PPC Pulse: Google Data Manager API, YouTube Shorts, LinkedIn Reserved Ads via @sejournal, @brookeosmundson

The PPC platforms rolled out a few meaningful updates this week that shape how we measure, plan, and buy media.

Google introduced a new API that makes it easier to bring first party data into Ads. YouTube shared improvements to the Shorts advertising experience. LinkedIn launched Reserved Ads to give advertisers more control over pricing and delivery.

Here is what stood out and why these updates matter for day-to-day execution.

Google Launches Data Manager API

Google announced the Data Manager API, a new way for advertisers to push their offline conversions and business data directly into Google Ads. The goal is to make measurement setups simpler and more reliable, especially as more teams rely on modeled conversions.

According to Google, the API helps advertisers turn first party data into performance signals that Smart Bidding can use. It also removes some of the friction that previously made offline tracking complicated.

Ginny Marvin, Google Ads Liaison, added helpful context on LinkedIn where she noted that this update is designed to support more flexible measurement setups across platforms and internal systems.

If you manage accounts with sales teams, long consideration cycles, or mixed online and offline activity, this is a welcome step. Better data pipelines usually translate to better bidding performance.

It also signals that Google is prioritizing easier paths for advertisers who have struggled to adopt accurate conversion tracking.

Why this matters for advertisers

Platforms continue to raise the bar on first party data. Advertisers who rely on spreadsheets, uploads, or manual CRM processes will fall behind.

The API helps teams move closer to real time signals, which Smart Bidding depends on. It also reduces the gap between what actually happens in the business and what Google sees inside Ads.

This update gives advanced teams more flexibility, and it gives mid sized teams a way to clean up measurement issues that have slowed performance.

YouTube Shorts Rolls Out New Ad Experience

YouTube shared several updates to help advertisers get more out of Shorts during the holiday season.

Google highlighted Kantar research showing that YouTube Creator Ads on Shorts increase purchase intent by 8.8% on average and drive higher consumer intent to spend compared to competitors.

The new updates focus on making Shorts ads feel closer to the organic experience while giving brands more ways to guide user action. The main updates include:

• Google is introducing comments on eligible Shorts ads so brands can respond to viewers in a more natural environment.
• Shorts creators can now link directly to a brand’s website in branded content, which gives viewers a clearer path to learn more.
• Google is also expanding Shorts ads to mobile web, which adds another surface for short form video placements across TV, web, desktop, and mobile app.

Why this matters for advertisers

Short form video still moves quickly, and advertisers need placements that offer both reach and some level of interaction.

These updates make Shorts more workable for teams that want clearer signals and more opportunities to understand how users respond. The added surfaces and creator linking options give brands more flexibility as they plan holiday and year-end campaigns.

LinkedIn Introduces Reserved Ads and New Creative Tools

LinkedIn announced a set of updates aimed at helping B2B marketers build awareness with more consistency and scale.

The platform is positioning these changes around brand building, noting that only a small percentage of buyers are in-market at any given time. The updates focus on giving advertisers more predictable visibility and more efficient ways to produce and personalize creative.

The biggest addition is Reserved Ads. This placement guarantees the first ad slot in the LinkedIn feed, which gives brands steady reach in a high-attention position.
LinkedIn describes it as a way to secure predictable impressions and a larger share of top-of-feed delivery. It supports multiple formats including Video Ads, Thought Leader Ads, Single Image Ads, and Document Ads.

LinkedIn also introduced ad personalization tools that allow marketers to tailor copy to individual members using profile-based fields like first name, job title, industry, or company name.

The goal is to make impressions feel more relevant without requiring one-off creative. These features are only available to managed accounts for now.
An important note is that Reserved Ads and Ad Personalization are only available to advertisers who have a LinkedIn Account Representative.

LinkedIn is also expanding its creative support with AI Ad Variants, which generate multiple copy versions from a single input, and a flexible ad creation workflow rolling out in early 2026.

