Ecommerce MGMT, Author at Ecommerce Management Education

Sep 11 2025

WordPress Versus Everyone: The Top CMS For Core Web Vitals via @sejournal, @martinibuster

The Core Web Vitals Technology Report by the open source HTTPArchive community ranks content management systems by how well they perform on Google’s Core Web Vitals (CWV). The July update shows that every major platform has improved since June, but not all gains were equal. Joomla posted the largest month-over-month increase, while Duda ranked first in July with 84.96% of sites passing CWV.

Why Core Web Vitals Matter

Core Web Vitals (CWV) are metrics created by Google to measure how fast, stable, and responsive a website feels to users. Websites that load quickly and respond smoothly keep visitors engaged, while sites that fall short frustrate users and increase bounce rates. For businesses and publishers, CWV scores reflect the user experience and competitiveness online.

How the Data Is Collected

The CWV Technology Report combines two public datasets:

Chrome UX Report (CrUX): Data from Chrome users who opt in to share performance statistics as they browse. This reflects how real users experience websites.
HTTP Archive: Lab-based tests that analyze how sites are built and whether they follow performance best practices.

Together, these sources provide a consistent picture of how different website platforms perform on Core Web Vitals in the real world.

Percentage Change from June to July

#1 Joomla — largest gain (+3.23%).

#2 Wix — +2.61%.

#3 Drupal — +1.47%.

#4 Duda — +1.33%.

#5 Squarespace — +1.27%.

#6 WordPress — smallest gain (+0.90%).

This ranking shows which platforms advanced most in July. Joomla experienced the highest level of growth, while WordPress improved the least. Wix’s CWV month over month performance improvement was a notable 2.51%.

Ranking by July CWV Score

Duda once again is the Core Web Vitals champion, ranked by the percentage of websites that has a good CWV score.

#1 Duda — 84.96%

#2 Wix — 73.37%

#3 Squarespace — 68.93%

#4 Drupal — 60.54%

#5 Joomla — 54.78%

#6 WordPress — 44.34%

Joomla showed the fastest growth, but it still ranked fifth in July. Duda led with the highest overall performance.

Why the Numbers Matter

Core Web Vitals scores translate into real differences in how users experience websites. Platforms with higher CWV scores offer faster, smoother interactions, while those at the bottom frustrate users with slower performance. While all six platforms in the comparison are improving month to month, what matters most is the actual experience users get right now.

Duda is the Core Web Vitals champion in July with a score of 84.96% of websites built with the Duda platform having a good CWV score.
Joomla had the largest gain, but still ranked near the bottom with only 54.78% of sites showing a good CWV score.
Wix and Squarespace ranked in the second and third places, showing strong performance but both significantly behind Duda by over ten percentage points.
WordPress ranked last, both in July scores and in the month over month rate of improvement.

Do Content Management Systems Matter For Ranking?

I have seen discussions online about whether the choice of content management system has an impact on rankings. Some people assert that plugins make WordPress easier to rank in Google.

There is also a perception that WordPress is faster than Wix, Duda, and Squarespace. The facts, of course, show that the opposite is true. WordPress is the slowest of the content management systems in this comparison.

The percentage of sites built with Duda that had a good Core Web Vitals score is 84.96%. The percentage of WordPress sites with a good CWV score is 44.34%. That means Duda’s percentage of sites with good CWV scores is about 92% higher than those built with WordPress.

Another issue with WordPress is that it has a considerable amount of technical debt, something that private content management systems do not have to struggle with to the same degree. Technical debt refers to the accumulation of outdated code and design decisions that make it harder to maintain, update, or improve the platform over time. It is not unique to WordPress, but it is an issue because of how WordPress is built and how its ecosystem works.

Some reasons for WordPress’s technical debt:

WordPress was originally conceived as a blogging platform and has evolved into a full CMS, able to be extended as virtually any kind of website.
Adding new features on top of legacy code means workarounds must be made for backward compatibility, which creates complexity and slows down innovation.

Technical debt was an issue discussed at WordCamp EU 2025, summarized on the official WordPress site as related to contributor burnout:

“Burnout Crisis & Sustainability

Contributor burnout is pervasive due to:

High volunteer demands with insufficient systemic support.

Lack of equitable financial remuneration or stipends for ongoing work.

Pressure to maintain legacy systems and innovate new features leads to overwhelming workloads.

Consequences

Loss of institutional knowledge and experienced contributors.

Increasing technical debt and slowed innovation cycles.

Threat to WordPress’s long-term ecosystem health.”

WordPress has recently moved to a slower annual release cycle, and one of the benefits of that change (summarized by WordPress here) is that it gives the project time to address the issue of technical debt.

The point is that if the content management system did have an effect on the ability to rank, WordPress sites would probably struggle to rank because of the relatively poor performance scores and the slower pace of development when compared to private content management systems like Wix. But that’s not the case.

WordPress websites rank very well despite all the issues with the platform, including security. So it may be that the choice of CMS does not necessarily matter for SEO, especially since private solutions like Wix and Duda are purposely built with SEO in mind. Nevertheless, performance is important for things that matter, such as conversions and the user experience, and the fact is that the HTTPArchive Technology Comparison Report ranks WordPress last for Core Web Vitals performance in July.

Featured Image by Shutterstock/Roman Samborskyi

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Sep 11 2025

Ahrefs Acquires Detailed.com & SEO Extension; Founder Joins Company via @sejournal, @MattGSouthern

Ahrefs has acquired Detailed.com and the Detailed SEO Extension, bringing a widely used on-page auditing tool and its audience under the Ahrefs umbrella.

As part of the deal, Detailed founder Glen Allsopp is joining Ahrefs full-time to work on marketing strategy, research, and product.

What’s Included

The acquisition covers the Detailed website and its browser extension, along with several smaller domains and extensions.

Launched in 2020, Detailed.com is known for long-form, data-driven SEO research and practitioner tips (including its analysis of how a small number of companies operate large networks of ranking sites). Over the past 12 months, Detailed.com recorded 970,000 unique visitors.

The Detailed SEO Extension reports over 450,000 weekly users on Chrome and approximately 7,000 on Firefox.

The extension speeds up page-level checks SEO professionals perform during audits and competitive reviews by surfacing title and meta tags, heading structure, robots directives, and schema markup in a single panel.

It also offers options for highlighting nofollow links, inspecting hreflang, viewing status codes, extracting People Also Ask results, switching the user agent to Googlebot, and jumping the current URL into popular research tools for deeper analysis.

