Google Posts is easier to manage and use with these new user interface updates.
Google has updated the Google Posts creation tool within Google
Business Profiles. The update makes it easier to use, by placing all the
posts in a centralized location with an easier way to manage those
posts.
This update should be live for all of you by now, as it quietly launched last Friday.
What changed. Google made several changes to the Google Posts screen, the changes were summarized by Lisa Landsman from the Google team. She wrote on LinkedIn the list of changes, which includes:
Centralized Posts Hub: The “Add Update” button has been replaced
with a new management screen where you can easily see and manage all
your posts in one place.
Simpler Creation Process: The post creation experience is now
streamlined into a single dialog, allowing you to quickly create
updates, events, or offers from one screen.
Enhanced Management View: You can now view key details for each
post, such as creation date, status, and post type, making it easier to
track and make changes.
Minor Visual Improvements: Google introduced small visual changes
throughout the experience to make it more intuitive and enjoyable to
use.
What it looks like. Here is a GIF of the new refreshed interface for Google Posts:
What are Google Posts. Google Posts allows
businesses to post updates on your Business Profile to share
announcements, offers, updates, and event details directly with your
customers on Search and Maps. These posts show up within Google Maps and
Google Search for searches on your business and within your Google
local panel.
Why we care. If you are a business with a local
footprint or do marketing for a local business, Google Posts can help
you get more attention and conversions for that business. By pushing
updates, promotions, offers, events and so forth in your local listing
on Google, it can attract new and repeat business for the organization.
This new interface may make things easier for you and your business to manage.
AI platforms are
transforming discovery. Traffic is surging. Now strategies must evolve,
according to the 2025 Previsible AI Traffic Report.
For the past year, we’ve talked about how AImight change search.
That moment is over.
This is no longer a “what if” conversation. We are seeing a measurable shift in web traffic movement.
At Previsible, we analyzed LLM-driven traffic across 19 GA4
properties and found something undeniable: AI platforms like ChatGPT,
Perplexity, Claude, Gemini, and Copilot are already influencing how
users find and engage with websites.
Not in theory. In actual traffic.
In just five months, total AI-referred sessions jumped from 17,076 to 107,100.
That’s a 527% increase between January and May 2025.
Some SaaS sites are now seeing over 1% of all sessions coming from LLMs.
Traffic from ChatGPT, Claude, and others is doubling and tripling across verticals like Legal, Health, and Finance.
If you work in SEO, content, or growth strategy, this moment will
feel familiar. Like when mobile-first flipped ranking factors overnight.
Or when social transformed from brand garnish into a legitimate
acquisition engine.
Every time the rules changed, early adopters won. This time is no different, except it’s moving faster.
So the question isn’t if AI is changing your traffic mix. It’s how much it already has, without you realizing it.
TL;DR: What you need to know about AI search
AI discovery is up 527%: Comparing the first 5
months of 2025 with the same time frame in 2024 we see how total
sessions from LLMs (like ChatGPT, Perplexity, and, Gemini) surged from
17,076 to 107,100 across 19 GA4 properties.
LLMs are already part of the user journey: Some
sites, especially in SaaS, are seeing over 1% of all traffic initiated
by AI results. Primarily to the bottom of funnel users and targeted
prospects.
High-consultive industries are leading: Legal,
Finance, SMB, Insurance, and Health make up 55% of all LLM-driven
sessions, showing that users turn to AI for complex, contextual
questions.
ChatGPT leads, but the field is widening: ChatGPT still dominates, but Perplexity, Copilot, and Gemini are gaining real traction.
SEO is splitting and speeding up: It’s no longer
just about ranking in Google. You now need to earn visibility in AI
assistants, summaries, and conversational UIs, and they prefer content
that’s structured, clear, and genuinely helpful.
AI discovery is up 527% – and it isn’t waiting for you to rank
AI is reshaping web traffic at warp speed.
When we compared January-May 2025 to the same period in 2024, we saw
total AI-sourced sessions across 19 GA4 properties jump from 17,076 to
107,100.
That’s a 527% year-over-year increase.
In one standout example, ChatGPT went from just 600 visits/month in early 2024 to over 22,000/month by May 2025.
And when you zoom in by industry, the growth in share is just as dramatic:
Legal: 0.37% → 0.86% of sessions from LLMs
Health: 0.17% → 0.56%
Finance and SaaS are showing similar trajectories, in some cases, exceeding 1% of total traffic
LLMs are becoming a legitimate discovery channel, and they’re doing it fast.
Why it matters:
Most SEO strategies are still stuck in the old timeline:
Optimize → Wait → Crawl → Rank → Convert
That playbook was built for Google’s crawling and indexing cycle – a
system that rewards patience, backlinks, and slow iteration.
But LLMs don’t care about that process.
They don’t crawl the same way. They don’t rank in the same order. They don’t wait for your canonical tag to propagate.
They surface content immediately if it’s useful.
The only thing that matters is whether your content helps answer the user’s question in a way the model trusts.
No indexing delay. No competition for blue links. No sandbox.
Just: Is this helpful right now?
That rewires everything.
Content doesn’t need to appear at the top of Google’s SERPs to be
found. It needs to be clear, structured, and cited by the model –
whether in a blog, a help doc, a case study, or a knowledge base.
And it means the old mindset — publish, wait, and hope Google figures it out — is now dangerously outdated.
We’ve entered the “instant surfacing era” of SEO, where content can be discovered before it even ranks.
If your SEO strategy doesn’t account for that, you’re already behind.
Where LLM traffic is actually going: The real breakdown
Not predictions. Not vibes. Actual traffic.
In the 2025 Previsible AI Data Study, we analyzed LLM-driven sessions
across 19 GA4 properties to understand where platforms like ChatGPT,
Claude, Gemini, Copilot, and Perplexity are already influencing real
user behavior.
Here’s what we found:
Legal topped the chart, with 0.28% of total traffic from LLMs
Finance followed at 0.24%, showing strong traction in regulated markets
Health came in at 0.15%, with a mix of ChatGPT, Gemini, and Perplexity sources
SaaS showed breakout performance but only in some domains, with a selected few getting 1%+ of total sessions from LLMs
But the most important finding?
Legal, Finance, Health, SMB, and Insurance account for 55% of all LLM-sourced sessions across the dataset.
