Nov 20 2025
How To Manage Demand Fluctuation During Key Ecommerce Shopping Seasons via @sejournal, @brookeosmundson

Ecommerce demand doesn’t rise and fall in a straight line throughout the years.

It can build gradually, spike hard, stall, or drop with little-to-no warning. During peak shopping periods like Black Friday, Cyber Monday, Prime Day(s), Back-to-School, these swings become even more intense.

For PPC marketers, that volatility affects far more than just traffic or CPCs. It influences bidding strategies, budgets, inventory planning, campaign structures, and even internal operations.

Managing demand fluctuation isn’t just about “spending more when demand is high.” It’s also about knowing when demand is coming, preparing your accounts before the surge, staying in control while competition rises, and stabilizing performance after the peak ends.

It means understanding that marketing decisions affect logistics and profitability, not just vanity metrics like impression share.

This article will walk you through how to manage demand in a way that improves performance and protects the business across each phase of the season.

1. Understand And Anticipate Seasonal Demand

Predictable seasonal spikes are only predictable if you know what to look for.

Demand rarely appears out of nowhere. It ramps up gradually. The marketers who recognize early changes in behavior are the ones who scale at the right time instead of reacting too late.

Start with historical data from your own account. Look at when impressions and clicks began to rise last year, not just when the holiday officially started.

Compare year-over-year and week-over-week trends to identify whether demand is starting earlier. In many industries, consumers begin researching long before they’re ready to buy, which means waiting until “the big day” is too late to build momentum.

Conversion lag is another signal. If your data shows it normally takes five days from first click to purchase, and your promo begins on Friday, you need to start increasing budget earlier in the week. Otherwise, you’ll miss buyers who started the journey before the event.

Don’t ignore external factors. Shipping cutoff dates, competitor promotions, weather trends, and even economic sentiment can accelerate or delay demand. The data in the platform only shows part of the picture, while market behavior provides the context.

Forecasting is also critical. Even a simple model based on past revenue, impression share, and growth targets can help you determine expected demand and budget requirements.

This helps create a baseline so you can recognize when performance is ahead or behind expectations and adjust accordingly.

2. Align Bids And Budgets With Demand

Once demand starts building, your bidding and budgeting strategy must evolve with it. This is where many marketers either scale too slowly and miss opportunity. On the opposite side, you scale too aggressively and burn through budget prematurely.

If you’re using Smart Bidding, seasonality adjustments in Google Ads or Microsoft Ads can help the algorithm prepare for a short-term spike that differs from typical trends. These are best used for specific, limited windows (e.g., a 3-day flash sale) rather than entire multi-week seasons.

When demand returns to normal, remove the adjustment so the system doesn’t keep bidding too high in a softening market.

Target settings also matter. A tROAS (Target Return on Ad Spend) goal that works during regular pricing may be too restrictive during steep discounts. Likewise, a CPA goal may need to be relaxed slightly if conversion rates are temporarily lower but lifetime value remains strong.

In some cases, switching to a “Maximize” strategy gives the system more flexibility to capture demand efficiently, especially when intent is high and margin is acceptable.

If using “Maximize Conversions” (or Conversion Value), you could set more flexible bid limits to let the algorithm know you’re willing to pay more for conversions without letting it go haywire and have a mind of its own.

Budgets require just as much attention as bids. If campaigns are capping out early in the day, you’re likely missing high-intent shoppers later. Increasing budgets, reallocating across campaigns, or adjusting bids to stretch delivery can help you maintain visibility during peak hours. Shared budgets can also allow strong-performing categories to pull in more spend without manual intervention.

Scaling back after the surge is equally important. Abrupt budget cuts or major bid changes can disrupt algorithmic learning. Gradual reductions give the system time to recalibrate as demand normalizes.

3. Keep Product Availability And Campaign Structures Aligned

Even the best campaign strategy falls apart if product availability isn’t properly managed.

During peak shopping seasons, inventory can change rapidly. If feeds don’t update quickly, ads may continue promoting items that are low or out of stock. This leads to wasting spend and hurting customer experience.

Be sure to increase your feed update frequency during high-demand periods. This could mean multiple syncs per day if possible.

Ensure that price, availability, and shipping information are accurate. If your platform or feed tool allows real-time inventory updates, take advantage of it.

Custom labels in your feed are one of the most valuable seasonality tools. Try labeling your products by margin, best seller status, promotion type, limited stock, or seasonality. This allows you to structure campaigns around business priorities, not just categories or sub-types.

For example:

  • Increase bids on high-margin or high-conversion products
  • Lower bids or pause products with low inventory
  • Separate promotional items so they receive dedicated budgets and messaging

Performance Max and Shopping campaigns require even more attention. In my experience, it’s common to see PMax concentrate budget on a narrow slice of the catalog while other SKUs receive little to no impression share.

If that pattern doesn’t match your merchandising goals, segmenting high-priority product groups and tightening feed signals usually helps. If you don’t segment campaigns thoughtfully or monitor product-level performance, the algorithm may stall.

Consider using a mix of Standard Shopping and PMax when you need more control over key seasonal categories. Standard Shopping can provide the structure you need, while PMax can help with scaling.

Just make sure they serve different roles to avoid internal competition.

Campaign structure should work hand-in-hand with inventory strategy. The goal is to ensure your best products get visibility when demand spikes and that you don’t waste spend on items you can’t fulfill.

4. Work With Internal Teams During Peak Demand

In normal months, PPC managers can operate with relative independence.

During major retail seasons, that approach can create problems.

Demand fluctuation affects far more than media spend. It touches logistics, merchandising, pricing, site operations, and customer experience.

For example, if marketing pushes a product heavily but the warehouse can’t fulfill orders quickly enough, conversion rates could drop, and customer complaints can arise.

If a PPC offer launches a “50% off” ad before the site reflects the discount, you’ll likely pay for unqualified clicks or see conversions drop.

If inventory runs low but product promotions continue, you’ll burn budget on products that can’t convert.

During peak periods, cross-functional alignment is necessary for optimal performance. Be sure to establish regular communication with:

  • Inventory and fulfillment (stock levels, restock timelines, shipping delays).
  • Merchandising (featured products, bundles, hero SKUs).
  • Pricing and promotions (exact discount timing and margin impact).
  • Creative (messaging changes, urgency vs. value).
  • Site operations (traffic capacity, potential downtime, landing page readiness).
  • Customer service (policy changes, support volume expectations).

Even short daily syncs with these teams can prevent costly mistakes. Something as simple as a delayed shipment or pricing error can change campaign performance within hours.

When teams are aligned, marketing decisions become less reactive and more strategic.

Also, be prepared to change messaging quickly. If shipping times increase, adjust ad copy or landing page expectations. If a product is selling out fast, highlight “limited availability” or shift spend to similar in-stock alternatives.

5. Plan For Post-Peak Performance And Future Seasons

When the surge ends, the work isn’t over.

The post-peak period can feel unstable. After peak periods, I’ve experienced many advertisers observe a short re-balancing window: Conversion intent normalizes faster than bidding pressure does. This is where many marketers overreact and cut budgets too aggressively, causing campaigns to lose momentum.

Instead, treat the cooldown as a transition phase. Reset any seasonality bid adjustments. Reevaluate ROAS or CPA targets. Gradually adjust budgets to align with current demand, rather than slashing them immediately.

Shift campaign focus to retention and LTV where appropriate. Remarketing, post-purchase offers, loyalty initiatives, and subscription promotions can help turn seasonal traffic into long-term value. The conversion window doesn’t always end when the sale does.

This is also the most important time to analyze. Don’t wait weeks to reflect; be sure to capture key insights while the data is fresh.

When analyzing, ask questions like:

  • Which categories or SKUs exceeded (or missed) expectations?
  • Were budgets or bids too slow to adjust?
  • Did any campaigns cap too early in the day?
  • Were there inventory issues that hurt performance?
  • How did different bidding strategies respond under pressure?
  • What messaging/ad copy resonated best with users?
  • What would you start earlier or stop entirely next time?

Document everything. Don’t assume you’ll remember next year.

Seasonality repeats, but consumer behavior and the corresponding algorithm responses evolve every year. The teams that improve each cycle are the ones who treat post-peak as planning time, not recovery time.

