Self-serve negative keyword lists are now live in Microsoft Advertising, according to Ads Liaison Navah Hopkins — giving advertisers long-requested control without submitting support tickets.
What’s happening. Advertisers can now create and manage shared negative keyword lists directly in the UI. Lists support up to 5,000 negative keywords (one per line) and can be applied at either the campaign or account level. Match types function the same way in Performance Max as they do in traditional Search campaigns.
Lists can also be edited, exported as CSV files, or removed from campaigns as needed.
Microsoft notes that match type formatting requires brackets for exact match and quotation marks for phrase match — not hyphens.
Why we care. Negative keywords are critical for filtering irrelevant traffic and protecting budgets. Making lists self-serve streamlines workflow, reduces reliance on support tickets, and gives advertisers faster control over search query exclusions.
The bottom line. Microsoft is handing more operational control back to advertisers — and eliminating friction in one of the most essential levers for campaign efficiency.
Google published a new help document outlining how passkeys work in Google Ads — a timely move as advertisers face a rise in account hacks and phishing attempts.
What’s happening. The new help page explains how passkeys function as a passwordless, phishing-resistant login method in Google Ads, and clarifies when they’re required — including for sensitive actions like user access changes and account linking updates.
The documentation walks advertisers through device requirements, setup steps and security considerations.
Why we care. Ad accounts are increasingly being targeted by attackers, with compromised logins leading to budget theft, campaign disruption and data loss. Clearer guidance from Google gives advertisers a straightforward path to strengthening account defenses at a critical moment.
The bottom line. As account takeovers become more common, better education around security tools like passkeys is a practical win for advertisers looking to lock down access and reduce risk.
You can now generate custom PPC tools in plain English. With GPT-5 enabling complete program generation, the competitive edge belongs to those who master AI-assisted automation.
Frederick Vallaeys is building tools in minutes, not days or months, with AI. Vallaeys spent 10 years at Google building tools like Google Ads Editor, then another 10 building tools at Optmyzr, where he’s CEO.
He’s watched automation evolve firsthand, and vibe coding is the next leap. At SMX Next 2025, he shared his journey with vibe coding.
The traditional script problem
If you work in PPC, automation has always been top of mind. In the early days, you relied on Google Ads scripts. Scripts are great because there’s always more work than fits in a day.
But here’s the problem: when Vallaeys asks who actually writes their own scripts, only three to five out of 100 raise their hands. Most people copy and paste scripts because they don’t know how to code.
This works, but it’s limiting. You’re stuck with what someone else built instead of implementing your own secret sauce.
GPT changes the game
A couple of years ago, GPT made it easy to write scripts without knowing how to code.
The best part? Large language models are multimodal. You can take a whiteboard flowchart of your campaign decision tree, give the image to AI, and it’ll write the full Google Ads script.
Vallaeys suggests rethinking meetings. Instead of seeing client meetings as more work, treat them as prompt-engineering sessions.
It’s easy to get frustrated when clients add more to your plate. But with a mindset shift, the meeting becomes the prompt that tells AI what to execute.
What is vibe coding?
Instead of writing lines of code, you describe what you want the software to do, and the AI handles the technical implementation. That’s vibe coding.
Imagine your team needs software that does X, Y, and Z. Write down what it needs to do, give it to a coding tool, and it builds the software. As Vallaeys says, it’s mind-blowing.
Scripts are old news. Vibe coding is the new frontier.
A live example: Building a persona scorer
Vallaeys showed how fast this works. He went to Lovable and said, “Build me a persona scorer for an ad that shows how well it resonates with five different audiences.”
In less than 20 seconds, the AI responded with its design vision, features, and approach. It explained exactly what it would build, so he could immediately say, “Actually, make it 10 audiences instead of five.”
You work with it like a human developer — without touching code. You just describe what you want changed.
The framework: What should you automate?
Traditionally, you automated two types of work: quick, frequent tasks (like reviewing search terms) and long, infrequent tasks (like monthly reporting with analysis).
Vallaeys advises you not to limit automation to what you already do. Think about what you wish you could do more often but haven’t because it’s too time-consuming. That’s prime automation territory.
The old way vs. The new way
The old process was painful. Launching something took at least a month.
You’d spend days writing specs. Engineers would spend days building. You’d find bugs, coordinate meetings, and repeat.
