% higher CTR yet delivered 42% fewer total conversions.
This isn’t an argument for universal adoption of dark themes.
It’s a case study in why audience context and industry-specific psychological associations matter more than following aggregate best practices derived from different populations.
We operate in a niche B2B SaaS vertical serving the transportation industry – specifically businesses that maintain commercial vehicles and equipment.
Our target buyers are shop owners and operators who spend their days in industrial environments managing technicians, equipment, and demanding commercial customers.
Going into this test, I had specific expectations.
I was wrong on both counts.
Dig deeper: 5 tips for creating a high-converting PPC landing page
We ran a standard 50/50 split test through Google Ads and Meta, directing traffic to two landing pages with identical copy but drastically different visual presentations.
The control featured a dark theme:
The treatment used a light theme:
The brand logo was prominently displayed in the header.
We kept everything else identical, particularly the:
This variable isolation is critical. If you change multiple elements, you cannot attribute results to any single change.
The test ran for 3 to 4 weeks on Google Ads search campaigns and Meta (Facebook and Instagram).
The total spend on Google was $8,205.97, resulting in 767 clicks and 30 conversions.
The results from Google Ads:
Dark theme:
Light theme:
The light theme’s CTR was 16.62% higher, which would typically be interpreted as a win.
But it attracted lower-quality traffic that converted at comparable or worse rates.
Meanwhile, Google’s algorithm allocated 44.6% fewer impressions to the light variant, resulting in 42% fewer total conversions despite essentially identical cost per conversion.
We ran the same test simultaneously on Meta, and the results were even more definitive.
The dark theme significantly outperformed the light theme in conversions, with the light variant rarely generating conversions at all.
This cross-platform consistency suggested the finding wasn’t an algorithmic quirk – it was an audience preference.
| Metric | Control (Dark) | Treatment (Light) |
|---|---|---|
| Impressions | 10,250 | 5,677 (-44.6%) |
| Clicks | 466 | 301 (-35.4%) |
| CTR | 4.55% | 5.30% (+16.62%) |
| Conversions | 19 | 11 (-42.1%) |
| Conversion Rate | 4.08% | 3.65% (-10.5%) |
| Cost per Conversion | $274.67 | $271.56 (-1.1%) |
Note: Google’s algorithm allocated significantly fewer impressions to the light theme, likely detecting lower engagement signals that affected Quality Score.
Dig deeper: Dynamic landing pages: What works, what fails, and how to test
The result makes sense when you consider who we’re targeting and what they respond to psychologically.
Commercial transportation businesses are industrial workplaces.
The aesthetic is functional, not decorative. Dark colors, metal surfaces, concrete floors, and equipment with black housings.
The environmental psychology of these spaces shapes what feels trustworthy to the people who work in them.
The dark landing page matched that identity. It signaled “built for your industry” without explicitly stating it.
The light theme, with its clean, modern aesthetic and prominent branding, resembled consumer SaaS: professional, polished, and aimed at someone else.
This pattern consistently appears in optimization testing: designs that reflect the visitor’s environment convert better than those that aspire to a different aesthetic standard.
The white form fields on the dark background created exceptional contrast. They were visually unmissable.
The form demanded attention not through size or position, but through contrast that made it impossible to ignore.
The light theme’s gray-on-white form fields blended into the page. They required conscious visual search.
For a 7-field B2B form targeting busy shop operators, reducing cognitive load through clarity matters more than aesthetic refinement.
Dark backgrounds communicate weight, substance, seriousness, and luxury. They feel significant.
Light backgrounds communicate ease, accessibility, and friendliness.
All valuable qualities for many products, but potentially wrong for expensive B2B software aimed at industrial buyers.
Industrial software is a significant operational investment. It touches every part of the business: scheduling, invoicing, inventory, and customer relationships.
Buyers need to feel that the software is substantial enough to handle that responsibility.
The dark theme’s visual gravity supported that perception. The light theme’s brightness worked against it.
Most heavy equipment, repair tools, and industrial software use dark interfaces.
Parts catalogs, diagnostic software, and inventory systems typically trend toward dark themes with high-contrast elements.
This isn’t random. It’s a category convention that has emerged because it works in these contexts.