Advertisers will be able to upload multiple images, videos, and copy variations, and LinkedIn will mix and match them across campaigns while shifting spend toward what performs best.

Why this matters for advertisers

LinkedIn continues to push deeper into brand advertising, and these updates reflect that direction.

Reserved Ads give marketers more certainty when planning top-of-funnel campaigns, something B2B teams often struggle to secure. Personalization and creative automation address a different challenge: producing enough message variation to keep performance stable across longer sales cycles.

For teams who rely on LinkedIn for both awareness and consideration, these tools may help streamline production and improve consistency without adding complexity.

The real value will come from how well these features integrate into existing campaign structures and how accurately they surface top-performing creative.

Theme of the Week: Platforms Are Reducing Friction

Across Google, YouTube, and LinkedIn, the updates had a similar goal. Each platform is trying to remove barriers that slow down planning, measurement, or creative production.

Google is making it easier to bring in first party data so advertisers can give better signals to their bidding strategies. YouTube is tightening tools around Shorts to help brands participate in short form video with fewer gaps in user flow. LinkedIn is focusing on predictability and creative efficiency so B2B marketers can maintain visibility without adding more operational work.

Each change supports a familiar goal: making it easier for advertisers to plan, measure, and adjust without unnecessary complexity. Folding these updates into your workflows can help create steadier execution and more reliable signals as planning continues into 2026.

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Featured Image: Pixel-Shot/Shutterstock

When To Say No To PMax: Strategic Use Cases For Standard Shopping Campaigns

Google is “strongly recommending” Performance Max to advertisers. With its promise of automated optimization across all Google inventory and AI-driven functions, it’s easy to see why Google pushes it so heavily. But here’s the reality: Performance Max isn’t always the best choice, and blindly migrating from Standard Shopping campaigns can actually hurt your performance.

B2B And Low-Conversion Industries Need Different Approaches

The Problem With PMax For Complex Sales

Performance Max thrives on conversion data. Its machine learning algorithms need volume, lots of it, to optimize effectively. But what happens when you’re in an industry where conversions are rare, high-value, or take months to materialize?

B2B companies selling industrial equipment, luxury retailers, or businesses with extended sales cycles face a critical challenge: Performance Max’s algorithms don’t have enough conversion data to learn from. When you’re generating five to 10 conversions per month instead of 500, PMax has almost no signals to optimize for. It’s a constant “learning mode,” making bid decisions based on insufficient data, which might work here and there, but will overall and long-term lead to worse results.

Why Standard Shopping Wins Here

Standard Shopping campaigns allow you to:

• Implement manual or target ROAS bidding based on your business intelligence, not Google’s incomplete picture.
• Track and optimize for micro-conversions like quote requests, catalog downloads, or contact form submissions that actually drive B2B pipeline.

The Micro-Conversion Trap In Performance Max

While Performance Max technically supports micro-conversion tracking, it introduces significant risk. When you feed PMax lower-funnel actions like add-to-cart events, contact form submissions, or page views, the algorithm optimizes aggressively for volume, often at the expense of quality, but quality is what matters in B2B and most low-conversion industries.

The result? Your budget shifts toward Display and YouTube placements, where these micro-conversions are abundant but largely meaningless. Display networks excel at generating cheap engagement metrics: a user scrolling through their favorite blog might accidentally trigger an “engaged view” or click, registering as a conversion event without any genuine purchase intent.

The Channel Quality Problem

This creates a vicious cycle:

• Display and YouTube generate high volumes of soft conversions (page views, brief site visits, accidental clicks).
• Performance Max interprets this as success and allocates more budget to these channels.
• Your spend shifts away from high-intent Shopping and Search traffic.
• You’re optimizing for what amounts to noise conversions that rarely lead to actual revenue.

This is a good example of an advertiser using many conversion types that had decent running campaigns for a long time, but all of a sudden, traffic shifted to display because of heavy soft-conversion usage.