The other problem? Traditional code was deterministic — pure if/then logic. Great for reliability, but terrible for nuanced decisions like, “Is this a competitor term?” It’s nearly impossible to program every variation of competitor keywords.
The promise of on-demand software
Sam Altman announced GPT-5, leading with “on-demand software generation.” The industry is moving beyond software-as-a-service to true on-demand software.
The new way? Write a one-paragraph spec (five minutes), give it to AI (15-minute build), then review and iterate (three minutes per change). In under an hour, you have working automation.
This new code is flexible, not just deterministic. LLMs can answer nuanced questions like, “Is this a competitor term?” with high probability. It’s the best of both worlds.
The expanding scope of automation
With vibe coding, anything you can explain to a human, a machine can build. Landing pages that follow brand guidelines? Done. Custom audience tools? Done.
Here’s the radical shift: you can now automate tasks that take just 90 minutes by hand. Build throwaway software for one-time tasks. Even if it breaks next month, it saved you time today.
What can you build with vibe coding?
You can build landing pages, microsites, interactive web apps, Chrome extensions, browser extensions, and WordPress plugins — all through simple prompts.
Available tools
Start with Claude or ChatGPT — tools you likely already subscribe to. They’re great for data analysis, calculators, and quick visualizations.
For more complex apps that need databases or login systems, use Lovable, V0.dev, Replit, or Bolt. They handle the complexity, so you don’t have to.
If you’re more technical, try Codex, Bolt.new, or Cursor. But for most people, the simpler tools handle almost everything.
Case Study 1: Seasonality analysis tool
Vallaeys asked someone on his team who had never coded to build a seasonality analysis tool. She fed PPC Town Hall podcast videos into Claude.
The process was simple: gather resources, write a prompt, give it to AI, and test it in the browser. No installation required.
The team iterated on the fly, asking for different plots and forecasting methods. In minutes, they had advanced enhancements. The AI knew where to add help text and simplify the interface because it’s trained on millions of web apps.
Case Study 2: Panel of experts tool
Vallaeys wanted multiple custom GPTs to review his blog posts in sequence, each giving feedback from its persona. Then a consolidator GPT would summarize the most common feedback into three to five bullet points.
He vibe-coded this in V0.dev by describing what he wanted. It generated a clean tool with text input, the ability to add custom GPTs, and everything worked.
Case Study 3: Chrome extension for demos
For customer demos, Vallaeys needed to blur sensitive numbers. He wanted options:
Fully redact or just blur?
Include currencies or only numbers?
Handle different separators?
He built a Chrome extension with all those options using simple prompts. Problem solved.
Prompting tips for success
Always include the use case. Say “seasonality tool” instead of vague terms like “time series analysis.” The AI makes better assumptions and may suggest approaches you hadn’t considered.
Ask questions: “How did you approach this?” or “Where do you store data?” It helps you learn.
Use chat mode to explore alternatives without changing the code. Ask for three approaches, pick one, go deeper, then say, “Execute that.”
The PPC audience analyzer
The audience analyzer Vallaeys’ team built is available to try. You can grab the code, add your logo, turn insights into action items — whatever you need. Just tell it what to change, and it updates.
Final thoughts: Stay competitive
Vallaeys makes one point clear: you’re not competing against AI. You’re competing against people who use it better than you do.
Try vibe coding today. Go to one of these tools and give it a single prompt. See what happens. The first time Vallaeys tried it, his mind was blown.
Now that you’ve learned something new, use it to get better at AI. That’s how you stay ahead.
Google DeepMind is rolling out Nano Banana 2 (Gemini 3.1 Flash Image), its latest image generation model, combining Nano Banana Pro’s intelligence and production controls with Gemini Flash’s speed.
What’s new. Nano Banana 2 introduces:
Advanced world knowledge: Powered by Gemini’s real-time web grounding to render specific subjects more accurately and generate infographics or data visualizations.
Precision text rendering and translation: Cleaner, legible in-image text, including localization.
Stronger instruction adherence: Better handling of complex, multi-layered prompts.
Subject consistency: Maintains up to five characters and 14 objects in a single workflow.
Production-ready outputs: Supports aspect ratios and resolutions from 512px to 4K.
