If you run ecommerce campaigns on target CPA or target ROAS and any of them sit at “Limited by budget,” Google’s August 17 bidding change is going to move your numbers, and we’re likely not talking about the direction you want. Starting August 17, campaigns that are limited by budget and use a target-based bid strategy will deliver more consistently toward the target you set instead of overshooting it. For the many accounts that have quietly been beating their targets, that means a higher cost per conversion or a lower ROAS unless you act first.

This one is not opt-in; Google is applying it automatically to eligible campaigns, and it has said it will not adjust your targets or budgets for you. The runway is getting shorter by the day. The Bid Target Adjustment Tool went live on July 6, and account notifications are landing now, with the change itself starting to roll out on August 17. That leaves a few weeks to decide, campaign by campaign, whether your over-delivery was a deliberate strategy or just a target you never updated.

What The Target-Based Bidding Update Changes

Today, a campaign that is limited by budget and running target CPA or target ROAS often beats its target, and it can swing around when you change the budget. After August 17, Google optimizes so that actual performance tracks closer to the target you set, including when you adjust budgets, which it frames as more predictable performance as you scale. Take a campaign with a $100 target CPA that has been delivering conversions at $50. After the change, it will move toward $100. The update applies to target-based campaigns across Search, Shopping, Performance Max, Demand Gen, Travel, and Display, while App, Video reach, and Video view campaigns are excluded. For multi-channel campaigns like Performance Max and Demand Gen, Google has also said you may see traffic shift between channels as the system rebalances toward the target.

Why Budget-Limited Campaigns Overdeliver

A campaign that is limited by budget beating its target was usually not a bidding miracle. The budget cap was the real constraint, so the algorithm never spent all the way up to the target. It bought the cheapest conversions it could inside the cap and left the rest of the target headroom untouched. That gap between your $50 actual and your $100 ceiling was efficiency you were getting for free, because budget, not the target, was doing the limiting.

After August 17, the system treats that headroom as room to work with. It will pursue additional conversions that cost more, which pulls your average up toward the target you set. In plain terms, your target stops being a ceiling you rarely touched and becomes a destination the algorithm actively aims for. This doesn’t mean that Google will actively raise your budget; it means the system pulls your actual performance up toward the stated target you already entered.

Google’s Ads Liaison Ginny Marvin has been clarifying the framing publicly, and two points are worth carrying into your own read. Bidding targets are meant to be your lever for efficiency and spend control, while Maximize Conversions and Maximize Conversion Value are the strategies built for a fixed budget with no target. She has also pushed back on the idea that this change is Google telling you to spend more, so treat August 17 as a reason to make your stated target honest rather than a nudge to loosen it.

The Real Risk Is A Bid Target You Never Tuned

Plenty of accounts carry a target CPA or target ROAS that someone set once as a rough ceiling and never revisited, because the campaign beat it every month anyway. Those targets are about to go live. If your $100 CPA was aspirational rather than a real break-even number, or your 400% ROAS target was a placeholder while the campaign quietly ran at 600%, August 17 exposes the gap. Miss it, and it surfaces in next month’s reporting as a cost increase you have to explain after the fact, which is a worse conversation than the one you could be having now.

The Decision For Each Budget Limited Campaign

For each campaign that is limited by budget and sitting comfortably inside its target, you have three honest options.

Reset the target to your actual performance. If a campaign has been running at a $50 CPA or a 600% ROAS and that is the efficiency you want to keep, update the target to match before August 17. The Bid Target Adjustment Tool lets you apply your recent performance as the new target in a couple of clicks, which holds your current numbers in place.

Raise the budget and scale at the stated target. If the overdelivery was really a sign the campaign could spend more, lift the budget so it is no longer limited by budget, and let it capture more volume at your true target. This is the growth path, and it only makes sense when the stated target reflects real profitability.

Let it drift toward the target on purpose. If your stated target was always your genuine break-even and you have been happy to take cheaper conversions while the budget cap allowed, you can accept the drift toward target and the added volume that comes with it. The point is to choose it, not to inherit it because you forgot to look.

How To Audit Your Bid Targets Before August 17

Pull every campaign flagged “Limited by budget” that uses Target CPA or Target ROAS. Compare actual CPA or ROAS to the stated target over the last 90 days, and flag any campaign where actual sits well inside target, because those are the ones that will move. Then apply the decision above to each.

The Bid Target Adjustment Tool, live in accounts since July 6, surfaces this historical performance and lets you apply updated targets directly, and the notifications Google is now sending point at where it thinks you are exposed, so treat them as a prompt to act rather than a recommendation to dismiss. One more step that has nothing to do with the platform: brief clients or your leadership before August 17, not after. A short proactive note about a possible cost shift beats explaining a surprise in next month’s report.

What The Update Means For Ecommerce PPC

Most accounts that regularly run “Limited by budget” are small and midsize stores, which is a large slice of ecommerce. On the Shopping and Performance Max side, two things are worth watching.

First, if you run Target ROAS on a budget-capped Shopping or Performance Max campaign that has been beating its target, the drift toward target shows up as a lower ROAS and more spend on the marginal conversion. For a thin margin catalog, that can quietly erase the profit you thought the campaign was printing. Reset the target to your real ROAS floor, ideally one built from contribution margin rather than a round number, before the change makes the call for you.

Second, because Performance Max spreads across Search, Shopping, YouTube, and more, Google has said you may also see traffic shift between channels as the system rebalances. Watch your channel-level reports in the weeks after August 17 so a move toward cheaper, lower-intent inventory does not slip past you.

Where Smart Bidding Exploration Fits

If your honest reaction is that you would take more volume, there is now a deliberate lever for that, instead of letting the August 17 drift spend your headroom at random. Smart Bidding Exploration, which Google expanded on June 15, lets you set a ROAS tolerance so the algorithm can bid on converting queries it would normally skip, widening reach beyond your current query coverage while staying inside a boundary you define. It is globally available for Performance Max campaigns without product feeds, and in beta for Shopping and Performance Max with feeds through your Google account team. Google reports that its own testing showed an 18% lift in unique converting query categories and a 19% lift in conversions, which are Google’s figures rather than independent ones, so treat them as directional.

The point for ecommerce is control. The August 17 change will use your headroom whether you want it to or not. Smart Bidding Exploration lets you decide how much of that headroom goes toward exploration and at what efficiency, which is a cleaner way to buy incremental volume than finding it in a report after the fact. Google also launched Promotion Mode in beta for Search and Performance Max, which schedules a temporary budget and ROAS tolerance boost for a defined peak window and then closes itself, so it is worth a look for flash sales and launches heading into Q4.

What To Do Before August 17

The August 17 bidding change rewards one discipline, which is running targets that reflect real business math instead of placeholders. Audit every campaign that is limited by budget and running Target CPA or Target ROAS, decide per campaign whether to reset the target, raise the budget, or accept the drift, and use the Bid Target Adjustment Tool, which is live now, to lock in the efficiency you want before the system settles it for you. If you would rather buy incremental volume on purpose than inherit it, Smart Bidding Exploration is the lever to reach for. The accounts that get caught out will be the ones that treated bid targets as set-and-forget ceilings, and this change turns every one of those ceilings into a live target.

More Resources:

Featured Image: tete_escape/Shutterstock

https://www.searchenginejournal.com/google-ads-target-based-bidding-update-for-ecommerce/581801/

Google AI Mode returned a text ad on 29% of the commercial keywords in a new SE Ranking analysis, and for most of those keywords the advertiser’s domain was not among the sources the answer cited.

SE Ranking checked if the pages or domains of each keyword that produced a text ad also appeared in the sources listed by AI Mode for the same query. The domain was present 11% of the time, while the exact URL appeared 1.95% of the time. For the remaining cases, the paid ad’s advertiser was not among AI Mode’s referenced sources.

Ad Frequency Rose With CPC

Ad frequency more closely correlated with cost per click than any other factor SE Ranking examined. The CPC rate increased across three bands: 24% below $2, 32.45% from $2 to $10, and 53.56% at $10 and above. Search volume and keyword difficulty didn’t show similar patterns. Since the report doesn’t provide a model or sample sizes for each band, this indicates a correlation in the data, not a proven predictor.

Ad Presence Swung Hard By Niche

Ad presence varied by niche, dropping from 72% of Pets keywords to 2% in Healthcare. SE Ranking interprets the categories with higher ad presence as primarily for lead-generation and those with lower presence as more informational or YMYL-oriented. So, the advertising potential for an account depends on its category before considering any specific keywords.

Most Advertisers Didn’t Rank Organically Either

Advertisers rarely appeared in the organic search results for the keywords they paid for. Only 2% of paid URLs also ranked organically for the same keyword, and 15.35% at the domain level.

Part of the URL gap results from campaign landing pages that are not intended to rank, but the domain-level gap persists across the top 10, 20, and 100 rankings. SE Ranking also compared advertising and non-advertising domains matched on authority and organic presence, finding no increased citations for advertisers, although the details provided are limited for verification.

