Do Faces Help YouTube Thumbnails? Here’s What The Data Says via @sejournal, @MattGSouthern

A claim about YouTube thumbnails is getting attention on X: that showing your face is “probably killing your views,” and that removing yourself will make click-through rates jump.

Nate Curtiss, Head of Content at 1of10 Media, pushed back, calling that kind of advice too absolute and pointing to a dataset that suggests the answer is more situational.

The dispute matters because thumbnail advice often gets reduced to rules. YouTube’s own product signals suggest the platform is trying to reward what keeps viewers watching, not whatever earns the fastest click.

Where The “Remove Your Face” Claim Comes From

In a recent post, vidIQ suggested that unless you’re already well-known, people click for ideas rather than creators, and that removing your face from thumbnails can raise CTR.

Curtiss responded by calling the claim unsupported, and linked to highlights from a long-form report based on a sample of high-performing YouTube videos.

The debate is one side arguing faces distract from the idea, while the other argues faces can help or hurt depending on what you publish and who you publish for.

What The Data Says About Faces In Thumbnails

The report Curtiss linked to describes a dataset of more than 300,000 “viral” YouTube videos from 2025, spanning tens of thousands of channels. It defines “outlier” performance using an “Outlier Score,” calculated as a high-performing video’s views relative to the channel’s median views.

On faces specifically, the report’s top finding is that thumbnails with faces and thumbnails without faces perform similarly, even though faces appear on a large share of videos in the sample.

The differences show up when the report breaks down the data:

  • In its channel-size breakdown, it finds that adding a face only helped channels above a certain subscriber threshold, and even then the lift was modest.
  • In its niche segmentation, it finds that some categories performed better with faces while others performed worse. Finance is listed among the niches that performed better with faces, while Business is listed among the niches that performed worse.
  • It also reports that thumbnails featuring multiple faces performed best compared to single-face thumbnails.

What YouTube Says About Faces In Thumbnails

Even if a thumbnail change increases CTR, YouTube’s own tooling suggests the algorithm is optimizing for what happens after the click.

In a YouTube blog post, Creator Liaison Rene Ritchie explains that the thumbnail testing tool runs until one variant achieves a higher percentage of watch time.

He also explains why results are returned as watch time rather than separate CTR and retention metrics, describing watch time as incorporating both the click and the ability to keep viewers watching.

Ritchie writes:

“Thumbnail Test & Compare returns watch time rather than separate metrics on click-through rate (CTR) and retention (AVP), because watch time includes both! You have to click to watch and you have to retain to build up time. If you over-index on CTR, it could become click-bait, which could tank retention, and hurt performance. This way, the tool helps build good habits — thumbnails that make a promise and videos that deliver on it!”

This helps explain why CTR-based thumbnail advice can be incomplete. A thumbnail that boosts clicks but leads to shorter viewing may not win in YouTube’s testing tool.

YouTube is leaning into A/B testing as a workflow inside Studio. In a separate YouTube blog post about new Studio features, YouTube describes how you can test and compare up to three titles and thumbnails per video.

The “Who” Matters: Subscribers vs. Strangers

YouTube’s Help Center suggests thinking about audience segments, such as new, casual, and regular viewers. Then adapt your content strategy for each group rather than treat all viewers the same.

YouTube suggests thinking about who you’re trying to reach. Content aimed at subscribers can lean on familiar cues, while content aimed at casual viewers may need more universally readable actions or emotions.

That aligns with the report’s finding that faces helped larger channels more than smaller ones, which could reflect stronger audience familiarity.

What This Means

The practical takeaway is not to “put your face in every thumbnail” or “go faceless.”

The data suggests faces are common and, on average, not dramatically different from no-face thumbnails. The interesting part is the segmentation: some topics appear to benefit from faces more than others, and multiple faces may generate more interest than a single reaction shot.

YouTube’s testing design keeps pulling the conversation back to viewer outcomes. Clicks matter, but so does whether the thumbnail matches the video and earns watch time once someone lands.

YouTube’s product team describes this as “Packaging,” which is a concept that treats the title, thumbnail, and the first 30 seconds of the video as a single unit.

On mobile, where videos often auto-play, the face in the thumbnail should naturally transition into the video’s intro. If the emotional cue in the thumbnail doesn’t match the opening of the video, it can hurt early retention.

Looking Ahead

This debate keeps resurfacing because creators want simple rules, and YouTube performance rarely works that way.

The debate overlooks an important point that top creators like MrBeast emphasize. It’s more about how you show your face than whether you show it at all.

MrBeast previously mentioned that changing how he appears in thumbnails, like switching to closed-mouth expressions, increased watch time in his tests.

The 1of10 data supports the idea that faces in thumbnails aren’t a blanket rule. Results can vary by topic, format, and audience expectations.

A better way to look at it is fit. Faces can help signal trust, identity, or emotion, but they can also compete with the subject of the video depending on what you publish.

With YouTube adding more testing to Studio, you may get better results by validating thumbnail decisions against watch-time outcomes instead of relying on one-size-fits-all advice.


Featured Image: T. Schneider/Shutterstock

Ironman, Not Superman via @sejournal, @DuaneForrester

I recently became frustrated while working with Claude, and it led me to an interesting exchange with the platform, which led me to examining my own expectations, actions, and behavior…and that was eye-opening. The short version is I want to keep thinking of AI as an assistant, like a lab partner. In reality, it needs to be seen as a robot in the lab – capable of impressive things, given the right direction, but only within a solid framework. There are still so many things it’s not capable of, and we, as practitioners, sometimes forget this and make assumptions based on what we wish a platform is capable of, instead of grounding it in the reality of the limits.

And while the limits of AI today are truly impressive, they pale in comparison to what people are capable of. Do we sometimes overlook this difference and ascribe human characteristics to the AI systems? I bet we all have at one point or another. We’ve assumed accuracy and taken direction. We’ve taken for granted “this is obvious” and expected the answer to “include the obvious.” And we’re upset when it fails us.

AI sometimes feels human in how it communicates, yet it does not behave like a human in how it operates. That gap between appearance and reality is where most confusion, frustration, and misuse of large language models actually begins. Research into human computer interaction shows that people naturally anthropomorphize systems that speak, respond socially, or mirror human communication patterns.

This is not a failure of intelligence, curiosity, or intent on the part of users. It is a failure of mental models. People, including highly skilled professionals, often approach AI systems with expectations shaped by how those systems present themselves rather than how they truly work. The result is a steady stream of disappointment that gets misattributed to immature technology, weak prompts, or unreliable models.

The problem is none of those. The problem is expectation.

To understand why, we need to look at two different groups separately. Consumers on one side, and practitioners on the other. They interact with AI differently. They fail differently. But both groups are reacting to the same underlying mismatch between how AI feels and how it actually behaves.

The Consumer Side, Where Perception Dominates

Most consumers encounter AI through conversational interfaces. Chatbots, assistants, and answer engines speak in complete sentences, use polite language, acknowledge nuance, and respond with apparent empathy. This is not accidental. Natural language fluency is the core strength of modern LLMs, and it is the feature users experience first.

When something communicates the way a person does, humans naturally assign it human traits. Understanding. Intent. Memory. Judgment. This tendency is well documented in decades of research on human computer interaction and anthropomorphism. It is not a flaw. It is how people make sense of the world.

From the consumer’s perspective, this mental shortcut usually feels reasonable. They are not trying to operate a system. They are trying to get help, information, or reassurance. When the system performs well, trust increases. When it fails, the reaction is emotional. Confusion. Frustration. A sense of having been misled.

That dynamic matters, especially as AI becomes embedded in everyday products. But it is not where the most consequential failures occur.

Those show up on the practitioner side.

Defining Practitioner Behavior Clearly

A practitioner is not defined by job title or technical depth. A practitioner is defined by accountability.

If you use AI occasionally for curiosity or convenience, you are a consumer. If you use AI repeatedly as part of your job, integrate its output into workflows, and are accountable for downstream outcomes, you are a practitioner.

That includes SEO managers, marketing leaders, content strategists, analysts, product managers, and executives making decisions based on AI-assisted work. Practitioners are not experimenting. They are operationalizing.

And this is where the mental model problem becomes structural.