Enhanced visual fidelity: Sharper detail, richer textures, and more dynamic lighting.
The rollout. Nano Banana 2 is launching across Google’s ecosystem, including Google Ads, Gemini app, Search AI Mode and Lens, and more.
Why we care. Nano Banana 2 helps you produce high-quality, production-ready images faster and at scale, cutting creative time and cost. With stronger text rendering, better subject consistency, 4K-ready outputs, and direct integration into Google Ads and Gemini, you can generate, launch, test, and iterate campaign assets in minutes instead of days.
Bottom line. With Nano Banana 2, you get speed, reasoning, and production-ready visuals in one default model.
ChatGPT’s emerging ad ecosystem is gaining momentum with more brands appearing, clearer trigger patterns, and evolving ad placements, according to AI ad intelligence firm Adthena.
What’s happening. After identifying the first advertisers inside ChatGPT last week, Adthena now reports a clear ramp-up in advertiser participation and ad delivery behavior.
Advertisers spotted so far:
Best Buy
AT&T
Pottery Barn
Enterprise
Qualcomm
Expedia
How ads are triggering. Based on a sample of 1,500+ prompts analyzed over the past week:
Most ads appear on the first prompt.
Some only trigger on the third or fourth repetition of the same query.
High-intent modifiers like “best” and “new” appear to carry significant weight.
Example prompts include:
“I am going to buy a new phone. What is the best phone?”
“I need a new phone.”
“I need to buy a new desk, what’s best?”
Between the lines. Keyword triggers appear relatively simple, focused on strong commercial intent rather than nuanced emotional language. In one example, Best Buy secured two ad placements in a single response for iPhone-related queries, signaling early experimentation with positioning and share of voice.
Why we care. As ChatGPT advertising scales, understanding trigger behavior — even at a basic keyword level — will be critical if you’re testing this new platform.
Spotted. Adthena CMO Ashley Fletcher shared the results of the competing ChatGPT ads, posting screenshots on LinkedIn.
Google is expanding beta access to text guidelines for all advertisers globally in AI Max, giving brands more control over how AI-generated ad copy aligns with their standards.
What’s happening. Text guidelines are now available worldwide across AI Max for Search and Performance Max campaigns, with full language and vertical support.
The feature lets you shape AI-generated creative using natural-language instructions — such as excluding certain terms or avoiding specific phrases — to ensure messaging stays on-brand.
Why we care. As AI-powered creative becomes central to your performance marketing, brand safety and tone control are top concerns. Text customization helps you match ads to user intent, and the new guidelines layer ensures they don’t drift from your brand positioning. You can guide AI with guardrails like “don’t imply our products are cheap” or “avoid language like ‘only for,’” helping you maintain consistency at scale. Early adopters like BYD have seen higher leads at lower costs, showing that combining AI speed with human-guided safeguards can directly improve your campaign results.
Bottom line. Keeping AI-generated ads aligned with your brand voice is likely high on your task list, so Google’s expanded text guidelines meet that need, giving you practical, easy-to-use tools to stay in control while leveraging AI at scale.
The U.S. ad rollout of ChatGPT ads is “iterative,” according to OpenAI’s COO. The early-stage push to monetize ChatGPT’s massive free user base will evolve gradually as the company works to refine the model without eroding user trust.
What OpenAI says. Speaking at the India AI summit, COO Brad Lightcap described the rollout as “iterative,” emphasizing user trust and privacy, TechCrunch reported.
Lightcap said ads, if done right, can be “additive” to the product experience — but acknowledged the company is still in early testing and will need time to refine the model.
Catch up quick. OpenAI started introducing ads to free and Go-tier users of ChatGPT in the U.S., marking a significant shift in its monetization strategy.
CEO Sam Altman recently sparred publicly with Anthropic over its Super Bowl ad campaign, defending OpenAI’s commitment to broad, free AI access. He argued that scale creates a “differently-shaped problem” for OpenAI compared to rivals with smaller user bases.
Reports suggest OpenAI is charging premium rates — as high as $60 CPM — with minimum commitments reportedly starting around $200,000.
Partners like Shopify are enabling merchants to advertise in ChatGPT through Shop Campaigns, alongside early testers such as Target and Adobe.
Bottom line. Ads are now part of ChatGPT’s future. Stay tuned to see whether OpenAI can monetize without compromising the product experience that fuelled its growth.