The Ad Layer Google Has Been Building

Google has gradually added ads to AI Mode. During Google Marketing Live, the company introduced two new AI mode ad formats: Conversational Discovery ads and Highlighted Answers, both embedded within AI responses. These are still in testing and not widely available yet.

This follows an annual letter from Vidhya Srinivasan, hinting at expanding AI Mode ads in 2026. Google also said AI Overview ads earn revenue similar to traditional search ads.

Why This Matters

AI Mode ads are independent, with data showing that ad placement, citations, and organic rankings often don’t align for the same keyword. Buying a slot doesn’t guarantee citations or rankings, so treat this as a separate paid channel, especially for high-CPC keywords.

The overlap between ads and citations is useful for visibility, not direct purchase. Remember, a competitor appearing in AI Mode isn’t necessarily cited as a source, as these usually don’t occur simultaneously. Monitor paid and citation presence separately.

Looking Ahead

Right now, paid ads and cited information are quite different, so you can track them separately. Google is trying out new formats like Conversational Discovery ads and Highlighted Answers, where the ad is part of the response itself, instead of being shown next to it. If these new formats become more common, the line between buying a spot and appearing in the response may start to blur.

SE Ranking sells AI Mode and competitor ad tracking. The keywords were preselected to trigger text ads and sampled about evenly across niches, so 29% reflects this test set on one date, not ad prevalence across commercial searches.

Featured Image: dintadonna/Shutterstock

https://www.searchenginejournal.com/google-ai-mode-shows-ads-on-1-in-3-commercial-keywords/582976/

You’re finalizing a monthly PPC report, excited to show improvements you’ve seen in the account. You highlight an A/B test that yielded an improvement in CPA, along with a new Meta campaign that is driving marketing qualified leads.

Yet when you present the report to leadership, you still get questions like, “How are these actions helping us grow revenue?”

Knowing your audience is a fundamental principle of marketing, and it applies equally so when creating marketing reports. A report geared to a marketing director who is more in the weeds of individual campaigns will look different from a report geared to a C-level executive.

When creating a report that will be viewed by senior leadership, consider what they are held accountable for. A CFO may answer to shareholders or VC firms, but ultimately, their main concern is increasing revenue. If a report doesn’t clearly answer the question of profitability from an investment in PPC, you’re setting yourself up for failure.

In this article, we’ll consider the metrics your CFO actually cares about when reviewing reporting on paid media campaigns.

A Note On Tracking

Before kicking off any ad campaigns or reporting, make sure that you’ve set up proper conversion tracking on your website to measure key actions in ad and analytics platforms. If you’re not confident in your data measurement approach, you can’t trust the numbers you put in your reports.

Agree On Shared Goals

Before building your first report, you should talk to key stakeholders about what internal revenue goals are and where PPC fits as part of those. For instance, a business may have set an annual goal to grow revenue by 10% or to increase the customer base by 20%.

When considering the metrics you include and how you talk about them, think about how measurement relates to the shared business goals. For instance, you may be able to show not only that Meta had a 10% increase in conversions but that it was the largest contributing channel to the previous month’s growth goal.

It may also be helpful to include a section in your reporting where you highlight overall goals, such as a graph showing total new accounts or revenue vs. planned.

CPA, But Consider The Conversion

Cost Per Acquisition (CPA) is a foundational metric for PPC campaigns. However, one common question faced when presenting performance and including this measure is: “What is a conversion?”

Microconversions, such as form fills and asset downloads, can be helpful for optimization in the right instances, but particularly for higher-level executives, you need to be very clear about what you’re reporting on when sharing a cost tied to a conversion action.

Ideally, CPA in this case should be tied as closely as possible to a customer. While, particularly for long lifecycle businesses, it may not be viable to report on actual customers signed in a monthly PPC report, you may be able to report on sales qualified leads.

In turn, if you have proper CRM tracking to monitor leads through the lifecycle of initial contact to customer, you can include CPAs for customer acquisition over a longer period. For instance, if your average time to final sale is 90 days, show a view of the past 90 days, including total cost and CPAs broken down by marketing qualified leads, sales qualified leads, and final sales.

Further reading: Why Do Budgets Overspend Even With A Target ROAS or CPA? – Ask A PPC

Customer Acquisition Cost

This leads to a more comprehensive metric: Customer Acquisition Cost (CAC), which represents total sales/marketing expenses divided by the number of customers obtained in the same period.

CAC can be shown as an overall metric, as well as attributed at the channel level if your CRM has the ability to measure customers by the source they came from. You should report on trends over time, which will show both how particular mixes of campaigns and channels are performing, as well as pointing to seasonal trends.

Return On Ad Spend

ROAS may be easier to attribute in some types of accounts than others (for instance, ecommerce vs. B2B products with long sales cycles), but can help point to return on investment from PPC campaigns. If revenue values are being properly measured, ROAS can help to answer the question, “How much did we make from this campaign?”

Of course, be ready to provide context and answer questions about how ROAS is being calculated for your brand. For instance, ad platform numbers may or may not include added costs such as shipping and taxes.

As with CPA and CAC, you should report on ROAS at a blended (cross-account and cross-campaign) level, as well as more granularly, where it makes sense to call out specific efforts.

Lifetime Value

Gaining new customers is great, but what if a customer buys one cheap product and never purchases from your brand again? Or if they pay for a one-month subscription but then cancel?

Incorporating LTV into reporting allows you to see not only which channels and campaigns are driving the most customers but which are contributing to the most valuable ones.

For an ecommerce business, you may look at data for how much revenue is generated from items any one person has purchased over time. For a SaaS business, you may look at the total subscription cost over time. For an industrial equipment supplier, you may look at both how much revenue has come from product purchases and if a customer uses your business for ongoing servicing.

Incremental Growth

When testing a new channel, campaign type, or offer, a key justification for funding is proof that it can drive new revenue that would not otherwise have come from existing efforts. Showing new customer counts and revenue amounts that are incremental to your testing efforts will help in maintaining funding for the future.

Relying solely on in-platform tracking can be tricky here, as a new Google campaign may readily take credit for conversions that are also being tracked in and influenced by Meta. While ad platforms are adding their own methodologies for tracking incremental attribution, these are ultimately still siloed at the platform level.

Using a Media Mix Modeling (MMM) tool here can provide a broader view of how adding to or subtracting from your paid media portfolio is impacting revenue. You can also run incrementality tests either by isolating campaigns to specific geographies and comparing against similar regions, or by comparing two periods of time. Looking at the results at the end of the test can show if a new initiative helped to lift customer and revenue growth.

When presenting on incremental performance, be transparent about the testing methodology, but explain concepts in a way that keeps in mind your leadership team’s level of technical knowledge. Lead with results, and include more technical documentation in an appendix.

Anticipate The Why

When including the above measures that are relevant to your client or stakeholder, think proactively about what questions will come from the data. If conversions are down, you’ll likely be asked why that is the case.

You’ll build rapport with executives reviewing the report if you can be transparent about negative performance, but also be able to provide a reasonable explanation why that is the case. For instance, you might compare seasonal performance to last year at the same time and note that business generally dips. Or a technical issue with a form on the website may have interfered with the ability of prospects to contact you.

Ideally, include brief bullet points in the report addressing these potential concerns up front, and be prepared to talk through deeper explanations if asked.

Start Building Better Reports

Think through the metrics surfaced in this article, along with tactics for presenting them to your CFO and other executives. Now think through how you’ve previously been reporting and any pain points you might have had in reaching shared understanding of performance.

Build on a foundation of solid tracking to highlight the numbers that will resonate the most with the individuals accountable for the purse strings. Be open to hearing out questions you’re asked and additional data that stakeholders might request, and continue to tweak your reports to meet your stakeholders where they are.

More Resources:

Featured Image: Natalya Kosarevich/Shutterstock

https://www.searchenginejournal.com/the-ppc-metrics-your-cfo-actually-cares-about-and-how-to-report-them/578813/

This month’s Ask A PPC tackles a very real concern: Search term visibility keeps shrinking on some platforms while other platforms continue to maintain more transparency. Advertisers still need to understand, diagnose, and optimize campaigns even when they do not have full search term signals.

“With search terms increasingly unavailable, what technical signals should advertisers prioritize to diagnose smart bidding?”

We’ll walk through three techniques advertisers can use on any platform, then unpack how Microsoft Advertising’s search term visibility can strengthen optimization across other channels.

Quick disclosure: I work for Microsoft, and I’ve written this as objectively and platform-agnostically as possible.

Technique 1: Use Behavioral Analytics To Understand User Quality

Losing access to individual search terms does not mean you lose access to meaningful insight. You can check traffic segments to see if they deliver value:

• Times: Certain times will be more prone to impulse purchases vs considered investments. If your product/service sees a large amount of non-converting activity during a time that doesn’t align with the conventional customer journey, you can make educated guesses about removing those times.
• Audiences: By including observation audiences, you can get a sense of how much traffic fits into desired demographics. These insights can be used to understand the intent behind the traffic.
• Devices: If you know you do better with phone calls and the lion-share of your traffic is desktop, there may be a need to apply device-specific rules to direct traffic in a more profitable way.
• Locations: Identifying locations with higher CPCs and lower conversion rates is the easiest way to ensure budget is scaling in the right way.