Practitioners generally do not treat AI like a person in an emotional sense. They do not believe it has feelings or consciousness. Instead, they treat it like a colleague in a workflow sense. Often like a capable junior colleague.

That distinction is subtle, but critical.

Practitioners tend to assume that a sufficiently advanced system will infer intent, maintain continuity, and exercise judgment unless explicitly told otherwise. This assumption is not irrational. It mirrors how human teams work. Experienced professionals regularly rely on shared context, implied priorities, and professional intuition.

But LLMs do not operate that way.

What looks like anthropomorphism in consumer behavior shows up as misplaced delegation in practitioner workflows. Responsibility quietly drifts from the human to the system, not emotionally, but operationally.

You can see this drift in very specific, repeatable patterns.

Practitioners frequently delegate tasks without fully specifying objectives, constraints, or success criteria, assuming the system will infer what matters. They behave as if the model maintains stable memory and ongoing awareness of priorities, even when they know, intellectually, that it does not. They expect the system to take initiative, flag issues, or resolve ambiguities on its own. They overweight fluency and confidence in outputs while under-weighting verification. And over time, they begin to describe outcomes as decisions the system made, rather than choices they approved.

None of this is careless. It is a natural transfer of working habits from human collaboration to system interaction.

The issue is that the system does not own judgment.

Why This Is Not A Tooling Problem

When AI underperforms in professional settings, the instinct is to blame the model, the prompts, or the maturity of the technology. That instinct is understandable, but it misses the core issue.

LLMs are behaving exactly as they were designed to behave. They generate responses based on patterns in data, within constraints, without goals, values, or intent of their own.

They do not know what matters unless you tell them. They do not decide what success looks like. They do not evaluate tradeoffs. They do not own outcomes.

When practitioners assign thinking tasks that still belong to humans, failure is not a surprise. It is inevitable.

This is where thinking of Ironman and Superman becomes useful. Not as pop culture trivia, but as a mental model correction.

Ironman, Superman, And Misplaced Autonomy

Superman operates independently. He perceives the situation, decides what matters, and acts on his own judgment. He stands beside you and saves the day.

That is how many practitioners implicitly expect LLMs to behave inside workflows.

Ironman works differently. The suit amplifies strength, speed, perception, and endurance, but it does nothing without a pilot. It executes within constraints. It surfaces options. It extends capability. It does not choose goals or values.

LLMs are Ironman suits.

They amplify whatever intent, structure, and judgment you bring to them. They do not replace the pilot.

Once you see that distinction clearly, a lot of frustration evaporates. The system stops feeling unreliable and starts behaving predictably, because expectations have shifted to match reality.

Why This Matters For SEO And Marketing Leaders

SEO and marketing leaders already operate inside complex systems. Algorithms, platforms, measurement frameworks, and constraints you do not control are part of daily work. LLMs add another layer to that stack. They do not replace it.

For SEO managers, this means AI can accelerate research, expand content, surface patterns, and assist with analysis, but it cannot decide what authority looks like, how tradeoffs should be made, or what success means for the business. Those remain human responsibilities.

For marketing executives, this means AI adoption is not primarily a tooling decision. It is a responsibility placement decision. Teams that treat LLMs as decision makers introduce risk. Teams that treat them as amplification layers scale more safely and more effectively.

The difference is not sophistication. It is ownership.

The Real Correction

Most advice about using AI focuses on better prompts. Prompting matters, but it is downstream. The real correction is reclaiming ownership of thinking.

Humans must own goals, constraints, priorities, evaluation, and judgment. Systems can handle expansion, synthesis, speed, pattern detection, and drafting.

When that boundary is clear, LLMs become remarkably effective. When it blurs, frustration follows.

The Quiet Advantage

Here is the part that rarely gets said out loud.

Practitioners who internalize this mental model consistently get better results with the same tools everyone else is using. Not because they are smarter or more technical, but because they stop asking the system to be something it is not.

They pilot the suit, and that’s their advantage.

AI is not taking control of your work. You are not being replaced. What is changing is where responsibility lives.

Treat AI like a person, and you will be disappointed. Treat it like a syste,m and you will be limited. Treat it like an Ironman suit, and YOU will be amplified.

The future does not belong to Superman. It belongs to the people who know how to fly the suit.

More Resources:


This post was originally published on Duane Forrester Decodes.


Featured Image: Corona Borealis Studio/Shutterstock

The Top 10 Digital Marketing Trends For 2026 via @sejournal, @gregjarboe

As we head into the new year, the age of experimentation is giving way to the age of execution. The past few years have been about “Can we do it?” – generative AI, the decline of cookies, retail media networks (RMNs), shoppable video, immersive experiences. Now, the question is: “Are we doing it, and doing it well?”

I’m going to walk through the top 10 digital marketing trends that I believe every forward-looking marketer must own in 2026. These aren’t just buzzwords; they reflect profound shifts in how consumers behave, how platforms operate, and how marketers must integrate strategy across data, media, and creativity.

What you’ll see: Conversational search rewriting SEO; video turning fully into commerce; privacy and data ownership as competitive advantage; retail media networks moving from niche to mainstream; creators and communities driving co-creation; AI becoming the operating system of marketing; measurement morphing as attribution crumbles; immersive gamification emerging; and above all, the human edge – the talent and culture that will decide who wins.

Let’s dive in, trend by trend.

1. Conversational Search Redefines SEO

The evolution of search is accelerating from keyword-based queries to conversational queries, away from clicks to answers inside the engine, and from “search” to “wherever people ask questions.” Platforms such as Google LLC (with AI Overviews), Bing Copilot, and other generative-search interfaces are rewriting what “visibility” means.

Search Everywhere Optimization – influence audiences in all the places they go to consume content about your topic – is no longer optional.

From the stats side: Digital marketing industry growth is forecast at a ~13.9 % CAGR over the next years.

For SEO practitioners: Shift from creating pages for keyword rankings to creating authoritative answer-centered content, structured with schema, designed for featured snippets, voice devices, and even generative AI-powered answer boxes. Also, anticipate more “zero-click” scenarios where users get answers without visiting your site.

Takeaway: Optimize for intent, structure for conversational and multimodal search, and measure outcomes beyond clicks (e.g., brand lift, FAQ visibility, conversational voice assistant triggers).

2. The Video-Commerce Boom

Short form, live video, interactive video – the convergence of video and commerce is now in full swing. Social platforms long treated video as engagement; now they’re treating it as transactional.

From recent stats: An IAB study found that 86% of advertisers are already using or plan to use generative AI for video ad production, and projected adoption suggests Gen AI-created video ads will represent ~40 % of all video ads by 2026.

In parallel, social commerce revenues continue to climb, for example, via live-shopping, shoppable posts, and in-stream checkout.

For brands: The key is to treat video not just as storytelling but as a direct path to purchase. That means interactive elements, product overlays, live shopping, shoppable end cards, integration with ecommerce platforms. And from a measurement perspective: Tie views to actions (add-to-cart, check-out) rather than just vanity metrics (views, likes).

Takeaway: Convert video from brand engagement to commerce engagement. Build video assets with embedded purchase triggers and assign them full-funnel measurement.

3. The Privacy-First Data Revolution

The demise of the third-party cookie, increased regulation, and heightened consumer sensitivity around data mean you must look inward: Your first-party data, consent-based profiling, and data architecture become your competitive center.

Recent forecasts by WPP Media suggest global digital advertising will hit north of US$1 trillion in 2025, with digital representing 73.2% of global ad revenue. And according to EMARKETER’s forecast from May 2025, “BUS advertisers are expected to allocate 66% of their digital budget to mobile in 2025.”

What this means: If you rely solely on third-party data or on open-web cookies for targeting and measurement, you’re exposed. You need to build a “data spine” – consent capture, a robust customer data platform (CDP), conversion event APIs (such as from paid platforms), identity resolution, and integrate offline + online signals.

Takeaway: Make first-party data and measurement architecture a foundational pillar of your 2026 strategy. Without it, media investment and optimization will degrade rapidly.

4. Retail Media Networks Go Mainstream

Once the playground of major ecommerce players, retail media networks (RMNs) are now becoming central to brand media planning. Because they combine rich first-party purchase or transaction data with premium placement, they offer one of the few “full-funnel” channels where exposure, consideration, and conversion can be directly tied to real SKU-level outcomes.