Google is rolling out a significant update to how average daily budgets pace in campaigns that use ad scheduling — and it could materially change monthly spend totals.
What’s happening. Starting March 1, 2026, Google Ads will begin proactively pacing budgets to spend up to the full 30.4x monthly limit, even if campaigns only run on specific days via ad scheduling.
How it works:
The 2x daily overspend rule stays in place.
The 30.4x average daily budget monthly cap remains unchanged.
Campaigns will not run outside scheduled hours.
But Google will now attempt to hit the full monthly ceiling within the allowed schedule.
Why we care. Until now, advertisers running limited schedules — like weekends only — effectively spent less per month because Google paced against active days. Campaigns using ad scheduling may start spending significantly more per month — even though daily budgets and billing caps haven’t changed.
Google will now push harder to hit the full 30.4x monthly limit within scheduled days, which could double spend for weekend-only or limited-hour campaigns. Without adjusting daily budgets, marketers risk unintentionally overshooting their intended monthly targets.
Example. A campaign set to weekends only with a $100 daily budget previously spent about $800/month (roughly eight weekend days).
Under the new pacing logic, it could spend up to $1,600/month — hitting $200 (2x daily budget) on each scheduled day.
What Google says. According to Google Ads Liaison Ginny Marvin, the goal is to better align pacing behavior with advertisers’ expectations around monthly spend limits. Spend will still be driven by campaign objectives like conversions or conversion value, and no campaign will exceed the existing billing caps.
Ginny also clarified that only advertisers who received notifications about this update will be affected and the change will be slowly rolled out.
Between the lines. This is less about raising limits — and more about how aggressively Google uses existing ones. For advertisers relying on ad scheduling to naturally suppress spend, this could lead to unexpected increases unless daily budgets are recalibrated.
What to do now:
Review campaigns using ad scheduling.
Recalculate daily budgets based on true monthly goals.
Lower daily budgets if you want to maintain previous monthly spend levels.
The bottom line. Google isn’t changing how much you can spend — it’s changing how quickly you will spend it. Flighted and part-time campaigns should adjust before March 2026.
First spotted. This updated was mentioned by Jordan Fry who shared the Google message he got on LinkedIn.
Google Ad Grants accounts can now optimize for real-world foot traffic. If you use the nonprofit program, you can set “shop visits” as an account-level goal, allowing your campaigns to optimize for in-person visits.
Driving the news. Previously, if you tried to mark shop visits as a goal in Ad Grants, you’d get an error. That restriction appears to be lifted, allowing eligible accounts to include store visit conversions in their primary goal configuration.
This update lets you align bidding and optimization with physical visits — especially for visibility in Maps placements and location-driven search results.
Why we care. If you run a nonprofit, museum, place of worship, community center, or other location-based organization, digital engagement doesn’t always translate into mission impact. Optimizing for shop visits bridges that gap, tying ad performance directly to foot traffic.
What to do. If you use Ad Grants, review your account-level goals and confirm shop visits are enabled where eligible. Optimizing for foot traffic could materially improve your local impact — especially if you rely on in-person engagement.
Between the lines. As Google continues to emphasize local intent and Maps-based discovery, bringing store visit optimization to Ad Grants expands your ability to compete for nearby audiences. It shifts the focus from clicks and website traffic to measurable offline action.
First seen. Google Ads expert Jason King spotted this update and shared it on LinkedIn.
Google’s unified video manager in Merchant Center is no longer empty. After months of showing up in accounts without visible content, the Video Assets section is now automatically populating with sourced videos.
Driving the news. Videos are now automatically pulled in, including content from external sources like YouTube.
The feature — first introduced at Google Marketing Live 2025 — was designed to centralize video content inside Google Merchant Center. It began rolling out in September, but many advertisers saw a blank interface with no assets.
Why we care. This confirms Google is moving ahead with its plan to make Merchant Center a central hub for commerce-ready creative — not just product feeds. With videos now auto-populating, you may gain additional visibility across Shopping and Performance Max without extra upload work, but you’ll also need to ensure your YouTube and site videos are optimized for commerce. In short, video is becoming embedded in retail ad delivery, and if you manage it proactively, you’ll have a competitive edge.
