I’ve noticed a peculiar issue with the Google Search Console’s page indexing report—it seems to be missing data prior to December 15th. Many of us are likely scratching our heads over this, and it appears to be some kind of reporting glitch affecting everyone.
So far, Google hasn’t provided any comments on this widespread issue. The absence of this data is creating challenges for all of us trying to analyze our website performance accurately.
What it looks like. To give you a clearer picture, Vijay shared a screenshot on X. You can verify this by checking your own page indexing report, and you’ll likely see the same gaps.
Why it matters to us. I plan to check back in the next few days to see if the data returns or if Google releases any updates about this problem. Currently, we’re all in the same boat, unable to access the prior data, which hinders our ability to run accurate reports and analyses.
Let’s hope Google resolves the issue soon, enabling us to resume our regular reporting and analysis for those missing data ranges.
I discovered that the Google Merchant Center is currently examining a problem that affects Feeds. This issue has been flagged on their public status dashboard, raising concerns for those of us who rely on these Feeds for product listings and Shopping ad performance.
Here’s what you need to know:
Incident began: Feb. 4, 2026, at 14:00 UTC.
Latest update (Feb. 20, 14:43 UTC): “We’re investigating reports of an issue with Feeds. We will provide more information shortly.”
Status: Service disruption
The notification you see is on the Merchant Center Status Dashboard, which closely monitors the availability of Merchant Center services.
Why is this important? Feeds are the backbone of product listings for Shopping ads and free listings. Any issues here can affect product approvals, updates, or their visibility in campaigns tied to retail inventory.
What to keep an eye on: Google has yet to clarify the extent, cause, or expected resolution timeline. If you’re experiencing any delay or disapproval in feed processing, I suggest keeping a close watch on the dashboard for updates.
The takeaway: Any disruption in feed processing can lead to a decline in ecommerce performance. As retail advertisers, we should continually check diagnostics and campaign delivery until we get more information.
I recently discovered that Google is changing how it attributes app campaign conversions. Instead of relying on the date when someone clicks on an ad, Google now ties the conversion to the actual install date of the app.
What’s Changing: Previously, Google linked conversions to the ad interaction date. Now, they’ll match the day of the app installation, aligning more closely with Mobile Measurement Partners (MMPs) like AppsFlyer and Adjust.
Why This Helps:
– This change reduces discrepancies between Google Ads and MMP dashboards, making life easier for mobile marketers who often deal with mismatched data.
– With Google’s old 30-day attribution window, many conversions were reported too late, hindering Smart Bidding’s access to the timely signals necessary for effective learning.
– By using the install date for attribution, Google’s algorithms will receive fresher, more accurate data, which could speed up optimization cycles and stabilize performance.
Why We Care: While it might seem technical, this change significantly affects how Google’s machine learning optimizes campaigns. The previous 30-day gap between ad clicks and conversion credit was a bottleneck. Now, Google’s machine learning gets the conversion data just when it needs it—right with the app install.
This shift should lead to smarter bidding and faster campaign optimization, helping to resolve the frustrating discrepancies between Google Ads and MMP reports. If you’ve ever been puzzled by inconsistencies between Google and platforms like AppsFlyer or Adjust, this update directly addresses that problem.
Between the Lines: Most advertisers don’t adjust their attribution window settings, leaving Google’s default 30-day window as is. Unfortunately, this was delaying crucial conversion signals that machine learning needs for improved bidding.
The Bottom Line: This seemingly minor tweak in attribution logic could have a significant impact on app campaign performance. I encourage mobile advertisers to monitor their data in the coming weeks for any shifts in conversion reports and optimization behaviors.
First Spotted: This update was first noticed by David Vargas, who shared a message about it on LinkedIn.
Are you looking to amplify the reach of your next press release? Employ this innovative framework to transform your announcements into exceptional successes for your clients.
I had given up on press releases years ago, convinced they had lost their impact. But a conversation with a trusted friend and mentor totally shifted my viewpoint.
She revealed that while the days of organic features from merely publishing a press release were over, great results were still attainable. Her secret? She effectively pitched relevant journalists, using the press release’s key points as leverage once it went live.
Skeptically, I gave her strategy a shot. The results were incredible, leading to multiple organic features for my client.
My immediate thought was, “If such a minor tweak yielded these results, imagine the possibilities with a full-fledged strategy.”
This method I’m about to share is the culmination of a year packed with trials and enhancements to amplify the efficacy of my press releases.