Then, you can start to understand whether those sources deserve more investment.

For example, if you see a high uptick in conversions at 7 a.m. on mobile devices, but they tend to be lower value than the conversions that happen at 4 p.m. on desktop, you might make some educated guesses that the former group were impulse shopping, while the latter have put more thought into engaging with you. The high-volume conversion group might also be on their way to work and not processing as clearly which brand they gave their information to.

That said, avoid snap decisions. Some interactions help start the conversion journey even if they do not complete the conversion action until later. This is why signals from offline conversions and view-through conversions matter so much.

Both Behavioral Analytics And CRM/Shop Data Can Help Fill In Gaps When Search Terms Are Missing

Behavioral analytics tools, including Microsoft Clarity, can help you understand how different humans and AI systems engage based on the times, platforms, and audience cohorts they come from. These insights can show whether your landing page gets in the way.

For example, if you see a high uptick of traffic coming to your site with no conversions, check to see if they’re trying to convert and can’t. Behavioral analytics tools can show you “rage clicks” as well as whether people are confused by page content.

They also can highlight potential CRM integration issues. If you are watching users complete conversion actions multiple times, but not seeing their info in your CRM, you are inviting false positives in the conversion tracking.

Technique 2: Open Yourself Up To Zero-Click Value Actions

The AI era is changing how people discover, evaluate, and act. People may complete valuable actions without clicking to a website. Search term visibility may shrink because of privacy mechanics, but limited visibility into the full query or conversation does not mean no value occurred.

Grounding queries and citation counts can begin to provide useful information. For example, if AI visibility reports show a lot of grounding queries, review whether those queries are contextually relevant to your brand.

For example, if you see that a grounding query is pulling you into financial advice topics and you’re a general business consultant, you may want to adapt your landing pages, search themes, and keywords to focus on “consultant.” While “advisor” is a close variant of “consultant,” financial topics tend to have higher CPCs and won’t be relevant to general business consulting. This is also where term exclusions and message constraints can be helpful, so AI tooling can provide a clearer picture into what product/service you offer.

You may also decide to remove unnecessary JavaScript from pages you want AI systems to engage with to reduce any potential blocks stopping crawlers from accessing the page.

If AI systems cannot engage with a page, we remove ourselves from opportunities to connect with customers before those customers even look for us. AI can only put forward what it can understand, take in, and parse as useful.

Technique 3: Use Offline Conversions And Human Data To Validate Platform Claims

This technique takes more work, but it gives you useful insight into campaign performance, or where AI-powered bidding, struggles when it does not receive clean data. Give bidding systems data that is as accurate and useful as possible while also using directionally correct conversion values when campaigns need to hit certain thresholds.

Conversion values and conversion value rules usually communicate value more effectively than bid adjustments. That matters because when we try to mitigate waste, we should use the technology that aligns with how platforms work rather than forcing newer models to operate through legacy controls.

Bid adjustments and bid caps can force auctions in ways that reflect older campaign management logic. Conversion values and conversion value rules offer a stronger path forward for mitigating waste in modern automated systems.

A Note On Search Term Visibility

This month’s question assumes a Google-first world. Microsoft Advertising takes a different approach: Advertisers can see search terms for traffic that resulted in a click. That transparency matters because advertisers should be able to understand how their budgets get spent.

With transparency comes search terms that invite scrutiny. Some may become useful negatives, while others may challenge biases in how you think about search behavior and how some queries drive valuable performance you may not have expected. People’s search habits change, and in a world where AI plays a larger role, bot-type queries will not always equal waste. Sometimes they represent genuine, useful queries.

One helpful way to explore this is to review the AI crawler bot report in Microsoft Clarity and look at the ratio of AI crawler bots. That context can help you understand whether AI engagement connects to meaningful behavior.

3 Ways To Use Microsoft Search Term Visibility Across Other Channels

1. Identify Winners

Because Microsoft Advertising shows search terms that result in clicks, you gain more transparency into what deserves focus. That insight can inform better search themes for Performance Max campaigns, stronger keyword targets for traditional search campaigns, and content ideas worth building around.

Do note that match types behave the same between Microsoft and Google.

2. Find Potential Negatives

If a query idea clearly does not make sense on Microsoft Advertising, there is a good chance it also does not make sense on Google or other keyword-targeted platforms. Microsoft requires negative keywords to use phrase or exact match, but you can still identify root words and apply them as negatives in the match types available on other platforms.

This added confidence can make Microsoft Advertising useful as a source of search terms that inform broader account hygiene.

3. Pair Behavioral Analytics With Conversion Tracking

Search term visibility helps you identify winners and losers, but the real insight and optimization happens when you understand what users do after they complete those searches. If a query brings people to your site but conversions do not register, you may have a conversion tracking issue rather than a query quality issue.

The reverse can also happen, if conversions increase but the queries tied to those conversions do not look quite right. Data exclusions can help in both Google and Microsoft when you need to account for tracking or data quality issues.

Behavioral analytics paired with search term visibility gives you one of the strongest ways to understand why people search the way they search and what influences them after they land on your website

Final Takeaway

Search term visibility may be shrinking on some channels, but it still exists on others. Rather than assuming visibility has disappeared entirely, advertisers can adapt their perspective and use multiple channels to capture different forms of insight.

Google and Microsoft do reach unique users, so the data will not map perfectly one-to-one. Still, if a search does not make sense for your brand and you can see it on one network even when you cannot see it on another, you gain value by identifying that idea once instead of paying for it repeatedly.

More Resources:

Featured Image: Paulo Bobita/Search Engine Journal

https://www.searchenginejournal.com/ask-a-ppc-how-to-optimize-ppc-accounts-with-less-search-term-visibility/581131/

Google Ads is expanding its Search campaigns for Travel beta to two additional verticals: Things to Do and Events.

Google announced the update in a post on X and LinkedIn on July 8, 2026. Advertisers selling attractions, tours, and event tickets can now access the campaign type through an open beta, although availability remains limited.

The expansion gives eligible advertisers another campaign option to test alongside existing Search ands Performance Max campaigns.

What’s Changing With Search Campaigns For Travel

Search campaigns for Travel is a Google Ads campaign type designed for travel-related advertisers. It first appeared as Google expanded AI-powered campaign types across Travel and Shopping earlier this year.

With this update, the beta now extends beyond traditional travel categories to include Things to Do and Events. That means advertisers promoting attractions, guided tours, and event tickets may now be eligible to use the campaign type.

The announcement came as part of a five-post thread. At the time of writing, Google has not shared complete details around eligibility, supported features, or geographic availability.

Why This Matters

Attractions, tours, and event tickets share many of the same characteristics as hotel or airline bookings. Availability changes frequently, pricing can fluctuate, and purchase decisions are often tied to specific dates or locations. Those are all areas where Google’s newer campaign types have increasingly relied on automation to determine which searches are most likely to convert.

Until now, advertisers in these verticals have generally relied on standard Search campaigns or Performance Max. Expanding the Travel campaign type suggests Google sees these businesses as a natural fit for a more specialized campaign format.

The update also aligns with Google’s broader push toward AI-driven campaign management. Over the past year, the company has introduced AI Max across additional campaign types while continuing to consolidate older campaign formats.

While Google hasn’t explained why it selected these verticals, they fit naturally alongside other travel-related advertisers already using the campaign type.

What Advertisers Should Do

If you’re eligible for the beta, treat it as a controlled test rather than a replacement for your existing campaigns.

Review your current Search and Performance Max performance, set aside a limited testing budget, and compare booking or ticket sales against your existing campaign mix. Since Google has not released complete feature details, it’s also worth setting expectations internally that functionality may continue to evolve throughout the beta.

What’s Still Unknown

Google has not yet confirmed which bidding strategies, assets, reporting capabilities, or feed requirements will be available for the Things to Do and Events verticals. It also remains unclear how these campaigns will interact with existing AI Max for Travel functionality.

We’ll update this article as Google shares additional details about eligibility, features, and availability.

Featured image: Master1305 / Shutterstock

https://www.searchenginejournal.com/google-search-campaigns-travel-things-to-do-events-beta/581816/

Google is clarifying its Smart Bidding update after advertisers questioned how budget-limited campaigns will behave beginning August 17.

The original announcement around Smart Bidding changes was June 22. The update essentially changes how Target CPA and Target ROAS campaigns behave when they’re limited by budget.

Today, many budget-limited campaigns outperform their bidding targets. Smart Bidding often enters only the auctions most likely to convert efficiently, producing stronger-than-expected CPA or ROAS.

Google says that wasn’t the intended behavior.

Instead, Smart Bidding will optimize more closely toward the Target CPA or Target ROAS advertisers actually set. Campaigns that currently outperform those targets may move closer to them after the update.

The announcement immediately raised questions across the PPC industry. Advertisers wanted to know why Google would reduce efficiency in campaigns that were already exceeding expectations.

Google’s follow-up comments answer many of those questions. They also explain why the company believes the change will make campaign scaling more predictable.

What’s Changing On August 17?