Between the lines. By centralizing videos from your website, social platforms, and potentially AI-generated sources, Google is turning Merchant Center into a more comprehensive creative hub—not just a product feed manager. That aligns with the broader shift toward video-first shopping experiences across Search, Shopping, and Performance Max.
What to watch. It’s still unclear how performance reporting, optimization controls, and editing tools will evolve in the Video Assets section. But the shift from an empty placeholder to a populated library shows the infrastructure is now active.
First spotted. PPC News Feed founder Hana Kobzová first spotted this update.
Advertisers contacting Google Ads support may now need to grant explicit authorization before they can even submit a help request — giving a Google specialist permission to access and make changes directly inside their account.
Here’s what’s happening. Users are first routed to a beta AI chat. If they opt to submit a support form instead, they must tick an “Authorisation” box. The wording allows a Google Ads specialist, on behalf of the company, to reproduce and troubleshoot issues by making changes directly in the account.
The fine print is clear. Google doesn’t guarantee results. Any adjustments are made at the advertiser’s own risk. And the advertiser remains solely responsible for the impact on campaign performance and spending.
Why we care. The required checkbox shifts more responsibility onto advertisers at a time when automation and AI already limit hands-on control. If support makes changes, the performance and spend risk still sits with the advertiser.
Between the lines. This creates a trade-off between speed and control. Granting access could accelerate troubleshooting, but it also opens the door to account-level changes that may affect live campaigns — without any assurance of improved outcomes.
The bottom line. Getting support may now mean temporarily handing over the keys — while keeping full accountability for whatever happens next.
First seen. This new caveats to getting support was spotted by PPC specialist Arpan Banerjee who shared spotting the message on LinkedIn.
Demand Gen marks a shift in Google Ads toward visual advertising beyond keywords and text. Relying on traditional strategies when testing it wastes budget, hurts performance, and limits opportunity. To succeed, you have to think more like a social advertiser than a search advertiser.
At SMX Next, Industrious Marketing owner Jack Hepp explained why many businesses struggle with demand gen campaigns — especially in B2B and lead generation — while also sharing insights relevant to ecommerce.
Understanding the Shift: From Intent to Interruption
Demand Gen reflects Google’s shift from intent-first search advertising to visual, discovery-based campaigns.
Instead of targeting users actively searching for your service, you reach them as they scroll through YouTube, Gmail, or Discovery feeds.
This changes your approach: visual creative becomes the new keyword, replacing traditional targeting.
Common misalignments in Demand Gen strategy
Applying outdated search strategies can lead to failure with Demand Gen. The four main mistakes:
Expecting bottom-of-funnel CPAs from mid-funnel traffic.
Using overly broad, “spray and pray” targeting.
Running bland, generic creative.
Not knowing how to optimize without negative keywords.
Success requires a social advertising mindset.
Campaign structure: Understanding the hierarchy
Demand Gen uses a two-level structure.
Campaign-level settings control broad parameters like bidding strategy, conversion goals, and device targeting.
Ad group–level settings control audiences, locations, and channels.
Each ad group learns independently—insights don’t transfer—allowing precise audience segmentation with tailored creative.
Creating interruption-based creative
You must stop their scroll within 3-4 seconds. Your creative must capture attention immediately, speak to a specific pain point, and present your solution.
Unlike search ads — where users are actively looking for you — Demand Gen interrupts browsing, so your message must be instantly compelling and problem-focused.
Aligning visuals to the customer journey
Match your offer to audience readiness.
Cold audiences need educational content like free guides or diagnostic tools.
Warm audiences respond to case studies, webinars, and comparison tools.
Hot audiences are ready for demos and direct purchase offers.
Misaligning them — like pushing demos to cold audiences — guarantees failure from the start.
The power of problem-focused creative
Generic ads with stock photos and basic headlines get scrolled past. Winning creative uses bold headlines, striking visuals, and problem-focused messaging.
For example, “43% of cyberattacks target small businesses” speaks to a specific pain point, making the ad stand out and prompting engagement instead of a scroll.
Bidding and budget strategies
Demand Gen uses campaign goals rather than traditional bidding strategies: conversion-focused, click-focused, or conversion–value–focused.
Aim for 50+ conversions per month and budget 10–15x your target CPA to build enough data.