According to recent reporting by Business Insider, RMN ad spend is projected to reach roughly $62 billion in 2025, representing about 17.9% of all digital media spend – and the expectation is that share will exceed 20% in 2026.

What this means for marketers: You cannot treat RMNs as an afterthought or “just another display buy.” They deserve full-funnel planning, dedicated measurement (e.g., via conversion APIs and offline attribution), and coordination with your broader media mix. If you’re still viewing RMNs as tactical or experimental, then you risk lagging behind brands that build internal capabilities now.

Takeaway: Build your RMN strategy today. Integrate product data, media planning, and measurement, and align with ecommerce/pricing/product teams to maximize return on investment (ROI).

5. The Creator Economy Evolves Into Co-Creation

Influencer marketing has matured. In 2026, the shift is from paying creators to post, to co-creating with creators – product, campaign, community. Creators are becoming strategic partners, not simply reach vehicles.

Academic research confirms that influencer marketing remains important, yet the landscape is shifting toward deeper partnerships and ownership of creative strategy. Brands will increasingly structure programs where creators ideate product features, create limited-edition lines, or participate in campaign planning. The value: authenticity, niche affinity, and stronger performance than generic sponsorship.

Takeaway: Shift from “influencer as amplifier” to “creator as partner.” Embed creators in product, marketing, and measurement cycles, and treat them as co-owners of the brand experience.

6. Community + Authenticity = The New Brand Moat

In 2026, audiences don’t just want to buy; they want to belong. And they demand authenticity. That means brand engagement built on community, and authenticity built on internal voices (employees, leadership) and genuine brand purpose.

Reports highlight that consumers increasingly seek interaction, transparency, and ethics in brand communications.

From a marketing operational standpoint: Companies will invest more in owned channels (forums, apps, micro-communities), user-generated content, peer-to-peer (P2P) mechanisms, and internal advocacy (employee social, leadership content).

Takeaway: Build and nurture community; activate internal voices; make authenticity measurable (engagement, membership retention, referral), not just “brand good feeling.”

7: AI As The Strategic Operating System

We often talk about AI in creative terms – generative text, images, videos. But the true breakthrough in 2026 is AI as the operating system behind marketing: analytics, optimization, media buying, workflow automation, customer journeys.

According to Reuters, media powerhouse Meta Platforms aims to fully automate advertising with AI by end of 2026. Brands may soon supply a product image and budget and let the AI build the ad, target it, optimize it.

Gartner also emphasizes that marketing’s future is built around data prepared for automated interactions.

For SEO professionals, digital marketers, and content writers: The decision is no longer “Should we use AI?” but “How do we govern, integrate and scale AI across planning, creative, measurement and optimization?” It means human-in-the-loop becomes essential – humans set strategy, guard for bias, ensure brand safety – while AI executes at scale.

Takeaway: Treat AI as your marketing OS. Design your workflows, data architecture, and governance accordingly. Upskill teams accordingly (see Trend 10).

8. Relearning ROI Through Marketing Mix Modeling

With traditional attribution (last click, multi-touch) collapsing under the weight of privacy, walled gardens, and cross-device fragmentation, marketing mix modeling (MMM) is regaining prominence as the lens through which brands measure business impact.

According to stats on EMARKETER, “by 2026, programmatic methods will account for 90% of all digital display ad spending worldwide,” And given these volumes, brands need robust measurement frameworks that go beyond platform-provided attribution.

Open-source tools such as Meta’s Robyn, or other MMM solutions, are being deployed to link media spend to business outcomes – revenue, margin, customer lifetime value. For 2026, you should build or refine your MMM engine and ensure it integrates both online and offline, as well as walled-garden signals.

Takeaway: Invest in MMM infrastructure, align media teams with finance/analytics, and report marketing performance in business terms (incremental lift, ROI), not just vanity metrics.

9. Immersive Experiences And Gamification Redefine Engagement

The boundary between entertainment, engagement, and commerce continues to blur. Augmented reality (AR), virtual reality (VR), gamified campaigns, live-interactive formats – all move marketers beyond static ad formats into memory-creating experiences.

A 2025 Digital Media Trends survey by Deloitte Insights shows that hyperscale social-video platforms are reshaping consumption habits, decidedly moving away from passive to interactive.

For brands: It’s no longer enough to show an image of a product and hope for clicks. Successful immersive programs will incorporate tangible utility (e.g., AR try-ons, live quiz/gamified product launches, metaverse showroom visits) and strong measurement frameworks (engagement → store visits → purchases).

Takeaway: Allocate a portion of media/experience budget to immersive, interactive formats; prioritize real utility and tie back to conversion metrics, not just “wow” experiences.

10. The Human Edge: Upskilling For An AI Era

At the heart of all these shifts is your team. Technology moves fast; people and culture move slower. In 2026, the brands that win will be those who invest in training, hybrid talent, decision-making agility, and cross-disciplinary skills (data, creative, media).

A McKinsey report found that while 92% of companies plan to boost AI investments in the next three years, only 1% consider themselves fully mature, having AI deeply integrated into their operations and delivering significant business results.

So, your 2026 mandate: Build your internal marketing capability around three pillars: data literacy (understanding analytics, measurement, first-party data), AI fluency (how to use, govern, and scale AI), and cross-channel orchestration (media, product, commerce, owned-community). Without that, your strategy may be robust on paper but fragile in execution.

Takeaway: Make upskilling, talent, and culture as important as technology and media. Build a team that can move quickly, learn continuously, and collaborate across functions.

Conclusion: The Age Of Integrated Authority

What ties these trends together? Two words: integrated authority. Marketers in 2026 must move beyond channel silos (search vs. social, media vs. commerce, data vs. creative) and build integrated systems that deliver unified experiences. At the same time, they must earn authority – through first-party data, community-based trust, creator partnerships, and measurable business impact.

As you plan and execute your 2026 marketing strategy:

  • Treat media as conduit to business outcomes (not just impressions).
  • Treat data as capital (not just input).
  • Treat AI as engine (not just experiment).
  • Treat measurement as proof (not just dashboard).
  • Treat talent and culture as differentiation (not just overhead).

The brands and teams that master this discipline will not only keep pace, but they will also define the next wave of digital marketing. The question isn’t which of these trends you pick; it’s how deeply you embed them in your organization and operations.

So, here’s to 2026, the year where strategy becomes execution, complexity becomes clarity, and digital marketing becomes truly business-driven.

While others may see new things and declare, “We’re toast,” we will continue to analyze, synthesize, and examine the top 10 digital marketing trends and declare, “We’re on it.”

More Resources:


Featured Image: beast01/Shutterstock

Redirection For Contact Form 7 WordPress Plugin Vulnerability via @sejournal, @martinibuster

A vulnerability in the popular WordPress Contact Form 7 plugin addon installed in over 300,000 websites enables attackers to upload malicious files and makes it possible for them to copy files from the server.

Redirection For Contact Form 7

The Redirection for Contact Form 7 WordPress plugin by Themeisle is an add-on to the popular Contact Form 7 plugin. It enables websites to redirect site visitors to any web page after a form submission, as well as store information in a database and other functions.

Vulnerable To Unauthenticated Attackers

What makes this vulnerability especially concerning is that it is an unauthenticated vulnerability, which means that an attacker doesn’t need to log in or acquire any level user privilege (like subscriber level). This makes it easier for an attacker take advantage of a flaw.

According to Wordfence:

“The Redirection for Contact Form 7 plugin for WordPress is vulnerable to arbitrary file uploads due to missing file type validation in the ‘move_file_to_upload’ function in all versions up to, and including, 3.2.7. This makes it possible for unauthenticated attackers to copy arbitrary files on the affected site’s server. If ‘allow_url_fopen’ is set to ‘On’, it is possible to upload a remote file to the server.”

That last part of the vulnerability is what makes exploiting it a little harder. ‘allow_url_fopen’ controls how PHP handles files. PHP ships with this set to “On” but most shared hosting providers routinely set this to “Off” in order to prevent security vulnerabilities.

Although this is an unauthenticated vulnerability which make it easier to take advantage, the fact that it relies on the PHP ‘allow_url_fopen’ setting to be “on” mitigates the likelihood of the flaw being exploited.