Category conventions matter. Violating them can signal innovation, but it can also signal unfamiliarity.
For risk-averse buyers making expensive B2B purchases, the familiar aesthetic reduced perceived risk rather than creating it.
Despite following best practices by using a blue CTA button on the light theme (the color associated with trust in B2B contexts), it underperformed against the black button with red outline on the dark theme.
This violated conventional color psychology, but the explanation is straightforward: contrast matters more than color choice.
The black-and-red button created a dramatic contrast against the dark background and white form fields, making it impossible to miss.
The blue button, while theoretically the “correct” choice, blended into the light design’s overall aesthetic, reducing its visual prominence despite proper color selection.
Dig deeper: How to design landing pages that boost SEO and maximize conversions
The lesson isn’t “dark beats light.”
It’s that design is a carrier for psychological signals that vary by context.
Your test hypothesis should be about the message your design sends, not the design itself.
Before your next test, ask:
These questions matter more than “which color converts better” because the answer to that question is always “it depends.”
Dig deeper: PPC landing pages: How to craft a winning post-click experience
If you want to run a similar experiment, here’s what I learned about proper test structure.
Don’t test shades of the same approach. Develop genuinely distinct aesthetic treatments that represent unique psychological perspectives.
Dark versus light is a clear contrast. Light blue versus light green is not.
Same copy, form, value prop, CTA, page structure, and URL parameters. Change only the visual treatment.
If you change multiple variables, you can’t attribute results to any single change.
Proper A/B testing requires variable isolation to draw valid conclusions.
Track CTR separately from conversion rate.
If one variation gets higher CTR but lower conversion rate, you’ve discovered a message-match problem – the ad is attracting the wrong traffic.
Also, monitor if Google’s algorithm allocates impressions differently.
If one variation gets significantly fewer impressions, the algorithm may be detecting lower quality scores or engagement signals.
Don’t just compare conversion rates.
Calculate actual cost per conversion including ad spend.
A variation with slightly lower conversion rate but significantly lower CPC might win on efficiency.
With smaller conversion volumes, confidence intervals matter more than point estimates.
The conversion rates were too close to call a definitive winner based on the sample size.
If possible, segment results by device, geography, time of day, or other demographic factors.
Dark themes might perform differently for mobile versus desktop, or for different age ranges.
Use heatmaps to see where users focus attention on each variation. Run session recordings to watch actual navigation behavior.
Survey converters and non-converters to understand perception differences. We didn’t do this for this test, but it would strengthen the analysis significantly.
Dig deeper: Audience targeting in Google Ads Search campaigns: How to layer data for better results
The dangerous part of best practices in optimization is the implicit universality claim.
“Light backgrounds convert better” becomes “light backgrounds always convert better for everyone,” which leads to cargo cult optimization, copying tactics without understanding context.
Light backgrounds do tend to outperform in aggregate data. But averages hide variation. Industry-specific contexts reveal massive differences.
What works for SaaS doesn’t work for events. What works for ecommerce doesn’t work for B2B services.
Your optimization framework should start with “who is my audience and what signals do they respond to?” – not “what does research say works on average?”
The most successful tests challenge assumptions rather than confirm them.
This test challenged the assumption that modern, clean, light design is universally superior. It wasn’t, at least not for this audience.
Dig deeper: Top 6 B2B paid media platforms: Where and how to advertise effectively
Industrial B2B is just one example, but the principle holds everywhere: design only works when its signals match the audience.
When you ground your tests in that question – not in aesthetics – you get cleaner data and clearer decisions.
That shift turns every experiment into a reliable read on what your audience actually values, and that’s what drives consistent, defensible gains over time.
Most brands don’t realize how much traffic they lose each day to unauthorized bidding, affiliate violations, and ad hijacking.
Industry data shows ad fraud reached an estimated $84 billion of global digital ad spend in 2023.
If your branded CPCs keep rising or competitors keep appearing above you in searches for your own name, this PPC brand protection guide can help you understand why – and what to do next.
Brand protection is the practice of defending your brand from unauthorized use of your branded search terms in PPC and from deceptive or fraudulent ad placements.