Standard Shopping sidesteps this entirely. By maintaining channel focus on product-search traffic, you ensure that your optimization efforts target genuine business outcomes rather than vanity metrics that inflate Performance Max’s reported success while destroying your actual return on investment (ROI).

Preventing Channel Dilution: When You Need Feed-Only Traffic

The Expansion Problem

One of Performance Max’s most frustrating characteristics is its aggressive expansion across Google’s entire inventory. You might launch a PMax campaign expecting Shopping results, only to find your budget spend into Display banner ads, YouTube pre-rolls, and Discovery placements that deliver clicks but no conversions.

This isn’t always what advertisers want. Sometimes you know that Shopping and Search traffic converts, while Display traffic doesn’t work for your product or brand.

Maintaining Traffic Quality

Standard Shopping keeps you focused on high-intent, product-search traffic. When someone searches “stainless steel refrigerator 36 inch,” they’re ready to buy. That’s fundamentally different from someone scrolling YouTube who sees your ad.

Use Standard Shopping when:

• Your products require high purchase intent: complex, considered purchases that need active research.
• Display traffic consistently underperforms: you’ve tested it, and it doesn’t work for your category.
• You want to avoid brand safety issues: maintaining control over where your ads appear matters for your brand.
• Creative asset requirements are a burden: you don’t have the resources to create quality images, videos, and headlines for all placement types.

A niche outdoor gear retailer, for example, might find that their technical climbing equipment only converts from Shopping traffic. Display and YouTube placements generate cheap clicks from casual browsers who aren’t serious buyers. Standard Shopping lets them stay focused on the traffic that actually drives revenue.

The Brand-Building Misconception

Some argue that Performance Max’s cross-channel reach provides valuable brand-building benefits that justify lower-performing Display and YouTube placements. While brand building certainly has benefits for established brands with sufficient budgets, this argument falls apart under scrutiny.

True brand building requires strategic planning: dedicated creative campaigns, carefully selected ad formats, intentional media placement, brand lift studies, and proper measurement frameworks to assess impact on awareness, consideration, and perception. Professional brand campaigns are controlled, measurable, and designed with specific brand objectives in mind.

Performance Max offers none of this. Running PMax and claiming “it also helps with brand building” is marketing rationalization, not strategy. You’re essentially paying for uncontrolled, unmeasured brand exposure as a byproduct of what should be a performance campaign. For retailers operating on thin margins who need every dollar to drive measurable ROI, this unplanned brand spend isn’t a bonus; it’s budget waste disguised as a benefit.

If brand building is genuinely important to your business, invest in dedicated brand campaigns where you control the message, placements, and measurement. Don’t let Performance Max’s algorithmic drift into Display masquerade as brand strategy.

Granular Control With Portfolio Bid Strategies And Bid Caps

The Control Gap In Performance Max

Performance Max operates in a black box. You set a Target ROAS or Target CPA, and Google does … something. You can’t set maximum cost-per-click (CPC) bids, you can’t implement bid caps across product groups, and you can’t fine-tune performance at a granular level.

For businesses operating on tight margins or managing diverse product catalogs with different profitability profiles, this lack of control is a deal-breaker.

Strategic Bid Management

Standard Shopping campaigns support portfolio bid strategies, giving you powerful options:

1. Bid Caps for Margin Protection: Set maximum CPC limits to ensure you never overpay for a click. If your margins can’t support more than $2 per click on certain products, you can enforce that hard limit. PMax might blow past that threshold in pursuit of its learning goals.
2. Product-Level Optimization: Create separate campaigns or ad groups for:

• High-margin vs. low-margin products.
• Seasonal vs. evergreen items.
• Different brands or product categories with varying profitability.

Real-World Application

Consider an electronics retailer with products ranging from 5% margin accessories to 40% margin premium headphones. With Standard Shopping:

• High-margin products get their own campaign with aggressive bidding.
• Low-margin items have strict bid caps to maintain profitability.
• Clearance items run on manual CPC with rock-bottom bids.
• Portfolio strategies ensure overall ROAS goals while respecting product-level economics.

