I’m thrilled to share that Google Posts now includes features that support scheduling and multi-location publishing within Google Business Profiles. These updates are designed to make it easier for us to manage our Google Posts, whether they are for our businesses or clients.
Scheduling. One exciting new feature when adding a Google Post within our Google Business Profiles is the option to “schedule this post.” We can now select the exact date and time when we want our posts to go live.
Lisa Landsman from Google shared on LinkedIn, “Plan your entire week or month in advance! You can now schedule your Google Posts to go live automatically at the perfect time.”
Multi-location publishing. If you, like me, manage several locations for a business, you’ll find the new multi-location feature incredibly convenient. It allows us to quickly copy Google Posts to some or all of our locations with just a click. Lisa Landsman explained, “Easily create a single post and apply it instantly to multiple business locations in one click.”
What it looks like. Here’s a GIF that shows this functionality in action:
Why we care. I care about these updates because I know how busy businesses can be. Often, we don’t have the time to pause everything just to create a timely Google Post about an upcoming event or important message. Now, we can schedule these posts in advance and copy them effortlessly across locations we manage.
As Lisa Landsman from Google pointed out, “We know the upcoming holiday season is a crucial, and hectic, time for your business. It’s also your biggest opportunity to get your events, offers, and updates in front of potential customers who are actively searching.”
I’m thrilled to share some exciting news with you! Profound is rolling out a new App Language Selector, giving all of us the ability to use the platform in over 30 different languages. This feature is currently in beta and represents a significant milestone in our global expansion, following the success of Zero Click London.
With this launch, we’re doubling down on our promise to create a multilingual and accessible experience for teams not just in Europe, but around the globe. Whether you’re collaborating internationally or simply prefer working in your native tongue, Profound is now more user-friendly than ever.
I recently came across a fascinating study highlighting how seasonality adjustments can actually backfire for advertisers during Black Friday, driving up costs and reducing efficiency.
A thorough analysis over three years, involving up to 6,000 advertisers, indicates that using Google’s seasonality bid adjustments during Black Friday and Cyber Monday (BFCM) often undermines efficiency, despite the platforms recommending them.
The big picture. Smart Bidding models are crafted to foresee predictable retail surges. Optmyzr analyzed tens of billions of impressions between 2022 and 2024, finding that advertisers who avoided seasonality adjustments usually had better efficiency metrics.
Without adjustments, Smart Bidding:
Recognized the BFCM conversion lift independently
Increased bids rationally
Maintained stable or improved ROAS, particularly in 2024
With adjustments: CPCs surged faster than the actual conversion rates, eroding efficiency.
Reality check: Google doesn’t need your “heads up.” Seasonality adjustments prompt Google to expect a conversion rate rise and to bid accordingly. If your prediction is off—and it usually is—Smart Bidding overshoots.
For example:
You predict a +50% CVR lift
The actual lift is +40%
This results in an overbid of about 7.1%
During BFCM’s high sales volumes, even minor mistakes become costly quickly.
The data: 3 years of the same story
1. Smart Bidding already adjusts for the CVR spike
2022: +17.5%
2023: +11.9%
2024: +7.5%
No additional guidance needed.
2. CPC inflation doubles with adjustments
Across all observed years, CPCs increased approximately twice as much when a seasonal adjustment was used.
3. ROAS drops significantly
Advertisers relying on Smart Bidding saw stable or improved ROAS, whereas those who intervened suffered double-digit losses.
The one exception: “Volume at all costs.” If the aim is pure revenue growth, disregarding margins, seasonality adjustments can be beneficial.
Revenue lifts were notably higher with adjustments:
2022: +50.5% vs. +25.0%
2023: +52.8% vs. +30.3%
2024: +39.9% vs. +33.8%
Efficiency may decline, but volume certainly increases.
When seasonality adjustments make sense. They’re useful when Google doesn’t have prior signals, like one-off or niche events.
Good for:
One-time flash sales
Email-only offers
Surprise clearance sales
Niche seasonal spikes
Not recommended for:
Black Friday
Cyber Monday
Christmas
Valentine’s Day
Any event with a predictable historic pattern
Why we care. Google already recognizes the significance of Black Friday. Smart Bidding is trained with years of BFCM data and can detect conversion rate spikes independently. Overriding this can lead to excessive bidding, increased CPCs, and reduced ROAS, so many marketers might be wasting their budget during this crucial week.