What Changes For Extension Users

Allsopp told SEJ that the extension and all current functionality will remain free for all users.

If premium capabilities are ever added in the future, they would be additions rather than moving existing features behind a paywall. There are no current plans to introduce paid tiers.

On branding and distribution, the extension will keep the Detailed SEO Extension name. Detailed will operate as “Detailed, an Ahrefs brand.”

Users don’t need to take any action, and updates will continue as normal through existing Chrome and Firefox listings.

Statement From Glen Allsopp

Allsopp told Search Engine Journal:

“At a time when so much is happening in SEO and digital marketing as a whole, I want to be at the forefront of the work that helps companies reach more of their target audience. Ahrefs provides tools, data and insights I’ve used in my own business for years, so to be joining the team behind that is really exciting.”

Financial terms were not disclosed.

Looking Ahead

The move adds a high-usage browser utility and a research-driven content brand to Ahrefs’ portfolio.

If Ahrefs integrates or expands the extension’s capabilities over time, practitioners could see faster iteration on features that support day-to-day site audits, on-page reviews, and competitive analysis.

Featured Image: Screenshot from Detailed.com, September 2025.

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Sep 11 2025

Bias In Search: Visibility, Perception, And Control via @sejournal, @DuaneForrester

Bias in search isn’t always negative. It’s easy to frame it as something sinister, but bias shows up for structural reasons, behavioral reasons, and sometimes as a deliberate choice. The real task for marketers and communicators is recognizing when it’s happening, and what that means for visibility, perception, and control.

Two recent pieces got me thinking more deeply about this. The first is Dejan’s exploration of Selection Rate (SR), which highlights how AI systems favor certain sources over others. The second is Bill Hartzer’s upcoming book “Brands on the Ballot,” which introduces the concept of non-neutral branding in today’s polarized market. Put together, these show how bias isn’t just baked into algorithms; it’s also unavoidable in how brands are interpreted by audiences.

Image Credit: Duane Forrester

Selection Rate And Primary Bias

Selection Rate can be thought of as the percentage of times a source is chosen out of the available options (selections ÷ options × 100). It’s not a formal standard, but a useful way to illustrate primary bias in AI retrieval. Dejan points out that when an AI system is asked a question, it often pulls from multiple grounding sources. But not all sources are selected equally. Over time, some get picked again and again, while others barely show up.

That’s primary bias at work.

For marketers, the implication is clear: If your content is rarely chosen as a grounding source, you’re effectively invisible inside that AI’s output ecosystem. If it’s selected frequently, you gain authority and visibility. High SR becomes a self-reinforcing signal.

This isn’t just theoretical. Tools like Perplexity, Bing Copilot, and Gemini surface both answers and their sources. Frequent citation enhances your brand’s visibility and perceived authority. Researchers even coined a term for how this feedback loop can lock in dominance: neural howlround. In an LLM, certain highly weighted inputs can become entrenched, creating response patterns that are resistant to correction, even when new training data or live prompts are introduced.

This concept isn’t new. In traditional search, higher-ranked pages earn more clicks. Those clicks send engagement signals back into the system, which can help sustain ranking position. It’s the same feedback loop, just through a different lens. SR doesn’t create bias; it reveals it, and whether you benefit depends on how well you’ve structured your presence to be retrieved in the first place.

Branding And The Reality Of Interpretation

Brands on the Ballot frames this as non-neutral branding: Companies can’t avoid being interpreted. Every decision, big or small, is read as a signal. That’s bias at the level of perception.

We see this constantly. When Nike featured Colin Kaepernick, some people doubled down on loyalty while others publicly cut ties. When Bud Light partnered with a trans influencer, backlash dominated national news. Disney’s disputes with Florida politicians over cultural policy became a corporate identity story overnight.

None of these were just “marketing campaigns.” Each was read as a cultural stance. Even decisions that seem operational (which platforms you advertise on, which sponsorships you accept, which suppliers you choose) are interpreted as signals of alignment.

Neutrality doesn’t land as neutral anymore, which means PR and marketing teams alike need to plan for interpretation as part of their day-to-day reality.

Directed Bias As A Useful Lens

Marketers already practice deliberate exclusion through ICP targeting and positioning. You decide who you want to reach and, by extension, who you don’t. That’s not new.

But when you view those choices through the lens of bias, it sharpens the point: Positioning is bias with intent. It’s not hidden. It’s not accidental. It’s a deliberate narrowing of focus.

That’s where the idea of directed bias comes in. You can think of it as another way to describe ICP targeting or market positioning. It’s not a doctrine, just a lens. The value in naming it this way is that it connects what marketers already do to the broader conversation about how search and AI systems encode bias.

Bias isn’t confined to branding or AI. We’ve known for years that search rankings can shape behavior.

A 2024 PLOS study showed that simply altering the order of results can shift opinions by as much as 30%. People trust higher-ranked results more, even when the underlying information is the same.

Filter bubbles amplify this effect. By tailoring results based on history, search engines reinforce existing views and limit exposure to alternatives.

Beyond those behavioral biases lie structural ones. Search engines reward freshness, meaning sites crawled and updated more frequently often gain an edge in visibility, especially for time-sensitive queries. Country-code top-level domains (ccTLDs) like .fr or .jp can signal regional relevance, giving them preference in localized searches. And then there’s popularity and brand bias: Established or trusted brands are often favored in rankings, even when their content isn’t necessarily stronger, which makes it harder for smaller or newer competitors to break through.

For marketing and PR professionals, the lesson is the same: Input bias (what data is available about you) and process bias (how systems rank and present it) directly shape what audiences believe to be true.

Bias In LLM Outputs

Large language models introduce new layers of bias.

Training data is rarely balanced. Some groups, voices, or perspectives can be over-represented while others are missing. That shapes the answers these systems give. Prompt design adds another layer: Confirmation bias and availability bias can creep in depending on how the question is asked.

Recent research shows just how messy this can get.

MIT researchers found that even the order of documents fed into an LLM can change the outcome.
A 2024 Nature paper catalogued the different types of bias showing up in LLMs, from representation gaps to cultural framing.
A PNAS study confirmed that even after fairness tuning, implicit biases still persist.
LiveScience reported that newer chatbots tend to oversimplify scientific studies, glossing over critical details.

These aren’t fringe findings. They show that bias in AI isn’t an edge case; it’s the default. For marketers and communicators, the point isn’t to master the science; it’s to understand that outputs can misrepresent you if you’re not shaping what gets pulled in the first place.