The update affects campaigns using Target CPA or Target ROAS that are limited by budget.

Historically, those campaigns often outperformed their bidding targets. A campaign with a $50 Target CPA, for example, might consistently generate conversions at $35.

Beginning August 17, Google will optimize those campaigns more closely toward the Target CPA or Target ROAS advertisers set. The company says this should create more predictable performance when advertisers adjust campaign budgets.

Google also clarified several points after announcing the update:

• Budgets will not automatically increase
• Google won’t automatically change Target CPA or Target ROAS settings
• Advertisers who want to maintain current performance may need to lower their bidding targets before the rollout
• Google is rolling out account notifications and a Bid Target Adjustment Tool to identify affected campaigns

Those clarifications addressed some of the initial confusion. They also sparked a broader discussion about how the update could affect campaign performance in practice.

The Biggest Concern: Is Google Becoming Less Efficient?

One question surfaced repeatedly as advertisers discussed the update: Is Google making Smart Bidding less efficient?

Kirk Williams summed up that concern in a LinkedIn post.

He wrote:

…How and why will the system stop trying to be as efficient as possible… Does that mean smart bidding when limited by budget will no longer be trying to find better auctions?… So does that mean they’re building the system to literally choose to be dumber when limited by budget?

Williams questioned why Google would move campaigns closer to their stated targets if Smart Bidding could already deliver stronger performance.

Mike Ryan offered one of the most detailed explanations in the comments.

Ryan argued that Google isn’t making Smart Bidding less intelligent. Instead, he believes the system has become too conservative in budget-limited campaigns.

According to Ryan, Smart Bidding has favored exploitation over exploration. Rather than entering more auctions that still satisfy an advertiser’s target, the system has focused on the safest opportunities. That produced stronger-than-expected efficiency. It also meant campaigns didn’t consistently optimize toward the Target CPA or Target ROAS advertisers actually set.

Ryan believes the updated system will follow those bidding targets more closely. That may reduce the overperformance many advertisers have seen in budget-limited campaigns, but it also aligns with Google’s stated goal of making bidding targets behave more predictably.

Predictable Scaling vs. Peak Efficiency

Aaron Levy focused on a different part of the update: campaign scaling.

He described a campaign with an $8 CPA and a $12 Target CPA. If an advertiser doubled the budget today, the CPA might unexpectedly climb to $16 instead of remaining near the target.

Levy believes the update should make that behavior more predictable. Rather than introducing large swings in efficiency, Smart Bidding should continue optimizing toward the advertiser’s Target CPA as budgets change.

Kirk Williams questioned whether that tradeoff benefits advertisers. If Smart Bidding can already outperform a target, he argued, some advertisers may prefer that extra efficiency over more predictable budget increases.

Google has consistently framed the update around predictability. They say campaigns should optimize toward the targets advertisers actually set, making budget changes easier to manage and forecast.

Whether advertisers agree with that tradeoff will likely depend on how their campaigns perform after the rollout.

Google Clarifies Several Misconceptions

Google Ads Liaison Ginny Marvin responded directly to several concerns advertisers raised after the announcement.

One of the biggest misconceptions was that Google was encouraging advertisers to simply spend more money.

Responding to Barry Schwartz, Marvin wrote:

To be clear, this won’t result in campaign spend changes… Our guidance for those with budget-constrained campaigns currently over-performing on their target is to ensure the targets are in line with your goals.

She also emphasized that advertisers will only spend more if they choose to raise their campaign budgets. The update itself does not change campaign budgets or automatically adjust bidding targets.

Jack Carr raised a similar concern, arguing that budget constraints have historically acted as an efficiency lever and that Google’s recommendation effectively removes that advantage.

Marvin responded with a longer explanation:

Our advice is not to ‘let the system spend more money’… this change won’t result in spend changes on a campaign already budget constrained.

She also explained why Google is making the change.

Performance has often fluctuated unexpectedly… especially with budget changes. That’s not been a great experience for advertisers & made it challenging to scale campaigns with confidence.

According to Google, the backend update will make Smart Bidding optimize more consistently toward the Target CPA or Target ROAS advertisers actually set, even when campaigns are limited by budget.

Kristen Kelleher questioned whether the change would simply push campaigns into lower-quality traffic.

Marvin pushed back on that assumption as well.

The system sets bids to find as many conversions as possible at the ROAS/CPA target you set… With this update, advertisers can also expect this same behavior in budget-constrained campaigns with targets.

She added that advertisers who want to maintain today’s stronger-than-target performance should consider updating their Target CPA or Target ROAS before the rollout.

Google’s position has remained consistent throughout the discussion. The company says the update changes how closely Smart Bidding follows bidding targets. It doesn’t change campaign budgets or automatically modify campaign settings.

What This Means For Advertisers

Not every advertiser will need to make changes before August 17.

Campaigns already hitting their intended Target CPA or Target ROAS may continue operating much as they do today. The biggest impact will likely fall on budget-limited campaigns that have consistently outperformed their bidding targets.

For example, if a campaign has averaged a $20 CPA against a $35 Target CPA, Google says advertisers should consider whether $20 is now the more appropriate target. Leaving the original target unchanged could allow performance to move closer to $35 after the update.

Before the rollout, review any budget-limited campaigns that consistently outperform their Target CPA or Target ROAS. Compare current performance against your configured targets and decide whether those targets still reflect your business goals.

The update also changes how advertisers should think about bidding controls. Many advertisers have treated limited budgets as an efficiency lever because campaigns often outperformed their targets. Google has made it clear that budgets and bidding targets serve different purposes. Budgets control spend. Target CPA and Target ROAS control efficiency.

If Google’s explanation plays out as expected, advertisers who keep bidding targets aligned with actual performance should see fewer surprises when adjusting campaign budgets after August 17.

What Happens Next

Google has explained how Smart Bidding should behave after August 17. The remaining question is how closely those expectations match real-world campaign performance.

Advertisers with budget-limited Target CPA or Target ROAS campaigns will likely be watching those accounts closely after the rollout. Campaigns that have consistently outperformed their bidding targets may provide the clearest indication of how much the update changes day-to-day performance.

Google has also encouraged advertisers to review bidding targets before the rollout if current performance already aligns with their business goals. As more accounts transition to the updated bidding behavior, advertisers should have a better understanding of how the change affects campaign efficiency and budget management in practice.

Featured image: Roman Samborskyi / Shutterstock

https://www.searchenginejournal.com/google-clarifies-smart-bidding-update-after-advertiser-concerns/581804/

Google is testing a new Search ads label that could give certain advertisers a visible endorsement directly within search results.

In a LinkedIn post, Google Ads Liaison Ginny Marvin announced a limited U.S. experiment that adds a “Strongest match” or “Strong match” label to select Search ads.

According to Marvin, the labels are intended to help users quickly identify the most relevant information for their query while helping advertisers connect with high-intent audiences.

The experiment is currently rolling out to a small percentage of users in the United States.

Marvin said the designation relies on existing ad quality and relevance signals that Google already uses to evaluate Search ads.

While the announcement itself was relatively brief, it immediately sparked questions from advertisers about how the label is determined, whether it could influence click behavior, and what it might signal about the future direction of Search.

Google Hasn’t Explained What Qualifies As A “Strongest Match”

Google’s announcement answered what the label is intended to do, but not how advertisers qualify for it.

According to Marvin, the designation is based on existing quality and relevance signals. Beyond that, Google has not shared any details about how the label is determined.

As a result, advertisers still don’t know:

• Which signals are used to determine the label
• How those signals are weighted
• Whether the designation is based on the query, keyword, ad, landing page, or a combination of factors
• Whether multiple advertisers can receive the label in the same auction
• Whether the label is tied to ad position

The lack of detail quickly became one of the main discussion points following the announcement.

Several advertisers questioned whether the designation reflects the same systems Google already uses to evaluate ad relevance or whether the experiment introduces an additional layer of evaluation.

Others questioned whether bid strength plays any role.

Google’s description suggests the label is intended to reflect relevance rather than spend. However, the company has not explained how those determinations are made.

Until Google shares more information, advertisers are left with a label that appears meaningful but lacks a clear definition.

Advertisers Are Asking For More Transparency

Advertisers quickly focused on a different question: how Google determines which ads receive the label.

Several commenters asked whether “Strongest match” reflects the same relevance systems Google already uses or whether additional factors are involved.

Terry Hogan questioned whether the designation is truly based on relevance or whether bid strength contributes to the decision.

Kristen Kelleher asked a popular question, based on the amount of likes she got:

What components make up the scoring underneath the match label? Is this based on the keyword based quality score, ad relevance, landing page exp or is it only based on the ad itself?

So far, Google has not provided additional detail.

Other comments asked measurement questions around the label testing.

Craig Graham asked: “Are there plans for any kind of advertiser-side reporting for this if the experiment rolls out more broadly?”

That visibility could become important if the designation influences click behavior. Advertisers will likely want to know when their ads receive the label and whether it impacts performance.

Questions also accumulated in Marvin’s LinkedIn post about how the label will appear within search results.

Bernt Muurling asked whether the strongest match will always be the first result shown.