Users of the plugin are encouraged to update to version 3.2.8 of the plugin or newer.

Featured Image by Shutterstock/katalinks

Google Files DMCA Suit Targeting SerpApi’s SERP Scraping via @sejournal, @MattGSouthern

Google sued SerpApi in the U.S. District Court for the Northern District of California, alleging the company developed methods to bypass protections Google deployed to prevent automated scraping of Search results and the licensed content they contain.

Why This Case Is Different

Unlike previous cases that focused on terms-of-service violations or broader scraping methods, Google’s complaint is built on DMCA anti-circumvention claims.

Google argues SearchGuard is a protection measure that controls access to copyrighted works appearing in Search results. The complaint describes SearchGuard as a system that sends a JavaScript “challenge” to requests from unrecognized sources and requires the browser to return specific information as a “solve.”

Google says the system launched in January and initially blocked SerpApi. The complaint claims SerpApi then developed ways to bypass it.

The complaint document reads:

“Google developed and deployed a technological measure, known as SearchGuard, that restricts access to its search results pages and the copyrighted content they contain. So that it could continue its free riding, however, SerpApi developed a means of circumventing SearchGuard. With the automated queries it submits, SerpApi engages in a wide variety of misrepresentations and evasions in order to bypass the technological protections Google deployed. But each time it employs these artifices, SerpApi violates federal law.”

Why DMCA Section 1201 Is The Center Of The Complaint

Google’s complaint leans on DMCA Section 1201, which targets circumvention of access controls and also the sale of circumvention tools or services.

Google is bringing two claims: one focused on the act of circumvention (Section 1201(a)(1)) and another focused on “trafficking” in circumvention services or technology (Section 1201(a)(2)). The complaint says Google may elect statutory damages of $200 to $2,500 per violation.

The filing also argues that even if damages were awarded, SerpApi “reportedly earns a few million dollars in annual revenue,” and Google is seeking an injunction to stop the alleged conduct.

What Google Claims SerpApi Did

Google claims SerpApi circumvented SearchGuard in multiple ways, including misrepresenting attributes of requests (such as device, software, or location) to obtain authorization to submit queries.

The complaint quotes SerpApi’s founder describing the process as:

“creating fake browsers using a multitude of IP addresses that Google sees as normal users.”

Google estimates SerpApi sends “hundreds of millions” of artificial search requests each day, and says that volume increased by as much as 25,000% over two years.

The Licensed Content Angle

Google’s issue is not just “SERP data.” It centers on copyrighted content embedded in Search features through licensing and partner relationships.

The complaint says Knowledge Panels “often contain copyrighted photographs that Google licenses from third parties,” and it points to other examples like merchant-supplied product images in Shopping and third-party imagery used in Maps.

Google alleges SerpApi “scrape[s] this copyrighted content and more from Google” and resells it to customers for a fee, without permission or compensation to rights holders.

Why This Matters For SEO Tools

If your workflows depend on third-party SERP data (rank tracking, feature monitoring, competitive intelligence), this case is worth watching because Google is asking for an injunction that could cut off a source of automated SERP access.

Bigger vendors typically run their own collection systems. Smaller products, internal dashboards, and custom tools are more likely to depend on outside SERP APIs, which can create a single point of failure if a provider is forced to shut down or change methods.

Industry Context: Scraping Lawsuits Are Increasing

Google’s filing follows other litigation over scraping and content reuse.

Reddit sued SerpApi and other scraping companies in October over alleged scraping tied to Perplexity, but also notes Perplexity isn’t mentioned in Google’s lawsuit.

Antitrust Context, Briefly

This also lands after Judge Amit Mehta’s August 2024 liability ruling in the U.S. search antitrust case, with remedies ordered in 2025 and appeals expected.

That case deals with distribution and defaults. This one is about automated access to Search results pages and the content embedded in them. Still, they both sit inside the same broader debate about how much control platforms can exert over access and reuse.

What People Are Saying

Some reaction on X has framed the lawsuit as an existential threat to AI products that depend on third-party access to Google results, with one post calling it “the end of ChatGPT.”

The court filing and Google’s announcement are narrower, focused on SerpApi’s alleged circumvention of SearchGuard and the resale of copyrighted content embedded in Google Search features.

SerpApi, for its part, says it will “vigorously defend” the case and characterizes it as an effort to limit competition from companies building “next-generation AI” and other applications.

What Comes Next

Google is asking the court for monetary damages and an order blocking the alleged circumvention. It also wants SerpApi compelled to destroy technology involved in the alleged violations.

If the case proceeds, the central issue is whether SearchGuard qualifies as a DMCA-protected access control for copyrighted works, or whether SerpApi argues it functions more like bot-management, which it may contend falls outside Section 1201.

The Download: China’s dying EV batteries, and why AI doomers are doubling down

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.

China figured out how to sell EVs. Now it has to bury their batteries.

In the past decade, China has seen an EV boom, thanks in part to government support. Buying an electric car has gone from a novel decision to a routine one; by late 2025, nearly 60% of new cars sold were electric or plug-in hybrids.

But as the batteries in China’s first wave of EVs reach the end of their useful life, early owners are starting to retire their cars, and the country is now under pressure to figure out what to do with those aging components.

The issue is putting strain on China’s still-developing battery recycling industry and has given rise to a gray market that often cuts corners on safety and environmental standards. National regulators and commercial players are also stepping in, but so far these efforts have struggled to keep pace with the flood of batteries coming off the road. Read the full story.

—Caiwei Chen

The AI doomers feel undeterred

It’s a weird time to be an AI doomer.This small but influential community believes, in the simplest terms, that AI could get so good it could be bad—very, very bad—for humanity.

The doomer crowd has had some notable success over the past several years: including helping shape AI policy coming from the Biden administration. But a number of developments over the past six months have put them on the back foot. Talk of an AI bubble has overwhelmed the discourse as tech companies continue to invest in multiple Manhattan Projects’ worth of data centers without any certainty that future demand will match what they’re building.

So where does this leave the doomers? We decided to ask some of the movement’s biggest names to see if the recent setbacks and general vibe shift had altered their views. See what they had to say in our story.

—Garrison Lovely

This story is part of our new Hype Correction package, a collection of stories designed to help you reset your expectations about what AI makes possible—and what it doesn’t. Check out the rest of the package.

Take our quiz on the year in health and biotechnology

In just a couple of weeks, we’ll be bidding farewell to 2025. And what a year it has been! Artificial intelligence is being incorporated into more aspects of our lives, weight-loss drugs have expanded in scope, and there have been some real “omg” biotech stories from the fields of gene therapy, IVF, neurotech, and more.

Jessica Hamzelou, our senior biotech reporter, is inviting you to put your own memory to the test. So how closely have you been paying attention this year?

This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.

The must-reads

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

1 TikTok has signed a deal to sell its US unit 
Its new owner will be a joint venture controlled by American investors including Oracle. (Axios)
+ But the platform is adamant that its Chinese owner will retain its core US business. (FT $)
+ The deal is slated to close on January 22 next year. (Bloomberg $)
+ It means TikTok will sidestep a US ban—at least for now. (The Guardian)

2 A tip on Reddit helped to end the hunt for the Brown University shooter
The suspect, who has been found dead, is also suspected of killing an MIT professor. (NYT $)
+ The shooter’s motivation is still unclear, police say. (WP $)

3 Tech leaders are among those captured in newly-released Epstein photos
Bill Gates and Google’s Sergey Brin are both in the pictures. (FT $)
+ They’ve been pulled from a tranche of more than 95,000. (Wired $)

4 A Starlink satellite appears to have exploded
And it’s now falling back to earth. (The Verge)
+ On the ground in Ukraine’s largest Starlink repair shop. (MIT Technology Review)

5 YouTube has shut down two major channels that share fake movie trailers
Screen Culture and KH Studio uploaded AI-generated mock trailers with over a billion views. (Deadline)
+ Google is treading a thin line between embracing and shunning generative AI. (Ars Technica)

6 Trump is cracking down on investment in Chinese tech firms
Lawmakers are increasingly worried that US money is bolstering the country’s surveillance state. (WSJ $)
+ Meanwhile, China is working on boosting its chip output. (FT $)

7 ICE has paid an AI agent company to track down targets
It claims to be able to rapidly trace a target’s online network. (404 Media)

8 America wants to return to the Moon by 2028
And to build some nuclear reactors while it’s up there. (Ars Technica)
+ Southeast Asia seeks its place in space. (MIT Technology Review)

9 Actors in the UK are refusing to be scanned for AI
They’re reportedly routinely pressured to consent to creating digital likenesses of themselves. (The Guardian)
+ How Meta and AI companies recruited striking actors to train AI. (MIT Technology Review)

10 Indian tutors are explaining how to use AI over WhatsApp
Lessons are cheap and personalized—but the teachers aren’t always credible. (Rest of World)
+ How Indian health-care workers use WhatsApp to save pregnant women. (MIT Technology Review)

Quote of the day

“Trump wants to hand over even more control of what you watch to his billionaire buddies. Americans deserve to know if the president struck another backdoor deal for this billionaire takeover of TikTok.”

