I’ve discovered something exciting about how Google and Walmart are teaming up to enhance our advertising experiences. They’re enabling advertisers to tap into Walmart shoppers through YouTube, using Display & Video 360 (DV360) to measure sales more effectively. It’s a game-changer for those of us who focus on retail success.
This collaboration means I can access valuable shopper data from Walmart while also tracking whether my YouTube ads are translating into sales. It’s a win-win, giving me more control over my advertising efforts and results.
What’s happening? For brands like mine, this integration is a breakthrough. I can activate Walmart Connect audiences within DV360, reaching potential shoppers through YouTube with precision.
With closed-loop measurement now possible, I can directly connect the dots between ad exposure and purchasing actions at Walmart, making my advertising dollars work harder.
Why do I care? The amalgamation of Walmart’s rich shopper data with YouTube’s vast audience reach allows me to focus on real retail behavior rather than mere inferences, optimizing my targeting strategies.
Crucially, I can move beyond just monitoring views or clicks. I now have the capability to trace if my ads are actually driving Walmart sales, which helps justify my investments and refines my video advertising strategies.
Understanding the bigger picture, retail media networks are increasingly venturing beyond their platforms, delivering shopper insights and measurement capabilities into broader digital advertising spaces where I’m channeling more of my budget.
Reading between the lines, Walmart Connect’s ambition stands out, as they’re pushing to make their audience and analytics tools compatible with more advertising platforms. The conclusion of their exclusivity with The Trade Desk last year certainly paved the way for such integrations.
What do advertisers gain? As an advertiser, I unlock access to Walmart’s audience insights, can reach 150 million weekly U.S. customers via YouTube, and gain precise sales attribution tied to Walmart transactions—all streamlined within DV360.
What’s next for us? The initial focus is on YouTube campaigns, but I’m eager to see how Google and Walmart will expand this integration to cover more inventory over time.
The bottom line? This partnership is a powerful alignment of retail data, media activation, and sales measurement, offering advertisers like me a direct way to connect our YouTube ads with consumer behaviors at Walmart, both in-store and online.
I’ve got some exciting news to share! Google is expanding its enhanced Local Services Ads (LSAs) for Home Listings all across the U.S., and it’s set to revolutionize the home-buying process.
As someone who frequently turns to Google at the start of my own home-searching journey, I see this as a fantastic opportunity for connecting homebuyers like me with local agents earlier in the process.
What’s New: With the updated LSA experience, I’m thrilled to see that ads now include detailed property information, such as pricing, photos, and key home features, right within the ad itself.
This new functionality is made possible through a collaboration with HouseCanary, which provides the property data showcased in the ads.
Why It’s Important: For me, having access to actual property listings, including visuals, pricing, and details directly through Google’s Local Services Ads, means I can better evaluate homes and reach out to agents without ever leaving the search page. This could very well boost lead quality and conversion rates.
How It Works: If I’m in the market for a new home, I can contact agents directly from these ads, whether through a call, message, or by booking an appointment.
Who Benefits: Existing LSA advertisers are automatically included in this enriched experience. Real estate professionals not yet using Local Services Ads have the chance to sign up and start receiving high-quality leads. Additionally, portal partners can sign up agents through Google’s managed partner program.
The Bottom Line: Google’s strategy, combining rich listing information with direct agent connections, seems designed to make Search a more beneficial starting point for homebuyers like myself. It’s poised to become a valuable resource for agents looking for high-intent leads.
Not too long ago, I remember broad match being hailed as the future of paid search. Today, AI Max has taken on that mantle.
Over recent months, I’ve received plenty of suggestions to activate AI Max on brand campaigns, even when these campaigns are performing just as I want them to.
The reality is, many accounts still aren’t equipped with the essentials AI Max requires for optimum function. Conversion tracking issues, the lack of offline conversion imports, and budget-constrained generic campaigns are common hurdles.
AI Max thrives on robust conversion signals, adequate volume, and enough variation for effective learning. I often find that brand campaigns provide most of these signals.
However, applying AI Max to brand campaigns means layering additional automation over our most efficient and predictable traffic source.
The promise and limitations of AI Max
AI Max can broaden search targeting beyond your key phrases by using keywords, landing pages, and site content as signals instead of specific targeting criteria.
Much like dynamic search ads (DSA), AI Max can align with queries you didn’t explicitly target, and it ventures even further by transcending the intent limits set by your keyword arsenal.
Google portrays AI Max as the future of Search automation, preparing to merge DSA, automatically created assets, and broad match settings into AI Max this September.