Pulling The Threads Together

Selection Rate shows us bias at work inside AI retrieval systems. Branding shows us how bias works in the marketplace of perception. Directed bias is a way to connect those realities, reminding us that not all bias is accidental. Sometimes it’s chosen.

The key isn’t to pretend bias doesn’t exist; of course, it does. It’s to recognize whether it’s happening to you passively, or whether you’re applying it actively and strategically. Both marketers and PR specialists have a role here: one in building retrievable assets, the other in shaping narrative resilience. (PS: An AI cannot really replace a human for this work.)

So what should you do with this?

Understand Where Bias Is Exposed

In search, bias is revealed through studies, audits, and SEO testing. In AI, it’s uncovered by researchers probing outputs with structured prompts. In branding, it’s revealed in customer reaction. The key is knowing that bias always shows itself somewhere, and if you’re not looking for it, you’re missing critical signals about how you’re being perceived or retrieved.

Recognize Who Hides Bias

Search engines and LLM providers don’t always disclose how selections are weighted. Companies often claim neutrality even when their choices say otherwise. Hiding bias doesn’t make it go away; it makes it harder to address and creates more risk when it eventually surfaces. If you aren’t transparent about your stance, someone else may define it for you.

Treat Bias As Clarity

You don’t need to frame your positioning as “our directed bias.” But you should acknowledge that when you pick an ICP, craft messaging, or optimize content for AI retrieval, you’re making deliberate choices about inclusion and exclusion. Clarity means accepting those choices, measuring their impact, and owning the direction you’ve set. That’s the difference between bias shaping you and you shaping bias.

Apply Discipline To Your AI Footprint

Just as you shape brand positioning with intent, you need to decide how you want to appear in AI systems. That means publishing content in ways that are retrievable, structured with trust markers, and aligned with your desired stance. If you don’t manage this actively, AI will still make choices about you; they just won’t be choices you controlled.

A Final Danger To Consider

Bias isn’t really a villain. Hidden bias is.

In search engines, in AI systems, and in the marketplace, bias is the default. The mistake isn’t having it. The mistake is letting it shape outcomes without realizing it’s there. You can either define your bias with intent or leave it to chance. One path gives you control. The other leaves your brand and business at the mercy of how others decide to interpret you.

And here’s a thought that occurred to me while working through this: What if bias itself could be turned into an attack vector? I’m certain this isn’t a fresh idea, but let’s walk through it anyway. Imagine a competitor seeding enough content to frame your company in a certain light, so that when an LLM compresses those inputs into an answer, their version of you is what shows up. They wouldn’t even need to name you directly. Just describe you well enough that the system makes the connection. No need to cross any legal lines here either, as today’s LLMs are really good at guessing a brand when you just describe their logo or a well-known trait in common language.

The unsettling part is how plausible that feels. LLMs don’t fact-check in the traditional sense; they compress patterns from the data available to them. If the patterns are skewed because someone has been deliberately shaping the narrative, the outputs can reflect that skew. In effect, your competitor’s “version” of your brand could become the “default” description users see when they ask the system about you.

Now imagine this happening at scale. A whisper campaign online doesn’t need to trend to have impact. It just needs to exist in enough places, in enough variations, that an AI model treats it as consensus. Once it’s baked into responses, users may have a hard time finding your side of the story.

I don’t know if that’s an actual near-term risk or just an edge-case thought experiment, but it’s worth asking: Would you be prepared if someone tried to redefine your business that way?

More Resources:

This post was originally published on Duane Forrester Decodes.

Featured Image: Collagery/Shutterstock

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Sep 11 2025

Explaining Google’s AI Search Experiments To Your C-Suite via @sejournal, @TaylorDanRW

Google is testing a series of experimental AI-powered features that could change how people interact with search and digital discovery.

Tools like Doppl, Food Mood, Talking Tours, and Learn About are not yet mainstream, but they give us a glimpse into where Google may be heading. Each experiment highlights a distinct way AI can influence consumer experiences, ranging from shopping and travel to food and education.

For business leaders, the importance lies in how these features could influence visibility, customer engagement, and competitive positioning if they are developed further.

Having these on your radar now can avoid sharp surprises and knee-jerk tactical pivots later down the line.

Doppl

Doppl is a new experimental app from Google Labs that lets users try on different looks and explore their personal style. It blends fashion discovery with AI-driven recommendations, acting like a personal stylist in app (on both Android and App Store).

This was initially talked about on the Google blog in 2024 and referred to as Virtual Try-On (VTO).

Screenshot from labs.google/doppl, September 2025

Given the adoption statistics Google has claimed around Google Lens and Circle to Search, Doppl could further change how consumers might approach online fashion and homeware buying.

Instead of browsing catalogs or searching by product type, users can explore outfits in a more playful, visual, and interactive way. This creates opportunities for fashion brands that invest in rich product imagery and metadata, while also introducing risks for those that fail to prepare.

It also highlights that outfit imagery doesn’t need to be professional; users can use Doppl to visualize outfits from their friends’ photos, branded Instagram posts, or what you include in your blogs and style guides.

For ecommerce websites, Doppl could reduce the importance of traditional product listings and increase the value of enriched product data. Style-driven discovery may also accelerate purchase decisions, compressing the sales cycle from browsing to checkout.

For example, a fashion retailer that provides detailed imagery, size data, and styling suggestions may see its outfits recommended more often when users test new looks in Doppl. A competitor with limited product data and imagery could be excluded from the experience entirely.

The takeaway for leaders here is that Doppl illustrates how AI may reshape online shopping into an interactive discovery experience. Fashion and lifestyle retailers should prioritize high-quality product data and imagery to remain competitive.

Food Mood

Food Mood is a recipe generator that combines ingredients and cooking styles to provide creative inspiration for meals.

Instead of entering exact recipes, users can describe their mood or inspiration and receive unique fusion-style ideas.

If rolled out and expanded, this could shift recipe discovery from rigid keyword searches to open-ended, experience-based prompts.

Screenshot from artsandculture.google.com/experiment/food-mood/,September 2025

Food Mood is less about finding the perfect “chicken pasta” recipe and more about encouraging users to experiment. For food publishers and recipe sites, the challenge will be ensuring their content is structured and tagged so it can be effectively integrated into these creative outputs.

Recipe publishers that rely on SEO traffic could see reduced visibility if users embrace AI-generated inspiration instead of searching for specific dish names. On the other hand, sites that invest in structured recipe data, nutritional information, and culinary storytelling may benefit by having their recipes pulled into Food Mood’s suggestions.