Performance Max would treat everything as one bucket, potentially overspending on low-margin items while underbidding on your profit drivers. You could segment those products with PMax and dedicated ROAS settings, like giving low-margin items a 1,000-2,000% ROAS to force the algorithm to lower CPC’s, but in certain cases, you might want to make use of a hard bid cap to avoid any surprises.

The Fallback Strategy: Why You Need A Safety Net

Don’t Put All Your Eggs In One Basket

Here’s a scenario that plays out constantly: An advertiser migrates completely to Performance Max, pauses their Standard Shopping campaigns, and watches performance crater. PMax enters an extended learning period, traffic drops, and suddenly they’re scrambling to recover lost revenue.

Another example is when you heavily rely on custom labels and advanced segmentations. If something fails, your campaigns might be down. An always-on standard shopping campaign as a fallback can quickly jump in.

Maintaining Your Fallback

Smart advertisers maintain Standard Shopping campaigns as a strategic fallback:

During PMax Testing: Keep your proven Standard Shopping campaigns running at reduced budget (maybe 20-30%) while you test Performance Max. If PMax underperforms, you still have baseline traffic and conversions coming in.

Seasonal Insurance: Peak seasons (Black Friday, holiday shopping, back-to-school) are not the time to experiment. Many advertisers switch back to Standard Shopping during their most critical revenue periods, knowing exactly what performance to expect, but also have Standard Shopping as a backup, just in case anything happens to PMax campaigns.

Quick Recovery Option: If PMax goes sideways, and it can, having a Standard Shopping campaign ready to scale up means you can recover quickly rather than starting from scratch.

Preserving Campaign History: Years of optimization data, conversion history, and Quality Score built up in Standard Shopping campaigns have value. Once you delete them, that institutional knowledge is gone forever.

Strategy Over Automation

Performance Max represents Google’s vision of fully automated advertising, but automation without strategy is just expensive guesswork.

Standard Shopping campaigns remain essential tools for advertisers who need:

• Control over bidding and budget allocation.
• Transparency into what’s actually driving results.
• Flexibility to optimize for their specific business model.
• Protection against algorithmic overspending.

The key isn’t choosing one over the other; it’s understanding when each approach serves your business goals.

Before migrating to Performance Max, ask yourself:

• Do I have sufficient conversion volume for machine learning?
• Am I willing to sacrifice visibility for automation?
• Does my business model require specific controls PMax doesn’t offer?
• Do I have a fallback plan if performance drops?

If you answered yes to any of these questions, Standard Shopping campaigns deserve a permanent place in your account structure.

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Featured Image: Roman Samborskyi/Shutterstock

PPC Pulse: AI Max Insights, Cyber Monday Trends & A New Google Asset via @sejournal, @brookeosmundson

The conversations shaping PPC this week focused on how AI interprets intent, how holiday demand played out across Shopping and Performance Max, and how Google is adding more automated language directly into ads.

Google shared more clarity around AI Max, while Adalysis shared AI Max match type behavior, retail analysts broke down early Cyber Monday performance trends, and a potential new Google automated ad asset surfaced that raises questions about brand control.

Here is what stands out for advertisers this week and where you should pay attention.

AI Max Clarifications & New Insights On Match Types

The conversation around AI Max is not slowing down.

A YouTube short circulating this week highlighted Google reaffirming a key message. Match types still serve a purpose, even as AI takes on more interpretation of intent.

This also aligns with a LinkedIn post from two weeks ago where Google Ads Liaison, Ginny Marvin, clarified some misconceptions around the use and functionality of AI Max. Specifically, around:

• What AI Max is designed to do.
• If AI Max repackages existing features.
• What users should expect based on their current keyword match type setup.
• How to measure incremental lift.

The post got a lot of chatter in the comments, specifically around Brad Geddes’s comment, with refuting information, stating:

We’re seeing many instances of AI max matching to exact match keywords or exact match variants. So when you look at your totals, the AI max column is a mixture of the AI max matches along with search terms your exact match keywords would have matched to if AI max didn’t exist.