Why these five?
Because people aren’t using LLMs like search engines.
They’re asking contextual, trust-heavy, consultative questions. The kind they’d normally ask a real expert:
“What should I ask a lawyer before signing this contract?”
“Is this medication safe with XYZ conditions, XYZ personal information, and XYZ symptoms?”
“How do I structure payroll as a small business owner that owns a flower shop with 5 employees, 2 part-time and 3 full-time?”
These are high-context moments, and that’s where LLMs are starting to win.
So if your brand plays in a space where trust, clarity, or expertise
matters, and your content isn’t optimized for AI, you’re likely missing
the exact kinds of requests these models are built to answer.
Model-level insight: Who’s actually driving the traffic?
It’s not just about how much AI traffic you’re getting, but also about who’s sending it.
Across nearly every vertical, ChatGPT is the dominant contributor, consistently driving 40–60%+ of all LLM traffic.
But this isn’t a single-player story. Other models are gaining share, especially in specific sectors:
Perplexity is surprisingly strong, contributing over 0.073% of Finance traffic, 0.041% in SMB, and 0.041% in Legal.
Copilot makes up a meaningful chunk of Legal (0.076%) and Finance (0.036%) sessions. Second only to ChatGPT in both.
Gemini is emerging in Insurance (0.0075%) and SMB (0.035%).
Claude is still marginal (<0.001% in most industries), but present across the board.
Bottom line: While ChatGPT leads, LLM discovery is becoming a multi-model landscape, and performance is beginning to vary by vertical and use case.
This has two implications:
You can’t just optimize for one model. Visibility across platforms will matter more over time.
Different models favor different formats, sources, and structures. Understanding how each one pulls and presents content is your next strategic edge.
How to adapt to the LLM traffic surge starting now
If you’re still treating LLMs like a 2026 conversation, you’re already behind.
The shift is no longer theoretical; it’s happening in your analytics
right now. And the teams that move early will stay visible and build a
lasting competitive edge.
Here’s how to respond:
1. Start tracking LLM-driven sessions, even if it’s imperfect
You can’t manage what you don’t measure.
Set UTM parameters for AI platforms. Monitor for unexplained spikes
in direct traffic. Annotate content that gets surfaced in ChatGPT or
Perplexity.
Look for surges in branded search that coincide with AI exposure. Start tracking mentions, not just clicks.
Attribution won’t be perfect – but waiting for standardized reporting is how you miss the wave.
2. Structure your content for AI interfaces, not just human readers
LLMs favor content that’s clean, clear, and scannable. Think bullet points, tight intros, FAQ sections, and strong summaries.
If featured snippets were SEO 2.0, this is 3.0. Answers need to perform inside a model’s response, not just on a results page.
3. Shift your mindset: from ranking to being selected
It’s not about being in position #1 – it’s about being the answer a model chooses to surface.
That means relevance, clarity, and trust signals matter more than ever.
Audit the content already being cited or linked by AI platforms and
build a strategy for becoming the go-to source in your space.
If you don’t, your competitor will.
4. Make your content AI-ready across the entire funnel
This isn’t just about blogs.
Product pages, help docs, onboarding flows – every touchpoint is now eligible to be surfaced in an AI conversation.
You need cross-functional alignment between SEO, content, UX, and
product teams to ensure your entire site is conversation-ready.
SEO isn’t dying – it’s evolving
SEO is splitting into two tracks: traditional search and LLM-driven discovery.
The second one is growing faster than anyone expected and it’s
already rewriting how users find answers and how brands earn visibility.
Traditional SEO isn't
enough in the world of answer engines. Optimize for LLMs, boost AI
citations, and engineer relevance at scale.
The shift from traditional search engines to AI-powered answer engines signals more than a technical upgrade.
It marks a fundamental change in how people discover, evaluate, and act on information.
Search is no longer a discrete game of isolated queries and static rankings.
It’s becoming an infinite game – one shaped by context, memory, and ongoing interaction.
For many users, large language models
(LLMs) now offer a more effective starting point than classic search
engines, especially when the task calls for clarity, research, or a more
conversational experience.
How search evolved: From static queries to continuous conversations
Traditional search: A one-off query model
Traditional search engines (like classic Google Search) operate on a deterministic ranking model.
Content is parsed, analyzed, and displayed in SERPs largely as provided.
Ranking depends on known factors:
Content quality.
Site architecture.
Links.
User signals.
A user types a query, receives a list of results (“10 blue links”), clicks, and typically ends the interaction.
Each query is treated independently, with no memory between sessions.
This model supports advertising revenue by creating monetization opportunities for every new query.
AI-powered search: Built for continuity and context
AI-powered answer engines use a probabilistic ranking model.
They synthesize and display information by incorporating:
Reasoning steps.
Memory of prior interactions.
Dynamic data.
The same query can yield different results at different times.
These systems are built for ongoing, multiturn conversations,
anticipating follow-up questions and refining answers in real time.
They operate continuously, even while you sleep, and focus on
delivering direct, synthesized answers rather than just pointing to
links.
How output and experience differ between search and answer engines
The differences between traditional search and AI-powered answer
engines aren’t just technical. They show up in what users see and how
they interact.
From output format to underlying signals, the user experience has fundamentally changed.
From link lists to zero-click answers
Traditional search engines: Return a ranked list of links generated by complex algorithms.
Answer engines: Deliver full answers, summaries,
direct responses, or even product recommendations by blending
large-scale training data with real-time web results. They reduce the
need for users to click through multiple sites, leading to more
zero-click experiences.
From keywords to context
Traditional search: Relies on keyword matching, backlinks, and on-page optimization.
AI search/generative engines: Rely on semantic
clarity, contextual understanding, and relationships between entities
enhanced by attention mechanisms and references in credible sources.
Even content that doesn’t rank highly in traditional search may appear
prominently in AI summaries if it is well-structured, topical, and cited
across trusted platforms.
Key characteristics of answer engines
Conversational search
LLMs like ChatGPT, Google Gemini, and Perplexity
enable conversational interactions, often serving as a more intuitive
starting point for users seeking clarity, context, or nuanced
understanding.
Queries tend to be longer and phrased as full questions or instructions.
Personalization and memory
Unlike traditional search, AI-powered search incorporates user context, such as:
Past queries.