—Democratic senator Elizabeth Warren queries the terms of the deal that TikTok has made to allow it to continue operating in the US in a post on Bluesky.

One more thing

Synthesia’s AI clones are more expressive than ever. Soon they’ll be able to talk back.

—Rhiannon Williams

Earlier this summer, I visited the AI company Synthesia to create a hyperrealistic AI-generated avatar of me. The company’s avatars are a decent barometer of just how dizzying progress has been in AI over the past few years, so I was curious just how accurately its latest AI model, introduced last month, could replicate me.

I found my avatar as unnerving as it is technically impressive. It’s slick enough to pass as a high-definition recording of a chirpy corporate speech, and if you didn’t know me, you’d probably think that’s exactly what it was.

My avatar shows how it’s becoming ever-harder to distinguish the artificial from the real. And before long, these avatars will even be able to talk back to us. But how much better can they get? And what might interacting with AI clones do to us? Read the full story.

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.)

+ You can keep your beef tallow—here are the food trends that need to remain firmly in 2025.
+ The Library of Congress has some lovely images of winter that are completely free to use.
+ If you’ve got a last minute Christmas work party tonight, don’t make these Secret Santa mistakes.
+ Did you realize Billie Eilish’s smash hit Birds of a Feather has the same chord progression as Wham’s Last Christmas? They sound surprisingly good mashed together.

The Good, Bad, and Ugly of 2025

I talk a lot on the podcast about business, growth, and solving problems, but at some point it’s worth stepping back to ask why we’re doing any of this in the first place.

This recap is about Beardbrand (my company) and our 2025 performance: What worked, what didn’t, what was painful, and what made it all worth it.

It’s also a reminder to take stock of your own priorities — how you’re allocating your time, energy, and attention — and whether they align with the life you’re trying to build.

The Good

Longtime listeners know that 2023 and 2024 were extremely challenging for me personally and for Beardbrand. We lost a lot of money in 2023 and less, but still meaningful, in 2024. The good news is that in 2025, we became profitable again.

Looking back, our conservative financial strategy before things turned bad helped us survive. It allowed us to withstand rapid market changes and support our staff for as long as possible. That discipline helped us weather the storm.

From a growth standpoint, subscriptions have been a major win. At our lowest point, we had roughly 1,500 subscriptions. We made a focused effort to rebuild, and recently we surpassed 11,000 active subscriptions. Hitting 10,000-plus gives us predictable revenue and long-term stability. Churn has remained low, and we’re still adding members weekly, which is encouraging.

Another big win was finding the right fulfillment partner. After two moves — including one near our manufacturer that didn’t work out — we landed on a small Austin-based provider. The staff offers white-glove service, takes responsibility when issues arise, and aligns with the customer experience we want to deliver. Plus, being local helps. We can visit, meet the team, and fine-tune packaging and shipping costs.

Manufacturing has also improved. Finding the right manufacturing partner is a Goldilocks problem — not too big, not too small, just right. One of our supplier-partners discovered us through this podcast. They’ve allowed us to keep inventory lean, place smaller, more frequent orders, and maintain quality. That’s reduced customer complaints, lowered stress, and helped us avoid unsellable inventory — a major contributor to losses in prior years.

Engagement with customers has improved as we let them vote on which limited-edition fragrance would become permanent.

Another win — we subleased our oversized office, a costly remnant from when our team size was at its peak, easing a significant financial burden until the lease ends in 2026.

The Bad

The biggest hurdle is that the beard care industry has shifted from a blue to a red ocean. A blue ocean is wide open — lots of opportunity, little competition. Today, beard care feels saturated and stagnant.

I see this in search data. Terms like “how to grow a beard,” “beard oil,” and “beard balm” are flat or declining. Meanwhile, other personal care categories such as shampoo, bar soap, and cologne continue to grow. When I look at Beardbrand and our top competitors, we’re all flat or down.

One way to resume growth is with organic content. We’ve had content hits and misses, but we haven’t reliably delivered the quality and volume I want. If we fix it, we can deepen relationships with our audience and stand out again.

Paid media has also been frustrating. Like many brands, we haven’t cracked Meta at scale. We’ll find an ad that works, get excited, then watch it fall flat days later. We’ve hovered around $30,000 a month in spend without breaking through. We recently started integrating more data-driven decision-making.

I expected revenue to grow in 2025 after fixing problems from 2023 and 2024. That didn’t happen. We likely won’t beat last year’s numbers, which forced us to make painful staffing cuts — letting go of two long-tenured, incredible team members. That was one of the hardest decisions I’ve had to make.

Amazon sales have also regressed. We’ve worked with the same agency for three years, and while they’ve done good work, it feels like we’ve plateaued. We’re planning to switch partners.

The Ugly

Overall, 2025 was fairly stress-free, which I’ll gladly take. The biggest issue was that we got sued again. This one came from a patent troll.

Patent lawsuits are very different from the Americans with Disabilities Act lawsuit, which we chose to fight. We had invested heavily in making our site accessible for people with disabilities, including those with vision impairments, and ultimately, we were able to get that case dismissed.

Patent cases are another story. The financial risk of fighting is much higher. Defending the ADA lawsuit cost roughly the same as a settlement. Given where Beardbrand was after multiple years of losses, I swallowed my pride and settled.

What made the decision easier is that, once settled, a patent holder cannot sue again for the same alleged infringement. Another party would need to hold the same patent, which is unlikely. I feel at peace with the choice. The direct-to-consumer community on X was also incredibly helpful, connecting us with a great attorney, which made the process smoother.

Hopefully, that’s the last lawsuit for a while. We’re doing everything we can to protect ourselves — updated privacy policies, cookie consent for pixel tracking in applicable states, and ongoing ADA audits.

Personal Wins and Losses

One of my goals for 2026 is to return to a “profit first” mindset — building a business that’s profitable while also supporting my personal life. Over the past few years, I’ve pulled from savings to maintain our standard of living. I’m grateful I had that cushion, but I don’t want it to be the norm.

The highlight of 2025 was a trip to Japan with my 12-year-old daughter. Travel is something we both love, and it gave us a shared experience during a fleeting stage of life. This trip felt meaningful for her and me as she grows into her own independence. I’m incredibly pleased we did it.

Health-wise, it’s been a good year. I’m rowing again, lifting consistently, and I avoided major injuries. My wife and kids have been healthy, which I never take for granted.

I’m also profoundly grateful for my friends — in Austin, online, and the broader D2C community — who’ve helped me navigate challenging moments.

There was a personal loss, however. My wife and I transferred our final IVF embryo, and it wasn’t successful. That chapter is now closed after more than a decade of infertility and loss. I share this because many are going through similar struggles. You’re not alone.

Microsoft Explains How Duplicate Content Affects AI Search Visibility via @sejournal, @MattGSouthern

Microsoft has shared new guidance on duplicate content that’s aimed at AI-powered search.

The post on the Bing Webmaster Blog discusses which URL serves as the “source page” for AI answers when several similar URLs exist.

Microsoft describes how “near-duplicate” pages can end up grouped together for AI systems, and how that grouping can influence which URL gets pulled into AI summaries.