The goal: make sure people searching for your brand or product name land on your official pages – not a competitor’s, affiliate’s, or reseller’s.
When done well, brand protection safeguards traffic while strengthening your brand image and customer loyalty.
Without a brand protection strategy, you’ll face steep losses – higher CPCs, rising affiliate costs, and a drop in customer acquisition.
Activities tied to PPC brand protection include:
The three main sources of threats are:
If you don’t protect your brand in paid search, you’re likely to face these common risks:
These risks demand a dedicated PPC protection strategy. Left unchecked, they drive up acquisition costs and cause you to lose customers at the final decision stage.
Failing to protect your brand in PPC erodes trust, skews attribution, and weakens your marketing over time. As a result, conversions drop, ROI slips, and your paid media becomes less effective.
Key facts:
When your campaigns are organized clearly and systematically, you can control risks more easily and respond faster to unauthorized activity.
Key elements of a well-planned brand protection strategy include:
Manual monitoring can’t keep up with competitors and fraudsters who constantly rotate tactics. A strong brand protection strategy relies on automated monitoring to catch threats early and resolve them before they affect your budget, CPCs, or conversions.
Core components of effective automation include:
You can measure the effectiveness of your PPC brand protection efforts by tracking metrics that show the scale of violations and how efficiently you respond to them.
Key metrics include:
Together, these metrics provide a clear view of how well your brand protection strategy is performing and where you may need to make improvements.
UAWC agency shared a use case involving a car company that was losing branded traffic in paid search. The source of the problem turned out to be competitors’ aggressive brand bidding tactics.
To recover the losses, the brand had to employ UAWC to audit competitors, identify branded keyword conflicts, restructure ad campaigns, and closely monitor auction dynamics.
As a result, branded impression share rose to 95%, protecting high-intent traffic and stabilizing CPCs.
Rhino was grappling with affiliate fraud and unauthorized brand bidding on its flagship brand. With the help of Bluepear, they uncovered 105 violators.
Using reports and screenshots as evidence, Rhino successfully disputed payments – ultimately saving €131,000 and restoring their branded search visibility.
Monitoring is the operational backbone of brand protection – that’s exactly where Bluepear delivers the most impact.
After signing up: You create an account and fully customise it with the help of a built-in AI-assistant – it only takes 10 minutes. From there, you get instant access to automated brand monitoring. Bluepear reveals every violation, including:
Bluepear alerts you to every violation and backs each one with clear evidence and screenshots. This gives you airtight proof for fast escalation and cuts the time you spend disputing payments with affiliates and PPC platforms.
Impact: After removing unauthorized bidders, you gain cleaner attribution, lower acquisition costs, and stronger efficiency across all paid channels.
Most of the damage to your branded traffic happens out of sight – hidden ads, affiliate rule breaks, and impersonation fraud. Bluepear uncovers it all instantly, starting at just $169 a month after a free trial.
See what’s been slipping through:
Try Bluepear’s solution for brand protection and detect hidden brand bidding in minutes.
Shopify is expanding its advertising ambitions with the Shopify Product Network, a new system that surfaces products from participating merchants – even when a store doesn’t sell the item a shopper is viewing.
The pitch. If a shopper searches for “organic cleaning supplies” on a Shopify store that doesn’t carry them, the Product Network can show alternatives from other merchants. These items may also appear on another store’s homepage, blending in with its own inventory. Shoppers can buy everything in a single cart, often without realizing some products come from different merchants.
Shopify’s angle. The Product Network mirrors ad platforms like Google Performance Max, Meta Advantage+ Shopping, and Amazon Performance+. Advertisers set a cost-per-acquisition target, and the system automatically optimizes the rest.
Key difference: Shopify emphasizes merchandising over advertising. Network placements only appear if contextually relevant, rather than filling predefined ad spots.
Revenue and structure. Shopify has long avoided heavy ad monetization. For example, its Audiences program builds customer segments for use on channels like Google and Meta without taking a cut of ad spend.
What they are saying. Shopify reached out to say that the it would be easy to distinguish which products are coming from different merchants:
In my opinion – unsophisticated shoppers will still easily miss that label as a lot of people shop in a rush especially during the current holiday season.