With controls like brand exclusions, URL exclusions, text guidelines, and location targeting, AI Max might tap into growth opportunities in accounts rich with strong conversion signals and enough search volume.
Yet, many accounts haven’t reached that point.
With Google’s AI Surface eligibility expanding, it’s tempting to dive headfirst into AI Max. But it’s essential to focus on account fundamentals—measurement accuracy, conversion integrity, and solid account structures—before relying solely on AI Max.
Why AI surface eligibility isn’t reason enough to rush into AI Max
The growing interest in AI Max is fueled by Google’s push toward AI-powered search experiences. AI Overviews now engage approximately 2.5 billion users monthly, presenting ads in 25.6% of AI Overview results, according to Semrush data.
While maintaining visibility in these surprising new fields is advisable, rushing to apply AI Max without assessing your campaign structure and conversion strategies can be detrimental.
Typically, Google Ads representatives pitch AI Max for brand campaigns to ensure their eligibility in AI Mode and associated AI Overviews. However, this isn’t always the truth.
Ginny Marvin, a Google Ads liaison, confirmed that three campaign types are eligible for AI Overviews: broad match with Smart Bidding, Performance Max (PMax), and AI Max for Search. Meanwhile, exact match keywords never qualify for AI Overviews.
Thus, PMax and AI Max generally serve the same purpose concerning AI surface eligibility. Running PMax brand campaigns already gives you the necessary coverage, without the need for adding another layer of automation.
Before adding AI Max into your mix, examine whether it’s genuinely necessary over addressing your account’s foundational needs.
Test data doesn’t fully endorse Google’s AI Max assertions
Google claims that enabling AI Max could increase conversions by 14%, and those employing exact and phrase matches might experience a 27% increase. Nevertheless, independent tests have yielded a wide array of results.
The evidence for AI Max remains mixed
In tests covering 600 accounts, Smarter Ecommerce observed AI Max produced 35% lower ROAS than traditional match types. This outcome aligns with intentional budget minimization by advertisers.
Through a four-month examination, Xavier Mantica discovered AI Max resulted in the priciest conversions compared to phrase and exact match. While Mantica noted $100.37 per conversion with AI Max, phrase match was at $43.97, and exact match was at $52.69.
Moreover, 99% of impressions during Ezra Sackett’s 30,000 search term analysis returned zero conversions under AI Max.
Significantly, none of this data is brand-focused. AI Max may provide benefits in certain settings, but a successful, exact match defensive brand campaign may not be the right candidate for testing new automation.
If your brand is still the standout performer in your account, you may want to question why the rest of your campaigns haven’t met similar standards.
What to consider before testing AI Max on brand
Ask yourself these critical questions before branching AI Max into your brand campaigns:
1. Are the conversion signals trustworthy?
Does your setup cleanly distinguish between macro and micro conversions? Are offline imports running smoothly? Does the lead quality feedback enhance platform optimization?
If the underlying signals falter, AI Max will simply magnify those issues.
2. Have you already explored generic growth?
In the accounts I review, problems like budget constraints, misaligned landing pages, outdated queries, and suboptimal structure frequently hinder generic campaign growth.
Real growth is often found within these issues, rather than an already strong brand campaign.
3. Can the account provide AI with sufficient learning data?
Remember, AI Max is not some sorcery; it mirrors the quality of the signals it receives.
Relying heavily on brand conversions will only amplify these markers and obstruct other growth pathways.
4. Are brand + modifier searches already structured properly?
Search variations like “Brand + pricing” or “Brand + reviews” ought to be treated as separate strategic campaigns. AI Max should not substitute for robust account architecture.
5. Do you have a strategic reason to expand the brand campaign?
Consider testing strategically through experiments, rather than viewing AI Max as a straightforward switch to augment visibility.
AI Max only works as efficiently as the signals guiding it
AI Max might develop into a truly beneficial tool over time, much like PMax did. Automation effective at any level still requires strong foundational signals for success.
The existing issue remains with insufficient solid foundations supporting the automation. Improved conversions, precise measurement, sound account structures, and comprehensive feedback loops are vital to making automation wiser.
Above all, don’t conflate Google’s automation agenda with your campaign objectives.
I’m intrigued by Google’s decision to update its Local Services Ads on July 6. This change isn’t just a simple update—they’re renaming policies as “requirements” and aligning everything with a recent badge system overhaul.
So, what’s going on? Google is working to refine the rules governing Local Services Ads. They’re not just updating the language; they’re also aligning advertiser requirements with their new verification standards.