Preferences.
Location.
Even data from connected ecosystems (e.g., Gmail within Google’s AI Mode).
This context allows the engine to deliver tailored, dynamic, and unique answers.
Instead of processing a single query, answer engines deconstruct a
user’s question into dozens or even hundreds of related, implicit,
comparative, and personalized sub-queries.
These synthetic queries explore a broader content pool.
From one query, systems like AI Mode or AI Overviews:
Instead of retrieving or ranking entire pages, AI engines work at the passage level.
They extract and rank smaller, highly relevant chunks of content to build precise, context-rich answers.
Advanced processing features
User embeddings and personalization
Systems like Google’s AI Mode use vector-based profiles that represent each user’s history, preferences, and behavior.
This influences how queries are interpreted and how content is
selected, synthesized and surfaced as a result – different users may
receive different answers to the same query.
Deep reasoning
LLMs evaluate relationships between concepts, apply context, and weigh alternatives to generate responses.
Content is judged on how well it supports inference and problem-solving, not just keyword presence.
Pairwise ranking prompting
Candidate passages are compared directly against each other by the
model to determine which is most relevant, precise, and complete.
This approach departs from traditional scoring models by favoring the best small sections rather than entire documents
A step-by-step guide to answer-engine-optimized content
Content best practices remain the same – it should be people-centric,
helpful, entity-rich with healthy topical coverage based on audience
intent.
However, the content creation process needs to incorporate answer-engine optimization best practices in the details.
Here’s our recommended seven-step process for content creation.
1. Content audit
When auditing existing content:
Check current visibility signals, including impressions, rich
results, and whether the page is cited in AI platforms like Google AI
Overviews, ChatGPT, or Perplexity.
Identify signs of content decay to establish a baseline for measuring improvement.
Spot and document issues such as:
Topical gaps or missing subtopics.
Unanswered user questions.
Thin or shallow content sections.
Outdated facts, broken references, or weak formatting.
Grammatical errors, duplicate content, or poor page structure.
2. Content strategy
It is not all about creating new content.
Your content strategy should incorporate aligning existing content to the needs of answer engines.
Retain: High-converting content with high visibility and high traffic.
Enhance: Pages with high impressions but low click-through rate, pages with low visibility, impressions, and rich results.
Create: Content around topical gaps found in the audit.
3. Content refresh
Update existing content to close topical gaps to make information easily retrievable
4. Content chunking
This involves breaking long blocks into:
Scannable sections (H2/H3).
Bullet lists.
Tables,
A short TL;DR/FAQs.
Keep each chunk self-contained so LLMs can quote it without losing context, and cover just one idea per chunk.
Cover topics AI can’t easily synthesize on its own.
Cite and link to primary sources within the text (where relevant and meaningful) to boost credibility.
6. Layer on machine-readable signals
Insert or update schema markup (FAQPage, HowTo, Product, Article, etc.).
Use clear alt text and file names to describe images.
7. Publish → monitor → iterate
After publishing, track organic visibility, AI citation frequency, and user engagement and conversion.
Schedule content check-ins every 6–12 months (or after major core/AI updates) to keep facts, links, and schema current.
Make your content LLM-ready: A practical checklist
Below is a checklist you could incorporate in your process to ensure
your content aligns with what LLMs and answer engines are looking for.
Map topics to query fan-out
Build topic clusters with pillar and cluster pages.
Cover related questions, intents, and sub-queries.
Ensure each section answers a specific question.
Optimize for assage-level retrieval
Use clear H2/H3 headings phrased as questions.
Break content into short paragraphs and bullet points.
Include tables, lists, and visuals with context.
Build depth and breadth
Cover topics comprehensively (definitions, FAQs, comparisons, use cases).
Anticipate follow-up questions and adjacent intents.
Personalize for diverse audiences
Write for multiple personas (beginner to expert).
Localize with region-specific details and schema.
Include multimodal elements (images w/ alt text, video transcripts, data tables).
Strengthen semantic and entity signals
Add schema markup (FAQPage, HowTo, Product).
Build external mentions and links from reputable sources.
Use clear relationships between concepts.
Show E-E-A-T and originality
Include author bios, credentials, and expertise.
Add proprietary data, case studies, and unique insights.
Ensure technical accessibility
Clean HTML, fast load times, AI-friendly crawling (robots.txt).
Maintain sitemap hygiene and internal linking.
Align with AI KPIs
Track citations, brand mentions, and AIV (attributed influence value).
Monitor engagement signals (scroll depth, time on page).
Refresh content regularly for accuracy and relevance.
How SEO is evolving into GEO
As the mechanics of search evolve, so must our strategies.
GEO
(generative engine optimization) builds on SEO’s foundations but adapts
them for an environment where visibility depends on citations, context,
and reasoning – not just rankings.
Many “new” AI search optimization tactics, such as focusing on
conversational long-tail searches, multimodal content, digital PR, and
clear content optimization, are essentially updated versions of
long-standing SEO practices.
New metrics and goals
Traditional SEO metrics like rankings and traffic are becoming less relevant.
The focus shifts to being cited or mentioned in AI-generated answers,
which becomes a key visibility event and a brand lift moment, rather
than just driving traffic.
New KPIs at the top of the funnel include:
Search visibility.
Rich results.
Impressions.
LLM visibility.
With declining traffic, engagement, and conversion metrics become critical at the bottom of the funnel.
Relevance engineering
This emerging discipline involves:
Strategically engineering content at the passage level for semantic similarity.
Anticipating synthetic queries.
Optimizing for “embedding alignment” and “informational utility” to ensure the AI’s reasoning systems select your content.
Your website acts as a data hub.
This also means centralizing all types of data for consistency and
vectorizing data for easy consumption, and distributing it across all
channels is a critical step.
Importance of structured data
Implementing schema markup and structured data is crucial for GEO.
It helps AI engines understand content context, entities, and
relationships, making it more likely for content to be accurately
extracted and cited in AI responses (53% more likely).
Brand authority and trust
AI models prioritize information from credible, authoritative, and trustworthy sources.
Building a strong brand presence across diverse platforms and earning
reputable mentions (digital PR) is vital for AI search visibility, as
LLMs may draw from forums, social media, and Q&A sites.