They also shared this image of the feature:
Why we care. Shopify’s Product Network gives advertisers a new way to reach shoppers across a wide network of independent merchants – without requiring those merchants to stock their products. By surfacing relevant items contextually, whether in search results or directly on another store’s homepage, advertisers gain broader exposure while the shopping experience stays seamless.
Unlike traditional ads, the network optimizes for conversions and purchase likelihood instead of simply filling ad space, which can deliver higher-quality traffic. Merchants also earn commissions on third-party sales, creating a clear incentive to participate and expanding the network’s reach and value for advertisers.
What’s next. Shopify plans to refine personalization and monetization as the network grows, but its core goal remains the same: keep shoppers on the platform and help merchants sell more – even when the products aren’t theirs.
LinkedIn is rolling out new ad tools that help you boost brand awareness, personalize your messages, and speed up creative work so you can reach potential buyers earlier in the funnel.
What’s new. LinkedIn announced these new features:
Why we care. LinkedIn’s updates may make it easier for brands to get noticed, personalize their ads, and produce creative faster. Reserved Ads guarantee top-of-feed placement, while Ad Personalization adjusts messages based on a person’s name, company, or job title to make them feel more relevant. New AI tools also help create and test ads quickly, improving engagement and reaching early-stage buyers more efficiently.
What’s next. B2B advertisers should experiment with Reserved Ads, ad personalization, and AI-driven creative tools to strengthen top-of-funnel impact, refine messaging, and optimize performance – all without adding significant manual effort.
LinkedIn’s announcement. How New LinkedIn Features Help You Scale Personalized Creative and Boost Awareness
Google is releasing the Google Ads API Developer Assistant v1.0, a new Gemini CLI extension that lets developers interact with the Ads API using natural language — turning plain-English prompts into answers, code, and even live API calls.
How it works. The assistant sits inside the Gemini CLI and uses project context from GEMINI.md and configuration files to generate accurate code based on the user’s environment.
Logingoogle-ads-python client library.Key features. Developers can run generated scripts directly from the terminal to execute read-only API calls, with results displayed in neatly formatted tables.
saved_code/ folder.Why we care. The new Developer Assistant helps teams build, test, and refine Google Ads API workflows faster. It turns natural language into GAQL queries and ready-to-run code, which cuts technical roadblocks and speeds up the insights that fuel smarter optimization. With one-command execution and easy CSV exports, analysts and engineers spend less time wrestling with code and more time improving performance.
The big picture. Google is positioning the assistant as both an educational entry point and a productivity booster. For newcomers, natural language prompts flatten the learning curve.
For power users, code generation, automatic file organization, and command-line execution remove repetitive work from day-to-day API operations.
Getting started. Developers need a Google Ads API token, a configured google-ads.yaml, Python 3.10+, the Gemini CLI, and a local clone of the google-ads-python library. A setup script can handle the cloning, and full instructions are available on GitHub.
What’s next. Google is encouraging early adopters to submit feedback, request features, and participate in the community Discord channel as it explores additional enhancements and AI-driven tooling.
Google’s announement. Introducing the Google Ads API Developer Assistant v1.0: Interact with the API using Natural Language
YouTube is rolling out new ad features for Shorts to help brands stretch their holiday budgets and tap into the momentum of short-form video.
What’s new:
Why we care. These updates make Shorts ads more interactive, natural, and actionable, which can help brands stand out and perform better during the busy holiday season. Comment-enabled ads reveal real-time audience reactions, creator link-outs make it easier for viewers to move from discovery to purchase, and wider mobile web placement increases reach when shopping demand is highest.
The big picture. As more people watch short-form video across screens, YouTube is positioning Shorts as the platform that blends creator authenticity with measurable performance – a pitch aimed squarely at holiday-focused advertisers.
What’s next. Advertisers could benefit from YouTube’s more interactive, creator-friendly Shorts ads, which can help cut through the noise and turn attention into holiday sales.
Google’s announcement. New updates to YouTube Shorts will help brands maximize their holiday budgets.
Do you want to immediately raise the blood pressure of the Google Ads practitioner sitting next to you? Say one word: Recommendations.