If the label only appears on the top-ranked ad, it reinforces Google’s existing ranking decisions. If it can appear elsewhere on the page, it introduces a new signal that users may evaluate alongside ad position.

Justin Windschitl pointed to what may be the biggest challenge for the experiment:

Interested what the criteria are for labeling “match types” and if there can be flaws with the labeling, hurting businesses. On the flip side, if it’s buttoned up, it could be very beneficial for filtering best matches and more effective ad spend!

If the designation is occasionally inaccurate, advertisers may question whether Google is effectively endorsing one business over another.

Could This Become A Public Relevance Signal?

The experiment stands out because it could make Google’s assessment of relevance visible to users.

Advertisers have always known that Google evaluates factors such as ad relevance, landing page experience, expected click-through rate, and other quality signals when determining which ads appear and where they rank. Those evaluations largely happen behind the scenes.

A “Strongest match” label would move part of Google’s relevance evaluation from Google Ads into the user experience itself.

That may seem like a small change, but it introduces a new dynamic into the search experience.

Users already see ad position. A visible label gives them another signal to evaluate.

That is one reason several advertisers immediately questioned how the designation is determined and whether it could influence click behavior.

It also raises questions about whether the label becomes a competitive advantage of its own.

If users begin viewing the designation as a recommendation from Google, advertisers who receive the label could benefit beyond the visibility that comes with ranking well in the auction.

Whether that happens will likely depend on how often the label appears and whether users respond to it.

For now, Google has positioned the experiment as a way to help users identify relevant information more quickly. The broader question is whether advertisers and users eventually view the designation as a relevance signal, a recommendation, or something in between.

Why Google May Be Testing This Now

While Google hasn’t shared the reasoning behind the experiment, the test arrives as Search continues to evolve beyond a traditional list of links.

Google already makes relevance decisions every time an auction takes place. The difference is that those decisions typically remain behind the scenes.

This experiment tests what happens when part of that evaluation becomes visible to users.

Google already makes relevance decisions every time an auction takes place. This experiment tests whether those assessments should be visible to users.

Like many Search tests, the feature may never move beyond experimentation. If it does, it could mark another step toward Google making more of its relevance decisions visible within the Search experience itself.

What This Means For Advertisers

At this point, advertisers should view the label as an experiment rather than a new optimization opportunity.

Google hasn’t introduced any controls, reporting, or guidance around how advertisers qualify for the designation.

For now, the announcement is getting a lot of attention because it introduces a new user-facing signal in Search ads. Whether that signal influences click behavior or campaign performance is unclear until Google provides more information.

We’ll continue watching the rollout and update this story if Google shares additional details about qualification criteria, reporting, or broader availability.

Featured image: Kues / Shutterstock, Phone image courtesy of Google 

https://www.searchenginejournal.com/google-strongest-match-search-ad-labels-test/580378/

Microsoft announced a wave of AI updates this week, and most of the coverage will likely focus on the individual launches. New targeting options, diagnostics, commerce tools, Copilot enhancements, and campaign features will naturally get the headlines.

What stood out to me was the broader vision behind them.

Microsoft is not just talking about better ads. They’re talking about a different internet, where businesses need to be relevant to both people and AI systems helping shape decisions.

In their announcement this week, AI agents are becoming the fastest-growing audience. The company says automated traffic is growing 8x faster than human traffic, AI-driven sessions nearly tripled in 2025, and agentic browser traffic is up roughly 8,000% year over year. Those visitors don’t browse the way people do. They evaluate, select, and act. If a brand’s data is weak, incomplete, or untrusted, they move on.

That changes what modern performance marketing may require. Visibility inside AI answers, stronger product data, better measurement, faster diagnostics, audience precision, and clearer control over automation all start to matter more in that environment.

Google is pushing many of these same themes in its own way, especially around product feeds, automation, and AI-assisted search experiences. But Microsoft’s recent announcements offer a distinct perspective on where advertiser value may come from as discovery and buying behavior continue to shift.

Because underneath the product updates is a bigger question for PPC teams: how do you compete when the next valuable audience may not always be human?

Microsoft Is Selling A Different AI Future

Most platform announcements focus on what a new feature does. Microsoft spent more time explaining why advertiser behavior may need to change.

Their framework centered on three parallel realities:

• People still searching on their own (the Human web)
• People using AI to compare options (the LLM web)
• AI systems taking action on behalf of users (the Agentic web)

What they’re saying beyond these parallels is that customer journeys are less linear and are finally being recognized as such.

For years, many PPC teams optimized around the click because the click was the clearest measurable moment. Someone searched, clicked, landed, and converted. That model still matters, but it no longer explains every influence that leads to a sale.

If an AI assistant narrows the shortlist before a search happens, the brand has already won or lost ground. If a shopping assistant compares shipping speed, loyalty perks, and product availability in seconds, the decision may be shaped before the landing page visit. If an agent eventually completes more transactions directly, structured data and transaction readiness become part of media performance.

That is why this announcement deserves more attention than a standard product roundup. Microsoft is describing a future where paid media performance depends on more than media settings.

Why This Matters For PPC Managers

Many advertisers are still operating with a channel mindset. Additionally, these channels likely sit within different teams in an organization (Search, SEO, CRM data, Analytics, etc.)

That separation becomes harder to sustain and sustains friction if buying journeys are influenced by connected systems rather than isolated clicks.

This is where the role of PPC teams can start to expand and/or evolve.

Strong practitioners still need campaign skills – that’s never going to change. They also need to spot when the real constraint sits outside the account, bring the right teams together, and push improvements that create better inputs for the platform.

Having these skills become your advantage as a PPC marketer down the road when campaign management and optimization become automated, but that’s a subject for another day.

How Microsoft’s AI Vision Takes A Different Approach

Google remains the largest force in paid search. It also continues to launch strong AI updates across bidding, creative, search experiences, and campaign management. This is not about Google falling behind.

What stood out to me was where Microsoft placed its focus.

A lot of AI discussion still centers on better ads, faster automation, or the next big interface. Microsoft spent more time talking about how buying behavior is changing and what advertisers may need to do differently.

Their view suggests the audience is no longer only the customer.

It can also be the AI system helping compare products, narrow options, recommend brands, or complete tasks on someone’s behalf.

That is where I think Microsoft’s message becomes more interesting than a standard product launch. They are pushing marketers to think beyond clicks and impressions and pay closer attention to how decisions are being shaped before a traditional ad interaction ever happens.

If that shift continues, many teams will realize they were optimizing the final step of the journey while missing the earlier moments that influenced the outcome.

AI Visibility In Microsoft Clarity Is Their Competitive Advantage

If I had to choose the most useful announcement for marketers, I would put AI Visibility in Microsoft Clarity near the top of the list.

Why? Because it speaks to a blind spot many businesses may already have.

A lot of performance reporting has been built around clicks, visits, and conversions that happen in trackable sessions. As AI tools start summarizing answers, citing brands, and influencing decisions before someone reaches a site, that model becomes less complete.

Some brands may already be winning attention in those moments. Others may be losing ground. Many likely cannot see either clearly today.

That is what makes this update so interesting.

Microsoft is giving businesses a way to understand how AI systems discover, cite, and surface their content. You do not need to advertise on Microsoft for that to matter. SEO teams, content teams, e-commerce leaders, and paid media teams all have a reason to care about how their brand appears in AI-driven experiences.

My bigger view is that tools like this will eventually become normal. Right now, Microsoft is one of the first major platforms speaking clearly about the problem and trying to give marketers something actionable to measure.

Audience Generation Could Be More Useful Than It Sounds

Audience Generation may sound like another setup feature, but I think it deserves more attention than that.

Microsoft describes it as an AI-powered audience assistant where advertisers can describe an ideal customer in natural language and receive recommended targeting settings. That can include demographics, locations, in-market signals, and dynamically generated audiences.

What interests me most is how this could improve strategic thinking, not just save time during campaign creation.

Many advertisers already know their obvious audience. But strong audience strategy often depends on ideas a team does not think to test.

For example, an advertiser may know they want “young professionals interested in fitness.” They may not think about adjacent areas where those consumers spend time, neighborhoods with stronger purchase intent, seasonal behaviors tied to events, or combinations of signals that reveal higher-value segments.

That is where a tool like this can become valuable.

Used thoughtfully, it can help marketers find new angles to test, challenge stale audience assumptions, and build stronger targeting plans than they may have created manually.

How Microsoft Is Turning That AI Vision Into Practical Tools

A broader vision only matters if it shows up in tools advertisers can actually use.

That is where Microsoft’s recent updates become more interesting.

Explainability Is Part Of The Product

One of the more useful launches was performance shift root-cause analysis inside the Microsoft Advertising Platform.

When results move sharply, most marketers don’t need another dashboard. They need to know what changed and clear “why”. Without the why, marketers can’t identify how to improve campaigns or pivot strategy.

Getting to that answer faster can save hours of manual work. It can also help teams act with more confidence instead of making reactive changes.

Google is thinking in a similar direction. Its Ads Advisor experience is also designed to help advertisers ask questions, surface insights, and understand account performance faster.