This being said, Food Mood is still experimental, and as the result below shows from my testing, it still needs some refinement around ingredient quantities and measurements.

The generative response to make a meal for one, combining the cuisines of Curaçao and Norway… The ingredients list might be off… (Screenshot from Food Mood, September 2025)

A food blog known for creative plant-based recipes might be highlighted when a user asks Food Mood for “a fun weekend dinner that feels indulgent but healthy.” If the content is tagged and structured correctly, it could be surfaced in ways traditional keyword targeting never allowed.

Food Mood shows how search may evolve toward inspiration-driven discovery. Recipe sites and food brands should prepare by enriching their content with detailed metadata that connects recipes to moods, occasions, and dietary preferences.

Talking Tours

Talking Tours is an active audio experiment from Google Arts & Culture that allows users to tour cultural landmarks in Street View.

Instead of passively looking at images, users can listen to narrated, AI-generated stories about what they are exploring.

This has the potential to change how people engage with cultural and travel content. Rather than relying solely on guidebooks or blog posts, users may interact with AI-driven narratives directly inside Google’s ecosystem. It offers an immersive layer that could shift attention away from traditional content publishers.

Screenshot from artsandculture.google.com/experiment/talking-tours/, September 2025

For travel businesses, the opportunity lies in being part of the authoritative content that fuels these AI tours. Travel agencies, tour operators, and cultural organizations that create structured, authentic content may find new visibility if their information is integrated. Without that presence, competitors or third-party providers could dominate the AI-driven storytelling.

A cultural travel company that produces detailed content about European landmarks might benefit from incorporating Talking Tours’ insights during a virtual tour of Rome. Without participation, their competitors may own the conversation.

This also offers would-be travellers the opportunity to explore landmarks and other key locations ahead of travelling, which could influence the comparison and deliberation phases of the decision-making process.

Talking Tours points to a future where immersive, AI-driven experiences shape travel planning. Travel brands should ensure their content is authoritative, structured, and ready to be used in AI-generated narratives.

Learn About

Learn About is an experiment that helps users learn new topics at their own pace using conversational AI. Acting like a digital tutor, it breaks down complex ideas into simple explanations and guides learners to further resources.

Screenshot from learning.google.com/experiments/learn-about/, September 2025

For education providers, this alters how learners find and engage with content. Instead of searching for “best beginner coding course,” a student might ask Learn About to “explain how websites work” and then follow guided prompts.

Learn About uses various YouTube and web results as sources, and from experimentation, it isn’t afraid to show older content and videos (even those with “for 2023” in the video title) if it believes the content and source are strong enough.

Educational publishers and online learning platforms may experience shifts in traffic if “Learn About” becomes a common entry point. Being cited in AI-driven tutoring sessions could become as valuable as traditional SEO discovery. Institutions that provide well-structured, authoritative, and trustworthy content stand to gain.

A site offering structured beginner-friendly coding lessons might be featured in Learn About when a user begins exploring “how to build a website.” If absent, a competitor may be the one shaping the learner’s first impression of the topic.

Learn About underscores the need for clear, structured, and authoritative educational content. Providers should optimize not only for keywords but also for AI-driven educational journeys.

Preparing For AI Experiments In Search

Google’s experimental features like Doppl, Food Mood, Talking Tours, and Learn About reveal how search may evolve from keyword-driven results to AI-guided discovery experiences beyond what we perceive as traditional search.

These experiments may not all become mainstream, but they indicate where search is heading. Businesses that begin preparing now will be better positioned if and when these ideas are rolled out more widely.

Is your organization ready to compete in a world where AI guides the first step of customer discovery?

More Resources:

Featured Image: insta_photos/Shutterstock

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Sep 11 2025

Amazon Experiences Drop In Google Search Visibility via @sejournal, @martinibuster

New data from the Audience Key content marketing platform indicates that Amazon’s visibility has suffered a significant drop. The decline follows two changes Amazon made to its presence in Google Shopping, although it is uncertain whether those changes are direct or indirect causes.

The first change was the discontinuation of its paid Shopping ads, and the second was the consolidation of its three merchant store names (Amazon, Amazon.com, and Amazon.com – Seller) into a single store identity, “Amazon.” These changes appear to have had a measurable effect on how often Amazon product cards appear in Google’s organic Shopping results.

Audience Key is a content marketing platform that fills a gap in competitive intelligence by tracking and reporting on Google’s organic product grid rankings at scale. This is a new product that has recently rolled out.

According to Audience Key:

“Across 79,000+ keywords, Audience Key’s first-of-its-kind tracking showed the effects of Amazon’s changes to its merchant feed — the approach initially wiped out 31% of its organic product card rankings. Weeks later, Amazon has now disappeared completely — creating a seismic shift that is immediately reshaping e-commerce SERPs and freeing up prime shelf space for rivals.”Tom Rusling, founder of Audience Key notified me today that Amazon has subsequently completely dropped out of the organic search results, beginning on August 18th.

Anecdotally, I’ve seen Amazon completely dropped out of Google’s organic product grids, including for search queries I know for certain they used to rank for and are now completely gone from the search engine results pages (SERPs).

Overall Impact

The most immediate change was the overall scale of Amazon’s presence. Before July 25, Amazon’s listings appeared in 428,984 organic product cards. After the change, that presence dropped to 294,983.

Before July 25: 428,984 product cards
After July 25: 294,983 product cards

Net change: -134,001 cards (31% decline)

This shows that Amazon’s move was not just a brand consolidation but also a large reduction in visibility. It is possible that the brand consolidation triggered a temporary drop in visibility because it’s such a wide-scale change.

Category-Level Changes

The reduction was not spread evenly. Some product categories were hit harder than others. Apparel had the steepest losses, while categories like Home Goods and Laptop Computers also fell sharply.

Smaller categories such as Tires and Indoor Decor declined more moderately, but all showed the same downward trend.

Apparel Category Experiences The Largest Declines

Apparel stands out as the category where Amazon saw the steepest reductions, with its presence cut by more than half across several tracked segments.

Below is the data I currently have, I’m waiting for clarification from Audience Key about whether the following apparel categories are more specific:

Apparel: 4,571 → 1,804 (-60%)
Apparel: 4,503 → 1,859 (-59%)
Apparel: 31,852 → 13,632 (-57%)
Apparel: 6,932 → 3,029 (-56%)

Several Other Major Categories Affected

The losses were also large in high-volume categories. Home Goods, Laptop Computers, and Outdoor Furnishings all saw reductions, while Business Supplies and Technology products also suffered visibility declines.