Although it demands more research, planning, and execution, the pay-off is exponential and undoubtedly justifies the additional effort.
Research Phase
You’ll start with what your client wants to communicate to the world. Here’s how to proceed:
Identify related topics like economic impact, related technology, legislation, and key industry players.
Locate media coverage in the past quarter on these topics in outlets where you’d like your client featured.
Compile a list with links to each article, its main points, the journalist’s contact information, and links to related social media posts they’ve shared.
Organize the list by how closely it aligns with your client’s message.
Planning Phase
Draft your client’s press release, using opportunities to cite articles from your compiled list with relevant links.
Ensure each citation is relevant and adds value to your message. Aim for three to five citations to maintain focus.
Simultaneously, create personalized pitches to the journalists whose articles you’re citing, ensuring they align with their beat and previous coverage.
Briefly mention their past work — a short, recognizable quote suffices. Include links to current social media discussions showcasing interest in the topic. Conclude with your press release link and a specific call to action.
Avoid trying to win favor through citations. Instead, illustrate the link between your client’s message and their prior coverage, making it easier for journalists to revisit the topic from a fresh angle.
Execution Phase
Initially, interact with journalists on your list via social media for several days. Comment on recent posts, especially those covering your target topics. This starts building name recognition and rapport.
Once your press release is published, promptly send your pitches to the three to five journalists you cited, including the live release link. (I recommend linking to the most credible syndication rather than the wire service version.)
Subsequently, approach other pertinent journalists, customizing each pitch with relevant points from their past articles that align with your client’s message.
Track all earned organic features. While some may emerge from the press release publication itself, more commonly, they result from direct pitches, opening new doors for visibility.
Review each new feature for references to other articles from your compiled list. Then approach the original article’s journalist, referencing the new piece that relates to or enhances their work.
The Psychology Behind Why This Works
This strategy taps into two potent psychological principles:
Everyone likes to see their work acknowledged, validating their viewpoint in the process.
Building on a previously covered topic is less labor-intensive than starting from zero, appealing to journalists’ needs to streamline their work.
This framework will elevate your next press release, garnering more media coverage, increasing client satisfaction, and achieving impactful results with minimal effort — truly shining as a professional.
I’ve recently discovered an intriguing feature in Google Ads that provides advertisers, like myself, with enhanced visibility into how our landing page images can be automatically converted into ad creatives in Performance Max (PMax) campaigns. It’s fascinating to see the potential of these visuals beyond their traditional use.
Imagine having the ability to transform your website’s visuals into dynamic ads. By opting into this feature, Google can extract images from your landing pages and present them as ads. As I set up my campaigns, I can preview these automated creations before they go live, which grants me significant control over my advertising strategy.
Why this matters to us. With PMax, our website isn’t just a storefront but a vital component of our ad strategy. Any image—from banners to product visuals—can appear across platforms like Search, Display, YouTube, or Discover. This update offers a clear understanding of how our landing page images could become part of these campaigns, helping us visualize our potential reach.
I no longer have to speculate how Google might utilize my site’s visuals. Now, I can foresee, scrutinize, and regulate what content is utilized in my ads. This feature enables me to refine my landing pages and align them with my campaigns, minimizing surprises.
Between the lines: While automation is growing, so is the need for careful creative oversight. This update serves as a crucial tool for advertisers, ensuring we’re informed about what content goes live before it happens.
Bottom line: Our websites have transcended their roles as mere landing pages; they’re now integral to our ad engines, driving our marketing efforts forward.
First seen. Digital Marketer Thomas Eccel was among the first to highlight this development on LinkedIn, showcasing a practical example.
I find Reddit’s new pilot program fascinating. They’re using AI to transform our beloved community recommendations into interactive, shoppable product carousels within search results.
What’s happening: Right now, a select group of U.S.-based folks, including myself, might notice these exciting product carousels popping up in search results whenever our queries suggest a buying intent, like when searching for “best noise-canceling headphones” or “top budget laptops.”
These carousels conveniently appear right at the bottom of the search results, showcasing pricing, images, and direct links to retailers. The coolest part? These products are derived from actual Reddit posts and comments rather than existing ad inventories.
For those of us interested in consumer electronics, Reddit also collects data from specific Dynamic Product Ads (DPA) partner catalogs.
How it works: The AI cleverly identifies queries with purchase intent, scans through relevant Reddit discussions for any product mentions, and arranges them into tidy, shoppable cards. When a card catches my attention, I can simply tap it to gain more information or be redirected to a retailer.