By recognizing when Smart Bidding has an adequate signal, advertisers can avoid expensive errors, maintain efficiency, and reserve seasonality adjustments for when they add true value.
Bottom line. Smart Bidding effectively manages major retail holidays. Seasonality adjustments often bring more chaos than benefits during predictable retail peaks. Keep them for unique, brand-specific events that Google can’t predict.
Smart move: Trust the algorithm — use tools like anomaly alerts, pacing monitors, and bid caps for control without conflicting with Smart Bidding’s core models.
During Black Friday, I’ve noticed many retailers, including myself, wasting substantial advertising budgets on Google Shopping ads. The main issue arises when these ads are still running for products that have already sold out, clearly demonstrating a pressing need for real-time stock management.
As we all know, Black Friday marks the peak of the retail season. However, it’s disheartening to find that so many brands, myself included, end up losing money on Google Shopping ads for items no longer available in inventory.
The problem: The ads continue to run even after items are out of stock, incurring cost-per-click charges with no possibility of conversion. Through a comprehensive study by ShoppingIQ involving 500 global retailers, it was revealed that a staggering 97% kept paying for clicks on items no longer in stock, sometimes persisting for 24–48 hours.
Why I care. Out-of-stock ads are not just a financial drain; they also skew campaign performance and disrupt algorithmic learning. When conversion rates plummet for unavailable products, it damages rankings, reduces ROI, and hampers future bidding strategies.
Example: Take Argos, for instance; they reportedly advertised items that were out of stock during Black Friday, leading to frustrated customers and depleted ad budgets.
Stock update refresh rates:
~24 hours: 90% of retailers
6–23 hours: 5%
48 hours: 2%
Other: 3%
Retailers’ response: Some companies, such as Mamas & Papas, have started leveraging ShoppingIQ’s real-time stock technology. This helps them focus ads solely on products that are actually available. Samantha Dabek, Senior Digital Marketing Manager, shares that they have managed to cut unnecessary costs and ensure advertising is targeted toward in-stock products.
The bigger picture: Google Shopping commands around 75% of US retail search spending. However, the default settings let out-of-stock ads run unchecked. ShoppingIQ strongly advocates for retailers to seek more transparency and control from Google to prevent wasted spending.
Bottom line: For those of us running high-stakes campaigns during Black Friday and other peak times, real-time stock management is essential. Otherwise, each wasted click represents money lost.
As I explore the latest updates to ChatGPT, I’m excited to share that it now incorporates more images into its answers, bringing a fresh, multimodal approach to search. This enhancement makes images just as vital as text for exploring brands and products.
OpenAI has unveiled this visual upgrade, which pulls images from the web to enrich answers about a variety of topics, such as people, places, and products. It’s a fascinating development that shifts ChatGPT from providing simple text responses to offering a more interactive search experience.
How it works. With this update, ChatGPT becomes more than just a text generator. It now offers a search experience similar to what I’m used to:
Images will appear when they add clarity to the information.
These images, sourced from the web, align with the most relevant text.
If I’m curious about an image, clicking on it expands it to its original size and shows the source.
Where it’s live. The rollout of this update is occurring globally, and I’ve noticed it gradually becoming available across all ChatGPT plans that I access:
I’ve used it on web, iOS, and Android platforms.
It’s important to note that it only works with responses created by GPT 5.1.
Why we care. I realize that search is evolving to be more multimodal, integrating text, images, videos, and audio. Beyond ensuring that my brand is part of AI-driven replies, it’s crucial to consider how our visuals show up when ChatGPT responds to queries.
I recently discovered a game-changing update from Google that’s bound to catch the attention of many advertisers. Google’s Performance Max now allows me to upload video files directly in the “Edit assets” panel, simplifying the campaign setup process significantly. What’s even better? I don’t need a YouTube channel or Shared Library for this.
Here’s the scoop. This handy feature pops up as an “Upload” tab in the Google Ads UI, making it super easy to add video assets during PMax campaign creation. Just a simple drag-and-drop, and I’m set to move on, especially helpful if I’m new to video advertising.
In the YouTube ad setup, I’ll find a clear, highlighted box prompting me to drop in my video file, smoothing out what used to be a more complicated process.
How does it work? These video files are stored in a Google-managed channel, not on my personal YouTube account. While they’re usable in ads, they don’t function like typical YouTube uploads, which might affect how I manage my content.