Business Supplies: 12,510 → 9,786 (-22%)
Home Goods: 133,717 → 73,833 (-45%)
Laptop Computers: 30,520 → 19,615 (-36%)
Outdoor Furnishings: 58,416 → 41,995 (-28%)
Scientific and Technology: 58,880 → 50,666 (-14%)

Smaller Categories Also Affected

Even niche verticals were affected, though the percentage losses were less severe than in Apparel or Home Goods. These declines show Amazon’s reductions were spread across both major and smaller categories.

Structures: 6,241 → 4,229 (-32%)
Tires: 3,063 → 2,609 (-15%)
Indoor Decor: 23,634 → 19,789 (-16%)
Indoor Decor (variant): 6,626 → 5,926 (-11%)

Merchant Store Consolidation

Another change came from how Amazon presented itself in Shopping results. Before July 25, the company appeared under three names: Amazon, Amazon.com, and Amazon.com – Seller. Afterward, only the unified “Amazon” label remained.

Total before consolidation (all three names): 428,984 product cards
After consolidation (single “Amazon”): 294,980 product cards

This simplified Amazon’s presence by unifying it under one name, but it also coincided with a decline in overall coverage.

Where Amazon Is At Today?

Even with the July drops in visibility, Amazon remained the most visible merchant in Google Shopping, with smaller visibility than before. But that’s not longer the case, the situation for Amazon appears to have worsened.

Audience Key speculated on what is going on:

“We thought the first chapter of this story was complete, but just as we prepared this study for publication, everything changed. Again. Our latest U.S. search data reveals a stunning shift: Amazon vanished from the organic product grids.

Whether this is a short-term anomaly or a more permanent new normal, only time will tell. We will continue to monitor and report on our findings. The sudden removal leaves us — and the industry — asking one big question: WHY???

That is certainly a topic for speculation.”

Audience Key speculates that Amazon may be withholding their product feed from Google or that this is a technical or strategic change on Amazon’s part.

One thing that we know about Google organic search is that large-scale changes can have a dramatic impact on search visibility. Audience Key has a unique product that is focused on tracking Google’s product grid, something that many ecommerce companies may find useful. They are apparently well-positioned to notice this kind of change.

Read Audience Key’s blog post about these changes:

Beyond Paid: The Hidden Organic Shockwave from Amazon’s Google Shopping Exit

Featured Image by Shutterstock/Sergei Elagin

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Sep 11 2025

The Download: AI’s energy future

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

Video: AI and our energy future

In May, MIT Technology Review published an unprecedented and comprehensive look at how much energy the AI industry uses—down to a single query. Our reporters and editors traced where AI’s carbon footprint stands now, and where it’s headed, as AI barrels towards billions of daily users.

We’ve just produced a short video to accompany that investigation. You can read the original full story here, and check out—and share— the full video on YouTube here.

AI is changing the grid. Could it help more than it harms?

The rising popularity of AI is driving an increase in electricity demand so significant it has the potential to reshape the grid. Energy consumption by data centers has gone up by 80% from 2020 to 2025 and is likely to keep growing. Electricity prices are already rising, especially in places where data centers are most concentrated.

Yet many people, especially in Big Tech, argue that AI will be, on balance, a positive force for the grid. They claim that the technology could help get more clean power online faster, run our power system more efficiently, and predict and prevent failures that cause blackouts. How much merit is there to that argument?

—Casey Crownhart

Three big things we still don’t know about AI’s energy burden

—James O’Donnell

Earlier this year, when my colleague Casey Crownhart and I spent six months researching the climate and energy burden of AI, we came to see one number in particular as our white whale: how much energy the leading AI models, like ChatGPT or Gemini, use up when generating a single response.

We pestered Google, OpenAI, and Microsoft, but each company refused to provide its figure for our article. But then this summer, after we published, a strange thing started to happen. They finally started to release the numbers we’d been calling for.

So with this newfound transparency, is our job complete? Did we finally harpoon our white whale? I reached out to some of our old sources, and some new ones, to find out. Read the full story.

MIT Technology Review Narrated: Google DeepMind has a new way to look inside an AI’s “mind”

We don’t know exactly how AI works, or why it works so well. That’s a problem: It could lead us to deploy an AI system in a highly sensitive field like medicine without understanding its critical flaws.But a team at Google DeepMind that studies something called mechanistic interpretability has been working on new ways to let us peer under the hood.

This is our latest story to be turned into a MIT Technology Review Narrated podcast, which we’re publishing each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Meta suppressed research into the harms young users face in VR
Two former employees told a Senate committee the firm did it to avoid regulatory scrutiny. (WP $)

2 The MAGA movement is full of AI skeptics
But the White House is ditching regulatory obstacles and trying to accelerate AI’s adoption. (FT $)

3 Pfizer says its new covid vaccine boosts immune responses fourfold
If you can get one, that is. (Ars Technica)
+ Americans who can’t access a booster are increasingly fearful. (The Guardian)
+ Vaccine guidance is incredibly confusing these days. (Vox)
+ Why limited access to covid vaccines isn’t all bad. (MIT Technology Review)

4 The EU will examine banning social media for under-16s
Following governments across Europe pushing for mandatory age restrictions. (Bloomberg $)

5 RFK Jr is going all-in on ChatGPT
All US health department employees have been given access to the tool. (404 Media)
+ Humans may be more likely to believe disinformation generated by AI. (MIT Technology Review)

6 An “AI-supported” coder won in a man vs machine hackathon
But AI tools seem to slow down some experienced human developers. (Wired $)
+ The second wave of AI coding is here. (MIT Technology Review)

7 Mark Zuckerberg is suing Meta
No, not that Mark Zuckerberg. (NYT $)
+ The bankruptcy lawyer is fed up with being mistaken for him. (The Guardian)

8 Apple’s new AirPods can translate languages in real time
Via a robotic voice in your ear. (Ars Technica)
+ A new AI translation system for headphones clones multiple voices simultaneously. (MIT Technology Review)

9 AI is threatening Latin America’s diverse music scenes
Fake songs are flooding streaming platforms and depriving artists of an income. (Rest of World)
+ How Pandora fumbled its streaming lead. (Fast Company $)
+ How to break free of Spotify’s algorithm. (MIT Technology Review)

10 Auction house Christie’s is axing its digital art division
But don’t worry—it’ll still sell you NFTs. (Cointelegraph)
+ I tried to buy an Olive Garden NFT. All I got was heartburn. (MIT Technology Review)

Quote of the day

“If you don’t lay the groundwork culturally for bringing in these stars, you’re going to end up burning a bunch of them out and pissing them off, and a bunch of them are going to quit and you’re going to waste millions of dollars.”