Connecting the dots: UX and omnichannel in the age of AI search
The typical user journey is no longer linear. The options for discovery have diversified with AI acting as a disruptor.
Most platforms are answering questions, are multimodal, delivering agentic and personalized experiences.
Your audience expects similar experiences on the sites they visit. As
the user journey evolves, our approach to marketing needs to change,
too.
In a linear journey, having channel-based strategies worked.
Consistency of messaging, content, visuals and experiences at every touchpoint are today key to success.
That means you need an audience strategy before mapping channels to the strategy.
To make it happen effectively, you need to orchestrate the entire
content experience – and that starts with your platform as the
foundation.
Your website today needs to act as the data hub feeding multimodal information across channels.
How to make your content discoverable by LLMs
To show up in LLM-driven search experiences, your content needs more than depth. It needs structure, speed, and clarity.
Here’s how to make your site visible and machine-readable.
Foundational SEO
The fundamentals of SEO still apply.
LLMs have to crawl and index your content, so technical SEO elements like crawlability and indexability matter.
LLMs do not have the crawl budgets or computing power that Google and Bing have.
That makes speed and page experience critical to maximize crawling and indexing by LLMs
Digital assets
With search going multimodal, your digital assets – images and videos – matter more than they ever did.
Optimize your digital assets for visual search and make sure your
page structure and elements include FAQs, comparisons, definitions, and
use cases.
Structural integrity
Your site and content need to be both human and machine-readable.
Having high-quality, unique content that addresses the audience’s needs is no longer enough.
You need to mark it up with an advanced nested schema to make it machine-readable.
Deep topical coverage
Ensure your content aligns with the best practices of Google’s E-E-A-T.
People-first content that:
Is unique.
Demonstrates expertise.
Is authoritative.
Covers the topics that your audience cares about.
Make your content easy to find – and easy to use
While the building blocks of SEO are still relevant, aligning with
LLM search calls for refining the finer points of your marketing
strategy to put your audience before the channels.
Start with the basics and ensure your platform is set up to let you centralize, optimize and distribute content.
Adopt IndexNow to push your content to LLMs instead of waiting for
them – with their limited computing and crawling capabilities – to crawl
and find your content.
Thank you, Tushar Prabhu, for helping me pull this together.
Cloudflare says
Perplexity evades crawl directives with stealth tactics; Perplexity
calls the claims a misunderstanding – or a PR stunt.
Cloudflare accused AI answer engine Perplexity of “stealth crawling,”
saying it uses deceptive techniques to bypass website blocks and access
content it’s been explicitly told not to touch.
In response, Perplexity said Cloudflare has a fundamental
misunderstanding of how AI assistants work and accused the company of
either publicity-seeking or technical incompetence.
The big picture. Cloudflare said Perplexity uses
declared bots when it can, but switches to “stealth crawling” when
blocked. That includes mimicking normal browser behavior, rotating IPs,
and ignoring robots.txt rules (tactics that can be associated with
scrapers and bad actors).
Cloudflare tested this by setting up honeytrap sites and found
Perplexity answering questions using content it shouldn’t have been able
to access.
Perplexity insisted its requests are made on behalf of users, not as
preemptive crawling. The company says these are real-time fetches, akin
to what a browser or email client does, and claims Cloudflare mistook
its behavior for something it wasn’t.
Why we care. If AI assistants can sidestep
robots.txt by posing as browsers, brands, creators, and publishers lose
control over how and when their content is used. That breaks the old deal between search engines and websites.
What’s next. Cloudflare said it’s already blocking
the behavior in question and expects Perplexity’s tactics to change in
response. It’s calling for standardization of bot behavior through IETF
(the Internet Engineering Task Force) and other policy efforts.
Perplexity, meanwhile, is doubling down on its identity as an
agentic AI platform and says it shouldn’t be governed by rules designed
for traditional web crawlers.
The blog posts. You can view the full back and forth here:
A researcher reveals
Perplexity’s ranking logic, including entity reranking, manual domain
boosts, and signals driving content visibility.
Want to know how content is scored, ranked, and in some cases,
discarded by Perplexity? Independent researcher Metehan Yesilyurt
analyzed browser-level interactions with Perplexity’s infrastructure to
reveal how the AI answer engine evaluates and ranks content.
Why we care. Everybody involved with driving SEO and/or GEO
success wants to understand how to gain visibility (citations and
mentions) in AI answer engines. This research (albeit unverified at this
point) offers some clues about Perplexity’s ranking signals, manual
overrides, and content evaluation systems that could improve your
optimization strategies for Perplexity (and possibly other answer
engines) to gain a ranking advantage.
Entity search reranking system. One significant
Perplexity system uncovered is a three-layer (L3) machine learning
reranker. It is used for entity searches (people, companies, topics,
concepts). Here’s how it works:
Initial results are retrieved and scored, like traditional search.
Then, L3 kicks in, applying stricter machine learning filters.
If too few results meet the threshold, the entire result set is scrapped.
This means quality signals and topical authority are super important
for L3 – and keyword optimization isn’t enough, according to Yesilyurt.
Authoritative domains. Yesilyurt also discovered manual lists of authoritative domains (e.g., Amazon, GitHub, LinkedIn, Coursera). Yesilyurt wrote:
“This manual curation means that content associated with or
referenced by these domains receives inherent authority boosts. The
implication is clear: building relationships with these platforms or
creating content that naturally incorporates their data provides
algorithmic advantages.”
YouTube synchronization = ranking boost. Another
interesting find: YouTube titles that exactly match Perplexity trending
queries see enhanced visibility on both platforms.
This hints at cross-platform validation. Perplexity might validate
trending interest using YouTube behavior – rewarding creators who act
fast on emerging topics, according to Yesilyurt.
Core ranking factors. Yesilyurt documented dozens of what he called Perplexity’s “core ranking factors” that influence content visibility:
New post performance: Early clicks determine long-term visibility.
Topic classification: Tech, AI, and science get boosted; sports and entertainment get suppressed.
Time decay: Publish and update content frequently to avoid rapid visibility declines.
Semantic relevance: Content must be rich and comprehensive – not just keyword-matched.
User engagement: Clicks and historic engagement signals feed performance models.
Feed distribution: Visibility in feeds is tightly controlled via cache limits and freshness timers.