Then, build your playbook for the next season. Define earlier ramp-up timing if needed. Establish bidding and budget frameworks. Create inventory and messaging coordination workflows.

When the next seasonality surge comes, you’ll be ready to scale strategically.

Sustain Stability Through Every Season

Managing demand fluctuation is more about staying in control when the market becomes unpredictable. That requires preparation, data awareness, cross-team coordination, flexible bidding and budgeting, and deliberate post-peak analysis.

Demand shifts will always happen. The difference between chaotic seasons and successful ones comes down to how well you anticipate, adapt, and learn from each cycle.

The marketers who treat seasonality as a workflow system (not an event) are the ones who can turn volatility into growth.

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Featured Image: Roman Samborskyi/Shutterstock

Ecommerce MGMT 0 Comments
Nov 19 2025
Should Advertisers Be Worried About AI In PPC?

One scroll through LinkedIn and you’d struggle not to see a post, video, or ad about AI, whatever the industry you work in.

For digital marketing, it’s completely taken over, and it has woven itself into nearly every aspect of day-to-day life, especially within PPC advertising.

From automated bidding to AI-generated ad creative, platforms like Google Ads and Microsoft Advertising have been doubling down on this for years.

Naturally, this shift raises questions and concerns among advertisers, with one side claiming it’s out of control and taking over, the other side boasting about time saved and game-changing results, and then you’ve got the middle ground trying to figure out exactly what the impact is and where it is going.

It’s a difficult topic to answer with a simple yes or no, with so many opinions and platforms for sharing them; it’s everywhere, and although certainly not a topic that is in its infancy, it does feel that way in 2025.

In this article, we’ll explore how AI is used in PPC today, the benefits it offers, the concerns it brings, and how advertisers can best adapt.

What Role Does AI Play In PPC Today?

The majority of advertisers are already using some form of AI-driven tool in their workflow, with 74% of marketers reported using AI tools last year, up from just 21% in 2022.

Then, within the platforms, PPC campaigns are heavily invested in artificial intelligence, both above and below the hood. Key areas being:

Bid Automation

Gone are the days of manual bidding on hundreds of keywords or product groups (in most cases).

Google’s and Microsoft’s Automated Bidding use machine learning to set optimal bids for each auction based on the likelihood to convert.

These algorithms analyze countless signals (device, location, time of day, user behavior patterns, etc.) in real-time to adjust bids far more precisely than a human could.

In this scenario, the role of the advertiser is to feed these bidding strategies with the best possible data to then take forward in making decisions.

Then at a strategic level, advertisers will need to determine the structure, targeting, goals, etc, and this is where Google has further pushed AI into the hands of PPC teams.

From Google’s side, it’s an indication of trust that the AI will find relevant matches and handle bids for them, and I have seen this work incredibly well, but I’ve also seen this work terribly, and it’s all context-dependent.

Dynamic Creative & Assets

Responsive Search Ads (RSAs) allow advertisers to input multiple headlines and descriptions, which Google’s AI then mixes and matches to serve the best-performing combinations for each query.

Over time, the algorithm learns which messages resonate most.

Google has even introduced generative AI tools to create ad assets (headlines, images, etc.) automatically based on your website content and campaign goals.

Similarly, Microsoft’s platform now offers a Copilot feature that can generate ad copy variations, images, and suggest keywords using AI.

Of all the AI-related changes in Google Ads, in my experience, this was one that advertisers welcomed the most, as it is a time saver and created a nice way to test different messaging, call to actions, etc.

Keyword Match Types

The recipe for Google Ads in 2025 that advertisers are given from Google is to blend broad match and automated bidding.

Why is this? According to Google, machine learning attempts to understand user intent and match ads to queries that aren’t exact matches but are deemed relevant.

Think about it this way: You’ve done your research for your new search campaign, built out your ad groups, and are confident that you have covered all bases.

How will this change over time, and how can you guarantee you’re not missing relevant auctions? This is rhetoric Google runs with for broad match as it leans into the stats with billions of searches per day, with ~15% being brand new queries, pushing advertisers to loosen targeting to allow machine learning to operate constraint-free.

There is certainly value in this, and it’s reported that 62% of advertisers using Google’s Smart Bidding have made broad match their primary keyword match type, a strategy that was very much a no-go for years; however, handing all control over to AI doesn’t fully align with what matters most (profitability, LTV, margins, etc) and there has to be a middle ground.

Audience Targeting And Optimization

Both Google and Microsoft leverage AI to build and target audiences.

Campaign types like Performance Max are almost entirely AI-driven; they automatically allocate your budget across search, display, YouTube, Gmail, etc., to find conversions wherever they occur.

Advertisers simply provide creative assets, search themes, conversion goals, etc, and the AI does the rest.

The better quality the data inputted, the better the performance to a large degree.

Of all the AI topics for Google Ads, PMax is very much debated within the industry, but it’s telling that 63% of PPC experts plan to increase spend on Google’s feed-based Performance Max campaigns this year.

Recommendations, Auto Applies, And Budget Optimization

If you work within/around PPC, you’ll have seen, closed, shouted at, and maybe on a rare occasion, taken action off the back of these.

The platforms continuously analyze account performance and suggest optimizations.

Some are basic, but others (like budget reallocation or shifting to different bid strategies) are powered by machine learning insights across thousands of accounts.

As good as these may sound, they are only as good as the data being fed into the account and lack context, which, in some cases, if applied, can be detrimental to account performance.

In summary, advertisers have had to embrace AI to a large extent in their day-to-day campaign management.

But with this embrace comes a natural question: Is all this AI making things better or worse for advertisers, or is it just a way for ad platforms to grow their market share?

What Are The Benefits Of AI In PPC?

AI offers some clear advantages for paid search marketers.

When used properly, AI can make campaigns more efficient, effective, and can save a great deal of time once spent on monotonous tasks.

Here are some key benefits:

Efficiency And Time Savings

One of the biggest wins is automation of labor-intensive tasks.

AI can analyze massive data sets and adjust bids or ads 24/7, far faster than any human.

This frees up marketers to focus on strategy instead of repetitive tasks.

Mundane tasks such as bid adjustments, budget pacing, creative rotation, etc, can be picked up by AI to allow PPC teams to focus on high-level strategy and analysis, looking at the bigger picture.

It’s certainly not a case of set-and-forget, but the balance has shifted.

AI can now take care of the executional heavy lifting, while humans guide the strategy, interpret the nuance, and make the judgment calls that machines can’t.

Structural Management

A clear benefit of AI in many facets of paid search is the consolidation of account structures.

Large advertisers might have millions of keywords or hundreds of ads, which at one time were manually mapped out and managed group by group.

With automated bidding strategies adjusting bids in real time, serving the best possible creative and doubling down on the keywords, product groups, and SKUs that work, PPC teams are able to whittle down overly complex account structures into consolidated themes where they can feed their data.

Campaigns like Performance Max scale across channels automatically, finding additional inventory (like YouTube or Display) without the advertiser manually creating separate campaigns, further making life easier for advertisers who choose to use them.

Optimization Of Ad Creative And Testing

Rather than running a handful of ad variations, responsive ads powered by AI can test dozens of combinations of headlines and descriptions instantly.

The algorithm learns which messages work best for each search term or audience segment.

Additionally, new generative AI features can create ad copy or image variations you hadn’t considered, expanding creative possibilities, but please check these before launch, and if set to auto apply, maybe remove and review first, as these outputs can be interesting.

The overarching goal from the ad platforms is to work towards solving the problem many teams face regarding getting creatives produced and fast, which they do to an extent, but there’s still a way to go.

Audience Targeting And Personalization

AI can identify user patterns to target more precisely than manual bidding.

Google’s algorithms might learn that certain search queries or user demographics are more likely to convert and automatically adjust bids or show specific ad assets to those segments, and as these change over time, so do the bidding strategies.

This kind of micro-optimization of who sees which ad was very hard to do manually, and has great limitations.

In essence, the machine finds your potential customers using complex signals that adjust bids in real time based on the user vs. setting a bid for a term/product group to serve in every ad set, essentially treating each auction the same.

What Are The Concerns Of AI In PPC?

Despite all the promise, it’s natural for advertisers to have some worries about the march of AI in paid search.

Handing over control to algorithms and black box systems comes with its challenges.