This led Adalysis to publish a thoughtful breakdown of search term behavior within AI Max. The post shows clear examples where the model expands into adjacent intent that still feels relevant, but not necessarily tied to the exact keyword chosen.

This mirrors what many practitioners are already seeing. Search terms look broader. Relevance varies. The model relies on intention, not precision, which shifts how advertisers think about coverage.

Why This Matters For Advertisers

The bigger takeaway here is that your structure still steers the model. AI Max may evaluate intent more flexibly, but it is not inventing direction on its own.

It relies on the signals you set through match types, keyword groupings, and the guardrails you place around your campaigns. When advertisers downplay match types or assume AI will sort everything out, query quality usually becomes harder to manage.

A thoughtful keyword strategy gives the model clearer boundaries to work within. It also helps you understand why certain queries show up and how the system interpreted them.

The more intentional your structure, the more predictable your outcomes. This is the difference between AI supporting your strategy and AI creating a strategy for you.

Cyber Monday PPC Trends Across Shopping And PMax

Cyber Monday data and insights came in quickly this year. Optmyzr shared performance highlights from accounts it manages, showing steady results and more predictable cost patterns than many expected.

Some of its main findings included:

• Brands spent more YoY to stay visible, even though impressions declined.
• Clicks and CTR increased YoY.
• Early conversion data reports decreased ROAS and increased CPA, but noted this isn’t final

Optmyzr reiterated that they would share more final details around conversions and ROAS at a later time due to conversion lag.

Mike Ryan also reviewed more than 2.5 million euros spent on Black Friday in PMax and Shopping spend across retailers and reported noticeable differences from previous years. Some of his findings were similar to Optmyzr, including that advertisers spent 31% more, but average order value (AOV) decreased 6%.

Essentially, advertiser spend efficiency decreased significantly YoY.

As he observed hourly trend data, he noted revenue peaked during early evening hours, advocating to keep budget healthy all throughout the day to capitalize on that intent.

Lastly, he found unique competition up 12%, and confirmed that Amazon still runs Shopping ads in Europe (while they’ve stopped running in the United States earlier this year).

Why This Matters For Advertisers

The data tells a consistent story. Attention is still there, but it is more expensive to earn. Optmyzr’s numbers show higher spend year over year, even as impressions dipped, which reinforces that visibility continues to cost more. Clicks and CTR were up across both ecommerce and lead gen, which signals that people were still shopping and comparing options. The interest is not gone. The price of reaching that interest simply climbed.

The bigger takeaway for advertisers is that strong engagement does not solve the efficiency problem. Costs rose across the board, which puts even more pressure on the post-click experience. When attention is not the constraint anymore, landing page clarity, offer strength, and conversion flow become the real differentiators. The accounts that invested in those areas will feel less of the margin squeeze that defined this year’s shopping window.

New Automated Ad Asset Appears In Google Ads

A new automated asset gained attention this week when Anthony Higman shared a screenshot showing Google testing a “What People Are Saying” asset.

The asset included AI-generated summary text that looked more like a sentiment recap than a traditional review snippet. What stood out is that the text did not appear to be pulled from the advertiser’s site or from structured reviews. It looked generated by Google based on potential store ratings and reviews.

This is another example of Google introducing language directly into ads, even before advertisers get official documentation or a clear explanation of how the text is produced. The extension reads confidently, but the source of the claims is not obvious.

That has already sparked discussion about accuracy, oversight, and how much creative control advertisers may lose as automated assets continue to expand.

Why This Matters For Advertisers

This asset signals that Google is continuing to explore new ways to surface AI-generated supporting text in ads. That makes oversight more important, simply because advertisers may see language that does not come directly from their own assets.

While the goal is to enhance relevance and provide helpful context to users, it also means brands should keep an eye on auto-applied assets to ensure the messaging aligns with how they want to show up in search. A quick review process can go a long way in avoiding surprises and keeping ad copy consistent with your broader strategy.