Negative signals: User feedback and redundancy checks can bury underperforming content.
What’s next. Yesilyurt said success on Perplexity
requires a combination of strategic topic selection, early user
engagement, interconnected value, continuous optimization, and
prioritizing quality over gaming.
Sound familiar? To me, it sure sounds like doing the SEO fundamentals.
Despite AI’s promise
of inclusion, search and LLMs still sideline minority languages. Here’s
why it matters – and what must change.
Despite thousands of languages spoken worldwide, only a small fraction are meaningfully represented online.
Most of what we see in search results, AI outputs, and digital
platforms is filtered through just a handful of dominant languages –
shaping not only what we find, but whose knowledge counts.
The multilingual promise, the monolingual reality
We live in an era where technology promises frictionless communication:
Seamless translation.
Real-time AI interpretation.
Instant access to the collective knowledge of humanity.
In theory, language should no longer be a barrier.
But look more closely – at search results, AI-generated answers, digital discourse – and the cracks start to show.
The web might be global, but it still speaks mostly English, Russian, Spanish, and a handful of other dominant tongues.
For those of us working at the intersection of language, search, and AI, this isn’t just a missed opportunity.
It’s a structural flaw – one with far-reaching implications for discoverability, inclusion, and even the shape of truth online.
I’ve seen this firsthand.
My browser and search settings are configured for Belarusian, a language I read, speak, and deliberately engage with.
And yet, whether I search in English or Belarusian, Google often
serves me Russian-language results – Russian perspectives from Russian
sources.
This isn’t a quirky algorithmic hiccup or a localization bug. It’s a
pattern – a form of bias rooted in how search engines interpret, weigh,
and prioritize language.
And it’s not just Belarusian.
Globally, users who search in non-dominant languages or come from
minority linguistic contexts are quietly, systematically funneled toward
dominant language zones.
That funneling doesn’t just affect what we read. It shapes what we
believe, what we share, and ultimately, which voices define our reality.
How the web fails most of the world’s languages
There are more than 7,100 living languages spoken around the world. Roughly 4,000 have writing systems.
But in practice, only 150 or so are meaningfully represented online, and fewer than 10 dominate over 90% of the web’s content.
English alone accounts for more than half of all indexed webpages.
Add Russian, German, Spanish, French, Japanese, and Chinese, and you cover the lion’s share of searchable content.
The rest? Fragmented, under-indexed, or invisible.
That imbalance has serious consequences.
Search engines, AI systems, and social platforms don’t just surface facts – they shape the informational universe we inhabit.
When those systems overwhelmingly prioritize English or other
dominant languages, they don’t just filter out voices – they flatten
nuance and erase local context.
They let a handful of dominant languages tell everyone else’s story.
This is especially true in politically sensitive, culturally complex, or rapidly evolving contexts.
Consider Russia, a nation with well over 100 languages, of which 37
are officially recognized, yet whose international digital presence is
nearly monolingual.
Where are the Tatar-language blogs? The Sakha cultural archives? The Chechen oral histories?
They exist, but they don’t make it into the global conversation, because search doesn’t bring them forward.
And the same is true across Africa, Asia, South America, and indigenous communities in the U.S., Canada, and elsewhere.
We don’t lack content. We lack systems that recognize, rank, and translate that content appropriately.
AI promised more, but it’s still speaking the same few languages
We had reason to believe AI would break the language barrier.
LLMs like GPT-4, Gemini, and Claude can process dozens of languages,
translate on the fly, and summarize content far beyond what traditional
search could offer.
Chrome translates entire pages in real time.
DeepL handles high-fidelity translation from Finnish to Japanese to Ukrainian.
But the promise of multilingual AI hasn’t fully translated to
practice, because AI’s fluency across languages is far from equal.
Their understanding of smaller or less-represented languages remains inconsistent and is often unreliable.
Take Belarusian as an example.
Despite being a standardized national language with a rich cultural
and literary tradition, Belarusian is often misidentified by GPT
models.
They may respond in Russian or Ukrainian instead, or produce Belarusian that feels flattened and oversimplified.
The output often ignores the language’s expressive range, inserting
Russian or Russified vocabulary that erodes both authenticity and
nuance.
Google fares no better.
Belarusian search queries often get auto-corrected to Russian, and
results – including AI Overviews – are also in Russian, citing from
Russian sources.
This reflects an embedded assumption: that queries in smaller or
politically adjacent languages can be safely redirected to a dominant
one.
But that redirection isn’t neutral. It quietly erases linguistic
identity and undermines informational authority, with real consequences
for how people and places are represented online.
As LLMs become the default layer for information retrieval, powering
decisions in business, medicine, education, and elsewhere, this
imbalance becomes a liability.
It means the knowledge we access is incomplete, filtered through a
narrow set of linguistic assumptions and overrepresented sources,
shaping what we see and whose voices we hear.
What needs to change and who needs to move first
The issue isn’t just technical, but also cultural and strategic.
Solving it means addressing multiple layers of the ecosystem at once.
Google (and major search engines)
Google must relax the linguistic boundaries in its ranking systems.
If a query is in English, but the most accurate or insightful answer
exists in Belarusian, Swahili, or Quechua, that content should surface
with clear, automatic translation as needed.
Relevance should take precedence over language match, especially when the content is high-quality and current.
Today, language signals, like inLanguage, hreflang, description, and translationOfWork, exist in Schema.org, but they remain weak signals in practice.
Google should strengthen its weight in ranking, snippet generation, and AI output.
Google’s AI Overviews should be explicitly multilingual by design,
sourcing answers from across languages and transparently citing
non-English sources.
Inline translations or hover-over summaries can bridge comprehension without sacrificing inclusivity.
Needless to say, Google must stop auto-correcting queries across languages.
AI platforms, LLM providers, content distributors, and self-publishing
Companies like OpenAI, Anthropic, Mistral, and Google DeepMind need to move beyond the illusion of linguistic parity.
Today’s LLMs can process dozens of languages, but their fluency is uneven, shallow, or error-prone for many non-dominant ones.
Users can ask language models to pull from sources in specific
languages – for example, “Summarize recent articles in Burmese about
monsoon farming” – and sometimes, the results are useful.
But this capability is fragile and unreliable.
There’s no built-in way to set preferred source languages, no guarantee of accuracy, and frequent hallucinations.