How AI Systems Handle Duplicates

Fabrice Canel and Krishna Madhavan, Principal Product Managers at Microsoft AI, wrote:

“LLMs group near-duplicate URLs into a single cluster and then choose one page to represent the set. If the differences between pages are minimal, the model may select a version that is outdated or not the one you intended to highlight.”

If multiple pages are interchangeable, the representative page might be an older campaign URL, a parameter version, or a regional page you didn’t mean to promote.

Microsoft also notes that many LLM experiences are grounded in search indexes. If the index is muddied by duplicates, that same ambiguity can show up downstream in AI answers.

How Duplicates Can Reduce AI Visibility

Microsoft lays out several ways duplication can get in the way.

One is intent clarity. If multiple pages cover the same topic with nearly identical copy, titles, and metadata, it’s harder to tell which URL best fits a query. Even when the “right” page is indexed, the signals are split across lookalikes.

Another is representation. If the pages are clustered, you’re effectively competing with yourself for which version stands in for the group.

Microsoft also draws a line between real page differentiation and cosmetic variants. A set of pages can make sense when each one satisfies a distinct need. But when pages differ only by minor edits, they may not carry enough unique signals for AI systems to treat them as separate candidates.

Finally, Microsoft links duplication to update lag. If crawlers spend time revisiting redundant URLs, changes to the page you actually care about can take longer to show up in systems that rely on fresh index signals.

Categories Of Duplicate Content Microsoft Highlights

The guidance calls out a few repeat offenders.

Syndication is one. When the same article appears across sites, identical copies can make it harder to identify the original. Microsoft recommends asking partners to use canonical tags that point to the original URL and to use excerpts instead of full reprints when possible.

Campaign pages are another. If you’re spinning up multiple versions targeting the same intent and differing only slightly, Microsoft recommends choosing a primary page that collects links and engagement, then using canonical tags for the variants and consolidating older pages that no longer serve a distinct purpose.

Localization comes up in the same way. Nearly identical regional pages can look like duplicates unless they include meaningful differences. Microsoft suggests localizing with changes that actually matter, such as terminology, examples, regulations, or product details.

Then there are technical duplicates. The guidance lists common causes such as URL parameters, HTTP and HTTPS versions, uppercase and lowercase URLs, trailing slashes, printer-friendly versions, and publicly accessible staging pages.

The Role Of IndexNow

Microsoft points to IndexNow as a way to shorten the cleanup cycle after consolidating URLs.

When you merge pages, change canonicals, or remove duplicates, IndexNow can help participating search engines discover those changes sooner. Microsoft links that faster discovery to fewer outdated URLs lingering in results, and fewer cases where an older duplicate becomes the page that’s used in AI answers.

Microsoft’s Core Principle

Canel and Madhavan wrote:

“When you reduce overlapping pages and allow one authoritative version to carry your signals, search engines can more confidently understand your intent and choose the right URL to represent your content.”

The message is consolidation first, technical signals second. Canonicals, redirects, hreflang, and IndexNow help, but they work best when you’re not maintaining a long tail of near-identical pages.

Why This Matters

Duplicate content isn’t a penalty by itself. The downside is weaker visibility when signals are diluted, and intent is unclear.

Syndicated articles can keep outranking the original if canonicals are missing or inconsistent. Campaign variants can cannibalize each other if the “differences” are mostly cosmetic. Regional pages can blend together if they don’t clearly serve different needs.

Routine audits can help you catch overlap early. Microsoft points to Bing Webmaster Tools as a way to spot patterns such as identical titles and other duplication indicators.

Looking Ahead

As AI answers become a more common entry point, the “which URL represents this topic” problem becomes harder to ignore.

Cleaning up near-duplicates can influence which version of your content gets surfaced when an AI system needs a single page to ground an answer.

What is a redirect? Types, how to set them up, and impact on SEO 

Ever clicked a link and landed on a “Page Not Found” error? Redirects prevent that. They send visitors and search engines to the right page automatically. Redirects are crucial for both SEO and user experience. For SEO, they preserve link equity and keep your rankings intact. Additionally, it enhances the user experience, as no one likes dead ends. 

Table of contents

Key takeaways

  • A redirect automatically sends users and search engines from one URL to another, preventing errors like ‘Page Not Found.’
  • Redirects are crucial for SEO and user experience, preserving link equity and maintaining rankings.
  • Different types of redirects exist: 301 for permanent moves and 302 for temporary ones.
  • Avoid client-side redirects, such as meta refresh or JavaScript, as they can harm SEO.
  • Use Yoast SEO Premium to easily set up and manage redirects on your site.

What is a redirect? 

A redirect is a method that automatically sends users and search engines from one URL to another. For example, if you delete a page, a redirect can send visitors to a new or related page instead of a 404 error. 

How redirects work

  1. A user or search engine requests a URL (e.g., yoursite.com/page-old).
  2. The server responds with a redirect instruction.
  3. The browser or search engine follows the redirect to the new URL (e.g., yoursite.com/page-new).

Redirects can point to any URL, even on a different domain. 

Why redirects matter 

Redirects keep your website running smoothly. Without them, visitors hit dead ends, links break, and search engines get lost. They’re not just technical fixes, because they protect your traffic, preserve rankings, and make sure users land where they’re supposed to. Whether you’re moving a page, fixing a typo in a URL, or removing old content, redirects make sure that nothing gets left behind. 

When to use a redirect 

Use redirects in these scenarios: 

  1. Deleted pages: Redirect to a similar page to preserve traffic. 
  2. Domain changes: Redirect the old domain to the new one. 
  3. HTTP→HTTPS: Redirect insecure URLs to secure ones. 
  4. URL restructuring: Redirect old URLs to new ones (e.g., /blog/post → /articles/post). 
  5. Temporary changes: Use a 302 for A/B tests or maintenance pages. 

Types of redirects 

There are various types of redirects, each serving a distinct purpose. Some are permanent, some are temporary, and some you should avoid altogether. Here’s what you need to know to pick the right one. 

Not all redirects work the same way. A 301 redirect tells search engines a page has moved permanently, while a 302 redirect signals a temporary change. Client-side redirects, like meta refresh or JavaScript, exist because they’re sometimes the only option on restrictive hosting platforms or static sites, but they often create more problems than they solve. Below, we break down each type, explain when to use it, and discuss its implications for your SEO. 

Redirect types at a glance 

Redirect type  Use case  When to use  Browser impact  SEO impact  SEO risk 
301  Permanent move  Deleted pages, domain changes, HTTP→HTTPS  Cached forever  Passes (almost) all link equity  None if used correctly 
302  Temporary move  A/B testing, maintenance pages  Not cached  May not pass link equity  Can dilute SEO if used long-term 
307  Temporary move (strict)  API calls, temporary content shifts  Not cached  Search engines may ignore  High if misused 
308  Permanent move (strict)  Rare; use 301 instead  Cached forever  Passes link equity  None 
Meta Refresh  Client-side redirect  Avoid where possible  Slow, not cached  Unreliable  High (hurts UX/SEO) 
JavaScript  Client-side redirect  Avoid where possible  Slow, not cached  Unreliable  High (hurts UX/SEO) 

301 redirects: Permanent moves 

A 301 redirect tells browsers and search engines that a page has moved permanently. Use it when: 

  • You delete a page and want to send visitors to a similar one.
  • You change your domain name.
  • You switch from HTTP to HTTPS.

SEO impact: 301 redirects pass virtually all link equity to the new URL. But be sure to never redirect to irrelevant pages, as this can confuse users and hurt SEO. For example, redirecting a deleted blog post about “best running shoes” to your homepage, instead of a similar post about running gear. This wastes link equity and frustrates visitors. 

Example HTTP header

HTTP/1.1 301 Moved Permanently 
Location: https://example.com/new-page

302 redirects: Temporary moves 

A 302 redirect tells browsers and search engines that a move is temporary. Use it for: 

  • A/B testing different versions of a page.
  • Temporary promotions or sales pages.
  • Maintenance pages.

SEO impact: 302 redirects typically don’t pass ranking power like 301s. Google treats them as temporary, so they may not preserve SEO value. For permanent moves, always use a 301 to ensure link equity transfers smoothly. 