Why we care: These shopping carousels are a real game-changer for advertisers. They bring products to the spotlight right when consumers, like me, are contemplating a purchase and seeking peer approval. Unlike typical ads, here these products merge with Reddit’s trusted community vibe, making them seem more like genuine recommendations than mere advertisements.
For brands already involved in Dynamic Product Ads on Reddit, this development offers a seamless pipeline from community buzz directly to action.
Between the lines: Reddit is really onto something big here, doing what many competitors have struggled to achieve—using organic, community-driven content as the foundation for a shopping experience, rather than depending solely on targeted advertising.
This approach is ingenious because consumers, myself included, are becoming warier of sponsored content. Reddit’s value relies on authentic community engagement, and by integrating that into a shopping feature, it elevates their credibility beyond traditional retail media networks.
The big picture: Retail media is booming, and platforms catering to audiences with high purchase intent are in a race to claim their portion of the pie. With Reddit’s increasing search traffic, especially after partnering with Google, this development seems like the perfect next step.
The bottom line: Reddit is testing how it can turn search intent directly into transactions, making it smoother for users like me to transition from recommendations to purchase, all while staying within the community context that fosters trust.
Recently, I’ve noticed something fascinating — ChatGPT ads have started making their presence felt, and they’re not hiding in the background. They’re right there from the start, catching users’ attention straight away.
It seems OpenAI’s approach to advertising within ChatGPT is evolving. Currently, ads pop up for signed-in desktop users in the U.S. based on findings from AI ad intelligence firm Adthena. It’s quite a shift from earlier expectations.
The biggest twist? Many thought ads would only show up after longer conversations. However, that’s not the case. Imagine asking, “What’s the best way to book a weekend away?” and seeing a sponsored message immediately. That’s the reality.
What do these ads look like? They’re marked by a brand favicon and a clear “Sponsored” label, a departure from the initial designs OpenAI shared publicly.
Why does this matter to us? ChatGPT ranks among the top sites globally, and advertising integrated into its responses indicates a major development in AI monetization. It could change how brands connect with consumers right when they’re seeking information.
Reading between the lines, the fact that ads are triggered by single, intent-driven prompts shows OpenAI sees these interactions as valuable ad space. This is a significant move for advertisers figuring out where to allocate their budgets.
The bottom line is clear — the era of ChatGPT advertising has quietly kicked off. As a marketer, I now understand it’s not about questioning the need for an AI search strategy anymore. It’s about asking if I’m already behind.
The first glimpse of these ads came from Adthena’s CMO, Ashley Fletcher, shared on LinkedIn.
I’ve recently discovered some exciting updates in Google Analytics that I think are real game-changers for marketers like me. They’ve introduced AI-generated insights on the Home page, alongside a new cross-channel budgeting feature in beta. These changes help me quickly identify key performance shifts and optimize how I spend my paid budgets.
What’s happening. The introduction of these AI-generated insights right on the Home screen means I can now see the top three changes that occurred since my last visit. This includes notable updates, performance anomalies, and those tricky seasonality trends—all without sifting through the detailed reports.
This feature is all about speed and convenience. Instead of spending time manually scanning dashboards, it offers me a quick snapshot of what’s changed and why it could matter.
Cross-channel budgeting (Beta). As a marketer, I find the new cross-channel budgeting feature incredibly useful. It allows me to track performance across various paid channels and optimize my investments based on the results I get.
While access to this feature is currently limited, I’m eagerly looking forward to broader availability in the near future.
Why I care. These updates make it easier and faster for me to spot performance changes and directly link insights to budget decisions. The automated insights reduce the time I spend combing through reports, while cross-channel budgeting helps me allocate spending more strategically across various channels.
Together, these features streamline my analysis process and enhance how quickly my team and I can adapt our strategies.
Bottom line. In combining Generated insights and cross-channel budgeting, Google Analytics aims to reduce reporting friction and improve decision-making. This means faster answers and more control over how I allocate budgets across channels.
I’m thrilled to share that Google has just launched its Scenario Planner, an incredibly user-friendly, no-code tool. This planner empowers me to transform Marketing Mix Model insights into practical budget and ROI forecasts effortlessly.
Google’s new Scenario Planner allows me to test various budget scenarios and forecast ROI using Meridian’s marketing mix model, all without requiring any data science expertise.
What’s new? The Scenario Planner makes complex MMM outputs accessible and actionable:
Intuitive, code-free interface: Testing different budget allocations and viewing ROI estimates is a breeze without needing to write any code.