Users also have no control over – or visibility into – which languages the model is actually pulling from.
Large content platforms – from books to video to music – need to
support and index content in all languages, not just the few preloaded
in their metadata dropdowns.
Many niche or regional languages still have tens of millions of
speakers, yet they’re excluded simply because platforms don’t support
those languages for titles, tags, or descriptions.
When content is auto-rejected or left untagged due to missing
language options, it becomes effectively invisible – no matter how
relevant or high-quality it is.
What publishers in smaller languages can do
Not every publisher can afford a multilingual content operation. But full localization isn’t the only path forward.
If you publish in a smaller language, here’s how you can increase visibility and access without breaking your budget.
Include a summary in a dominant language: Even a
100-200-word English summary can make your content more discoverable,
both by Google and LLMs. This doesn’t need to be a full translation –
just a faithful, plain-language overview of what the article is about.
Use schema metadata smartly:
inLanguage to declare the language clearly (e.g., be, tt, qu, eu).
description for English summaries.
alternateName and translationOfWork to link related content.
Submit multilingual sitemaps: Consider experimenting with hreflang-enabled sitemaps, even if they link from the original content to its summary or abstract.
Tag your posts consistently: Make sure your language settings are properly set in your CMS, page headers, andsyndication feeds.
Build a parallel “About” page or glossary: A single
English page explaining your mission, language, or context can go a
long way toward increasing your presence among English-speaking
audiences.
Use social platforms strategically: While Facebook
and X aren’t search engines, they are discovery engines. Leveraging the
AI post translations feature and hashtags can help surface local content
across global audiences.
What users can do to stay aware and see more
Searchers and readers have more power than they think.
If you want to move beyond linguistic silos and see the full(er) spectrum of what the web has to offer:
Use better search operators: Try combining your query with site: and country TLDs:
"agriculture policy" site:.by
"digital ID systems" site:.in
"housing protests" site:.cl
Explore queries in the target language: Even if
you’re not fluent, translate your query and run it in another language.
Then use browser translation tools to read the results.
Install real-time translation extensions: DeepL, Lingvanex, or even Chrome’s built-in tools can make foreign-language content feel more native.
Prompt your AI tools with specific language instructions:
“Answer in English, but pull from Georgian sources only.”
“Summarize news from Belarusian-language media from the past 7 days.”
Push your platforms: Influencer content generation
tools like ProVoices.io or news aggregators like Feedly should expand
their multilingual sourcing. Many content and news-related startups are
hungry for feedback and nimble enough to implement it.
The web we deserve
We often talk about democratizing knowledge – about giving everyone a
voice and building systems that reflect the true diversity of the
world.
But as long as our search engines, AI tools, and content platforms
continue to prioritize only a handful of dominant languages, we’re
telling a partial story.
True inclusion means more than translation.
It means designing systems that recognize, surface, and respect
content in all languages – not just those with geopolitical or economic
weight.
The web will only become more accurate, more nuanced, and more
trustworthy when it reflects the full range of human experience – not
just the perspectives most easily indexed in English, Russian, or
Mandarin.
We have the models. We have the data. We have the need.
It’s time to build systems that listen – in every language.
A new Google blog post shares some broad traffic trends and tells us that AI drives more queries and higher quality clicks
Google is touting AI as the biggest upgrade to Search in its history –
claiming more queries, higher quality clicks, and a healthier web. But a
new blog post (authored by Liz Reid, VP, head of Search) leaves out
actual details about who’s winning, and losing – and how much control
publishers really have.
Here’s what Google says, and what they’re not saying.
Google: AI Overviews are driving more searches
“People are able to ask questions they could never ask before… searching more than ever.”
Yes, but Google doesn’t share how many queries are actually leading to clicks or how many are now fully answered on Google without the need to visit a site.
Google: Traffic is ‘relatively stable’ year-over-year
“We’re actually sending slightly more quality clicks to websites than a year ago.”
Yes, but: No data, no definitions. “Slightly” and
“quality” are vague, unverified metrics. Google wouldn’t say how many
total clicks are down or which sites are losing them.
Google: AI Overviews show more links, so more chances to click
“People are seeing more links on the page than before.”
Yes, but: Google Search Console data shows for many
sites that impressions are going up and clicks are down. People may
“see” the links – but I may also “see” a display ad on a webpage that I
completely ignore.
Google: Click quality is up
“Users don’t quickly click back… typically a signal that a user is interested in the website.”
Google: Search behavior is shifting – users want “authentic voices”
“People are increasingly seeking out and clicking on sites with forums, videos…”
Yes, but: That shift may not be entirely natural. It could simply reflect Google’s favoring its partner Reddit (though the Google’s Reddit partnership is unrelated to Reddit’s huge search visibility boost, according to Google) and its own video platform – YouTube.
Although, granted, there was much discussion a couple years back
that people had to add “Reddit” to their searches to find what they
actually wanted. Regardless, Reddit’s organic traffic has been booming
since last year, often appearing directly under AI Overviews or ads as
the de facto top organic listing.
Google: The web is healthy and thriving
“We continue to send billions of clicks to websites every day.”
Yes, but: Billions mean nothing without context.
The distribution of that traffic matters, especially for publishers
whose traffic is vanishing. All we know is Google sees more than 5 trillion searches per year. And also numerous reports (flawed or not) indicate that CTR is down and impressions are up (a.k.a., the great decoupling) when AI Overviews appear.
Google: Search is built to highlight the web
“It’s not the web or AI — it’s both.”
Yes, but: AI Overviews often repurpose and
repackage web content, reducing the need to click. Google’s framing of
“highlighting” may be seen as summarizing what creators have created,
without compensation and sometimes without credit.
Bottom line
Google wants credit for expanding the web’s reach, but won’t or can’t
show us the data. Without real transparency, it’s hard to know where
the truth lives. For now, creators, SEOs, and publishers are left
guessing how much of their traffic has been eaten by AI – and how much
is simply hidden
Tests reveal ChatGPT
Plus quoting content only indexed by Google. Is ChatGPT Plus somehow
sourcing answers using Google Search results?
A new Backlinko test adds fresh fuel to speculation that ChatGPT Plus
may be relying on Google Search, at least some of the time, to surface
web content.