—Laszlo Bock, a tech industry adviser and former head of people operations at Google, points out where Meta’s AI division is going wrong to the Wall Street Journal.

One more thing

The $100 billion bet that a postindustrial US city can reinvent itself as a high-tech hub

On a day in late April 2023, a small drilling rig sits at the edge of the scrubby overgrown fields of Syracuse, New York, taking soil samples. It’s the first sign of construction on what could become the largest semiconductor manufacturing facility in the United States.

The CHIPS and Science Act was widely viewed by industry leaders and politicians as a way to secure supply chains, and make the United States competitive again in semiconductor chip manufacturing.

Now Syracuse is about to become an economic test of whether, over the next several decades, aggressive government policies—and the massive corporate investments they spur—can both boost the country’s manufacturing prowess and revitalize neglected parts of the country. Read the full story.

—David Rotman

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)

+ This 1981 Sony Trinitron TV is the last word in luxury.
+ It’s not just you—as we age, we really do become less adventurous musically.
+ It appears as though our human ancestors hibernated—but weren’t very good at it.
+ Did renowned painter Vermeer duplicate his own painting? You be the judge.

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Sep 11 2025

New Ecommerce Tools: September 10, 2025

This week’s rundown of new products and services from vendors to ecommerce merchants includes updates on AI tools, shipping, video editing, shopping assistants, international commerce, B2B platforms, and crypto-to-cash payments.

Got an ecommerce product release? Email releases@practicalecommerce.com.

New Tools for Merchants

ESW partners with Shopify to power international ecommerce. ESW, a global direct-to-consumer ecommerce platform for brands, has announced a strategic agreement with Shopify. The collaboration aims to empower enterprise Shopify merchants to scale, localize, and optimize their ecommerce presence in more than 200 markets worldwide.

ESW

OnTrac introduces multiple cross-country delivery services. OnTrac, a last-mile ecommerce delivery company, has unveiled three new coast-to-coast services. The company will launch Express Service with ClearJet, a hybrid air-and-ground service offering 2– and 3-day nationwide (U.S.) delivery. Second, OnTrac’s new deferred delivery service, Ground Essentials, offers transit times two days longer than the company’s standard ground service at discounted rates. Third, 7-Day Play, an enhancement of its current daily service, integrates predictive AI technology to manage delivery times.

PayPal and Venmo customers get access to Perplexity’s Comet browser. PayPal and Venmo customers in the U.S. and select global markets can noew receive early access to Perplexity’s AI-powered Comet browser. Comet offers an integrated AI assistant, native answer-focused search, product comparisons, and more. PayPal users in the U.S. can sign up for Perplexity Pro directly in the PayPal app. Venmo users can access the offer through the Venmo app.

Nuvei partners with Early Warning Services to deliver Paze online checkout. Nuvei, a unified platform for payment processing, has partnered with Early Warning Services to bring Paze, an online checkout tool, to merchants and consumers. Nuvei will integrate Paze checkout into its payments platform, enabling U.S. merchants to offer a streamlined checkout experience where consumers can use the credit cards they already have with participating financial institutions without needing to manually enter card details.

Paze

Adobe Premiere brings professional-quality video editing to iPhone for free. Video-editing platform Adobe Premiere is releasing a mobile app, Premiere on iPhone, enabling users to create professional-looking videos for free. The app features a multi-track timeline with vibrant colors and dynamic audio waveforms. Users can (i) trim, layer, and fine-tune with frame-accurate precision and no watermarks, (ii) generate audio and video assets, and (iii) get automatic captions with stylized subtitles, unlimited video and audio, text layers, support for 4K HDR, and more.

Ant International’s Bettr launches AI-powered lending service. Bettr, a provider of embedded financing and tech solutions under Ant International, has launched its AI-driven accounts receivable financing service to provide global ecommerce platforms with rapid and secure access to working capital. The AI system analyzes real-time business data, including invoices, sales history, and customer ratings, to instantly generate a credit risk assessment and provide loan offers tailored to each vendor.

Etsy introduces AI tools to support sellers. Etsy has introduced AI tools to help sellers save time and grow their businesses. An optional tool in the Search Visibility dashboard suggests clear listing titles that are likely to perform well in search. The AI Writing Assistant drafts messages to buyers. Etsy also utilizes AI in its search, recommendations, and shopping features. Buyers can now see quick, AI-powered highlights from reviews as well as delivery arrival estimates.

Zenbundle debuts its retail media platform for Shopify. Zenbundle, a Dublin-based startup with a mission to transform Shopify-powered stores into retail media platforms, is now available on the Shopify App Store. Zenbundle says it helps Shopify merchants automate shoppable campaigns, boost online sales, and unlock supplier-funded revenue at scale. The system analyzes shopper behavior in real-time, matches products with shoppable video and native placements, and publishes campaigns across Shopify storefronts.

Zenbundle

AI logistics startup Augment raises $85 million. Augment, an AI-powered logistics platform from the co-founder of shipping provider Deliverr, has raised $85 million in a Series A round led by Redpoint. Augment offers an AI assistant called “Augie” that automates tedious and repetitive work typically performed by freight shippers, carriers, and brokers. Augie can perform seven key tasks in the logistics process, including gathering and reviewing pricing bids, tracking packages, building a load by combining shipments, and collecting invoicing for timely billing.

Easyship integrates with the Shein marketplace. Easyship, a multi-carrier shipping software for global ecommerce, has integrated with the Shein marketplace, enabling sellers to sync orders, access discounted shipping rates, and automate global fulfillment directly through the Easyship platform. Shein sellers can leverage Easyship’s advanced shipping automation rules, tax and duty calculations, and cost-saving features. Sellers can access live, multi-carrier rates to automatically compare and select the cheapest, fastest, or best-value shipping option for every marketplace order.

Novatize launches Spine to streamline Shopify implementation for B2B. Novatize, a B2B commerce developer, has launched Spine, a tool that simplifies Shopify implementation for manufacturers, distributors, and wholesalers. According to Novatize, Spine includes features for complex B2B needs, such as real-time ERP-fetched pricing, account-based purchasing, multi-user access, and system integrations, as well as streamlined workflows for approvals, quotes, and shipping rules.