Examples of when to use a 301 and 302 redirect:  

Example 1: Temporary out-of-stock product (302): An online store redirects example.com/red-sneakers to example.com/blue-sneakers while red sneakers are restocked. A 302 redirect keeps the original URL alive for future use. 

Example 2: A permanent domain change (301): A company moves from old-site.com to new-site.com. A 301 redirect makes sure visitors and search engines land on the new domain while preserving SEO rankings. 

307 and 308 redirects: Strict rules 

These redirects follow HTTP rules more strictly than 301 or 302: 

  1. Same method: If a browser sends a POST request, the redirect must also use POST. 
  2. Caching
    • 307: Never cached (temporary). 
    • 308: Always cached (permanent). 

When to use them

  • 307: For temporary redirects where you must keep the same HTTP method (e.g., forms or API calls). 
  • 308: Almost never, use a 301 instead. 

For most sites: Stick with 301 (permanent) or 302 (temporary). These are for specific technical cases only. 

What to know about client-side redirects:

Client-side redirects, such as meta refresh or JavaScript, execute within the browser instead of on the server. They’re rarely the right choice, but here’s why you might encounter them: 

  • Meta refresh: A HTML tag that redirects after a delay (e.g., “You’ll be redirected in 5 seconds…”).
  • JavaScript redirects: Code that changes the URL after the page loads.

Why should you avoid them? 

  • Slow: The browser must load the page first, then redirect.
  • Unreliable: Search engines may ignore them, hurting SEO.
  • Bad UX: Users see a flash of the original page before redirecting.
  • Security risks: JavaScript redirects can be exploited for phishing. 

When they’re used (despite the risks): 

  • Shared hosting with no server access. 
  • Legacy systems or static HTML sites.
  • Ad tracking or A/B testing tools.

Stick with server-side redirects (301/302) whenever possible. If you must use a client-side redirect, test it thoroughly and monitor for SEO issues. 

How redirects impact SEO 

Redirects do more than just send users to a new URL. They shape how search engines crawl, index, and rank your site. A well-planned redirect preserves traffic and rankings. A sloppy one can break both. Here’s what you need to know about their impact. 

Ranking power 

301 redirects pass most of the link equity from the old URL to the new one. This helps maintain your rankings. 302 redirects may not pass ranking power, especially if used long-term. 

Crawl budget 

Too many redirects can slow down how quickly search engines crawl your site. Avoid redirect chains (A→B→C) to save crawl budget

User experience 

Redirects prevent 404 errors and keep users engaged. A smooth redirect experience can reduce bounce rates. 

Common redirect mistakes 

Redirects seem simple, but small errors can cause big problems. Here are the most common mistakes and how to avoid them. 

Redirect chains 

A redirect chain happens when one URL redirects to another, which redirects to another, and so on. For example:  

  • old-page → new-page → updated-page → final-page

Why it’s bad

  • Slows down the user experience. 
  • Wastes crawl budget, as search engines may stop following the chain before reaching the final URL. 
  • Dilutes ranking power with each hop. 

How to fix it

  • Map old URLs directly to their final destination. 
  • Use tools like Screaming Frog to find and fix chains. 

Redirect loops 

A redirect loop sends users and search engines in circles. For example:  

  • page-A → page-B → page-A → page-B...

Why it’s bad

  • Users see an error page (e.g., “Too many redirects”). 
  • Search engines can’t access the content, so it won’t rank. 

How to fix it

  • Check your redirect rules for cblonflicts. 
  • Test redirects with a tool like Redirect Path (Chrome extension) or curl -v in the terminal. 

Using 302s for permanent moves 

A 302 redirect is meant for temporary changes, but many sites use it for permanent moves. For example: 

  • Redirecting old-product to new-product with a 302 and leaving it for years. 

Why it’s bad

  • Search engines may not pass link equity to the new URL. 
  • The old URL might stay in search results longer than intended. 

How to fix it

  • Use a 301 for permanent moves. 
  • If you accidentally used a 302, switch it to a 301 as soon as possible. 

Redirecting to irrelevant pages 

Redirecting a page to unrelated content confuses users and search engines. For example: 

  • Redirecting a blog post about “best running shoes” to the homepage or a page about “kitchen appliances”. 

Why it’s bad

  • Users land on content they didn’t expect, increasing bounce rates. 
  • Search engines may ignore the redirect or penalize it for being manipulative. 
  • Wastes ranking power that could have been passed to a relevant page. 

How to fix it

  • Always redirect to the most relevant page available. 
  • If no relevant page exists, let the old URL return a 404 or 410 error instead. 

Ignoring internal links after redirects 

After setting up a redirect, many sites forget to update internal links. For example: 

  • Redirecting old-page to new-page but keeping links to old-page in the site’s navigation or blog posts. 

Why it’s bad

  • Internal links to the old URL force users and search engines through the redirect, slowing down the experience. 
  • Wastes crawl budget and dilutes ranking power. 

How to fix it

  • Update all internal links to point directly to the new URL. 
  • Use a tool like Screaming Frog to find and fix outdated links. 

Not testing redirects 

Assuming redirects work without testing can lead to surprises. For example: 

  • Setting up a redirect but not checking if it sends users to the right place. 
  • Missing errors like 404s or redirect loops. 

Why it’s bad

  • Broken redirects frustrate users and hurt SEO. 
  • Search engines may drop pages from the index if they can’t access them. 

How to fix it

  • Test every redirect manually or with a tool. 
  • Check Google Search Console for crawl errors after implementing redirects. 

Redirecting everything to the homepage 

When a page is deleted, some sites redirect all traffic to the homepage. For example: 

  • Redirecting old-blog-post to example.com instead of a relevant blog post. 

Why it’s bad

  • Confuses users who expected specific content. 
  • Search engines may see this as a “soft 404” and ignore the redirect. 
  • Wastes ranking power that could have been passed to a relevant page. 

How to fix it

  • Redirect to the most relevant page available. 
  • If no relevant page exists, return a 404 or 410 error. 

Forgetting to update sitemaps 

After setting up redirects, many sites forget to update their XML sitemaps. For example: 

  • Keeping the old URL in the sitemap while redirecting it to a new URL. 

Why it’s bad

  • Sends mixed signals to search engines. 
  • Wastes crawl budget on outdated URLs. 

How to fix it

  • Remove old URLs from the sitemap. 
  • Add the new URLs to help search engines discover them faster. 

Using redirects for thin or duplicate content 

Some sites use redirects to hide thin or duplicate content. For example, redirecting multiple low-quality pages to a single high-quality page to “clean up” the site. 

Why it’s bad

  • Search engines may see this as manipulative. 
  • Doesn’t address the root problem, which is low-quality content. 

How to fix it

  • Improve or consolidate content instead of redirecting. 
  • Use canonical tags if duplicate content is unavoidable. 

Not monitoring redirects over time 

Redirects aren’t a set-it-and-forget-it task. For example: 

  • Setting up a redirect and never checking if it’s still needed or working. 

Why it’s bad

  • Redirects can break over time (e.g., due to site updates or server changes). 
  • Unnecessary redirects waste crawl budget. 

How to fix it

  • Audit redirects regularly (e.g., every 6 months). 
  • Remove redirects that are no longer needed. 

How to set up a redirect 

Setting up redirects isn’t complicated, but the steps vary depending on your platform. Below, you’ll find straightforward instructions for the most common setups, whether you’re using WordPress, Apache, Nginx, or Cloudflare.  

Pick the method that matches your setup and follow along. If you’re unsure which to use, start with the platform you’re most comfortable with. 

WordPress (using Yoast SEO Premium) 

Yoast SEO Premium makes it easy to set up redirects, especially when you delete or move content. Here’s how to do it: 

Option 1: Manual redirects 

  1. Go to Yoast SEO → Redirects in your WordPress dashboard. 
  2. Enter the old URL (the one you want to redirect from). 
  3. Enter the new URL (the one you want to redirect to). 
  4. Select the redirect type: 
  • 301 (Permanent): For deleted or permanently moved pages. 
  • 302 (Found): For short-term changes. 
  1. Click Add Redirect
Manually redirecting a URL in Yoast’s redirect manager

Option 2: Automatic redirects when deleting content 

Yoast SEO can create redirects automatically when you delete a post or page. Here’s how: 

  1. Go to Posts or Pages in your WordPress dashboard. 
  2. Find the post or page you want to delete and click Trash
  3. Yoast SEO will show a pop-up asking what you’d like to do with the deleted content. You’ll see two options: 
    • Redirect to another URL: Enter a new URL to send visitors to. 
    • Return a 410 Content Deleted header: Inform search engines that the page is permanently deleted and should be removed from their index. 
  4. Select your preferred option and confirm. 