One key change is the renaming of “Local Services platform policies” to “Local Services Ads requirements.” It might sound administrative, but these adjustments suggest a more straightforward way for businesses to comply and earn those coveted Google Guarantee badges.
For those of us in advertising, these updates are vital. They not only promise clarity but hint at the possibility that compliance will tie directly to badge status. Agencies and local businesses must stay vigilant and ensure their credentials and standards are spot-on.
What does this mean in the grand scheme of things? Google aims to make the advertiser requirements crystal clear, aligning them with the new badge framework while simplifying the guidance on compliance.
To be clear, Google isn’t cracking down hard on policy. Instead, they’re focused on clarity and modernization, simplifying how businesses access these requirements.
In summary, Google is refreshing its Local Services Ads policies. The shift is towards “requirements,” backed by a badge-driven approach, enhancing trust and eligibility for businesses.
As part of OpenAI’s exciting expansion, I’ve learned they’re extending ChatGPT ads into five fresh markets, including the UK. Excitingly, new campaign management features are on the horizon!
I can see OpenAI ramping up its ad strategies within ChatGPT through an early test that presents the possibility for multiple advertisers to showcase their ads in a single space.
What’s happening. From what I’ve gathered, OpenAI is trialing a new multi-advertiser format over a limited number of ChatGPT ads, which was confirmed in a recent update to their advertisers.
This new approach consolidates several relevant ads into one space instead of just one sponsored result. I understand these ads will be sold using a second-price auction model, commonly employed in digital advertising.
I’m excited to share that OpenAI aims to enhance user product discovery and provide ample avenues for advertisers to connect with users during high-intent interactions.
Meanwhile, in Ads Manager Beta. There’s more good news, as OpenAI rolled out some updates to campaign management features, and here’s what caught my attention:
It’s now possible to shift existing campaigns from lifetime budgets to daily budgets, which makes budgeting more flexible.
CPM campaigns can seamlessly transition to CPC bidding with just a click.
I’ve noticed that impression-based campaigns now support customized CPM max bids.
Bulk editing right in the Ads Manager interface—how convenient is that?
Daily budgets will start working under an average daily budget system, touting weekly pacing flexibility.
There’s fantastic geographic targeting expansion, beyond the U.S., Canada, Australia, and New Zealand, now including the U.K., Japan, South Korea, Brazil, and Mexico.
Why we care. The updates are instrumental in aligning OpenAI’s ad structure with what we as marketers expect from established ad systems, easing campaign management while widening international targeting.
What to watch. This multi-advertiser test might just be the indicator of how OpenAI plans to monetize ChatGPT. If it’s successful, the strategy could be key to expanding advertisers’ reach during users’ purchasing and research phases.
The bottom line. I see OpenAI carefully crafting its advertising framework, with the introduction of multiple advertisers in a single placement potentially redefining sponsored content’s role within AI-driven conversations.
I’m excited to share with you the top senior living marketing agencies of 2026. Through extensive research and an internal ranking system, we’ve identified these leaders. Our criteria focused on several key factors, including:
1. Notable Clients (30%): We looked at the well-known senior living clients featured on each agency’s website. In cases where specific senior living clients weren’t listed, we expanded our analysis to related sectors like assisted living and healthcare.
2. Average Review Score (30%): Agencies were scored 1-5 based on the average rating from online reviews.
3. Leadership Experience (25%): We assessed the agency’s leadership in terms of their experience with marketing for senior living facilities, scoring them from 1 to 5.
4. Year Established (10%): An agency’s founding year hinted at its adaptability to market changes and evolving customer needs.
5. Median Employee Tenure (5%): This metric indicated the agency’s workplace culture and the experience level of their team.
Let’s dive into the top 9 scoring agencies and see what makes them stand out in the senior living marketing landscape.
The Top Senior Living Marketing Agencies of 2026
First Page Sage: Leading the pack, this agency builds personalized SEO strategies, fostering community trust through expert content. They’ve revolutionized online presence with GEO, positioning clients in AI search engines like ChatGPT and Google Gemini.
Love & Company: Known for its robust brand development and advertising prowess, this agency offers extensive strategic services to help businesses grow, although lacking some cutting-edge techniques like GEO.
SenioROI: Specializes in traditional media, providing a solid approach for engaging directly with prospective residents through TV, radio, and print channels.
Senior Living Smart: Offers a diverse array of services, integrating marketing automation with call center management to create an omnichannel presence for clients.
Comrade Digital Marketing: Focuses on boosting local SEO and paid advertising, ideal for senior living facilities in expansion phases.
Markentum: Younger but promising, with strong customer reviews in social media marketing and branding, catering to tech-savvy audiences.