Forward-looking planning: I can simulate investment scenarios and stress-test strategies, which moves beyond mere retrospective reporting.
Digestible insights: These technical model outputs are visualized in clear, easy-to-understand formats, making them highly usable for my strategy decisions.
Why do we care? With these predictive marketing insights at my fingertips, I can test budgets, foresee potential returns, and adjust campaigns in real-time. This helps me plan smarter and optimize every dollar I spend.
Closing the MMM actionability gap. The Scenario Planner effectively bridges the “usability gap” long existing in Marketing Mix Models, which previously required specialized skills. According to Harvard Business Review, nearly 40% of organizations face challenges in turning MMM outputs into actionable decisions.
Bottom line. By combining the rigor of MMM with an easy-to-use, interactive interface, Scenario Planner empowers me to plan more strategically, optimize spending, and make confident, data-driven decisions without having to rely on technical experts.
I’ve recently come across an interesting study highlighting a significant shift in search click dynamics. It turns out that text ad clicks have dramatically increased year over year, while the traditional organic clicks in major verticals have taken a sharp decline.
This transformation isn’t solely due to AI Overviews for sure. Google’s expansion of paid search real estate is playing a pivotal role here. In the U.S., data reveals a steep drop in classic organic click share across product categories like headphones, jeans, greeting cards, and online games between January 2025 and January 2026.
The numbers are quite telling. Classic organic click share fell significantly across these categories, making way for text ads, which emerged as the biggest beneficiaries, gaining a notable share of clicks.
Why does this shift matter to us? As digital marketers, it’s no longer just AI-powered features that we’re contending with. Text ads have won substantial ground, capturing about one-third of the clicks in several product categories. For brands seeing a dip in organic visibility, increasing paid efforts seems to be a necessary strategy.
Numbers tell the story. When diving into four main verticals, text ads showed consistent click-share increases. Classic organic lost between 11 to 23 percentage points, while text ads gained anywhere from 7 to 13 percentage points across the board. Paid click share has doubled in several key product categories.
Comprehensive breakdown: Classic organic click shares have seen a year-over-year decline across all verticals. For instance, headphones lost dramatically, shrinking from 73% to 50%, and even organic-heavy areas like online games dropped by double digits. Such declines emphasize the urgent need for many brands to reassess their search strategies.
Data shows that text ads inched forward share-wise in every industry examined. For instance:
Headphones: Rose from 3% to 16%
Online games: Up from 3% to 13%
Jeans: Climbed from 7% to 16%
Greeting cards: Up from 9% to 16%
Moreover, Product Listing Ads (PLAs) are further supporting this change in product sectors:
Headphones: Increased from 16% to 36%
Jeans: Went from 18% to 34%
Greeting Cards: Rose from 10% to 19%
AI Overviews have seen a diverse impact. While the presence of Google AI Overviews on SERPs has certainly increased, the extent varies significantly across sectors:
Headphones: 2.28% → 32.76%
Online games: 0.38% → 29.80%
Greeting cards: 0.94% → 21.97%
Jeans: 2.28% → 12.06%
Zero-click searches remain significant but stable. Even though the overall zero-click rates haven’t seen dramatic changes, online games have witnessed a noticeable uptick:
Headphones: 63% (unchanged)
Jeans: Down from 65% to 61%
Online games: Up from 43% to 50%
Greeting cards: Increased from 51% to 53%
Brands adapt by increasing paid presence. In the headphones market, for example, companies like Amazon boosted paid clicks by 35% despite losing organic traffic, while Walmart increased theirs nearly sixfold.
In the jeans sector, Gap saw a 137% growth in paid clicks, rising to become the leading paid player.
For online games, CrazyGames quadrupled its paid clicks, and Arkadium entered the paid scene after a significant drop in organic clicks.
These shifts have led to a self-reinforcing cycle, as pointed out by Aleyda Solis, the study’s author. Organic share declines, competition increases, and brands continuously boost their paid-search budgets.
Study insights. This study was conducted using Similarweb data, thoroughly examining the SERP composition and click patterns for the top 5,000 U.S. queries in the areas of headphones, jeans, and online games, alongside the top 956 greeting card-related queries. Over time, it has highlighted a marked shift in click distribution among classic organic results, text ads, PLAs, zero-click searches, and AI Overviews.
If you’re curious about deeper insights, you can check out the full study by Aleyda Solis.