The opportunity for marketers is not choosing one assistant over another. It is using these tools to reduce analysis time and spend more time on better decisions.

Guardrails Still Matter

Microsoft also emphasized brand exclusions, term exclusions, and messaging constraints tied to AI-powered products like AI Max.

It mimics where Google has gone with their AI Max direction and broader advertiser controls across automated products.

That matters because many advertisers are not operating in a world where they can simply turn everything on and hope for the best. Legal review, brand standards, regulated categories, stakeholder approvals, and internal risk tolerance all shape how new tools get adopted.

That is why control features deserve more attention than they usually get. They are often what make adoption possible in the first place.

Product Data Continues To Be Bigger Than Shopping Campaigns

One of the clearest signals from both Microsoft and Google right now is that product data is starting to matter far beyond traditional Shopping campaigns.

Clean titles, accurate availability, pricing consistency, strong attributes, shipping details, and trustworthy structured data can now influence how products are surfaced across search experiences, AI recommendations, comparison journeys, and agent-assisted buying flows.

That is exactly why I wrote last week that Google’s product feed strategy points to the future of retail discovery. Product data is no longer just supporting Shopping campaigns. It is becoming part of how platforms understand inventory, evaluate relevance, and decide what gets shown in newer discovery environments.

Microsoft’s recent announcements point to the same shift through a different lens. Google is emphasizing Merchant Center and commerce surfaces. Microsoft is emphasizing agentic commerce, Copilot experiences, and AI visibility.

Feed health is becoming a growth issue, not just an operations issue – something that both Google and Microsoft are telling the industry.

What Advertisers Are Saying

Navah Hopkins, the Microsoft Ads Liaison, took to LinkedIn to share her thoughts on these updates. She highlighted diagnostics, clearer explanations, and the idea that marketers should decide what they own, what they share with AI, and what they delegate. That framing reflects how adoption actually happens inside businesses. Teams rarely hand over everything at once. They test where trust has been earned.

She also pointed to Microsoft Clarity as an increasingly valuable source of behavioral insight as AI-driven experiences grow, which I completely agree with.

Mark Creusen added his thoughts to her post:

The owning and sharing bit always pops for me. Way easier to chill about AI when you just mark out what’s “yours” and what you’re happy to throw to the bots instead of trying to wrangle it all. Otherwise teams just end up dragging each other to burnout mountain.

Frederick Vallaeys focused on another risk: invisibility. In his write-up after Microsoft’s partner event, he argued that many businesses may be unprepared for AI-driven discovery and cited Microsoft’s discussion around sites still blocking AI agents through robots.txt. He also highlighted strong early commerce statistics shared at the event, including higher purchase likelihood after Copilot interactions and conversion lifts tied to Brand Agents.

What This Means For Your Campaigns

The bigger lesson from Microsoft’s updates is that campaign performance may increasingly be shaped by factors that sit outside the traditional campaign build. That includes how your products are structured, how clean your measurement setup is, how well your audiences reflect real buying behavior, and whether your brand is visible in AI-assisted discovery moments before a search click ever happens.

Below are a few areas worth reviewing that can help shape a broader operating mindset:

• Product data quality: If your feeds are incomplete, outdated, or inconsistent, the risk may extend beyond Shopping campaigns. Product titles, availability, pricing, shipping details, and attributes can influence how platforms understand and surface your inventory across emerging discovery experiences.
• Measurement health: Now is a good time to audit conversion actions, tag coverage, offline imports, and attribution settings. As journeys become less direct, weak measurement creates larger blind spots and poorer optimization inputs.
• Audience strategy: Many accounts still rely on narrow audience assumptions or static segments. Revisit whether your current targeting reflects how customers actually behave today. There may be untapped value in layered signals, geographic nuance, seasonal behaviors, or adjacent intent patterns.
• Search term coverage: If AI tools help users refine decisions earlier, the searches that remain may become more specific, comparative, or action-oriented. Review whether your keyword strategy and ad copy are aligned to that shift in intent.
• Platform diversification: Secondary channels can become valuable learning environments before they become major budget lines. Even modest investment in Microsoft Ads can help teams test new audience models, automation controls, and reporting approaches that may influence broader strategy later.

Looking Ahead

Microsoft’s biggest advantage may not be trying to out-Google Google.

It may be continuing to invest where it already has a credible edge: advertiser workflow tools, B2B audience intelligence through LinkedIn, clearer visibility into AI-driven discovery, and commerce experiences built for a world where assistants help shape decisions.

That is a different lane, and it could be a valuable one for marketers if Microsoft keeps executing.

The next year will likely tell us whether these announcements were a strong signal of where the platform is headed or simply another round of product updates.

Which of Microsoft’s new AI features, if any, would you seriously consider testing in your own campaigns?

More Resources:

Featured Image: Juan Roballo/Shutterstock

https://www.searchenginejournal.com/why-microsofts-ai-ad-strategy-deserves-more-attention-from-ppc-managers/572874/

For years, many advertisers treated product feeds as a channel task tied mainly to Shopping campaigns.

If you were running Shopping ads, feed optimization likely got attention. If you weren’t, it often slipped behind priorities for the PPC campaigns you were running.

Now, that approach is starting to show its age.

Google’s recent Ads Decoded podcast episode suggests that mindset may need to change. Product data was discussed in connection with free listings, AI-powered search experiences, YouTube formats, Lens, virtual try-on, and newer e-commerce surfaces still evolving.

That reflects a much broader role than many advertisers have historically assigned to their feed.

Google appears to be positioning product data as a larger part of how products are discovered across its platforms, not just how Shopping campaigns perform.

Advertisers who still view Merchant Center as a side task may be underestimating how much visibility now starts with product data.

The more interesting question is what that shift tells us about where Google wants retail advertising to go next.

Merchant Center Is Starting To Look Like Retail Infrastructure

What stood out most in the podcast was how broadly Google described the role of Merchant Center data.

Nadja Bissinger, General Product Manager of Retail on YouTube, described Merchant Center feeds as the “backbone that powers organic and ads experiences,” adding that merchants should submit the most robust product data possible to increase discoverability.

That is a wider role than many advertisers have traditionally associated with Merchant Center.

Google said in a 2025 retail insights piece that people shop across Google more than 1 billion times per day. It also highlighted Search, YouTube, Maps, and visual discovery as key parts of modern shopping journeys. That helps explain why reusable product data is becoming more valuable than channel-specific assets alone.

Google also said Google Lens now sees more than 20 billion visual searches per month, and 1 in 4 Lens searches carry commercial intent. That is another signal that structured product data is becoming more important outside traditional Shopping ads.

For years, many brands viewed Merchant Center as a necessary setup for Shopping campaigns. Google now appears to be positioning it as a core input for how products are surfaced across its platforms.

That should change how feed work is prioritized internally.

Feed optimization is no longer just a PPC responsibility. It can influence:

• Organic visibility
• Merchandising strategy
• Creative presentation
• Promotions
• How products appear in newer AI-led experiences.

For larger organizations, that may require closer coordination between paid media, SEO, e-commerce, merchandising, and product teams.

For smaller brands, it may be as simple as giving feed quality the same level of attention already given to ad copy, landing pages, and campaign structure.

Many advertisers still treat feed work as cleanup work. That mindset is becoming expensive as product data plays a larger role in who gets seen across Google.

Why Is Google Pushing Product Data So Hard Right Now?

Google’s direction here makes sense when you look at where its retail products are heading.

The company wants more e-commerce activity to happen across Search, YouTube, Maps, AI experiences, and future agentic tools. To support that expansion, it needs merchant data that is accurate, structured, and easy to reuse across different surfaces (as Google refers to them as).

Google has financial reasons to expand e-commerce activity beyond traditional ad clicks. In their 2025 Q4 Earnings Release, they reported a 17% growth in Google Search, and YouTube revenue across ads and subscriptions over $60 billion.

A strong feed helps Google understand:

• What a product is
• Who it is for
• What makes it different
• Where it is available
• What it costs
• How the product should be presented

That matters even more as retail experiences, paid or organic, become more visual, more personalized, and more automated.

Traditional search ads leaned heavily on keywords, headlines, and landing pages. Newer e-commerce formats can also depend on product images, attributes, ratings, promotions, availability, shipping details, and other feed inputs that help match products to user intent.

Better data can lead to better experiences for users. It can also create more places where merchants can appear across Google’s properties.

Google is building more e-commerce surfaces, and product data is the fuel behind them. Advertisers who ignore that may keep optimizing campaigns while missing the larger shift happening around them.

Is Google Prepping For A More Strategic Shift?

From my perspective, there is a larger strategic shift behind Google’s product data push.

I don’t see this as a routine push for better feeds or cleaner campaign inputs. I see Google working to become more of a growth engine for advertisers, with a role that reaches beyond media buying and campaign delivery.

That expansion is moving into areas that shape business performance, including merchandising, product discovery, pricing visibility, local commerce, measurement, and newer purchase-ready experiences.

Google is not only trying to improve how ads run. It appears to be building a deeper position in how products are surfaced, how demand is created, how buying decisions are influenced, and how performance is measured.