Anywhere Commerce launches crypto-to-cash payments platform. Anywhere Commerce, a provider of mobile and omnichannel point-of-sale payment tools, has launched its crypto-to-cash platform. The platform allows merchants to accept cryptocurrency and receive instant cash settlements in local currency. Transactions include encryption and authentication security layers and provide automatic crypto-to-cash settlement in local currency at the moment of sale, so that merchants never hold crypto exposure. The platform supports real-time payment rails, such as Pix (Brazil) and CoDi (Mexico).

Anywhere Commerce

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Sep 10 2025

Google Retiring Core Web Vitals CrUX Dashboard via @sejournal, @martinibuster

Google has announced that the CrUX Dashboard, the Looker Studio-based visualization tool for CrUX data, will be retired at the end of November 2025. The reason given for the deprecation is that it was not designed for “wide-scale” use and that Google has developed more scalable alternatives.

Why The CrUX Dashboard Is Being Retired

The CrUX Dashboard was built in Looker Studio to summarize monthly CrUX data. It gained popularity as Core Web Vitals became the de facto standard for how developers and SEOs measured performance.

Behind the scenes, however, the tool struggled to keep up with demand. According to the official Chrome announcement, it suffered “frequent outages, especially around the second Tuesday of each month when new data was published.”

The Chrome team concluded that while the dashboard showed the value of CrUX data, it was not built on the right technology.

Transition To Better Alternatives

To address these issues, Google launched the CrUX History API, which delivered weekly instead of monthly data, allowing more frequent monitoring of trends. The History API was faster and more scalable, leading to adoption by third-party tools.

In 2024, Google introduced CrUX Vis, which was more scalable and faster. Today, in 2025, CrUX Vis receives four to five times more users than the CrUX Dashboard, showing that users are increasingly moving to the newer tool.

What the Change Means for Users

Chrome will shut down the CrUX Connector to BigQuery in late November 2025. When this connector is removed, dashboards that depend on it will stop updating. Users who want to keep the old dashboard will need to connect directly to BigQuery with their own credentials. The announcement explains that the CrUX Connector infrastructure is unreliable and requires too much monitoring to maintain, which is why investment has shifted to the History API and CrUX Vis.

Some users have asked Google to postpone the shutdown until 2026, but the announcement makes it clear that this is not an option. Although the dashboard and its connector will be retired, the underlying BigQuery dataset will continue to be updated and supported. Google stated that it sees BigQuery as a valuable, longer-term public dataset.

Check out the CrUIX Vis tool here.

Read the original announcement:

CrUX Dashboard deprecation

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Sep 10 2025

GEO: How To Position Your Agency As An AI Search Authority

This post was sponsored by Visto. The opinions expressed in this article are the sponsor’s own.

Clients keep asking a new question: “Are we visible in AI search?”

This is the reality: Google’s AI Overviews are reducing organic traffic by 30-70% for many businesses.

In fact, we’re seeing that SEO agencies that incorporate GEO (Generative Engine Optimization) tactics into their SEO strategy and offerings are charging $4,000/month for these additional menu services.

However, when it comes to GEO, a newly evolved and still-evolving branch of SEO, answering the AI visibility question is:

Less about grand strategy.
More about a quick field check.

But if you skip the check and jump straight to fixes, you risk solving the wrong problem.

Phase 1. Perform An AI Visibility Audit To Confirm If There Is A Visibility Gap

Start with a simple AI Visibility Audit:

Select five to 10 key phrases that align with the business’s goals.
Search those phrases across Google’s AI Overviews, Bing Copilot, Perplexity, and ChatGPT.
Look at the AI answer first, not the classic blue links.
Do you show up? Are you cited? Which competitors are visible and cited? Notate this for each phrase.
Notate down which competitors are cited and where any links point; take screenshots to showcase in any presentations.

Once you identify which phrases you display and those you do not, you can begin to build a comprehensive audit, repeating the steps as you would for keyword research or, traditionally, People Also Ask research.

The Easy Way: Use this AI Visibility audit and bring the snapshot to your next client call. It gets you out of the “we think” zone and into “here’s what we saw today.”

Phase 2. Interpret Your AI Visibility From The Audit Results

Once you have your audit results in hand, it’s time to determine where you stand:

Highly visible: Your brand is named inside the answer. Great. Assess what’s working, and expand upon it.
Partially visible: Your content fuels the answer, but the brand is missing. That erodes authority over time.
Absent: The answer engines are leaning on other sources. That’s your gap, and your opportunity.

Notice how some of this is traditional ranking talk, and other facets are new.

So, it’s time for a new lens here.

Look at GEO as more of a traffic channel, as opposed to a new technique: Do we show up in the answer people actually read?

This is where agencies need to act fast. If you’re not helping clients with GEO now, they’ll find someone who will.

Phase 3. Showcase The Real Problem Behind Falling Organic Traffic

In this step, it’s time to connect the dots for everyone outside of your SEO team.

How will clients or bosses handle a change to your reporting?

What is the best way to convince a stakeholder that they need additional SEO services to stay ahead during the GEO boom?

How To Clarify The AI Addition To SEO For Clients & Stakeholders

This is how to turn a vague “traffic is down” conversation into “here’s where we’re missing in the answer and what we’ll fix.”

Within your audit presentation, the AI Search findings should follow this structure:

Rule out serving issues that can tank crawl or clicks. Do not include these in the report during this part of the conversation.
Split branded from non-branded terms, as AI answers often cluster around certain intents. Display this information broken out.

Pro Tip: Leverage a side-by-side comparison. The left side could include the AI answer with your brand’s status. The right side a quick look at on-site metrics for those same topics.

Phase 4. Consider The Perfect Mix Of Traditional SEO & GEO

Once your audit is approved, and a contract is in place to expand your SEO offerings to include GEO techniques, it’s time to apply the perfect mix of traditional SEO and GEO to improve visibility in the areas you’ve identified in the audit.

From a high level, there are two constraints that change the game, especially when adding GEO tactics to your SEO offerings:

Speed (“time to first token”). AI systems have to answer fast. Crawlers are impatient, so pages that surface the right answer early tend to win the tie.
Context window. Models skim and compress. Think skim-friendly, middle-school clarity: straightforward headings, unambiguous entities, and no padding.

That’s why old habits can backfire. You’re optimizing for clarity, entities, and extractability, not density.

How Do I Approach SEO & GEO The Right Way?