Theme Of The Week: Context Shapes Performance

Across all three updates, the common thread is how context influences outcomes.

AI Max decisions depend heavily on the structure you set. Cyber Monday performance reflected a market where attention remained strong but came at a higher cost, putting more weight on what happens after the click. The new automated extension shows Google continuing to experiment with ways to add context inside ads.

Together, these updates point to a simple reality. The more intentional you are with structure, creative, and user experience, the more predictable your results become, even as automation takes on a larger role.

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Featured Image: Pixel-Shot/Shutterstock

PPC Pulse: Nano Banana Pro, Image Animation & The Top PPC Influencers via @sejournal, @brookeosmundson

PPC news this week focused on creative tool updates and the people shaping how we use them. Google Ads brought Nano Banana Pro into its creative workflow, giving advertisers sharper, more flexible options for generating images.

Microsoft Ads introduced Image Animation and new Performance Comparison features in Copilot, so turning static assets and raw numbers into something usable feels less painful. And the Top 100 PPC Influencers shortlist sparked a wave of personal posts, especially from people like Jyll Saskin Gales, about what real influence actually feels like.

Here is a closer look at what changed and how it might affect your accounts.

Nano Banana Pro Arrives In Google Ads

Google introduced Nano Banana Pro, a new image generation and editing model built on Gemini 3 Pro and now available across products like Gemini, Workspace, and Google Ads.

Compared with the earlier Nano Banana model, this version focuses on sharper reasoning, better text rendering inside images, and stronger brand consistency. It is designed to turn rough ideas into studio-quality visuals while keeping on-brand details intact.

From a Google Ads standpoint, Google Ads Liaison positioned Nano Banana Pro as a creative engine inside Asset Studio and campaign setup flows. Advertisers can create and edit high-resolution images, adjust details like lighting and camera angles, and even showcase multiple products in a single scene for formats like Performance Max and Demand Gen.

Per Ginny Marvin’s post, advertisers can expect:

• Better brand alignment.
• More creative control.
• Higher-quality output and multi-product showcasing.
• Easier iteration and testing.

The big promise is speed with control. You can work in a conversational way with assets rather than rewriting prompts every time you want a version with a new background or seasonal setting.

Why Advertisers Should Pay Attention

Most teams feel constant creative pressure to keep up with the volume and scale of testing. For visual-focused campaigns like Performance Max, Shopping, and Demand Gen, those campaigns need a steady stream of fresh assets. As a result, many brands struggle to keep up without sacrificing quality.

Nano Banana Pro aims to ease that bottleneck. If it does what Google claims, it should help you:

• Scale image production while staying closer to your brand guidelines.
• Produce on-brand “sets” of images for seasonal pushes or product bundles.
• Improve text inside images for promos, headlines, and localized creative.

There are tradeoffs to keep in mind. You still need clear brand rules, review steps, and legal guardrails. Watermarked AI visuals do not replace proper approvals, especially in regulated categories.

If you want to test Nano Banana Pro in Google Ads, start with a structured plan: pick a few PMax or Demand Gen campaigns, create AI-only asset groups, and compare performance to your current best creatives. Treat it as a creative accelerator, not a replacement for your existing brand work.

Microsoft Announces Image Animation And Performance Comparison

In the same week, Microsoft announced its own updates to image creative: Image Animation.

Image Animation lets you turn static images into short videos using templates in Ads Studio. The feature is in global pilot, with the exception of mainland China, and is meant to extend the life of existing image assets across video inventory on the Microsoft network.

Microsoft also announced a new feature called Performance Comparison. Per the Microsoft Liaison’s LinkedIn post, the feature is meant to allow you to “have meaningful conversations with your data.”

For example, you can now ask Copilot to compare periods, A/B tests, campaigns, or top keywords and get a narrative summary plus charts, instead of building everything manually in spreadsheets.