In practice, there have been hiccups and valid concerns that explain why some in the industry are cautious.

Loss Of Control And Transparency

A common gripe is that as AI takes over, advertisers lose visibility into the “why” behind performance changes.

Take PMax, for example. These fully automated campaigns provide only limited data when compared to a segmented structure, making it hard to understand what’s driving conversions and putting advertisers in a difficult position when feeding back performance to stakeholders who once had a wealth of data to dig through.

Nearly half of PPC specialists said that managing campaigns has become harder in the last two years because of the loss of insights and data due to automated campaign types like PMax, with one industry survey finding that trust in major ad platforms has declined over the past year, with Google experiencing a 54% net decline in trust sentiment.

Respondents cited the platforms’ prioritization of black box automation over giving users control as a key issue, with many feeling like they are flying partially blind, a huge worry considering budgets and importance of Google Ads as an advertising channel for millions of brands worldwide.

Performance And Efficiency Trade-Offs

I’ve mentioned this a couple of times so far, but as with most AI in the context of Google Ads, the data being fed into the platform determines how well the AI performs, and adopting AI in PPC does not result in immediate performance improvements for every account, however hard Google pushes this narrative.

Algorithms optimize for the goal you set (e.g., achieve this ROAS), sometimes at the expense of other metrics like cost per conversion or return on investment (ROI).

Take broad match keywords combined with Smart Bidding; this might bring in more traffic, but some of that traffic could be low quality or not truly incremental, impacting the bottom line and how you manage your budgets.

To be taken with a pinch of salt due to context, however, an analysis of over 2,600 Google Ads accounts found that 72% of advertisers saw better return on ad spend (ROAS) with traditional exact match keyword targeting, whereas only ~26% of accounts achieved better ROAS using broad match automation.

Advertisers are rightly concerned that blindly following AI recommendations could lead to wasted spend on irrelevant clicks or diminishing returns.

Then, you have the learning period for automated strategies, which can also be costly (but necessary) where the algorithm might spend a lot figuring out what works, something not every business can afford.

Mistakes, Quality, And Brand Safety

AI isn’t infallible.

There have been instances of AI-generated ad copy that miss the mark or even violate brand guidelines.

For example, if you let generative AI create search ads, it might produce statements that are factually incorrect or not in the desired tone.

Having worked extensively in paid search for luxury fashion brands, the risk of AI producing off-brand creative and messaging is often a roadblock to getting on board with new campaign types.

In a Salesforce survey, 31% of marketing professionals cited accuracy and quality concerns with AI outputs as a barrier.

To add further complexity to this, many of the features, such as auto applies in Google Ads, are not the easiest to spot within the accounts and are dependent on the level of expertise within the team managing PPC; certain AI-generated assets or enhancements could be live without teams knowing, which can lead to friction within businesses with strict brand guidelines.

Over-Reliance And Skills Erosion

Another subtle worry is that marketers relying heavily on AI could see their own skills become redundant.

PPC professionals used to pride themselves on granular account optimization, but if the machine is doing everything, how will their jobs change?

A study by HubSpot found that over 57% of U.S. marketers feel pressure to learn AI tools or risk becoming irrelevant in their careers.

With PPC, all this means is that less and less time is spent within the accounts undertaking repetitive tasks, something that I’ve championed for years.

Every paid search team is different and is built from different levels of expertise; however, the true value that PPC teams bring shouldn’t be the intricacies of campaign management, it’s the understanding of the value their channel is driving and everything around this that influences performance.

So, Should Advertisers Be Worried About AI In PPC?

As with most topics in PPC (and most articles I write), there isn’t a simple yes or no answer, and it’s very much context dependent.

PPC advertisers shouldn’t panic; they should be aware, informed, and prepared, and this doesn’t mean knowing the exact ins and outs of AI models, far from it.

Rather than asking if you trust it or not, or if you really should give up the reins of manual campaign management, ask yourself how you can use AI to make your job easier and to drive better results for your business/clients.

Over my last decade and a half in performance marketing, working in-house, within independents, networks, and from running my own paid media agency, I’ve seen many trends come and go, each one shifting the role of the PPC team ever so slightly.

AI is certainly not a trend, and it’s fundamentally changing the world we live in, and within the PPC world, it’s changing the way we work, pushing advertisers to spend less time in the accounts than they once did, freeing up time to allocate to what really moves the needle when managing paid media.

In my opinion, this is a good thing, but there is definitely a balance that needs to be struck, and what this balance looks like is up to you and your teams.

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Featured Image: Roman Samborskyi/Shutterstock

Ecommerce MGMT 0 Comments
Nov 14 2025
PPC Pulse: PMax Expands, Clarity Now Mandatory & AI Max Data Debate via @sejournal, @brookeosmundson

This week, the paid media world focused less on new tools and more on what’s changing beneath the surface.

Google expanded Performance Max into a new channel and offered long-awaited reporting visibility. Microsoft took a firm stance on brand safety by requiring Clarity across its publisher network. And one viral LinkedIn post questioned the effectiveness of Google’s newest “AI-powered” campaign model.

Each of these stories points to the same theme: Platforms are redefining what control and accountability mean for advertisers.

Performance Max Expands To Waze And Adds Channel Reporting

Google confirmed two changes for Performance Max campaigns.

The first notable update is that for PMax campaigns using “Store Visits” as a campaign goal, your business can now show up on Waze ads inventory. The business will show up as a “Promoted Places in Navigation” pin for users.

This update is for all advertisers in the United States, and no additional setup is required.

The second update is that Google rolled out Channel Reporting for all PMax campaigns. While this has been rolling out for a few months now, not every advertiser had this available.

Why Advertisers Should Pay Attention

Local intent now includes the navigation moment. If your brand depends on foot traffic, showing up while someone is driving near a location adds a fresh, real-world touchpoint.

The channel reporting update matters just as much. It helps shift PMax conversations from “trust the system” to “here’s where the system actually worked.”

In my opinion, this is progress on transparency and reach. It also adds variables you’ll be asked to explain.

The win isn’t “more placements.” The win is being able to connect surfaces to outcomes with fewer leaps of faith.

Microsoft Clarity Now Mandatory For Third-Party Publishers

Microsoft Ads Liaison, Navah Hopkins, shared an important announcement for all 3P publishers on Microsoft:

Screenshot taken by author, November 2025

In her post, she mentions that all Microsoft Ads clicks need to make sure those pages have Microsoft Clarity enabled.

Her post got attention from the PPC industry, where she clarified in the comments that an official announcement from Microsoft will be coming out shortly. All Microsoft Ads partners have already been notified via email.

The post also sparked some questions and potential confusion about how Microsoft Ads wouldn’t be charged if they weren’t running Clarity.

Andy Hawes asked:

Thanks for this Navah Hopkins, but when you say “Any Microsoft Advertising clicks that do not have Clarity will be filtered out and result in nonbillable impressions/clicks.” Are you suggesting that if you don’t run clarity then you’re Microsoft Ads won’t cost anything? I’m assuming that is not the case? So could you explain that part please?

Hopkins clarified during the exchange:

Screenshot taken by author, November 2025

Why Advertisers Should Pay Attention

Microsoft seems to be taking a quality stance, not just making a tracking footnote.

Based on the conversation on LinkedIn, Microsoft is tying billable media to verifiable on-site experience. In theory, that should reduce questionable placements and give brands greater confidence that their ads appear in environments that meet baseline standards.

I see this as Microsoft is trading raw reach for higher trust. Advertisers should expect fewer gray-area placements and stronger conversations with brand-safety teams.

It also nudges the market toward a new normal where “transparency” includes a window into on-site behavior, not just a placement report.

The Industry Reacts To AI Max Performance Data

AI Max was another hot topic on LinkedIn this past week.

Xavier Mantica shared four months of results comparing AI Max to traditional match types.

Screenshot taken by author, November 2025

His data showed AI Max at $100.37 per conversion versus $43.97-$61.65 for most non-AI setups (and $97.67 for phrase close variants). His view: AI Max behaves like broad match with a new label, expanding beyond intended relevance and driving up cost.

As of this writing, the post has 991 engagements with over 170 comments from the PPC industry.

How Advertisers Are Reacting

Looking at the comments, it appears that many PPC pros agree that AI Max isn’t living up to the hype that Google made it out to be when originally announced.