For click-based bidding, set budget based on desired traffic volume and target CPC.
Demand Gen is highly data-reliant, so hitting these thresholds is critical to performance.
Can Demand Gen work with small budgets?
Yes, with strategic planning.
Focus on mid- or upper-funnel audiences and optimize for MQLs instead of bottom-funnel conversions. This helps you reach 50+ monthly conversions for data density, even with smaller budgets.
Align your goals, targeting, and budget to generate enough conversion data.
Building the right audience
Avoid two extremes:
Audiences that are too broad (billions of impressions) where Google can’t identify your target.
Audiences too narrow (a few thousand impressions) where you can’t build data density.
The sweet spot: start with custom segments based on search terms or competitor websites, then layer in lookalike segments and strategic first-party data. Avoid optimized targeting at first — it works best to expand already successful campaigns.
The role of creative in targeting
Your creative shapes who Google targets. The people who engage with your ads teach Google who to show them to next.
Performance peaks when your creative speaks to your ideal customer profile. Align messaging to the buyer’s stage — cold audiences need different messaging than hot prospects.
Strategic exclusions
Use exclusions surgically, not broadly. It’s tempting to exclude like negative keywords, but over-excluding shrinks your audience too much.
Focus only on clear non-converters (e.g., specific age groups, locations, or audiences you know won’t respond). Give Google room to find engaged users within your parameters, rather than narrowing to the point of ineffectiveness.
Optimization: Where to focus
Without negative keywords, optimize through three levers: creative, audience, and offer. Test multiple formats (video, image, carousel) and styles (UGC, testimonials, problem-focused messaging). Continuously refine what works with new hooks and data points.
Test offers to match audience readiness — cold audiences need educational content, while hot audiences need direct CTAs.
Prioritize post-click optimization: improve landing pages, strengthen tracking with CRM integration, and ensure clean data feeds Google’s learning.
Real-world case study
A telecommunications company targeting B2B managed IT services drove strong results by aligning all three elements.
Offer: An interactive quiz showing businesses how managed IT could reduce costs.
Targeting: Custom segments based on proven search terms and competitor website visitors.
Creative: Problem-focused messaging about cybersecurity threats to small businesses.
Results:
$10 cost per MQL.
3.8% conversion rate.
40% of quiz takers became SQLs.
20% increase in total SQLs.
Key takeaways
As you plan your next campaign:
Match your creative to your customer and their stage in the journey.
Target the right audience at the right point in that journey.
Test and optimize creative and offers to find what resonates and drives action.
Looking to take the next step in your search marketing career?
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Google Merchant Center is investigating an issue affecting Feeds, according to its public status dashboard.
The details:
Incident began: Feb. 4, 2026 at 14:00 UTC
Latest update (Feb. 20, 14:43 UTC): “We’re investigating reports of an issue with Feeds. We will provide more information shortly.”
Status: Service disruption
The alert appears on the official Merchant Center Status Dashboard, which tracks availability across Merchant Center services.
Why we care. Feeds power product listings across Shopping ads and free listings. Any disruption can impact product approvals, updates, or visibility in campaigns tied to retail inventory.
What to watch. Google has not yet shared scope, root cause, or estimated time to resolution. Advertisers experiencing feed processing delays or disapprovals may want to monitor the dashboard closely.
Bottom line. When feeds stall, ecommerce performance can follow. Retail advertisers should keep an eye on diagnostics and campaign delivery until more details emerge.
PPC is evolving beyond traditional search. Those who adopt new ad formats, smarter creative strategies, and the right use of AI will gain a competitive edge.
Ginny Marvin, Google’s Ads Product Liaison, and Navah Hopkins, Microsoft’s Product Liaison, joined me for a conversation about what’s next for PPC. Here’s a recap of this special keynote from SMX Next.
Emerging ad formats and channels
When discussing what lies beyond search, both speakers expressed excitement about AI-driven ad formats.
Hopkins highlighted Microsoft’s innovation in AI-first formats, especially showroom ads:
“Showroom ads allow users to engage and interact with a showroom where the advertiser provides the content, and Copilot provides the brand security.”
She also pointed to gaming as a major emerging ad channel. As a gamer, she noted that many users “justifiably hate the ads that serve on gaming surfaces,” but suggested more immersive, intelligent formats are coming.