If you’ve spent any time in the Google Ads platform, you’ve seen Recommendations jumping out at you on every screen: when you’re adding keywords, when you’re adjusting your campaign settings, when you’re changing your bid strategy, when you’re minding your own business! And we’ve all received that email from a client asking why their “Optimization Score” is falling.
In this article, I’ll explain what Recommendations actually are (and aren’t), where they come from, and how you should handle them.
First, let’s address the elephant in the room: Why do so many Google Ads practitioners dislike recommendations?
In my opinion, it’s a misalignment of understanding and expectations. While Recommendations are personalized for your account, they are not necessarily personalized for your business context and goals.
The Recommendations algorithm looks at your account data (keywords, bids, targeting, etc.) and identifies patterns where it thinks it can improve performance based on its own logic.
For example, if the system sees you are only using Exact and Phrase match keywords, it will likely flag a recommendation to “Test Broad Match.” It does this simply because the feature is available and you aren’t using it. It’s logical from a platform capability standpoint, but it might be terrible for your specific budget or niche.
To understand why this happens, it helps to know the history.
Recommendations actually started as an internal sales tool for Google Ads sales representatives. It was designed to help reps spot opportunities to provide support (and upsells) to clients. However, there was that “human filter” element to ensure that reps were only pitching relevant opportunities. Now that Recommendations surface automatically in every account, that human filter is gone.
One of the biggest sources of anxiety for business owners in Google Ads is the Optimization Score. It’s that 0%-100% number sitting prominently on your dashboard – and the one Google loves to highlight in its automated emails.
Many people treat this score like a report card. If they see a 60%, they panic, thinking their campaign is failing. This can lead to users blindly clicking “Apply All” just to get that number back up to 100%.
Do not do this.
Here is the secret that doesn’t need to be a secret: The optimization score is not a measure of how well your account is performing; it is a measure of whether you are reviewing your recommendations.
Don’t take my word for it – see for yourself! You do not have to accept a recommendation to increase your score. Dismissing a recommendation gives you the exact same score uplift as applying it. You can literally dismiss every single recommendation in the list and, like magic, you’ll have a 100% optimization score.
No, optimization score doesn’t really matter. Keep it at 100% if it makes you feel good, or if you need to maintain Google Partner status. Otherwise, feel free to ignore it.
Recommendations aren’t just confined to the Recommendations tab. Google has integrated them throughout the entire ad platform. You’ll see them when you are setting up a new account, adding keywords, adjusting bid strategies, or even just viewing your campaign overview.
It can be startling to see a warning symbol on your account, or even in your email inbox, so here’s what you need to know to distinguish a “friendly” recommendation from an actual performance issue in your account:
Don’t let the blue and yellow icons scare you into making hasty, unnecessary changes. If you like the recommendation, accept it. If not, dismiss it.
When Google Ads practitioners complain that recommendations are just designed to make you spend more money, my response is: Yes, obviously.
Google is a for-profit company. They want you to spend more on Google Ads.
However, Google is smart enough to know that if you spend more money and get zero results, you will stop spending money. They need you to succeed so that you keep spending.
Therefore, not all recommendations are about spending more money. I split them into two categories:
No discussion about recommendations is complete without mentioning Auto-Apply Recommendations. For many years, Google pushed “AAR” heavily, encouraging users to let the system automatically apply changes without review.
Thankfully, this push seems to have slowed down recently, but you still need to ensure you have control over your account. You do not want Google making changes to your budget, bids, or keywords while you sleep.
Here’s what you need to do right now:
You want those boxes empty so that Google does not have permission to modify your account without your direct input.
All in all, recommendations aren’t “evil,” nor are they gospel truth. They are just a nudge. They are a starting point for testing.
Whether a recommendation comes from the Google Ads interface, an agency partner, or someone like me, the rule remains the same: You know your business best. Review the suggestion. If it aligns with your goals, test it. If it doesn’t, dismiss it and move on.
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.
Pinterest attracts users who want inspiration and solutions, not passive browsing.
The platform now reaches 600 million monthly active users, many of whom arrive with clear intent to research, plan, or purchase.
That makes its ad formats especially valuable for marketers who want to appear in moments when people are actively looking for ideas and products.