Collin Slatterly, Founder of Taikun, shared his skeptical optimism by not just dismissing AI Max entirely, but shared it may just not be ready for its full potential:

Give it a year, and it’ll probably be ready to deploy. Feels like PMax all over again.

One of the top comments to Xavier’s post came from Mike Ryan, who agreed after analyzing 250 campaigns of his own:

Screenshot taken by author, November 2025

There were others in the comments that had the opposite take of Xavier. Denis Capko replied in the comments, stating:

Screenshot taken by author, November 2025

Why Advertisers Should Pay Attention

This debate goes beyond one account. It reflects a wider tension between volume and control.

“AI increases conversions” is only persuasive if cost, relevance, and repeatability hold up under scrutiny.

While the comments seemed overly negative to AI Max, I see it as AI Max feels more like growing pains than failure.

Automation continues to move faster than the frameworks we use to evaluate it, and advertisers are still learning how to guide it effectively.

When data quality, conversion accuracy, and negative signals are strong, AI Max can deliver meaningful scale. But without clear visibility into how the system interprets intent, results can vary widely.

Posts like Xavier’s highlight the need for transparency as much as performance. Google also benefits from that same openness: It builds trust, helps advertisers use automation more responsibly, and ultimately makes the technology stronger for everyone.

Theme Of The Week: Accountability

The updates and discussions this past week all share one thread: accountability.

Google is expanding where automation can go, Microsoft is tightening the standards for who gets to monetize it, and advertisers are rethinking how much control they’re willing to trade for convenience.

As platforms lean further into automation, the real advantage won’t come from who adopts it first. It will come from who understands it best.

Are you confident in what your automation is doing, or just comfortable letting it run?

Top Stories Of The Week:

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Featured Image: Roman Samborskyi/Shutterstock

Ecommerce MGMT 0 Comments
Nov 13 2025
Google Sharpens Suspension Accuracy and Speeds Up Appeals for Advertisers via @sejournal, @brookeosmundson

Google account suspensions have long been one of the most stressful issues advertisers face. A single notification can pause revenue, disrupt campaigns, and leave teams scrambling to understand what went wrong, often at no fault of their own.

Over the past several months, Google has heard that feedback and is now rolling out measurable improvements aimed at reducing the burden on legitimate advertisers.

These updates should bring meaningful relief. Misapplied suspensions are down, appeals are moving faster, and Google is promising more transparency into why enforcement actions happen at all.

What’s Changed in Google’s Process

Google announced several updates aimed at preventing unnecessary enforcement actions and speeding up resolutions when mistakes happen.

Google Ads Liaison Ginny Marvin shared additional context in a LinkedIn video. She explained that advertisers often faced long, unclear appeal processes. Many of those advertisers were compliant, but still got caught in broad enforcement filters designed to protect users. The new improvements are meant to address that gap and create a smoother experience for legitimate businesses.

Screenshot taken by author, November 2025

According to Google’s data:

  • Incorrect account suspensions are down more than 80%
  • Appeals are being resolved 70% faster
  • 99% of appeals are reviewed within 24 hours

These numbers reflect improvements in Google’s automated systems, better internal checks, and more precise policy evaluation. The goal is to reduce the number of trusted advertisers who get suspended by mistake and to shorten the time it takes to recover when an account needs review.

Google also mentioned ongoing work to make enforcement decisions easier to understand. While full visibility into every signal is unlikely, these updates indicate an effort to give advertisers clearer direction when issues occur.

How This Helps Advertisers

These changes bring meaningful stability to daily operations. When incorrect suspensions drop by such a large margin, advertisers experience fewer unexpected pauses in performance.

That consistency matters for both in-house teams and agencies managing multiple accounts.

The faster appeal timeline also reduces the fallout from any suspension that does occur. Getting nearly all appeals reviewed within a day helps advertisers avoid extended downtime and protects campaign momentum.

Clarity matters as well. Advertisers have long asked for more detail when suspensions happen.

Even small improvements in transparency can save hours of troubleshooting and prevent repeated appeals that contribute to delays.

These updates should also improve confidence in Google’s enforcement systems. When advertisers trust the process, they can focus on optimization instead of worrying that a routine change will trigger a policy issue.

How This Shapes Future Enforcement

Google’s changes reflect a broader effort to balance user protection with a better advertiser experience. Automated enforcement will always play a significant role in preventing harmful behavior, but legitimate businesses need a system that treats them fairly and resolves issues quickly.

The latest results show encouraging progress. There is still room for improvement, especially in policy clarity and long-term consistency, but the direction is positive.

Google has stated that this work will continue and that advertiser feedback remains central to future updates. For marketers, this signals a more stable and predictable enforcement environment, which supports healthier performance and stronger planning across campaigns.

Ecommerce MGMT 0 Comments
Nov 7 2025
25 Years Of Google Ads: Was It Better Then Or Now? via @sejournal, @brookeosmundson

Twenty-five years ago, Google launched a modest advertising product that would evolve into one of the most influential tools in digital marketing.

Back then, it was called Google AdWords; today, it is Google Ads.

Over that quarter-century, the platform has transformed in format, scope, and ambition.

While the technology behind Google Ads has evolved dramatically, one question continues to spark debate among marketers: “Was Google Ads better back then, or now?”

To answer that, let’s first look at the major moments that shaped its evolution.

The Evolution Of Google Ads Through the Years

Few platforms have changed as dramatically as Google Ads.

In the early 2000s, advertisers logged into something simple and intuitive: an interface centered around keywords and bids.

But over time, the product grew alongside shifts in consumer behavior, device adoption, and technology. Here are some of the most defining moments in that evolution, as shared through Google’s own product history.

2000: Google AdWords Launches

Google AdWords officially went live in October 2000 with about 350 advertisers. The platform allows self-serve text ads on search results, based on cost-per-click bids.

2002: The Pay-Per-Click Model Expands

AdWords transitioned fully to a PPC model, giving advertisers the ability to pay only when users click their ads. This shift laid the groundwork for the accountability marketers still expect from digital ads today.

2005: Analytics And Conversion Tracking Arrive

After acquiring Urchin Software, Google launched Google Analytics, bringing much-needed visibility into campaign performance and website behavior. Conversion tracking follows soon after, tightening the connection between clicks and measurable outcomes.

2005: Quality Score Enters The Auction

In July, Google introduced Quality Score and quality-based minimum bids, tying ad eligibility to keyword relevance and performance rather than pure bid amount. In December, landing page quality was added to the algorithm.

2010: Remarketing Makes Its Debut

Advertisers can now reach users who’ve previously visited their site. This marked Google’s entry into behavioral targeting, which would later become the backbone of the Display Network.

2012: Google Shopping Transitions To A Paid Model

In May 2012, Google announced that Google Product Search (originally Froogle) would become Google Shopping, shifting from free product listings to a paid model using Product Listing Ads. The change, completed in the U.S. by October, aims to improve product data quality and merchant participation.

2013: Enhanced Campaigns Unify Devices

Google launched Enhanced Campaigns, consolidating desktop, mobile, and tablet targeting into a single structure. This simplifies management and allows bid adjustments based on device, location, and time.

2018: Rebranding To Google Ads

Google retired the AdWords name and introduced “Google Ads,” reflecting a unified platform for Search, Display, YouTube, Shopping, and app campaigns. Smart Campaigns debut, aimed at helping small businesses use automation effectively.

2021: Performance Max launches

In November, Google unveiled Performance Max, an AI-powered campaign type that reaches audiences across all Google properties from a single goal-based campaign. It represents a major step toward automation and multi-channel integration.

2023-2025: Generative AI And Transparency Updates

Google introduced Gemini-powered tools for creative generation and conversational campaign setup, alongside new transparency features in Performance Max. Advertisers gain asset-level insights and expanded brand controls.

What The Early Years of Google Ads Offered

The early years of Google Ads were simpler. In some ways, that simplicity was its biggest strength.

Advertisers had complete control over their campaigns. You picked your keywords, set bids manually, and saw immediate cause and effect. Every metric was transparent. If performance changed, you knew (almost) exactly why.

The learning curve was also more manageable. Smaller advertisers could compete with minimal budgets and basic knowledge of keyword matching.

Many early adopters built thriving businesses from nothing more than a spreadsheet of bids and a few lines of ad copy. In those days, optimization was a craft defined by hands-on management, not machine learning.