My view is that the more Google becomes embedded across those moments, the more connected it becomes to broader business growth rather than media performance alone.

Why Many Advertisers Are Still Measuring Feed Value Wrong

One reason feed optimization still gets deprioritized is simple: many teams are using an outdated scorecard.

Google cited a 33% conversion uplift for advertisers using Demand Gen with product feeds during the podcast discussion. Even if results vary by account, it is another sign that feed quality is being tied to campaign types beyond classic Shopping ads.

If the main question is whether Shopping ROAS improved last week, it becomes easy to undervalue the broader impact of stronger product data.

That measurement approach came from a time when feeds were more closely tied to Shopping campaigns. Google is now using the same data across a much wider set of retail experiences, including discovery surfaces, visual placements, AI-led results, and other formats that do not fit neatly into one campaign report.

That creates a gap between where feed work adds value and where many teams are looking for it.

A stronger title may improve discoverability. Better imagery can increase engagement in visual placements. Accurate pricing and promotions can improve click appeal. Richer attributes can help Google better understand relevance. Availability data can support local and omnichannel visibility.

Those gains may show up across multiple touchpoints, assisted paths, and blended performance trends rather than one Shopping dashboard.

That is why some advertisers continue to underinvest in feed quality. The value is there, but their reporting model was built for an earlier version of Google.

As Google expands where products can appear, feed optimization deserves to be measured more like a visibility and growth lever, not just a Shopping maintenance task.

One of the more important quotes from the podcast came from Ginny Marvin, Google Ads Liaison, as she wrapped up the episode:

Merchants with the most structured, high quality data foundations will be positioned to win.

Winning will not come from uploading a feed once and forgetting about it for months at a time.

It comes from treating product data as an ongoing optimization just like your existing campaigns.

What Google’s AI Max Focus May Be Signaling About Search

One of the more revealing parts of the podcast was how often Search strategy was discussed through the lens of AI Max for Search, while traditional standard Search campaigns were barely mentioned.

During the episode, Firas Yaghi, Global Product Lead for Retail Solutions, talked about how advertisers should be thinking about different campaign types:

I think the role of each campaign really depends on your high level objective. Whether you’re prioritizing cross channel efficiency, granular control or hybrid approach that balances top line sales with OKRs.

He mentioned a lot around Performance Max, Demand Gen, with a little bit of AI Max for Search.

I would avoid treating that as proof that standard Search is going away. There is still clear value in campaigns built around tighter search control, brand protection, and proven high-intent terms.

At the same time, it’s hard to ignore the direction of Google’s messaging.

When Google talks about growth, expansion, and newer retail opportunities, the conversation increasingly centers on AI-assisted campaign types. We have seen similar signals elsewhere, including Google’s announcement that Dynamic Search Ads will upgrade into AI Max for Search and that AI Max represents the next step for search expansion.

My read is that standard Search remains important, but it is no longer the only story Google wants advertisers thinking about.

The company appears to be steering incremental growth toward campaign types that rely on broader matching, stronger inputs, automation, and first-party signals.

I think that Search strategies built around legacy structures will become less competitive over time. I’m not confident enough yet to say that standard Search campaigns will go away completely in the near future, but the increasing signals around keyword-less technology has me thinking more changes for Search campaigns are bound to happen.

What This Means For Your Campaigns

The bigger risk for PPC managers is assuming the teams responsible for merchandising or product data already understand how much feed quality can affect campaign performance.

In many organizations, merchandising, e-commerce, product, or development teams control what goes into Merchant Center. Their priorities may be centered on inventory, pricing, site operations, or category management, not media efficiency or visibility across Google.

That is where PPC managers can add real value.

If product information is influencing how products appear across paid, organic, and AI-led surfaces, someone needs to connect those decisions to marketing outcomes. PPC managers are often in the best position to do that because they can see changes in impressions, traffic quality, conversion trends, and missed opportunities firsthand.

That may mean bringing examples into weekly meetings, showing where missing attributes are limiting reach, flagging weak imagery, highlighting pricing issues, or sharing results from tests that improved performance.

You may not own the feed, but you can help the business understand why it deserves greater priority and where better inputs can improve campaign results.

Put More Focus On Inputs That Can Scale Performance

Many teams spend valuable time on small bid changes, minor budget moves, or endless rounds of creative tweaks while core product data remains incomplete or outdated.

Those tasks still have value, but the upside is often limited when the underlying product information is weak.

If titles are thin, images are poor, attributes are missing, or product details are outdated, fixing those gaps may create more value than another round of minor account adjustments.

Add Feed Health To Regular Performance Reviews

Most reporting cycles focus on spend, ROAS, CPA, and conversion volume.

Those metrics are important, but they do not always show whether product data is helping or limiting visibility.

Feed health deserves a place in regular reviews. Look at disapprovals, missing fields, image quality, pricing accuracy, promotional coverage, and product-level gaps with the same discipline used for media metrics.

Broaden How You Test For Growth

Many retail accounts still treat Search, Shopping, YouTube, and newer campaign types as separate lanes.

Google’s recent direction suggests those lines are becoming less rigid.

Growth testing should include where products can appear across newer surfaces, how feeds support Demand Gen and AI-led placements, and whether stronger product data can unlock reach that existing campaigns are not capturing today.

Treat Better Product Data As A Competitive Advantage

Some advertisers will wait until these newer placements are fully mature before investing seriously in feed quality.

While that delay may be costly for them, your proactiveness can pay off significantly.

What PPC Professionals Are Saying

Recent LinkedIn discussions suggest many practitioners are viewing feed quality as a larger performance lever.

Comments from the podcast episode have been overall positive and has many marketers agreeing that feed management needs to be routine.

Zhao Hanbo commented:

Really interesting to see how something that used to feel mostly like ad ops plumbing is now becoming core infra for AI commerce.

Sophie Westall had similar sentiments, stating that “feed quality is quickly becoming a core part of overall media strategy, not just a hygiene task.”

In a recent LinkedIn post, Menachem Ani said that by fixing a product feed, “campaigns start working harder without touching a single bid.”

More marketers appear to be focusing less on isolated settings and more on the quality of the data – regardless if they’re running paid campaigns or not.

What Comes Next For Retail Marketers

Some advertisers will hear Google’s renewed focus on product data and assume it mainly matters for brands running Shopping campaigns.

That interpretation misses how much wider the opportunity has become.

Google is quickly expanding how products can show up across paid placements, organic surfaces, visual experiences, and newer AI-led formats. As that happens, feed quality becomes more connected to visibility and performance than many teams have historically assumed.

In many organizations, product data still gets treated as maintenance work. It gets attention when something breaks or when Shopping results decline, then falls back down the priority list.

That approach may be harder to justify going forward.

Product data needs a larger role in planning, testing, and cross-functional discussions because it can influence far more than one campaign type.

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Featured Image: Summit Art Creations/Shutterstock

https://www.searchenginejournal.com/googles-product-feed-strategy-points-to-the-future-of-retail-discovery/572291/

For years, many advertisers treated product feeds as a channel task tied mainly to Shopping campaigns.

If you were running Shopping ads, feed optimization likely got attention. If you weren’t, it often slipped behind priorities for the PPC campaigns you were running.

Now, that approach is starting to show its age.

Google’s recent Ads Decoded podcast episode suggests that mindset may need to change. Product data was discussed in connection with free listings, AI-powered search experiences, YouTube formats, Lens, virtual try-on, and newer e-commerce surfaces still evolving.

That reflects a much broader role than many advertisers have historically assigned to their feed.

Google appears to be positioning product data as a larger part of how products are discovered across its platforms, not just how Shopping campaigns perform.

Advertisers who still view Merchant Center as a side task may be underestimating how much visibility now starts with product data.

The more interesting question is what that shift tells us about where Google wants retail advertising to go next.

Merchant Center Is Starting To Look Like Retail Infrastructure

What stood out most in the podcast was how broadly Google described the role of Merchant Center data.

Nadja Bissinger, General Product Manager of Retail on YouTube, described Merchant Center feeds as the “backbone that powers organic and ads experiences,” adding that merchants should submit the most robust product data possible to increase discoverability.

That is a wider role than many advertisers have traditionally associated with Merchant Center.

Google said in a 2025 retail insights piece that people shop across Google more than 1 billion times per day. It also highlighted Search, YouTube, Maps, and visual discovery as key parts of modern shopping journeys. That helps explain why reusable product data is becoming more valuable than channel-specific assets alone.

Google also said Google Lens now sees more than 20 billion visual searches per month, and 1 in 4 Lens searches carry commercial intent. That is another signal that structured product data is becoming more important outside traditional Shopping ads.

For years, many brands viewed Merchant Center as a necessary setup for Shopping campaigns. Google now appears to be positioning it as a core input for how products are surfaced across its platforms.

That should change how feed work is prioritized internally.

Feed optimization is no longer just a PPC responsibility. It can influence:

• Organic visibility
• Merchandising strategy
• Creative presentation
• Promotions
• How products appear in newer AI-led experiences.