Here’s how each format works and when to consider it.
Pinterest Ads offers a variety of ad formats, many of which aren’t available on other social media platforms.
Let’s take a look at what formats they offer and when you might want to consider using them.
Carousel ads are an interactive format that showcase two to five cards (images), where users can swipe through the cards, tap a card to open a close-up view, or click through to a destination URL.
This format is a great way for advertisers to showcase multiple messages or products and encourage users to engage with the ad via the swipe capabilities.
Example: A wedding planner could use multiple cards to share statistics on the U.K. wedding market and rising costs of the average wedding, with the final card promoting an ebook on how to reduce costs, which is available to download for free on their website.
Similar to carousel ads, collection ads allow advertisers to show multiple products in one ad.
The ad starts with a “hero” creative (either an image, a video, or a slideshow), which sits above three smaller images.
When the user clicks on the ad and opens close-up mode, they are presented with up to 24 additional images or products.
This format can be used by advertisers who want to showcase multiple products, such as a specific collection or a product catalog.
Example: A jewelry store could use a looping video of a woman putting on a gold set of jewelry, with the three smaller images showing product images of each item.
Once the user clicks on the ad, they are presented with the full range of gold jewelry sold by the business.
Idea ads are made from a single full-screen image or video and appear on the homepage, in searches, and alongside related pins.
This is an ideal format for advertisers who want their ads to have a more native feel while still being shoppable or facilitating site visits.
This is the most basic ad offering on Pinterest, with the ad made from a single static image.
Standard ads are a great option for advertisers looking for a simple format, can offer a visually compelling image, and want to take users directly to their site.
Example: A CrossFit gym could use a photo from a recent shoot of one of its classes in action, with clear, bold text stating “Join us,” the logo in the top right corner, and a call to action to “Book your free class.”
There are two types of video ads available on Pinterest: standard and max-width.
Due to their autoplay nature, these formats are ideal for grabbing users’ attention and for advertisers who are able to tell a story with video content.
Shopping ads use a single, static product image, but unlike standard ads, they also show product details including price.
This format is ideal for ecommerce brands looking to showcase products through a shoppable format and those with a dependable product feed.
Quiz ads enable advertisers to build a quiz with two to three questions and, depending on the answers given, show users two to three results.
The results consist of a visual asset, a headline, and a description, from which the user can click through to a website to continue their journey.
This is another interactive format, ideal for advertisers looking to offer users a more customized experience.
Example: A beauty brand could use the quiz format to guide users to the product page for the right range for their skincare needs.
This helps address users’ wants and needs and provides a more personal experience than sending them to the website homepage.
Local inventory ads help advertisers promote their products alongside real-time pricing for in-stock items.
They require advertisers to set up store locations and local product information via a store feed and a local inventory supplemental feed.
This format works well for advertisers looking to drive store visits and promote their convenience to local platform users.
Dig deeper: Cross-platform, not copy-paste: Smarter Meta, TikTok, and Pinterest ad creative
Pinterest ads regularly offers new ad formats, with the following two currently in beta
In September 2025, Pinterest began testing Top of Search ads, which appear within the first 10 slots of search results and related pins.
Top of Search ads have a 29% higher average CTR than other campaigns, according to Pinterest’s test data. This is a promising format for advertisers looking to quickly and effectively capture the attention of high-intent users.
Lead ads are designed to help advertisers reach prospects on Pinterest by enabling them to collect information through a lead form, making them an ideal format for lead generation.
Advertisers can choose what text appears in the descriptions, questions, and confirmation card, giving them control over the information they want to collect.
Pinterest Ads offers a mix of visual and interactive formats that help brands stand out in front of a high-intent audience.
As the platform expands its ad lineup, marketers gain additional ways to support research, inspiration, and purchase journeys with creative built for how people use Pinterest.
With more formats in development and a growing user base, 2026 presents a clear opportunity for advertisers to build or deepen their investment in the channel.
Google is rolling out a new Data Manager API that lets you plug first-party data into Google’s AI-powered ad tools with less friction. The goal: stronger measurement, smarter targeting, and better performance without the hassle of managing multiple systems.