Ad costs were also lower, and competition was thinner. A small business could afford to experiment without being priced out by large brands or aggressive automated bidding strategies.

But simplicity came at a cost. Campaign management was time-consuming, requiring manual bid adjustments and constant monitoring.

There was no formal cross-device attribution (reports didn’t arrive until 2016), no remarketing (until 2010), and no way to scale campaigns beyond a few thousand keywords without significant effort. Reporting was limited, and insights were confined to surface-level performance data.

The early Google Ads environment rewarded technical skill and persistence. It was direct, measurable, and transparent. But, it was also labor-intensive and limited in scale.

What Google Ads Offers Advertisers Today

Today’s Google Ads platform bears little resemblance to its early years.

Campaigns are no longer built around individual keywords or devices, but around audiences, signals, and outcomes. Machine learning drives bidding, creative, and placements in real time, analyzing millions of data points per second.

Advertisers now have access to tools that were once unimaginable.

Smart Bidding strategies like Maximize Conversion Value and Target ROAS use historical and contextual signals to optimize bids automatically.

Performance Max and Demand Gen campaigns reach users across Search, YouTube, Display, Discover, and Maps without manual segmentation.

Creative tools have appeared just as rapidly. Gemini-powered AI features can generate ad copy, images, and videos aligned with brand tone and performance goals. Advertisers spend less time on repetitive tasks and more on strategy, messaging, and measurement.

At the same time, data integration has reached new levels. With Google Analytics 4, enhanced conversions, and first-party data connections, advertisers can measure and optimize complex user journeys while staying compliant with privacy standards.

The trade-off, of course, is control.

As automation grows, transparency into individual performance levers diminishes. You can’t always pinpoint which keyword, audience, or placement drove a conversion.

For some advertisers, that loss of granularity remains frustrating. But for many others, the efficiency and predictive power of automation far outweigh what was lost.

Modern measurement also operates under tighter privacy standards. With the loss of cookies and growing restrictions on user-level tracking, Google Ads has leaned on modeled conversions and consented first-party data to maintain accuracy.

For seasoned advertisers, this has shifted the skillset required for success. It’s gone from purely tactical management to data stewardship and strategy.

Teams that can align CRM data, offline conversions, and privacy-safe remarketing signals now have a competitive edge. It’s no longer just about optimizing for clicks; it’s about understanding the full data pipeline that powers automation.

How Google Is Responding To Advertiser Feedback In Its AI Era

Google’s 25th anniversary message emphasized one clear theme: Advertisers are still at the center of our evolution. That statement reflects an ongoing effort to balance automation with transparency and trust.

Performance Max, initially criticized for its lack of reporting detail, now includes asset-level performance and improved search term visibility.

Advertisers can better understand which creative elements drive results and where their ads appear.

Google also added account-level negative keywords and brand exclusion controls to address long-standing requests for greater oversight.

These updates are also a reflection of how the advertising landscape itself has changed.

Privacy regulations like GDPR and the phase-out of third-party cookies are forcing all ad platforms to rethink data transparency. Advertisers are demanding clearer insight into how machine-learning models use their data, while consumers are insisting on greater privacy.

Google’s move toward more transparent reporting, automated creative controls, and first-party data integrations is as much a response to market pressure as it is to advertiser feedback. The company knows that trust is now a competitive advantage.

When agencies and in-house teams can confidently explain how automation makes decisions, they’re more likely to scale their budgets across Google’s platform. In many ways, Google’s AI transparency efforts are as much about rebuilding confidence as they are about innovation.

The new conversational campaign setup, where marketers describe their goals and creative ideas in natural language, is another potential example of responding to feedback. Many small businesses found campaign setup intimidating; conversational AI simplifies the process without removing human judgment.

Google also continues to reinforce the role of human decision-making.

In its 2025 anniversary blog, Google reiterated that AI’s role is to support advertisers. It emphasizes collaboration between human creativity and automation rather than replacement.

It signals that even as automation deepens, Google recognizes advertisers’ desire to maintain control and understand what the system is doing on their behalf.

The relationship between advertisers and Google Ads has always been one of collaboration, and sometimes tension. But recent changes show a genuine effort to listen, adapt, and make the platform more transparent in an AI-first atmosphere.

“Better” Depends On What You Value

The question of whether Google Ads was better then or now ultimately depends on what you value most as an advertiser.

If you prize simplicity, transparency, and full control, the early years of AdWords were unmatched. Campaigns were manual but predictable. You could see every moving part and trace every click to a decision you made.

If you value scale, efficiency, and advanced targeting, today’s Google Ads is undeniably better. The ability to reach audiences across channels, powered by real-time automation and predictive data, has expanded what’s possible in digital marketing.

What’s clear across both eras is Google’s willingness to evolve alongside advertisers. Every major shift has aimed to improve relevance, performance, and user experience.

While not every change has been universally welcomed, the intent, to balance automation with advertiser trust, has remained consistent.

After 25 years, Google Ads continues to define the standard for paid media. The platform may look different, but its purpose hasn’t changed: helping businesses connect with people in meaningful, measurable ways.

Whether that’s better or worse depends less on the tool itself, and more on how we choose to use and embrace its technology.

More Resources:

Featured Image: Who is Danny/Shutterstock

Ecommerce MGMT 0 Comments
Nov 4 2025
Holiday PPC Guide 2025: Advanced Strategies For Smarter Bidding, Budgets & Audiences via @sejournal, @siliconvallaeys

The holiday this year brings more competition than ever, but the shopper journey is also shifting. Consumers begin research weeks earlier, often starting in October, and rely on conversational AI or chatbot-style searches to compare products. Microsoft’s holiday insights show that shopping behavior kicks off in October, with many November and December conversions originating from clicks made weeks earlier.

The funnel is changing shape: wider at the top as more shoppers browse early, but shorter at the bottom as they move quickly once urgency kicks in. The key lesson is that PPC strategy must nurture intent early and be ready for compressed buying cycles when urgency arrives.

Holiday shoppers are beginning earlier, researching longer, and converting later. The funnel is wider than ever, but also shorter once the urgency hits.

Bidding: Winning The Ad Auction

Don’t Fear Expensive Clicks, Fear Unprofitable Ones

Holiday auctions bring higher cost-per-click (CPCs), a natural result of more advertisers competing for limited inventory. Success is not about avoiding CPC increases but maintaining strong return on ad spend (ROAS) and protecting profit margins. Teika Metrics’ Black Friday and Cyber Monday (BFCM) data confirms that CPCs climb seasonally, especially on Black Friday and Cyber Monday.

Smart Bidding goals should be tied to profitability, not just revenue, and portfolio bidding can help balance volatility across campaigns. Microsoft and Google also recommend applying seasonality bid adjustments before major holidays so automation anticipates conversion spikes.

Pro Tip: Set seasonality adjustments 24-48 hours before and after Black Friday and Cyber Monday to help Smart Bidding avoid over- or under-reacting.

Smart Bidding With Guardrails: Train The Machine

Automation is powerful, but it is not infallible. It needs monitoring and guardrails. Trust tROAS or tCPA when conditions are stable, but ensure you have bid limits (through portfolio bidding) and guardrails to alert you about unusual performance during peak periods when volatility spikes.

Real-World Example: Last BFCM, a large retailer client of ours using offline conversion import (OCI) saw conversions suddenly vanish. Optmyzr automation flagged the anomaly right away, revealing a Google-side glitch in OCI reporting. Without that safeguard, Smart Bidding would have assumed conversions had dried up and slashed bids during the most important shopping week of the year. Guardrails prevented disaster.

Key Take: Automation doesn’t eliminate risk; it changes the type of risk. Without guardrails, a data glitch can quietly sabotage your bids. With guardrails, you catch it before it becomes a disaster.

Inventory And Feed-Aware Bidding: Don’t Burn Budget On Out-Of-Stock

Holiday shoppers expect items to be in stock, priced competitively, and available with fast delivery. Automating feed hygiene to pause out-of-stock products is essential. Structuring campaigns by margin allows for different tROAS bids that achieve your target profitability.

Pro Tip: If your price is not competitive, shift spend toward SKUs where you can compete on both offer and margin.