Senior Living Marketers: Offers a mix of digital and traditional marketing, though being new with fewer client reviews, suggests careful consideration.
SageAge: A veteran in the industry, providing a wide range of comprehensive marketing services backed by substantial experience.
Five19: Specializes in branding and creative strategy, perfect for senior living communities wanting a distinctive brand identity.
I’ve recently discovered that Google is reshaping our approach to Display Ads by integrating them into Demand Gen campaigns, providing us with wider reach and innovative AI-driven features.
What’s happening? Now, I can effortlessly manage my placements on the Google Display Network (GDN) through Demand Gen campaigns. Interestingly, I still have the option to keep my ads running exclusively on GDN if that’s more suitable for my needs.
Through Demand Gen campaigns, I’m able to extend my ad reach across YouTube, Discover, Gmail, Maps, and a vast array of Display Network sites, all within a more centralized system.
Why do I care? This strategic shift by Google is crucial because it centralizes more inventory, harnesses automation, and leverages AI for enhanced campaign optimization. It’s become an essential factor for my performance and discovery ad strategies.
As a Display advertiser, these adjustments mean I gain access to advanced AI features, greater cross-platform reach, and potentially increased efficiency. I see this as a shift towards less reliance on traditional standalone Display management over time.
The bigger picture. Google is steering Demand Gen to be the go-to campaign type for visual discovery advertising, merging creative social-style distribution with its powerful AI targeting capabilities.
Google claims an average ROI increase of 9.5% for those who’ve added GDN inventory to their Demand Gen campaigns, and I’m intrigued by the potential benefits.
Between the lines. These changes provide me with access to the latest Demand Gen features announced at Google Marketing Live, including enhanced channel controls and forward-looking AI campaign tools.
What to watch. With Google’s ongoing journey towards consolidating campaign management under AI-led products, I find myself reevaluating my strategies for upper-funnel discovery, Display, and performance-centric media purchasing.
Every Monday, I dive into my role as a paid media manager knowing the chaos that awaits. From Google Ads to TikTok and Reddit, my task is to pull the data from each platform, put it into a comprehensible spreadsheet, and report to my boss by 10 a.m. Amidst all this, I try to decipher what worked last week and why. It’s a frenetic start to the week, to say the least.
Remembering when managing multi-channel campaigns meant juggling just Google Ads and a Facebook campaign feels almost nostalgic now. Today, it’s a tangled web of 12 channels, each with their peculiarities in terms of attribution logic and campaign structures. The disarray is real and mostly ignored, to the detriment of performance marketers like me.
I realize that this Monday morning ritual is less about campaign management and more about tedious chores like data entry and reformatting. Managing campaigns across numerous networks involves reopening platforms repeatedly just to align disparate data points.
The prevailing problem isn’t just the time I lose, but the lag it introduces to my operations. When my performance data is scattered across various platforms, delays in identifying key insights can lead to wasted budgets. The inconsistency in strategies across channels further exacerbates the issue.
I’ve come to understand that relying on native dashboards from Google, Meta, and others won’t rescue us from this inefficiency. These platforms prefer keeping us tethered to their interfaces, contributing to the fragmentation. But a paradigm shift is on the horizon: AI-native management tools that promise seamless cross-platform synchronization without the need for multiple dashboards.
The change is happening right now, reimagining how campaigns are managed with AI. It means planning campaigns with simple briefs and automatically syncing creative adjustments across all channels. This reorientation is not just an incremental improvement but a transformational leap that alleviates the operational burdens we’ve carried for too long.
For agencies like mine, AI brings another boon: automated and branded client reports that compile multi-network performance data without the Sunday-night grind.
What actions can we take this week? First, I’ll track where my hours truly go throughout a week — seeing is believing when it comes to confronting administrative bloat. Second, standardizing naming conventions across accounts is surprisingly effective in smoothing out cross-platform wrinkles. Third, I’ll delve into evaluating current AI-native tools, as I suspect many teams are operating on outdated assumptions about their capabilities.
Achieving an operational edge in paid media transcends budget size. It’s about faster data-action cycles, unified cross-network performance views, and liberating our teams from the laborious chains of manual processing. This operational edge could mean the difference between thriving and merely surviving in a competitive landscape.
Today, I’m excited to share that Google is making significant enhancements to Asset Studio, aimed at helping advertisers like us generate creative assets more efficiently by leveraging the power of Gemini. This was announced at Google Marketing Live 2026.
Driving the news. Asset Studio will now feature AI-driven creation capabilities across text, images, and videos, allowing us to use natural language prompts to guide the process.