Finally, Microsoft highlighted new API-powered generation features. Background images, display ads, videos, and brand kits can all be created at scale through Copilot in the Campaign Management API. That piece is aimed squarely at high-volume advertisers and agencies who rely on automation to keep assets fresh.

Why Advertisers Should Pay Attention

If your team has wanted more video but never had the time or budget, Image Animation is worth a look. Converting top static assets into simple motion can help improve engagement without a full production effort.

The risk is lazy creative. Video built on weak images will not magically perform. Use this feature on proven winners first, then expand.
Performance Comparison is the more quietly powerful update. Many PPC managers still spend a lot of time exporting data, slicing it, and trying to tell a story in slides. Letting Copilot handle first-draft comparisons can save hours and surface trends you might miss.

You still need to validate your data and sense-check the narrative. Automation can speed up analysis, but it cannot know your client’s politics, internal benchmarks, or the context behind a bad week.

For larger accounts, the API updates could be significant. Teams with many markets, feeds, or brands can generate creative variations programmatically and keep evergreen campaigns from going stale. This is one of those features that rewards advertisers who have clean feeds, strong brand kits, and consistent naming structures already in place.

Top 100 PPC Influencers Shortlist Sparks Conversation

At the beginning of the week, PPC Survey launched its shortlist of the Top 100 PPC Influencers of 2025. The list serves as an alphabetical pool for the final Top 50 ranking, which is decided partly through votes in the State of PPC survey and other ranking factors.

To make the shortlist, most experts need at least 2,500 LinkedIn followers, though PPCsurvey notes that some exceptions are made for influence through speaking, content, or podcasts. Industry reporters and ad platform employees are excluded from the ranking itself, even though the organizers encourage people to follow them.

Voting is open until late December, and many shortlisted experts shared their nominations with gratitude, humor, or a bit of imposter syndrome.

In my opinion, one post stood out in particular amongst the noise of the announcements. In Jyll Saskin Gales’ LinkedIn post, she shared honest, mixed feelings about lists like this and how she defined influence.

She explained that the external recognition came first: speaking invites, writing opportunities, brand deals. The feeling of real influence came later, when people started sharing very personal outcomes tied to her work. Job offers they landed because of her content. Careers they felt more secure in. Emotional moments when readers met her in person and talked about how her book or resources changed their approach to Google Ads.

Jyll also used the post to talk about responsibility. She encouraged people to look at their voting choices and ask whether they are supporting diverse voices and asked readers to consider their own influence.

Why Advertisers Should Pay Attention

On the surface, a “Top 100” list can feel like industry inside baseball. But lists like this shape who teams follow, whose frameworks get repeated in decks, and which case studies clients see.

If your feed is filled with posts about this shortlist, it is a good moment to audit your inputs. Ask yourself:

• Do I follow people who work on similar problems as me, or only the most visible names?
• Do the voices in my feed reflect different markets, backgrounds, and company sizes?
• Am I sharing ideas from a small circle, or highlighting newer experts who have helped my work?

You do not need a badge to be influential. If you teach a junior teammate, write a clear client email, or share a thread that helps someone understand a platform change, you are shaping how PPC is practiced in your circles.

The list is simply a guide or another tool to find useful PPC information. Use it to discover new people, yes, but also to reflect on how you wield your own influence.

This Week In PPC: Creativity And Influence

On one side, Google and Microsoft are racing to make creative and analysis more automated. Nano Banana Pro promises faster, more on-brand visuals inside campaign workflows. Microsoft’s new features aim to turn static images into video and compress reporting time into simple chat prompts.

On the other side, the Top 100 shortlist and posts like Jyll’s remind us that tools do not drive strategy. People do. The frameworks you share, the way you explain changes to stakeholders, and the care you show in your content have a long tail that no platform roadmap can replicate.

As you test new creative models and Copilot features, it may help to ask a simple question: Are you giving as much attention to the influence you have on others as you give to the tools you use every day?

Top Stories Of The Week:

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