And before you worry about bids, ensure the feed can win the impression. Tighten mobile-friendly titles and human-readable attributes (e.g., use “light brown,” not obscure color names), add seasonal terms like “Black Friday deals,” and fix disapprovals early so you don’t lose visibility when auctions heat up.

Create label taxonomies that align with your profit strategy, like “hero products,” “doorbusters,” “low-margin,” “last-chance,” so you can direct bids and budgets to what actually drives profits.

Case Study Insight: When Amazon briefly exited the Google Ads auction, Optmyzr’s analysis showed other advertisers gained clicks at lower CPCs, but ROAS did not improve. Shoppers were expecting Amazon, and when they did not find it, they often failed to convert with alternatives. Winning an auction is meaningless if the offer and expectations do not align.

Budgeting: Flexibility Wins

Turn On Campaigns Now And Control Delivery With Budgets

I normally recommend pausing campaigns that are not needed, rather than reducing their budgets to a very low amount to keep them active. Advertisers sometimes use budget rather than status to “pause” a campaign because they fear the dreaded learning period that may kick in when a campaign is enabled after an extensive period of inactivity.

Pausing does not erase Google’s memory, since “learning” reflects new auction contexts rather than forgotten history. Longer pauses, however, risk drift as consumer behavior shifts. The bigger issue is that paused campaigns with new ads will not undergo review until they are re-enabled, which can delay serving during crucial moments.

So during BFCM, there are good reasons to use budget rather than status because it keeps campaigns actively learning about shifts in consumer behavior, and it ensures new creatives go into the approval process.

Holiday Pitfall Alert: Do not pause campaigns with unapproved creatives close to Black Friday. Get ads reviewed in advance.

Intraday Pacing: Don’t Get Fooled By Conversion Lag

Static daily budgets can be damaging in volatile holiday conditions. Dynamic pacing using scripts or APIs is a better approach, especially when aligned with key milestones like Black Friday, Cyber Monday, shipping cutoffs, and last-minute windows.

On Black Friday and Cyber Monday, pacing must be monitored throughout the day. Hourly reporting in Google Ads makes this possible, but advertisers must also account for conversion lag.

Looking at last year’s data, conversions appear smooth by the hour because lag has already resolved. On the day, however, conversions will often appear behind pace even when clicks and impressions are aligned. Saving hourly reports as the day unfolds will provide a baseline for analyzing lag in future years.

Pro Tip: Do not confuse lag with poor performance. Cutting budgets midday can mean missing the evening conversion surge.

Lock in your total Q4 budget and earmark a supplemental pool for Black Friday, Cyber Monday, and the biggest shopping weekends. Expect higher CPCs and raise day caps accordingly so campaigns don’t exhaust at noon. Finally, audit your automations – safety scripts that pause or cap spend are helpful, but if they fire at the wrong time during BFCM, they can suppress profitable traffic.

Targeting

Audience Signals Are Your Multiplier

First-party data goes beyond CRM lists. It includes your business’s unit economics, such as pricing and profit margins, which can guide automation toward profitability rather than vanity ROAS.

Key Take: First-party data is not only about who your customers are, but also includes all your business data, including how you price. Leverage this to guide when you run ads and how much you bid.

Microsoft has a unique feature that Google doesn’t have: impression-based remarketing, which allows advertisers to retarget users who saw their ads but did not click. This expands reach to pre-qualified audiences and often reduces costs. Combining CRM imports, impression-based remarketing, and profit-based bidding provides automation with richer signals.

Keywords And Keywordless Targeting

With match types getting broader every year, and the growth in keywordless campaign types like Performance Max, advertiser control over queries is eroding. This trend will continue as users shift from keyword searches to prompting, and Google eventually replaces synthetic keywords with a more precise targeting system.

Performance Max is performing well, and we shared details about what trends are working best in our PMax study. AI Max, on the other hand, doesn’t feel quite as ready for primetime, though there is unverified speculation that a September 2025 algorithm update improved performance significantly. Test AI Max using Experiments before setting it loose on your BFCM traffic this year.

Creative: Stand Out In Crowded Auctions

Ads That Win Auctions: CTR Beats Clever Copy

Auctions for bottom-of-the-funnel search ads reward click-through rate (CTR) and predicted CTR, not witty copy. Coverage and clarity matter most. Ad headlines, descriptions, and assets (formerly ad extensions) should be updated with current promotions, shipping cutoffs, and urgency messaging.

However, with 15 potential headlines that Google can choose from for your ad, controlling what is most important to include in messaging requires pinning during BFCM.

Optmyzr’s soon-to-be-published 2025 Responsive Search Ads (RSA) study shows that advertisers who pin multiple variations to the same position achieve better ROAS. Pinning one element restricts the machine too much, while no pinning gives it too much freedom. Multi-asset pinning balances human guidance with algorithmic optimization. Google’s RSA guidance confirms that variation improves performance.

Pro Tip: Plan RSAs in waves and use multi-asset pinning to balance brand strategy with system optimization.

Keep It Fresh: Creative Burnout Happens Faster In Q4

Shoppers tire quickly of repetitive ads, especially in Demand Gen campaigns. But even search ads should be kept fresh, and ads should be staged in waves to appeal to Black Friday and Cyber Monday shoppers, and reflect shipping cutoffs, last-minute gifts, and post-holiday clearance as the holidays approach.

Pre-loading assets ensures they are reviewed and ready to serve. Countdown customizers and promotion extensions can reinforce urgency, but messaging must stay consistent with site offers to maintain trust.

Pro Tip: Schedule creative waves in advance. Do not wait until Cyber Monday morning to swap assets.

Competitive Insights

Competitor Surge Alerts: Auction Insights As A Warning

Auction Insights is a powerful diagnostic tool. Google’s Auction Insights report reveals shifts in competitor behavior, such as impression share surges. Monitoring these trends in November helps advertisers react quickly, whether by increasing brand defense or positioning directly against rivals.

Auction Insights is your battlefield radar for Q4. Ignore it, and you could be blindsided.

Post-Holiday: Turn December Buyers Into January Fans

January Is Your PPC Lab: Retain, Don’t Just Acquire

Holiday buyers are the most expensive to acquire but can become the most profitable if nurtured in Q1. Segment holiday-only versus year-round buyers using customer relationship management (CRM) and ad data, then run loyalty and cross-sell campaigns. Feeding learnings back into bidding and audience systems ensures automation improves over time.

Holiday buyers are the most expensive you will ever acquire. Retarget them in January to make them more profitable.

Final Thoughts

Holiday PPC is the ultimate stress test. CPC inflation, automation, budgets, audiences, creative, competition, and fraud all converge at once. Winning requires guiding automation with better inputs, protecting profitability with strong signals, and owning your message at a time when keyword precision is fading. Prepare early, pace carefully, and place guardrails everywhere they matter most.

Checklist Summary

  • Expect CPC inflation in Q4. Optimize for profit and ROAS, not cheap clicks.
  • Set seasonality bid adjustments and add guardrails so Smart Bidding doesn’t misfire on BFCM.
  • Treat budgets as fluid with intraday pacing. Don’t confuse conversion lag with underperformance.
  • Use first-party data beyond CRM lists. Profit margins and pricing strategy are key signals.
  • Microsoft’s impression-based remarketing lets you retarget high-intent searchers who never clicked.
  • Make creative your control lever in a PMax and broad-match world. Use multi-asset RSA pinning.
  • Monitor Auction Insights, watch for fraud/MFA, and turn expensive Q4 buyers into Q1 loyalists.

More Resources:

Featured Image: Roman Samborskyi/Shutterstock

Ecommerce MGMT 0 Comments
Oct 22 2025
PPC Trends 2026: AI, Automation, And The Fight For Visibility via @sejournal, @MattGSouthern

If you manage PPC campaigns, you’ve seen it. Platforms are making more decisions without asking you first.

Campaign types keep consolidating into AI-first formats like Performance Max and Demand Gen. The granular controls you used to rely on keep disappearing or moving behind automation.

A year ago, Performance Max still felt experimental. Now it’s often the default option, with AI generating ad copy, and automation selecting audiences based on signals you can’t always see. When performance drops, you have fewer levers to pull and less visibility into what’s actually happening.

It can be disorienting to some, and the trend isn’t reversing.