Backlinko’s “sting” experiment appears to confirm earlier findings
from SEO pros Abhishek Iyer, Aleyda Solis, and Alexis Rylko that
visibility in Google’s index can directly impact ChatGPT Plus answers.
Why we care. These tests all seem to conclude that
SEO is far from dead – especially if ChatGPT is indeed somehow using
Google Search. If your page appears in Google but not Bing, for example,
it could be cited in ChatGPT responses. And if your content is
invisible to Google, you may be invisible to AI.
The experiment. Backlinko created a nonsense SEO
term – NexorbalOptimization – and published a page about it. The key:
only Googlebot was allowed to crawl the page. It had no links to it and
didn’t appear in the sitemap, making the page invisible unless
discovered by Google.
Once indexed in Google, the team asked various AI models: What is NexorbalOptimization?
Only ChatGPT Plus (with browsing) and Perplexity (surprisingly) returned accurate answers – quoting Backlinko’s page directly.
Other models (including Claude and ChatGPT free) failed to find or summarize the term.
What does it mean? Backlinko’s test strengthens a growing belief among SEOs that ChatGPT Plus is sourcing data from Google.
OpenAI’s documentation lists Bing as the default search partner.
However, the behavior observed across multiple controlled tests seems to
tell a different story.
No comments from OpenAI, Google. There’s no
confirmation of any kind of Google-OpenAI deal. An article declaring SEO
dead included this passage about Iyer’s experiment and the publisher’s
attempts to get a comment from either company:
“Asked about the experiment, OpenAI responded on background,
emphasizing its ongoing relationship with Microsoft, suggesting that it
used a variety of search providers, but not specifically denying that
ChatGPT could be Googling. Informed of Iyer’s findings, Google declined
to comment.”
Abhishek Iyer: The former Google engineer ran a nearly identical test,
indexing a hidden page only in Google. ChatGPT Plus found it. The free
version of ChatGPT did not — and no other search engine had access to
the page. He also analyzed ChatGPT’s search references and found strong
alignment with Google’s domain and snippet data, not Bing’s.
Aleyda Solis: The well-known consultant’s test
observed that ChatGPT responses mirrored Google Search snippets – down
to the wording – once a page was indexed. In contrast, Gemini accessed
the page directly, even before it was indexed by Google. When Bing
eventually indexed the page, ChatGPT continued quoting snippets from
Google SERPs, not Bing.
Alexis Rylko:This test
compared JSON search logs from ChatGPT against live search results.
Across multiple queries, up to 90% of ChatGPT’s cited URLs matched
Google’s top results – far outpacing overlap with Bing. He also noted
that snippet formatting, timestamps, and metadata all mirrored Google’s
structure, not Bing’s
Learn how to use
YouTube to improve SEO, drive traffic, and earn SERP features. Explore
advanced video strategies for search visibility and authority.
YouTube for SEO is more powerful than ever. It plays a crucial role
in modern-day marketing, where a multi-channel approach helps brands get
visibility.
Think of YouTube as a search engine in its own right. Users search
YouTube’s search bar to find videos that fulfill their search queries.
But it doesn’t stop there.
Optimized videos don’t just perform well on YouTube. They also rank
in search engine results pages (SERPs), enhance a brand’s visibility in
Google with SERP features (such as video carousels), and improve page
experience by offering video as a format for getting information, which
can increase time on page.
Whether you’re here to rank videos on YouTube or use video to bolster
your search ranking, this guide is for you. We cover the role of
YouTube SEO in modern-day search marketing. Plus, we share tips for
optimizing your YouTube channel and your presence in Google so you can maximize brand visibility.
YouTube is a search engine and social media platform
YouTube serves as both a search engine and a social media platform.
It’s a search engine because users type what they’re looking for directly into YouTube’s search bar and click on the most relevant video results.
It’s a social media platform because users engage with creators’ videos through likes, comments, and shares.
YouTube is the second largest search engine after—you guessed
it—Google. YouTube’s role in SEO shouldn’t be dismissed. Video
optimizations increase brand visibility because videos can rank via
pages on your site or through YouTube.
YouTube is a huge opportunity for search marketers. Users spend 27
hours and 26 minutes on YouTube in a month, just behind TikTok’s 33
hours and 38 minutes. While time spent on TikTok is incredibly high, it
doesn’t bring as much value to SEO because YouTube videos are
prioritized in Google search results pages.
The data below shows that YouTube ranks for 4.4 billion keywords versus TikTok’s 1.4 billion.
Sure, clicks and visits are good, but YouTube has more to offer. It’s
one of the most engaged social media platforms, second to WhatsApp. On
average, users spend 23 minutes and 19 seconds per visiton YouTube (compared to 29 minutes and 16 seconds on WhatsApp).
The takeaway?
Users are highly engaged on YouTube, and if your videos can capture
this level of engagement, it can only be good for your brand. What would
you say if you could connect and speak with your ideal customer for 20
minutes?
Here’s a fun example demonstrating how powerful YouTube can be for
brand visibility and ranking. For the search “how to knit,” Sheep &
Stitch, a channel that teaches beginners how to knit, stitch, and cast,
ranks three times.
It has secured:
A video carousel SERP feature, which is at the very top of Google SERPs
A traditional organic listing placed in rank two
A featured video within People Also Ask (PAA)
The screenshot below shows seven opportunities to rank, and Sheep
& Stitch has three of the rankings, or an impressive 42% of
available real estate.
This is cross-channel (and cross-stitch?) search marketing perfected.
Keyword research for YouTube and Google synergy
Dual-channel keyword research is a smart first step for multi-channel
SEO because you gather data from both search channels, which provides
the data needed to align both video SEO for YouTube (e.g., video titles,
tags, and descriptions) and traditional SEO for search engines (e.g.,
title tags, URLs, and meta descriptions).
Coordinating these two channels gives you the best possible chance of
visibility because you’ll have thought out your video and content
strategy to work in alignment.
Important note: Your
keyword research must be considered in tandem with your broader content
calendar, business goals, and your target audience. Before you get into
creating content, establishing goals, audience personas, and content
pillars will help you create videos that resonate with your audience.
For support on the early stages of content strategy, read this article
on content marketing strategy.