Marvin agreed that the landscape is shifting, driven by conversational AI and visual discovery tools. These changes “are redefining intent” and making conversion journeys “far more dynamic” than the traditional keyword-to-click model.
Both stressed that PPC marketers must prepare for a landscape where traditional search is only one of many ad surfaces.
Importance of visual content
A major theme throughout the discussion was the growing importance of visual content. Hopkins summed up the shift by saying:
“Most people are visual learners… visual content belongs in every stage of the funnel.”
She urged performance marketers to rethink the assumption that visuals belong only at the top of the funnel or in remarketing.
Marvin added that leading with brand-forward visuals is becoming essential, as creatives now play “a much more important role in how you tell your stories, how you drive discovery, and how you drive action.” Marketers who understand their brand’s positioning and reflect it consistently in their creative libraries will thrive across emerging channels.
Both noted that AI-driven ad platforms increasingly rely on strong creative libraries to assemble the right message at the right moment.
Myths about AI and creative
The conversation also addressed misconceptions about AI-generated creative.
Hopkins cautioned against overrelying on AI to build entire creative libraries, emphasizing:
“AI is not the replacement for our creativity… you should not be delegating full stop your creative to AI.”
Instead, she said marketers should focus on how AI can amplify their work. Campaigns must perform even when only a single asset appears, such as a headline or image. Creatives need to “stand alone” and clearly communicate the brand.
Marvin reinforced the need for a broader range of visual assets than most advertisers maintain. “You probably need more assets than you currently have,” she noted, especially as cross-channel campaigns like Demand Gen depend on testing multiple combinations.
Both positioned AI as an enabler, not a replacement, stressing that human creativity drives differentiation.
Strategic use of assets
Both liaisons emphasized the need for a diverse, adaptable asset library that works across formats and surfaces.
Marvin explained that AI systems now evaluate creative performance individually:
“Underperforming assets should be swapped out, and high-performing niche assets can tell you something about your audience.”
Hopkins added that distinct creative assets reduce what she called “AI chaos moments,” when the system struggles because assets overlap too closely. Distinctiveness—visual and textual—helps systems identify which combinations perform best.
Both urged marketers to rethink creative planning, treating assets as both brand-building and performance-driving rather than separating the two.
Partnering with AI for measurement
The conversation concluded with a deep dive into what it means to measure performance in an AI-first world.
Hopkins listed the key strategic inputs AI relies on:
“First-party data, creative assets, ad copy, website content, goals and targets, and budget. These are the things AI uses to optimize towards your business outcomes.”
She also highlighted that incrementality — understanding the true added value of ads — is becoming more important than ever.
Marvin acknowledged the challenges marketers face in letting go of old control patterns, especially as measurement shifts from granular data to privacy-protective models. However, she stressed that modern analytics still provide meaningful signals, just in a different form:
“It’s not about individual queries anymore… it’s about understanding the themes that matter to your audience.”
Both encouraged marketers to think more strategically and holistically in their analysis rather than getting stuck in granular metrics.
On episode 352 of PPC Live The Podcast, I spoke to Emina Demiri Watson, Head of Digital at Brighton-based Vixen Digital, where she to shared one of the most candid stories in agency life: deliberately firing a client that accounted for roughly 70% of their revenue — and what they learned the hard way in the process.
The decision to let go
The client relationship had been deteriorating for around three months before the leadership team made their move. The decision wasn’t about the client being difficult from day one — it was a relationship that had slowly soured over time. By the end, the toxic dynamic was affecting the entire team, and leadership decided culture had to come first.
The mistake they didn’t see coming
Here’s where it got painful. When Vixen sat down to run the numbers, they realized they had a serious customer concentration problem — one client holding a disproportionately large share of total revenue. It’s the kind of thing that gets lost when you’re busy and don’t have sophisticated financial systems. A quick Excel formula later, and the reality hit harder than expected.
Warning signs agencies should watch for
Emina outlined the signals that a client relationship is shifting — beyond the obvious drop in campaign performance. External factors inside the client’s business matter too: company restructuring, team changes, even a security breach that prevents leads from converting downstream. The lesson? Don’t just watch your Google Ads dashboard — understand what’s happening on the client’s side of the fence.