Why we care. The Data Manager API helps you get more value from the data you already have by sending reliable first-party data into Google’s AI. This improves your targeting, measurement, and bidding. It also replaces several separate APIs with one easy connection, cutting down on engineering work and getting insights back into your campaigns faster.
About the Data Manager API. It will replace several separate Google platform APIs with one centralized integration point for advertisers, agencies, and developers. It builds on Google’s existing codeless Data Manager tool, which tens of thousands of advertisers already use to activate their first-party data.
You can use it to:
Partnership push. To speed adoption, Google is launching with integrations from AdSwerve, Customerlabs, Data Hash, Fifty Five, Hightouch, Jellyfish, Lytics, Tealium, Treasure Data, Zapier, and others.
Available today. The API is available starting today across Google Ads, Google Analytics and Display & Video 360, with more product integrations on the way.
Google’s announcement. Data Manager API helps advertisers improve measurement and get better results from Google AI
In 2026 and well beyond, a core part of the performance marketer’s charter is learning to leverage AI to drive growth and efficiency.
Anyone who isn’t actively evaluating new AI tools to improve or streamline their PPC work is doing their brand or clients a disservice.
The challenge is that keeping up with these tools has become almost a full-time job, which is why my agency has made AI a priority in our structured knowledge-sharing.
As a team, we’ve honed in on favorites across creative, campaign management, and AI search measurement.
This article breaks down key options in each category, with brief reviews and a callout of my current pick.
One overarching recommendation before we dive in: be cautious about signing long-term contracts for AI tools or platforms.
At the pace things are moving, the tool that catches your eye in December could be an afterthought by April.
There’s no shortage of tools that can generate creative assets, and each comes with benefits as well as the risks of producing AI slop.
Regardless of the tool you choose, it must be thoroughly vetted and supported by a strong human-in-the-loop process to ensure quality, accuracy, and brand alignment.
Here’s a quick breakdown of the tools we’ve tested:
Our current tool of choice is AdCreative.ai. It’s easy to use and especially helpful for quickly brainstorming creative angles and variations to test.
Like its competitors, it offers meaningful advantages, including:
The usual caveats apply across all creative tools:
Dig deeper: How to get smarter with AI in PPC
There are plenty of workflow automation tools on the market, including long-standing options, like Zapier, Workato, and Microsoft Power Automate.
Our preferred choice, though, is n8n. Its agentic workflows and built-in connections across ad platforms, CRMs, and reporting tools have been invaluable in automating redundant tasks.
Here are my agency’s primary use cases for n8n:
As with any tool, n8n comes with caveats to keep in mind:
Dig deeper: Top AI tools and tactics you should be using in PPC
Most SEOs already have preferred platforms for measurement and insights – Semrush, Moz, SE Ranking, and others.
While many now offer reports on brand visibility in AI search results from ChatGPT, Perplexity, Gemini, and similar tools, these features are add-ons to products built for traditional SEO.
To track how our brands show up in AI search results, we use Profound.
While other purpose-built tools exist, we’ve found that it offers differentiated persona-level and competitor-level analysis and ties its reporting to strategic levers like content and PR or sentiment, making it clear how to act on the data.
These platforms can provide near real-time insights such as:
No matter which tool you choose, the key is to adopt one quickly.
The more data you gather on rapidly evolving AI search trends, the more agile you can be in adjusting your strategy to capture the growing share of users turning to AI tools during their purchase journey.
Dig deeper: Scaling PPC with AI automation: Scripts, data, and custom tools
I like to think most of my content for this publication ages well, but I’m not expecting this one to follow suit.
Anyone reading it a few months after it runs will likely see it as more of a time capsule than a set of current recommendations – and that’s fine.
What does feel evergreen is the need to:
We’re well past head-in-the-sand territory with AI in performance marketing, yet there’s still room for differentiation among teams that move quickly, test strategically, and pivot together as needed.
Dig deeper: AI agents in PPC: What to know and build today
In 1997, Apple launched a campaign that became cultural gospel. “Think Different” celebrated the rebels, the misfits, the troublemakers. The ones who saw things differently. The ones who changed the world.
Apple understood something fundamental: the constraints that limited imagination weren’t real. They were inherited. Accepted. Assumed. And the people who broke through weren’t smarter or more talented. They simply refused to believe the constraints applied to them.