This feature saves time and ensures visitors land on the right page. No manual setup required. 

Need help with redirects? Try Yoast SEO Premium

No code, no hassle. Just smarter redirects and many other invaluable tools.

Apache (.htaccess file) 

Apache uses the .htaccess file to manage redirects. If your site runs on Apache, this is the simplest way to set them up. Add the rules below to your .htaccess file, ensuring it is located in the root directory of your site. 

Add these lines to your .htaccess file: 

# 301 Redirect 
Redirect 301 /old-page.html /new-page.html
# 302 Redirect 
Redirect 302 /temporary-page.html /new-page.html

Nginx (server config) 

Nginx handles redirects in the server configuration file. If your site runs on Nginx, add these rules to your server block and then reload the service to apply the changes. 

Add this to your server configuration: 

# 301 Redirect 
server { 
    listen 80; 
    server_name example.com; 
    return 301 https://example.com$request_uri; 
}
# 302 Redirect 
server { 
    listen 80; 
    server_name example.com; 
    location = /old-page { 
        return 302 /new-page; 
    } 
}

Cloudflare (page rules) 

Cloudflare allows you to set up redirects without modifying server files. Create a page rule to forward traffic from one URL to another, without requiring any coding. Simply enter the old and new URLs, select the redirect type, and click Save. 

  1. Go to Rules → Page Rules
  2. Enter the old URL (e.g., example.com/old-page). 
  3. Select Forwarding URL and choose 301 or 302
  4. Enter the new URL (e.g., https://example.com/new-page). 

Troubleshooting redirects 

Redirects don’t always work as expected. A typo, a cached page, or a conflicting rule can break them, or worse, create loops that frustrate users and search engines. Below are the most common issues and how to fix them.  

If something’s not working, start with the basics: check for errors, test thoroughly, and clear your cache. The solutions are usually simpler than they seem. 

Why isn’t my redirect working? 

  • Check for typos: Ensure the URLs are correct. 
  • Clear your cache: Browsers cache 301 redirects aggressively. 
  • Test with curl: Run curl -v http://yoursite.com/old-url to see the HTTP headers. 

Can redirects hurt SEO? 

Yes, if you: 

  • Create redirect chains (A→B→C
  • Use 302s for permanent moves 
  • Redirect to irrelevant pages 

How do I find broken redirects? 

  • Use Google Search Console → Coverage report. 
  • Use Screaming Frog to crawl your site for 404s and redirects. 

What’s the difference between a 301 and 308 redirect? 

  • 301: Most common for permanent moves. Broad browser support. 
  • 308: Strict permanent redirect. Rarely used. Same SEO impact as 301. 

What is a proxy redirect? 

A proxy redirect keeps the URL the same in the browser but fetches content from a different location. Used for load balancing or A/B testing. Avoid for SEO, as search engines may not follow them. 

Conclusion about redirects

Redirects are a simple but powerful tool. A redirect automatically sends users and search engines from one URL to another. As a result, they keep your site running smoothly and preserve SEO value and ranking power. Remember: 

  • Use 301 redirects for permanent moves. 
  • Use 302 redirects for temporary changes. 
  • Avoid client-side redirects, such as meta refresh or JavaScript. 

Need help? Try Yoast SEO Premium’s redirect manager.  

PPC Pulse: More Apple Search Inventory, Exact Match Limits In AI Overviews via @sejournal, @brookeosmundson

In this week’s PPC Pulse: updates include an inventory expansion for Apple Ads, and Google confirms that Exact match keywords are not eligible to serve for Ads in AI Overviews.

Apple announced additional ad placements coming to App Store search results in early 2026.

Google confirmed that exact match keywords cannot serve in AI Overviews, even when identical broad match keywords exist in an account.

Both updates reinforce an ongoing shift. Search inventory is growing across new surfaces, but the level of control advertisers once relied on is changing.

Read on for more details and why they matter for advertisers.

Apple Search Ads Will Add New Search Placements In 2026

Apple officially announced that it will introduce additional ads within App Store Search Results starting in 2026. Today, advertisers can appear only in the top position. Beginning next year, ads will also show further down the results page across more queries, expanding total available inventory.

In its email announcement, Apple shared several supporting data points in its announcement:

  • Nearly 65% of App Store downloads occur directly after a search.
  • The App Store sees 800 million weekly visitors.
  • More than 85% of visitors download at least one app during their visit.
  • Current Search Results ads see 60% or higher conversion rates at the top of results.
Screenshot taken via email by author, December 2025

Per the announcement, advertisers will not need to adjust campaigns to qualify for the new placements. Apple noted that ads will be automatically eligible and cannot be targeted or bid separately by position. The format and billing model will remain the same.

Expanding On An Already Big Year For Apple

Apple has consistently rolled out upgrades and expansions throughout 2025, including:

  • Custom Product Page expansion (March 2025): Apple expanded testing capabilities by allowing more CPP variants tied to specific keywords, improving message alignment.
  • Reporting enhancements (June 2025): Apple introduced clearer diagnostics around impression share, keyword performance, and CPP impact. These updates made it easier to identify friction points in search campaigns.
  • Creative refinements for Today Tab and Search Tab (August 2025): Apple improved visual consistency and added support for higher-funnel experimentation, hinting at broader expansion across App Store surfaces.

These updates all point toward a more robust Apple Ads marketing platform, making the 2026 inventory expansion feel like a natural progression.

Why This Matters For Advertisers

More placements signal higher reach, but also more variability. Top-position performance is unlikely to change, but additional placements may bring new traffic patterns as more users scroll past the first result.

Advertisers should expect incremental installs paired with slightly wider performance swings.

This also means that metadata, product page quality, and CPP strategy will influence performance more than before, since every placement will rely on the same creative foundation.

Read More: An In-Depth Guide To Apple Search Ads

Google Confirms Exact Match Keywords Not Eligible For AI Overviews

A few questions came in to Google Ads Liaison, Ginny Marvin, this week on X (Twitter) regarding the eligibility of exact match keywords for ads in AI Overviews.

Marvin confirmed via a thread on X (Twitter) that exact match ads are not eligible to serve ads inside Google’s AI Overviews. This clarification explains a pattern many advertisers have seen over the last year. Even if an account contains the same query in both exact and broad match, only broad match can enter AI Overview auctions.

Screenshot taken by author, December 2025

The update circulated quickly after Arpan Banerjee shared it on LinkedIn, giving the topic more visibility among PPC practitioners.

Screenshot taken by author, December 2025

This means advertisers may see broad match triggering queries that they assumed would be handled by exact match. It also means AI Overview impressions are routed through a different layer of Google’s system with its own eligibility rules. Since Google does not provide separate AI Overview reporting, changes in performance may not be clearly attributed to this shift.

Why This Matters For Advertisers

This update makes it clear that match types do not operate the same way inside AI-driven surfaces.

The long-standing assumption that exact match provides clean, isolated coverage does not apply within AI Overviews. Broad match becomes the only entry point, which could influence spend allocation, campaign structure, query mapping, and performance diagnostics.

Advertisers should expect shifts in query distribution on terms where they rely heavily on exact match control.

Read More: AI-Enhanced Keyword Selection In PPC

This Week’s Theme: Search Control Looks Different Than It Used To

Both updates highlight a similar pattern. Platforms are expanding search inventory, but advertisers have less control over how placements are allocated.

Apple is opening new ad positions without letting advertisers bid separately for them. Google is routing some search coverage through AI Overviews, where exact match does not participate. In both cases, the legacy structure of “keyword plus bid plus placement” is giving way to a more interpretive system.

This does not mean advertisers lose influence. It means influence shifts to metadata quality, creative alignment, first-party data, and smart segmentation. Both updates remind advertisers to stay flexible because new surfaces will continue to emerge.

More Resources:


Featured Image: Pixel-Shot/Shutterstock