How they clawed back
Recovery came down to three things: tracking client concentration properly going forward, returning to their company values as a decision-making compass, and accepting that rebuilding revenue simply takes time. Losing the client freed up the mental bandwidth to pitch new business and re-engage with the industry community — things that had quietly fallen by the wayside.
Common account mistakes still haunting audits in 2026
When asked about errors she sees in audited accounts, Emina didn’t hold back. Broad match without proper audience guardrails remains a persistent problem, as does the absence of negative keyword lists entirely. Over-narrow targeting is another — particularly for clients chasing high-net-worth audiences, where the data pool becomes too thin for Smart Bidding to function.
The right way to think about AI
Emina’s take on AI is pragmatic: the biggest mistake is believing the hype. PPC practitioners are actually better positioned than most to navigate AI skeptically, given they’ve been working with automation and black-box systems for years. Her preferred approach — and the one she quietly enforces with junior team members via a robot emoji — is to treat Claude and other LLMs as a first stop for research, not a replacement for critical thinking.
The takeaway
If you’re sitting on a deteriorating client relationship and nervous about pulling the trigger, Emina’s advice is simple: go back to your values. If commercial survival sits at the top of the list, keep the client. If culture and team wellbeing matter more, it might be time.
Google is updating how it attributes conversions in app campaigns, shifting from the date of the ad click to the date of the actual install.
What’s changing. Previously, conversions were logged against the original ad interaction date. Now, they’re assigned to the day the app was actually installed — bringing Google’s methodology closer in line with how Mobile Measurement Partners (MMPs) like AppsFlyer and Adjust report data.
Why this helps:
It should meaningfully reduce discrepancies between Google Ads and MMP dashboards — a persistent headache for mobile marketers reconciling two different numbers.
Google’s default 30-day attribution window meant many conversions were being reported too late to be useful for campaign learning, effectively starving Smart Bidding of timely signals.
Tying conversions to install date gives the algorithm fresher, more accurate data — which should translate to faster optimization cycles and more stable performance.
Why we care. The change sounds technical, but its impact is significant. Attribution timing directly affects how Google’s machine learning optimizes campaigns — and a 30-day lag between ad click and conversion credit has long been a silent drag on performance. This change means Google’s machine learning will finally receive conversion signals at the right time — tied to when a user actually installed the app, not when they clicked an ad weeks earlier.
That shift should lead to smarter bidding decisions, faster campaign optimization, and fewer frustrating discrepancies between Google Ads and MMP reporting. If you’ve ever wondered why your Google numbers don’t match AppsFlyer or Adjust, this update is a direct response to that problem.
Between the lines. Most advertisers never touch their attribution window settings, leaving Google’s 30-day default in place. That default has quietly been working against them — delaying the conversion signals that machine learning depends on to make better bidding decisions.
The bottom line. A small change in attribution logic could have an outsized impact on app campaign performance. Mobile advertisers should monitor their data closely in the coming weeks for shifts in reported conversions and optimization behavior.
First spotted. This update was first spotted by David Vargas who shared receiving a message of this post on LinkedIn.
Google Ads is now displaying examples of how “Landing Page Images” can be used inside Performance Max (PMax) campaigns — offering clearer visibility into how website visuals may automatically become ad creatives.
How it works. If advertisers opt in, Google can pull images directly from a brand’s landing pages and dynamically turn them into ads. Now when creating your campaigns, before setting it live, Google Ads will show you the automated creatives it plans on setting live.
Why we care. For PMax campaigns your site is part of your asset library. Any banner, hero image, or product visual could surface across Search, Display, YouTube, or Discover placements — whether you designed it for ads or not. Google Ads is now showing clearer examples of how Landing Page Images may be used inside those PMax campaigns — giving much-needed visibility into what automated creatives could look like.
Instead of guessing how Google might transform site visuals into ads, brands can better anticipate, audit, and control what’s eligible to serve. That visibility makes it easier to refine landing pages proactively and avoid unwanted surprises in live campaigns.
Between the lines: Automation is expanding — but so is creative risk. Therefore this is a very useful update that keeps advertisers aware of what will be set live before the hit the go live button.
Bottom line: In PMax, your website is no longer just a landing page. It’s part of the ad engine.
First seen. This update was spotted by Digital Marketer Thomas Eccel who showed an example on LinkedIn.
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