The way we think about it is this: if SEO is about ranking for keywords, GEO is about showing up for prompts.

How Does A Prompt Differ From Keywords?

When someone types a prompt, modern AI doesn’t just “look up” one thing. It:

Breaks the prompt into sub-questions.
Runs background searches.
Shortlists a small set of pages worth crawling right now.

From our perspective, that’s the bridge between SEO and GEO: your classic search visibility still matters, but only as a feeder into which sources the AI decides to read.

What To Focus On When Incorporating GEO Into Your SEO Strategies

You will see overlaps here; that’s because there are slight changes to traditional methods that you’ll need to consider when optimizing for answer engines.

What to focus on, from a traditional SEO angle:

On-page SEO: answer-first structure, clean headings, scannable evidence.
Technical SEO (or GEO for Answer Engines): Fast paths to answers; crawlability that supports quick fetches.
Content gaps your competitors are filling in AI answers. We’re consistently surprised by how often the “nearly there” pages win. If the AI crawler already understands a page, one sharp paragraph and a clearer H1 can push it over the top.
Link analysis to strengthen credible citations.
Competitor analysis of who’s being named in answers (and why).
Sentiment analysis to catch how your brand is described when it’s mentioned.

What to focus on, from the GEO perspective:

The semantic space AI explores vs. the entity mapping in your content.
Technical GEO (or SEO for Answer Engines): Fast paths to answers; crawlability that supports quick fetches.
Content gaps your competitors are filling in AI answers.

The Easy Way: Visto can consolidate these checks into a single workflow, allowing you to baseline quickly and track progress without needing a dozen tools.

Phase 5. Implement GEO Tactics Into Your SEO Strategy To Regain & Grow Visibility

Step 1. Provide Answers Upfront

Within traditional SEO, this refers to improving readability.

Your goal here is to give the answer engine what it needs as quickly as a good support team would:

Lead your most important pages with the plain-English answer your buyer is after.
One or two sentences up top, then the detail and sources.

If the reader needs to scroll to find the point, the crawler will likely give up at that same point.

Step 2. Strengthen Entity Clarity

Next, make the page unambiguous with consistent:

Product names.
Categories.
Specs.
Simple schema to help the system map your entity to the right concepts.

Think of this as labeling the shelves in a small shop. If the labels are clear, the model finds what it came for without guessing.

Step 3. Implement Technical GEO

Then handle the technical side of GEO. AI crawlers care about time to the first useful token, so shorten the path to the answer.

Tighten titles and H1s, move key facts above the fold, and keep interstitials from blocking the first read. The AI crawler has a limited context window and reads fast. Help it skim the right lines.

Step 4. Assess Comparison Coverage

If your customers compare options, publish a straightforward comparison that highlights only the differences people ask about.

What we’ve seen is that honest tables and short “who it’s for” notes get cited more than glossy positioning.

Step 5. Manage Links & Sentiment

Finally, reinforce what supports the page. Link credible sources to the version you want cited. Check how your brand is described in the existing answers. If the tone is off, correct the original source you’re referencing.

Then, regularly review your metrics: presence, named mentions, and competitor share. GEO isn’t a set-and-forget channel, so a light monthly review helps prevent drift.

Visto’s platform automates much of this tracking, giving agencies the tools to prove value with measurable, prompt-level insights and easy-to-share reports.

Examples: Learn From Early GEO Adopters Who Are Rebuilding Traffic

“In the first two quarters, we have seen an 88% year-over-year increase in organic traffic and a 42% YoY increase in unique pageviews from organic traffic.“

Agencies using a platform like Visto’s see their clients’ brands referenced more in AI answers after tightening entities and updating a handful of high-value pages.

The agencies succeeding are those positioning themselves as AI search authorities now, not waiting to see how things shake out.

Get Started With Visto

Visto helps agencies measure AI visibility and manage the work.

Built specifically for marketing agencies, the platform shows where your brand appears in AI answers, summarizes citations across engines, and highlights the pages most likely to move the needle.

Visto provides:

Direct access to GEO experts who understand agency needs.
Consistent product updates aligned with the latest AI search trends.
The ability to influence the roadmap with your input.
Education and support to confidently lead your clients through the AI shift.
Sales enablement tools that are purpose-built for marketing agencies to prospect clients.
A focus on actionability and optimization, in addition to visibility and analytics.

Don’t wait for your clients to ask why they’re invisible in AI search. Position your agency as the AI search authority they need right now.

Special Offer: For SEJ readers, sign up for three months free access and start prospecting and serving clients.

Image Credits

Featured Image: Image by Visto. Used with permission.

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Sep 10 2025

Google Ads Rolls Out New Creative & Omnichannel Tools via @sejournal, @MattGSouthern

Google is rolling out creative and omnichannel updates across Ads and YouTube.

The tools are designed to help you keep assets fresh, connect store and online demand, and plan spend across key shopping windows.

What’s New

Creative: Asset Studio, Product Studio, And Imagen 4

A new suite of generative tools is coming to Asset Studio, with asset generation in Performance Max and Demand Gen powered by Imagen 4.

In Product Studio, you’ll be able to swap product scenes at scale, replace backgrounds, turn images or text into short videos, and get proactive campaign concept suggestions.

See an example of a campaign concept suggestion below:

Image Credit: Google

Google says the new tools can speed up testing while keeping brand direction intact.

Omnichannel & YouTube

Demand Gen can now optimize for total sales across online, in-app, and in-store conversions. You can also use local offers to show nearby shoppers in-store promotions.

On YouTube, a Creator partnerships hub is meant to simplify brand-creator collaborations, and the YouTube Masthead is now shoppable so you can feature specific products tied to your goals.

Insights And Budgets: Plan 3–90 Day Bursts

New AI-powered insights in Google Merchant Center aim to surface actionable tips. Google is also expanding campaign total budgets from Demand Gen and YouTube to include Search, Performance Max, and Shopping.

You can set a start date, end date, and a total budget for periods between 3 and 90 days, and Google’s systems will pace spend to match peaks in demand.

Loyalty: Member-Only Offers

Google is introducing loyalty features that let you display member-only pricing and shipping benefits, with retention goals available in loyalty mode for Performance Max or Standard Shopping.

Looking Ahead

If your holiday plan spans multiple bursts, these tools can help you keep creative fresh, capture store demand, and avoid end-of-month pacing surprises.

Start by aligning product feeds and assets, then test omnichannel optimization and short budget windows around your key dates.

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