We asked PPC professionals how they’re navigating this shift. Most aren’t pessimistic about AI-first campaigns. Many have found ways to work with platform automation without surrendering the strategic thinking that drives results.

You can use AI tools without losing your expertise in the process.

4 Key Findings From Industry Professionals

We surveyed professionals from agency, platform, and consultancy backgrounds for this year’s report. Clear patterns emerged in how they’re adapting to AI-first campaign management.

1. AI Tools Save Time But Still Need Babysitting

Most professionals now use AI daily for tasks like keyword research and ad copy variations. The tools are good enough to integrate into workflows.

But there’s a catch. Over half identify “inaccurate, unreliable, or inconsistent output quality” as the biggest limitation. AI accelerates production, but it hasn’t replaced the need for human oversight.

One contributor noted that in regulated industries where legal review is required, AI outputs often can’t be used without heavy editing.

The professionals who get results are the ones treating AI as an assistant, not a replacement.

2. “Control” Means Something Different Now

You can’t control exact search terms the way you used to. You can’t set precise bids on individual keywords or force campaigns to follow rigid parameters.

Several contributors argue you still have meaningful control, it just operates differently than before. One Google Ads coach compared it to giving a teenager the destination address and trusting they can navigate there, even if they take a few wrong turns along the way.

The new version of control means setting clear business objectives and providing high-quality conversion data. If your conversion tracking is messy or incomplete, AI will optimize toward the wrong goals.

3. Measurement Got More Honest (And More Uncomfortable)

Cookie deprecation was canceled in Chrome, but measurement challenges haven’t disappeared. What’s changed is how practitioners talk about attribution.

One agency founder admitted that focusing too heavily on perfect attribution might have been a strategic mistake. “Your marketing strategy should hold up even if granular tracking disappears.”

Other contributors emphasize that first-party data collection with proper consent is now essential for survival, especially in lead generation models.

Revenue remains the most reliable source of truth when platform-reported metrics conflict.

The most durable measurement approach involves choosing a limited set of reliable lenses rather than attempting to reconcile data from every available source.

4. Platform-Generated Creative Performs Better Than You’d Think

This finding surprises people. Several contributors report that AI-generated creative assets can perform competitively with human-created versions when they’re prompted effectively.

But “when prompted effectively” is doing substantial work in that sentence.

Quality depends heavily on how well you prompt the tools and how much brand context you provide. The tools still struggle with maintaining consistent brand voice and meeting legal compliance requirements in regulated industries.

Visual generation continues to need improvement, though contributors note it’s getting better for ecommerce product photography.

Most teams have settled on a hybrid workflow where AI handles idea generation and creates variations while humans manage final approval and anything requiring nuanced brand voice.

What Makes This Report Different

Previous years focused on specific platform changes or new features. This year’s questions dig into strategy.

How do you maintain visibility when platforms reduce transparency? What measurement techniques still work when attribution is murky? How do you adapt creative workflows when AI can generate assets on demand?

The contributors include:

  • Brooke Osmundson, Director of Growth Marketing, Smith Micro Software.
  • Gil Gildner, Agency Co-Founder, Discosloth.
  • Navah Hopkins, Product Liaison, Microsoft.
  • Jonathan Kagan, Director of Search & Media Strategy, Amsive.
  • Mike Ryan, Head of Ecommerce Insights, Smarter Ecommerce.
  • Jyll Saskin Gales, Google Ads Coach, Inside Google Ads.

The answers reflect an industry adapting in real time. Some contributors have embraced AI-first workflows fully, while others remain cautious about surrendering too much control. All are experimenting constantly because the platforms aren’t slowing down.

Why Download This Now

If you’re managing campaigns, you’re already wrestling with these challenges. Are you approaching them with a clear strategy, or just reacting to each platform change as it happens?

This report will show you how experienced professionals at agencies, platforms, and consultancies are thinking through the same problems you’re facing right now.

Download PPC Trends 2026 to see how industry professionals are adapting their strategies, maintaining accountability in automated campaigns, and finding ways to make AI-first advertising work without losing the strategic expertise that separates successful campaigns from mediocre ones.

PPC Trends 2026

Featured Image: Paulo Bobita/Search Engine Journal

Ecommerce MGMT 0 Comments
Oct 14 2025
Google Redesigns How Search Ads Are Labeled via @sejournal, @brookeosmundson

Google is rolling out a change to how ads appear in Search, and this time it’s focused on clarity and user control.

Text ads will now be grouped under a single “Sponsored results” label that stays visible as you scroll. In addition, a new “Hide sponsored results” option lets users collapse the entire ad block with one click.

This update doesn’t change how ads are served or ranked, but it does change how they’re presented to users. Even small interface updates can influence how people interact with search results, so advertisers should pay attention to how this evolves over time.

A Look at the New Sponsored Label on Google Search

Previously, each text ad showed a small “Sponsored” label at the top of each ad.

Now, Google is grouping all text ads together with a single header that clearly signals where the sponsored section begins and ends. That label remains visible even if the user scrolls down the page.

While doing a Search in the wild, the new format appeared, even with just one ad:

New 'Sponsored Result' layout on Google Ads search result.Screenshot taken by author

Google is also extending this approach to other formats. For example, Shopping placements will use a “Sponsored products” label.

On results that include AI Overviews, the sponsored section can appear above or below the AI-generated content, but it will still follow the same grouping and labeling format.

The most noticeable addition is the ability to collapse all sponsored results. Not every user will hide the section, but the option itself introduces a new behavior that didn’t exist before.

Google noted that these updates are rolling out globally to users on both desktop and mobile

Why This Matters to Advertisers

From a performance perspective, the underlying mechanics are unchanged. Bidding, Quality Score, ranking, and the maximum number of ads (up to four in a block) all remain the same.

That said, grouping ads together can influence how users perceive them.

When ads are visually separated from organic listings, the difference between the two becomes more intentional.

Users who skim results may pause and decide whether to interact with the sponsored block at all. For lower-intent searches, this could result in fewer casual clicks. For higher-intent queries, the impact may be minimal.

This puts more pressure on the quality of the ad itself. Clear value propositions, relevant messaging, and strong alignment with search intent will matter even more.

Ranking at the top will still be valuable, but visibility alone won’t guarantee engagement if users are more aware of what they’re clicking.

While the update is primarily visual, advertisers should keep an eye on performance once it fully rolls out across mobile and desktop. A few areas to watch include:

  • Changes in CTR or Impression-to-Click patterns
  • Differences in engagement based on query intent
  • Any vertical-specific impact where users are more likely to hide ads

Early shifts may be small, but trends could emerge over time as users adjust to the new layout.

Why Did Google Make This Change?

Google notes that these changes were driven by user testing and feedback. The goal is to create a more consistent and transparent experience across all ad formats. It also reflects increasing expectations around clarity in search results as AI-generated content becomes more common.

By making it easier to recognize sponsored content, Google is signaling that paid placements can be both visible and trustworthy, as long as they’re clearly labeled.

This approach may help maintain long-term confidence in search results as the interface continues to evolve.

Moving Towards a More Transparent SERP

Google’s update reinforces a larger shift: how ads appear on the page is becoming just as important as where they appear.

The auction logic and placement limits remain the same, but the experience around ads is becoming more clearly defined for users.

As presentation evolves, it’s reasonable to expect user behavior to follow. Some people will ignore the change. Others may start to be more selective about when they engage with ads.

This puts more weight on relevance, clarity, and value in the message itself.

Advertisers don’t need to overhaul their campaign structure or bidding strategy because of this change. Instead, the focus should be on tightening creative quality, aligning closely with intent, and paying attention to early performance shifts.

Even if the impact is subtle at first, updates like this often lead to gradual behavior changes over time.

Search has always been a balance between visibility and trust. Advertisers who adapt early and continue to prioritize useful, high-quality messaging will be in the best position to maintain performance as the SERP continues to evolve.

Ecommerce MGMT 0 Comments
Oct 14 2025
Get Your Ad Campaigns Ready Before Black Friday via @sejournal, @brookeosmundson

For most PPC marketers, the weeks leading up to Black Friday aren’t just doing busy work. They’re loaded with decisions, deadlines, and last-minute requests.

If you’re managing Google Ads, Microsoft Ads, or any ad platform in between, this time of year can either be a strong finish or a missed opportunity.

The difference usually comes down to planning.