Google assures us that the platform is capable of understanding:
Marketing briefs
Brand guidelines
Website content
Campaign goals
By doing so, it generates creative assets that span different themes and formats, tailored to our needs.
Additionally, Google is integrating the Gemini Omni, their multimodal model, into Asset Studio. This enhances our workflows, especially in video creation.
With 1-Click Creative Testing, we can quickly identify top-performing assets in terms of campaign objectives. This means more efficient testing and better results for us.
How it works. By applying Gemini models, Asset Studio interprets our marketing briefs, guidelines, and objectives. Using natural language prompts, we can generate and perfect our assets, whether they’re text, image, or video. Plus, Gemini Omni ensures our video workflows are seamless.
The aim is clear: centralize creative production and minimize the challenges we face when building campaigns across platforms like Google and YouTube.
Why we care. Creative production bottlenecks are a major issue for us advertisers. Google’s updates show that integrating generative AI into our workflows makes creative production much more streamlined.
For those of us managing cross-platform campaigns, the ability to swiftly generate and test creative assets is a game-changer.
What to watch. As we automate more of our creative processes, it’s important to compare the performance of AI-generated assets against those from traditional workflows. We might need to rethink approval processes and brand safety in light of AI’s growing role.
Availability. We can expect the new Asset Studio features to become globally available in English this summer, opening up new possibilities for our advertising strategies.
Dig deeper. There are more updates from Google Marketing Live 2026 that are worth exploring for additional insights and tools that could benefit our campaigns. For example:
In 2025, I’ve noticed that while the costs of Google Ads continue to climb, there’s been a silver lining. Advertisers like myself have been improving conversion efficiency, which means growth is still within reach.
I’ve observed that although we’re paying more per click, the data from WordStream by LocaliQ shows we’re getting better at converting those clicks. The benchmark report, analyzing over 16,000 campaigns, highlights an increase in average CPC to $5.42, up from $4.66 last year, with 87% of industries seeing a rise.
Despite this jump in CPC, the average conversion rate has improved to 8.18%. This indicates we’re becoming more efficient, even as traffic costs rise.
Why advertisers should care. The benchmarks clearly point out that inexpensive traffic is fading fast. For us advertisers, this means absolute reliance on volume is not sustainable anymore.
To maintain profitability, I’ve realized that focusing on stronger targeting, creative enhancements, better landing pages, and smarter automation is vital.
The report suggests advertisers who adapt well to automation and intent-driven targeting are improving conversion efficiency, despite the rising costs.
By the numbers. Here’s what stands out:
$5.26 — Average Google Ads CPC in 2025, increased from $4.66 in 2024.
87% — Percentage of industries experiencing CPC hikes annually.
7.52% — Across-the-board average conversion rate in 2025.
$70.11 — Average cost per lead in Google Ads, 2025.
Highest CPCs. Industries like Attorneys & Legal Services led with $8.58, while areas like Finance & Insurance, and Home Improvement consistently hovered in the $7+ range.
Lowest CPCs. The Arts & Entertainment and Travel & Hospitality sectors fell in the $2–$3 range, benefitting from reduced competition.
Highest conversion rates (strong intent / local services)
Automotive Repair led with 14.67%, followed by other high-intent services like home services ranging from 12–14%.
Lowest conversion rates (complex or high-consideration journeys)
Finance & Insurance was at the bottom with 2.55%, and B2B, legal, and high-ticket items were between 3–5%.
The cost-per-lead is stabilizing, thankfully. Although the average CPL rose modestly by 5.13% to $70.11 in 2025, it’s a relief after years of sharper increases. Legal services remain costly, while auto repair is more cost-effective.
Automation is changing performance benchmarks. I’ve seen how Google Ads has embraced AI-driven optimization. As conversion rates rise, smarter bidding systems and improved intent matching are effectively connecting advertisers with high-quality users.
While automation like Smart Bidding and Performance Max is shaping campaigns, I know that not every account is thriving. Some have zero conversions, and failure to optimize or poorly set up tracking continues to waste spend.
Interestingly, accounts using negative keywords experience conversion rates up to three times higher, underscoring how foundational practices are essential even in an AI era.
Between the lines. The benchmarks present a mixed message. Costs are rising, yet Google’s automation aids efficiency for those optimizing their campaigns effectively.
The biggest challenge now isn’t finding cheap clicks—it’s enhancing conversion quality and maximizing value from expensive traffic.
Bottom line.Google Ads is more costly than ever, but by embracing automation, focusing on conversion quality, and improving account efficiency, growth is still possible.