Why it matters to me. This update is a boon if I don’t have a YouTube presence or need a quick way to upload video assets. However, I should be mindful of the trade-offs: I’ll have no analytics, no remarketing capabilities, no metadata access, and crucially, I won’t own the assets long-term. It’s a convenient option for quick setups, but I must proceed with caution and ideally upload through a proper brand channel when possible.
Important limitations. Using this method imposes several restrictions:
No YouTube Analytics
No remarketing audiences
No metadata editing
No custom thumbnails
No ability to appeal rejections or restrictions
No brand-channel presence or asset ownership
How I found out. The first mention of this update came from Web Marketing Consultant Dario Zannoni, who shared it on LinkedIn. I appreciated his insights into how this could change my advertising approach.
The takeaway. This feature is a great shortcut if I’m in a hurry or don’t have a robust YouTube setup. Still, maintaining best practices by using my official brand channel ensures I preserve analytics, gather audience data, and retain creative control.
Recently, I’ve noticed Google has started automatically linking YouTube channels with Google Ads accounts. This innovation allows advertisers like me to quickly tap into valuable audience data, though it does require careful permission management.
When Google’s system detects a strong connection between a YouTube channel and a Google Ads account, it takes action by linking them. This gives us richer audience signals without us having to do a manual setup.
What’s happening now? Google will set up these links automatically if a strong relationship is identified, notifying us 30 days in advance. This email notification allows us to decide whether to opt out or connect sooner.
How does it work?
During the 30-day period, if no one opts out, the link will be completed automatically. If I manage both accounts, I can even connect them immediately. There’s flexibility here, too, as I can always adjust permissions or unlink later if needed.
Why this matters to us. This development simplifies how we, as advertisers, access YouTube audience data. It makes it straightforward to target viewers and construct data segments. However, it also introduces uncertainties about control over our assets and the permissions we’ve set.
Benefits for advertisers. Once linked, I can:
Use YouTube interactions to run more effective ads.
Leverage organic views and earned actions for performance insights.
Create data segments from how audiences engage with my channel.
Consider channel engagement as conversion activities, like subscriptions.
Limitations I’ve noticed
Channel owners gain no control over the actual Google Ads account.
Copy or edit capabilities for channel videos are not given to advertisers.
If personalized ads are disabled, audience data reports are also turned off.
Restrictions on Video Ads Certification (VAC) are still applicable; removal of these is specific to the linked Ads account.
Managing these links. If I, as an admin, choose to opt out, I can easily do so through the links provided in the notification emails from Google. If opted out, the link won’t be made. Meanwhile, manual linking can always be done via the traditional Google Ads settings menu.
Initial discovery. The new auto-linking feature was first highlighted by Hana Kobzová, founder of PPC News Feed. More on this can be read here.
Final thoughts. With Google’s new auto-linking, we as advertisers can enjoy less setup hassle and better YouTube performance insights. However, it’s crucial to monitor our notifications to ensure that data sharing aligns with our privacy preferences and company policies.
When I reflect on the evolution of SEO and SEM, I realize just how much these fields have transformed alongside search technologies. As Gary Illyes from Google once pointed out, embracing change is vital, even when it’s hard to accept.
Gary Illyes reacted to a Microsoft Bing article by Fabrice Canel and Krishna Madhavan about AI Search and its impact on conversion measurement. He made a strong statement about the future of search, something I deeply resonate with.
Coevolve. On LinkedIn, Gary emphasized, “SEM and SEO will need to coevolve with search, just like it has for the past 30 years.” It’s a clear reminder that adaptation is a constant necessity in our field.
I’ve witnessed many SEOs and SEMs adapt to these shifts, much like the path SEO has taken since its inception as a service. The most successful professionals continue to evolve.
SEO is not dead. The notion that SEO is fading away is not new. I’ve heard it countless times, yet SEO remains a critical component of digital marketing, continuously evolving with technological advancements.
The challenge is real. As search features change, it’s vital to embrace this evolution to ensure continued success. Those ready to accept and adapt to these changes will find new opportunities.
Why we care. I encourage others to engage with the new search features. Understand them, learn how they can draw users to your content, and figure out how to turn these interests into conversions.
Change isn’t easy or comfortable, but it’s an inevitable part of the future that we must prepare for.
In my experience, the open web often feels like the Wild West, especially in recent times. Many creators, myself included, have watched as our hard work is scraped and fed into large language models without any hint of permission.
This situation has become a free-for-all, leaving website owners with almost no means to opt out or safeguard their creative endeavors. There have been attempts to address this, such as Jeremy Howard’s llms.txt initiative. Much like robots.txt helps us manage site crawlers, llms.txt aims to provide guidelines for AI companies’ crawling bots.