If you’re looking to approach Black Friday with a more structured and thoughtful strategy, keep reading. This article focuses on what you can control (like budgets, campaign builds, and feed readiness) and includes specific examples across platforms to help you avoid common pitfalls.

Let’s start with what to revisit from last year.

Take The Time To Audit Last Year’s Wins And Pitfalls

Before building anything new, it’s worth taking a closer look at last year’s performance.

The strategy here isn’t about copying old campaigns; it’s about understanding where they overdelivered, where they stalled out, and how the landscape might have changed since then.

In Google Ads, start with the attribution reports. Look beyond just last-click conversions and examine how various campaign types contributed throughout the funnel.

If Performance Max campaigns played more of an assist role, that should inform how you structure them this year.

If Standard Shopping capped out early or certain product categories were underrepresented, those are fixable issues.

You can also use auction insights to see when competitors ramped up spend, or whether you lost impression share due to budget or rank. These reports offer useful context if you’re planning to scale this year but didn’t last year.

If you’re using Microsoft Ads, review audience and device performance to see where volume shifted.

Holiday behavior isn’t always the same across platforms. What worked well on Google may not have translated to Bing or Meta, and vice versa.

The goal is to identify specific opportunities, not just assume last year’s playbook will hold up.

Build Early, Even If You’re Not Launching Yet

There’s value in building out your campaigns well in advance of Black Friday, even if you don’t plan to activate them until closer to the sale.

Whether you’re launching new campaigns or just updating ads in existing ones, getting ahead on structure gives you time to QA creative, troubleshoot disapprovals, and coordinate across teams.

If you’re planning to reuse existing campaigns, you can still stay organized using labels. For example:

  • Apply labels to new Responsive Search Ads (RSAs) that include holiday-specific copy or promotions.
  • Label sitelinks, callouts, or promo assets that reference Black Friday offers.
  • Tag ad groups or asset groups that are tied to limited-time sale messaging.

Using a clear naming convention makes it easier to filter, review, and schedule changes across campaigns without confusion.

If you want to automate this even further, you can create automated rules based on labels.

For example, you can set a rule to enable all ads with your Black Friday label at 12:01 a.m. on November 28. You can also set up rules to pause those same ads at the end of the promotion, reducing the chance that outdated messaging stays live.

You’d also want to create an automated rule to run to pause all non-Black Friday ads at the same time. This ensures that only your promo ads are running during Black Friday season.

If you end up creating Black Friday-specific campaigns, you can easily set start and end dates on them to ensure they only run during the allotted time.

While you don’t have complete scheduling control at the ad or asset level across platforms, you can use a combination of labels, automated rules, or campaign/ad group start and end dates. These give you enough flexibility to manage most scenarios without scrambling the morning of your launch.

If you’re running Meta Ads, be sure to upload your Black Friday creative and audience setups well in advance. Platforms are slower to review and approve ads during peak periods, and early delivery data will help the algorithm optimize once you start increasing budgets.

Give Smart Bidding Better Direction

Most advertisers are using some sort of Smart Bidding for their campaigns, especially around Black Friday. That doesn’t mean you should take a hands-off approach, though.

If you’re using Google Ads, consider seasonality adjustments if you’re planning for a short-term sale or expect a sudden fluctuation in conversion rates. These adjustments tell Google to expect better-than-usual performance during a specific window, and can help avoid underspending during flash sales.

Seasonality adjustments are currently available for these campaign types that use either a Target ROAS or Target CPA bid strategy:

  • Search.
  • Shopping.
  • Display.

If you’re using seasonality adjustments for conversion rates, then you can choose between these campaign types:

  • Search.
  • Display.
  • Shopping.
  • Performance Max.
  • App (in beta).

That said, they’re not suited for every situation. If you’re running a longer sale or have limited historical volume, the adjustment could cause more volatility than good.

For broader holiday performance, make sure your campaigns have enough data to support Smart Bidding decisions. Review the “Bid Strategy Report” and watch for signs of limited learning or constrained budgets.

Pushing into a critical promo window without stabilized bidding can lead to inefficient spend, especially with newer campaigns.

Check Your Product Feed Before It Becomes A Problem

It’s easy to focus on campaign settings and forget that your product feed is powering everything from standard Shopping campaigns to Performance Max. If it’s not accurate or timely, your best offers might not show up correctly.

In Google Merchant Center, navigate to the Diagnostics tab and resolve any disapprovals or mismatched pricing issues. These often spike around holidays when sale prices don’t sync correctly or out-of-stock products remain active.

Make sure your feed includes items like:

  • Up-to-date GTINs and product identifiers.
  • Attributes like ‘sale_price’ and ‘sale_price_effective_date’ for promotions.
  • High-quality images that meet platform guidelines.
  • Clear shipping and availability details.

If you’re running Performance Max campaigns, review the Listing Groups report to ensure your most valuable products are getting served. Many advertisers find that certain SKUs get minimal impressions due to budget spread or structural issues.

This is also a good time to upload holiday-themed creative assets, including lifestyle images and product videos. These can improve performance in placements like YouTube and Discover, which tend to ramp during PMax campaigns in Q4.

The more you control the feed and asset side, the less you have to worry about automation making subpar choices when competition is highest.

Expect Things To Break, And Plan Around That

Black Friday campaigns don’t always go according to plan.

Promo pages fail to update. Budgets cap out early. Tracking drops off mid-day. It’s worth thinking through what could go wrong now, while you still have time to build a backup plan.

Start with some of the basics in campaign planning:

  • Double-check conversion actions in Google Ads and Google Analytics 4. Make sure no duplicate events are being counted, and key actions like purchases, add-to-cart, and email sign-ups are being tracked.
  • Test final URLs on mobile and desktop. If you’re using promo pages, confirm they’re live and loading quickly. A slow checkout experience during Black Friday Cyber Monday (BFCM) will almost always tank performance.
  • Pre-schedule creative updates where possible. You don’t want to be manually swapping sitelinks or headlines in the middle of a surge.
  • Double-check your automated rules. If you’re using rules to enable sale ads and pausing evergreen ads, make sure to have the platform(s) email you with any changes so you can confirm with confidence the right ads are being shown at the right time.
  • Set up alerts for unusual activities. If campaigns showcase a sudden ROAS drop, zero conversions, or unusual spend, you’ll want to be alerted in real-time. Even something as simple as a budget cap hitting before 10 a.m. can throw off the day if it goes unnoticed.

The more you can troubleshoot before launch week, the fewer fires you’ll need to put out when things are moving fast.

Don’t Shut Down Campaigns The Minute Cyber Monday Ends

It’s common for brands to ramp hard through Cyber Monday, then pause everything until January. But, many shoppers are still active well into December, especially those looking for last-minute gifts or deals that weren’t available earlier.

Based on previous personal experience, Google Ads auction data may show that competition could dip after Cyber Monday and shopping intent doesn’t disappear. Conversion rates often stay steady through the first two weeks of December, particularly for brands with fast shipping or digital products.

Rather than winding down completely, consider updating your messaging to reflect the urgency. Swap out “Black Friday” language for “Still Time to Save” or “Guaranteed Delivery Before Christmas.” Countdown ads and shipping deadline assets work well here.

If you’re running remarketing campaigns, exclude recent purchasers and focus on users who visited key pages but didn’t convert. These audiences tend to convert at lower cost-per-acquisition (CPA) during post-Cyber sales, especially if you’ve got gift cards or bundled offers to promote.

December also gives you a chance to build audience pools for Q1. Visitors from BFCM campaigns can be remarketed to in January for loyalty or cross-sell efforts. Just make sure your campaign structure allows for clean audience segmentation.

Planning Ahead Is Still Your Best Defense

Black Friday doesn’t reward last-minute execution. It rewards structure, preparation, and proactive troubleshooting.

The platforms are going to do what they do. Smart Bidding will make the best decisions based on your inputs. Asset groups will mix and match in ways you can’t fully control.

But, what you can control, like budgets, tracking, and product feed health, still has a major impact on your campaign performance.

Getting your campaigns in order early gives you the breathing room to monitor performance, scale what’s working, and catch issues before they snowball.

And when something inevitably breaks or shifts unexpectedly, you’ll already have a plan in place.

More Resources:

Featured Image: Roman Samborskyi/Shutterstock

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