For larger organizations, that may require closer coordination between paid media, SEO, e-commerce, merchandising, and product teams.

For smaller brands, it may be as simple as giving feed quality the same level of attention already given to ad copy, landing pages, and campaign structure.

Many advertisers still treat feed work as cleanup work. That mindset is becoming expensive as product data plays a larger role in who gets seen across Google.

Why Is Google Pushing Product Data So Hard Right Now?

Google’s direction here makes sense when you look at where its retail products are heading.

The company wants more e-commerce activity to happen across Search, YouTube, Maps, AI experiences, and future agentic tools. To support that expansion, it needs merchant data that is accurate, structured, and easy to reuse across different surfaces (as Google refers to them as).

Google has financial reasons to expand e-commerce activity beyond traditional ad clicks. In their 2025 Q4 Earnings Release, they reported a 17% growth in Google Search, and YouTube revenue across ads and subscriptions over $60 billion.

A strong feed helps Google understand:

• What a product is
• Who it is for
• What makes it different
• Where it is available
• What it costs
• How the product should be presented

That matters even more as retail experiences, paid or organic, become more visual, more personalized, and more automated.

Traditional search ads leaned heavily on keywords, headlines, and landing pages. Newer e-commerce formats can also depend on product images, attributes, ratings, promotions, availability, shipping details, and other feed inputs that help match products to user intent.

Better data can lead to better experiences for users. It can also create more places where merchants can appear across Google’s properties.

Google is building more e-commerce surfaces, and product data is the fuel behind them. Advertisers who ignore that may keep optimizing campaigns while missing the larger shift happening around them.

Is Google Prepping For A More Strategic Shift?

From my perspective, there is a larger strategic shift behind Google’s product data push.

I don’t see this as a routine push for better feeds or cleaner campaign inputs. I see Google working to become more of a growth engine for advertisers, with a role that reaches beyond media buying and campaign delivery.

That expansion is moving into areas that shape business performance, including merchandising, product discovery, pricing visibility, local commerce, measurement, and newer purchase-ready experiences.

Google is not only trying to improve how ads run. It appears to be building a deeper position in how products are surfaced, how demand is created, how buying decisions are influenced, and how performance is measured.

My view is that the more Google becomes embedded across those moments, the more connected it becomes to broader business growth rather than media performance alone.

Why Many Advertisers Are Still Measuring Feed Value Wrong

One reason feed optimization still gets deprioritized is simple: many teams are using an outdated scorecard.

Google cited a 33% conversion uplift for advertisers using Demand Gen with product feeds during the podcast discussion. Even if results vary by account, it is another sign that feed quality is being tied to campaign types beyond classic Shopping ads.

If the main question is whether Shopping ROAS improved last week, it becomes easy to undervalue the broader impact of stronger product data.

That measurement approach came from a time when feeds were more closely tied to Shopping campaigns. Google is now using the same data across a much wider set of retail experiences, including discovery surfaces, visual placements, AI-led results, and other formats that do not fit neatly into one campaign report.

That creates a gap between where feed work adds value and where many teams are looking for it.

A stronger title may improve discoverability. Better imagery can increase engagement in visual placements. Accurate pricing and promotions can improve click appeal. Richer attributes can help Google better understand relevance. Availability data can support local and omnichannel visibility.

Those gains may show up across multiple touchpoints, assisted paths, and blended performance trends rather than one Shopping dashboard.

That is why some advertisers continue to underinvest in feed quality. The value is there, but their reporting model was built for an earlier version of Google.

As Google expands where products can appear, feed optimization deserves to be measured more like a visibility and growth lever, not just a Shopping maintenance task.

One of the more important quotes from the podcast came from Ginny Marvin, Google Ads Liaison, as she wrapped up the episode:

Merchants with the most structured, high quality data foundations will be positioned to win.

Winning will not come from uploading a feed once and forgetting about it for months at a time.

It comes from treating product data as an ongoing optimization just like your existing campaigns.

What Google’s AI Max Focus May Be Signaling About Search

One of the more revealing parts of the podcast was how often Search strategy was discussed through the lens of AI Max for Search, while traditional standard Search campaigns were barely mentioned.

During the episode, Firas Yaghi, Global Product Lead for Retail Solutions, talked about how advertisers should be thinking about different campaign types:

I think the role of each campaign really depends on your high level objective. Whether you’re prioritizing cross channel efficiency, granular control or hybrid approach that balances top line sales with OKRs.

He mentioned a lot around Performance Max, Demand Gen, with a little bit of AI Max for Search.

I would avoid treating that as proof that standard Search is going away. There is still clear value in campaigns built around tighter search control, brand protection, and proven high-intent terms.

At the same time, it’s hard to ignore the direction of Google’s messaging.

When Google talks about growth, expansion, and newer retail opportunities, the conversation increasingly centers on AI-assisted campaign types. We have seen similar signals elsewhere, including Google’s announcement that Dynamic Search Ads will upgrade into AI Max for Search and that AI Max represents the next step for search expansion.

My read is that standard Search remains important, but it is no longer the only story Google wants advertisers thinking about.

The company appears to be steering incremental growth toward campaign types that rely on broader matching, stronger inputs, automation, and first-party signals.

I think that Search strategies built around legacy structures will become less competitive over time. I’m not confident enough yet to say that standard Search campaigns will go away completely in the near future, but the increasing signals around keyword-less technology has me thinking more changes for Search campaigns are bound to happen.

What This Means For Your Campaigns

The bigger risk for PPC managers is assuming the teams responsible for merchandising or product data already understand how much feed quality can affect campaign performance.

In many organizations, merchandising, e-commerce, product, or development teams control what goes into Merchant Center. Their priorities may be centered on inventory, pricing, site operations, or category management, not media efficiency or visibility across Google.

That is where PPC managers can add real value.

If product information is influencing how products appear across paid, organic, and AI-led surfaces, someone needs to connect those decisions to marketing outcomes. PPC managers are often in the best position to do that because they can see changes in impressions, traffic quality, conversion trends, and missed opportunities firsthand.

That may mean bringing examples into weekly meetings, showing where missing attributes are limiting reach, flagging weak imagery, highlighting pricing issues, or sharing results from tests that improved performance.

You may not own the feed, but you can help the business understand why it deserves greater priority and where better inputs can improve campaign results.

Put More Focus On Inputs That Can Scale Performance

Many teams spend valuable time on small bid changes, minor budget moves, or endless rounds of creative tweaks while core product data remains incomplete or outdated.

Those tasks still have value, but the upside is often limited when the underlying product information is weak.

If titles are thin, images are poor, attributes are missing, or product details are outdated, fixing those gaps may create more value than another round of minor account adjustments.

Add Feed Health To Regular Performance Reviews

Most reporting cycles focus on spend, ROAS, CPA, and conversion volume.

Those metrics are important, but they do not always show whether product data is helping or limiting visibility.

Feed health deserves a place in regular reviews. Look at disapprovals, missing fields, image quality, pricing accuracy, promotional coverage, and product-level gaps with the same discipline used for media metrics.

Broaden How You Test For Growth

Many retail accounts still treat Search, Shopping, YouTube, and newer campaign types as separate lanes.

Google’s recent direction suggests those lines are becoming less rigid.

Growth testing should include where products can appear across newer surfaces, how feeds support Demand Gen and AI-led placements, and whether stronger product data can unlock reach that existing campaigns are not capturing today.

Treat Better Product Data As A Competitive Advantage

Some advertisers will wait until these newer placements are fully mature before investing seriously in feed quality.

While that delay may be costly for them, your proactiveness can pay off significantly.

What PPC Professionals Are Saying

Recent LinkedIn discussions suggest many practitioners are viewing feed quality as a larger performance lever.

Comments from the podcast episode have been overall positive and has many marketers agreeing that feed management needs to be routine.

Zhao Hanbo commented:

Really interesting to see how something that used to feel mostly like ad ops plumbing is now becoming core infra for AI commerce.

Sophie Westall had similar sentiments, stating that “feed quality is quickly becoming a core part of overall media strategy, not just a hygiene task.”

In a recent LinkedIn post, Menachem Ani said that by fixing a product feed, “campaigns start working harder without touching a single bid.”

More marketers appear to be focusing less on isolated settings and more on the quality of the data – regardless if they’re running paid campaigns or not.

What Comes Next For Retail Marketers

Some advertisers will hear Google’s renewed focus on product data and assume it mainly matters for brands running Shopping campaigns.

That interpretation misses how much wider the opportunity has become.

Google is quickly expanding how products can show up across paid placements, organic surfaces, visual experiences, and newer AI-led formats. As that happens, feed quality becomes more connected to visibility and performance than many teams have historically assumed.

In many organizations, product data still gets treated as maintenance work. It gets attention when something breaks or when Shopping results decline, then falls back down the priority list.

That approach may be harder to justify going forward.

Product data needs a larger role in planning, testing, and cross-functional discussions because it can influence far more than one campaign type.

Read more resources:

Featured Image: Summit Art Creations/Shutterstock

https://www.searchenginejournal.com/googles-product-feed-strategy-points-to-the-future-of-retail-discovery/572291/