Twenty-eight years later, marketing faces its own Think Different moment.
The constraints are gone. Technology has removed them. AI can generate infinite variants. Data platforms deliver real-time insights. Orchestration tools coordinate across every channel instantly. The infrastructure that once required armies of specialists, weeks of coordination and endless approvals now exists in platforms accessible to any marketer willing to learn them.
Yet most marketers still operate as if the box exists.
They wait for the data team to run the analysis. They wait for creative to deliver the assets. They wait for engineering to build the integration. They operate within constraints that technology has already eliminated, not because they must, but because assembly-line marketing taught them that’s how it worked.
Creative waits for data. Campaigns wait for creative. Launch waits for engineering. Move from station to station. Hand off to the next department. That was the assembly line. That was the box.
And that box is gone. But the habits remain.
The ones who see a customer signal at 3 p.m. and launch a personalized journey by 4 p.m., not because they asked permission but because the customer needed it now.
The ones who don’t send briefs to three different teams. They access the data, generate the creative and orchestrate the campaign themselves. Not because they’re trying to eliminate specialists, but because waiting days for what they can deliver in hours wastes the moment.
The ones who run experiments constantly, not occasionally. Who test 10 variants instead of two. Who measure lift instead of clicks. Who know that perfect insight arrives through iteration, not through analysis paralysis.
They don’t see a handoff to the analytics team. They see customer data they can access instantly to understand behavior, predict intent and target precisely.
They don’t see a creative approval process. They see AI tools that generate channel-ready assets in minutes, allowing them to personalize at scale rather than compromise for efficiency.
They don’t see an engineering backlog. They see orchestration platforms that automate journeys, test variations and optimize outcomes without a single ticket.
They’re simply operating at the speed technology now enables, constrained only by strategy and judgment rather than structure and process.
This is what Positionless Marketing means: Wielding Data Power, Creative Power and Optimization Power simultaneously. Not because you’ve eliminated everyone else, but because technology eliminated the dependencies that once made those handoffs necessary.
When marketers were constrained by assembly-line marketing infrastructure, their job was to manage the line. Write the brief. Coordinate the teams. Navigate the approvals. Wait for each station to finish its work. The marketer’s skill was project management. Their value was orchestrating others.
Your job is no longer to manage process. Your job is to enable potential. To help every person on your team (and yourself) realize what they’re capable of when the constraints disappear. To show them that the data they’ve been waiting for is accessible now. That the creative they’ve been briefing can be generated instantly. That the campaigns they’ve been coordinating can be orchestrated autonomously.
The data analyst who only ran reports can now build predictive models and operationalize them in real time. The campaign manager who only coordinated handoffs can now design, test and optimize end-to-end journeys independently. The creative strategist who only wrote briefs can now generate and deploy assets across every channel.
This is the revolution: not that technology does the work, but that technology removes the barriers that prevented people from doing work they were always capable of.
The misfits and rebels of 1997 saw possibilities where others saw limitations. They refused to accept that things had to be done the way they’d always been done.
They’re refusing to wait when customers need action now. They’re refusing to accept that insight takes weeks when platforms deliver it in seconds. They’re refusing to operate within constraints that technology has already eliminated.
They’re thinking differently. Not because they’re trying to be difficult. But because the old way of thinking no longer matches the new reality of what’s possible.
In 1997, Apple told us: “The people who are crazy enough to think they can change the world are the ones who do.”
In 2025, the people crazy enough to think they can deliver personalized experiences at scale, launch campaigns in hours instead of weeks, and operate without dependencies are the ones who will.
The constraints are gone.
The assembly-line marketing box can no longer exist.
Google is pushing back on an Adweek report that says the company told advertisers ads are coming to the Gemini app in 2026.
The post Google Pushes Back On Adweek Report About Gemini Ads In 2026 appeared first on Search Engine Journal.
A practical look at Google Ads’ 2025 releases, key takeaways for PPC managers, and what’s likely to shape strategy in 2026.
The post What Google’s 2025 Year in Review Tells Us About the Future of PPC appeared first on Search Engine Journal.