However, a promising new protocol is on the horizon, potentially granting site owners like myself more control over how AI firms utilize our content. It looks like this might become part of robots.txt, allowing us to set definitive rules around AI system access and usage.
IETF AI Preferences Working Group
In response to this issue, the Internet Engineering Task Force (IETF) began the AI Preferences Working Group earlier this year in January. Their mission is to craft standardized, machine-readable rules to empower site owners to articulate AI usage preferences for their content.
Since its inception in 1986, the IETF has established core Internet protocols like TCP/IP, HTTP, DNS, and TLS. Now, they’re laying down foundations for the open web’s AI era. Leading this group are co-chairs Mark Nottingham and Suresh Krishnan, joined by figures from Google, Microsoft, Meta, and more.
Of particular interest is Google’s involvement via Gary Illyes, who is part of this working group.
“The AI Preferences Working Group will standardize building blocks that allow for expressing preferences about how content is collected and processed for Artificial Intelligence (AI) model development, deployment, and use.”
What the AI Preferences Group is Proposing
This group aims to deliver new standards that empower site owners to determine how LLM-powered systems can utilize their open web content.
A standard track document detailing a vocabulary to express AI-related preferences, independent of content association methods.
Standard track document(s) that explain how to associate these preferences with content using IETF-defined protocols and formats, for example, Well-Known URIs and HTTP response headers.
A standard approach for reconciling multiple preference expressions.
At the time of writing, nothing is set in stone yet. Early documents, however, provide a sneak peek into potential standards.
This working group published two crucial documents in August.
These documents propose significant updates to the Robots Exclusion Protocol (RFC 9309), suggesting new rules and definitions enabling site owners to specify AI content usage permissions.
How It Might Work
AI systems on the web are categorized and assigned standard labels. Whether a directory will exist for site owners to identify system labels remains unclear.
Currently, the defined labels include:
search: for indexing/discoverability
train-ai: for general AI training
train-genai: for generative AI model training
bots: for all types of automated processing, such as crawling and scraping
For each label, you can set two values:
y to allow
n to disallow.
I found it interesting that these rules can be applied at the folder level and customized for different bots. In robots.txt, they’re implemented using a new Content-Usage field, akin to existing Allow and Disallow fields.
Here’s an example robots.txt that the working group shared in their document:
Explanation Content-Usage: train-ai=n indicates that no content on this domain may be used for training any LLM model, whereas Content-Usage: /ai-ok/ train-ai=y permits model training using content within the /ai-ok/ folder.
Why Does This Matter?
There’s significant buzz about llms.txt within the SEO community and its use alongside robots.txt. Yet, no AI company has confirmed adherence to these guidelines, and Google disregards llms.txt.
Website owners, including myself, crave more explicit control over how AI companies leverage our content—be it for training models or RAG-based responses.
I feel that the IETF’s new standards signify positive progress. With Illyes as a contributing author, I remain optimistic that once finalized, companies like Google will embrace these standards, respecting new robots.txt rules during content scraping.
Recently, I’ve noticed more Google Ads appearing directly within Google’s AI Mode results. This change suggests that Google’s test has been quietly advancing, signaling the emergence of a new ad space in Google Search.
Here’s what I’ve observed. Back in May, Google confirmed they were testing ads in AI Mode on desktop, and these sightings have notably increased:
One notable instance was when Greg Sterling shared a screenshot related to an HVAC repair query, marking the first time he noticed an AI Mode ad in the wild.
Brodie Clark soon after replicated this behavior, declaring “the time has come” as he provided multiple screenshots showing ads within the generated answers.
Additionally, Barry Schwartz reported ongoing instances of users encountering these AI Mode ads on Search Engine Roundtable.
Why this matters to us. The inclusion of ads within AI Mode represents a substantial shift in how Google’s merging sponsored content with AI-generated answers. This development could significantly alter visibility, click-through rates, and the overall search experience. For early adopters, this offers opportunities for reduced competition, novel formats, and greater engagement. It’s becoming clearer that AI Mode is transforming into a legitimate advertising channel rather than just an experiment.
Reading between the lines. This expansion indicates Google’s move to integrate ads within AI experiences, likely preceding a broader rollout in Search.
The bottom line. Starting as a small test, this feature appears more commonly now. Advertisers should prepare for AI Mode to evolve into a mainstream advertising surface in Google Search.