When conducting keyword research for multiple channels, you’re looking for:
One keyword to lead with on both platforms. This will be your focus keyword. Consider it the primary keyword you’re trying to rank on both YouTube and Google.
Supporting keywords that should also be used to rank your new video content.
Keywords that cross over on both platforms,meaning you’ll find search opportunities on both platforms.
Keywords that appear on one platform but not the other, so you can use them more strategically on one platform compared to the other.
Business and marketing goals so you can ensure
every piece of content created ties back to a goal, like increased sales
or engagement with specific target audiences.
Trending topics: the more significant the trend, the more you’ll want to prioritize it.
Pro tip:
While this guide covers Google and YouTube, a coordinated content
marketing strategy could take your efforts even further by repurposing
videos onto other platforms like TikTok or Instagram. You’d follow
similar channel-specific keyword research, like using TikTok’s Creative Content Keyword Insights.
Keyword research for YouTube
There are many tools for YouTube keyword research. In the spirit of
video and SEO, here’s a video that covers YouTube keyword research
tools.
And here’s a walkthrough of our favorites.
Semrush
Semrush has an app (free for seven days) that helps you identify YouTube keywords, competition, and search volume.
To use the app:
Go to Semrush > In the left-hand menu, click on “App Center” > Click “Store” > Use the search bar and type “Keyword Analytics for YouTube” > Click the magnifying glass >“Go to App”
Start the seven-day trial. (You can cancel any time.)
Using the keyword research tool, type a keyword into the search bar and click “Search.”
The tool lists your searched keyword and related keywords. You can
select the keywords you want to see more data about from the list on the
left. The “Competitive Rate” and “Search Volume” data in the top-right
will change to show data for the keyword selected.
You can use this tool to identify your focus keyword and supporting keywords. Select supporting keywords from the related list.
If you get serious about YouTube SEO, you can sign up for one of
TubeRanker’s plans and perform keyword research and keyword tracking.
TubeRanker is more of an all-around YouTube SEO tool, and it includes other functions such as:
Tag generator
Channel audit
Keyword tool
Rank tracker
Tag extractor
Hashtag generator
Title generator
Description generator
TubeBuddy
Another alternative is TubeBuddy, which has a Chrome extension. Toggle the extension on while using YouTube and it provides:
An analysis of your search term and how competitive it is to rank for
Related video searches, web searches, and video topics
Tags that are commonly used
Here’s what it looks like:
Google Trends
Google Trends
is a free tool that shows you how keywords are trending on YouTube,
across web search, image search, news search, and Google shopping.
You can get pretty granular with Google Trends by:
Comparing keywords to see what’s searched for the most
Filtering to specific countries so you can best target geographics
Changing date ranges
Categorizing keywords
Pro tip: Enhance data from Google Trends by installing a free Chrome extension called Glimpse, which shows trend lines, real-time search volumes, related keywords, and more.
YouTube’s autocomplete
You can do some keyword research for free using YouTube’s autocomplete.
Start typing a keyword into the search bar and see what YouTube
search recommends. The idea behind this keyword research method is that
the recommendations are commonly searched.
Keyword research for videos that rank on Google
To give your videos the best chance of ranking and visibility,
include keyword research for Google as part of the keyword research
process.
Start with research for YouTube, then identify keywords that return videos in Google search.
Combining these two keyword research methods will give you all the
data you need to create a comprehensive video strategy that meets every
searcher’s query. You’ll know the crossover of search between YouTube
and Google, but also any opportunities unique to each platform.
Your keyword research for video and Google doesn’t need to be guesswork.
Here’s how you find keywords that return videos using keyword research tools:
The report lists the keywords you searched for and related keywords,
with the “SERP Features” column featuring icons for video results. Use
the filters to see data for all video features:
Video appears on the side of traditional listings. A
video may show if it’s embedded within the content of your website.
It’s commonly included when YouTube’s domain ranks in SERPs with a
video.
Featured video is placed at the top of SERPs and has a large thumbnail.
Video carousel is the most common video SERP feature and presents multiple videos in a carousel.
Further reading:
if you want to see your videos in prominent positions in Google, read
this guide on how to rank SERP features, which includes all types of
video features and tips on how to achieve them.
If you’re starting with keyword ideation from scratch, some content and keywords lend themselves well to video, including:
Educational or tutorial-based content
If you’re learning how to do something for the first time, nothing beats a visual tutorial walking you through step-by-step.
Example keywords:
How-to…
The guide to…
Step-by-step [task]
Here’s an example video with multi-channel SEO success.
HubSpot ranks at least three times on page one for the keyword “keyword research guide.”
And there’s more…
The ranking page is a top page for HubSpot’s marketing blog.
Informational content drawing on experience and thought leadership content
Video connects creators and audiences. If you’re creating content about your experience, try a video.
Example keywords:
Everything I learned trying…
My experience at [conference]
What X taught me about Y
Example video:
Simon Squibbs’ “30 Years of Business Knowledge in 2 hrs 26 minutes”
video is a great format that many creators copy. In his video, he
covers his motivations for creating the video, then shares his best
business tips, such as starting a business with no money, winning
business, creating a mind map, finding purpose, and so much more.
As of this writing, Squibb’s one video has:
13,498,409 views
581,000 likes
8,706 comments
Brand or product comparisons and reviews
Audiences watching videos comparing products or brands benefit from
watching real-life experiences unfold through product unboxings and
walkthroughs.
Now that you’ve done your video keyword research, you’re ready to set
up your YouTube channel. Keyword research is a direct insight into your
audience and their pain points. It can inspire how you set up your
channel.
Use keywords to inspire your:
Channel name, which can be up to 50 characters, should represent you, your brand, and what you do
Channel description, which can be up to 5,000 characters, should include natural-reading keywords
Channel trailer, which is the first video channel
visitors will see, so make it a good one! It’s common to have an
introductory video showing what your channel is about, or you can add a
promotional video. HubSpot does this well (there’s an example below).
Channel tags, which are keywords you input in the backend channel settings
Tips for setting up your YouTube channel for SEO success:
Think about keywords and integrate researched keywords into channel names, descriptions, and your trailer where they make sense. For your channel name, a keyword might not work; your brand or full name is fine.
Optimize channel tags using keywords. Think about the keywords people will type into YouTube’s search to find you.
Hook your visitor. Remember, your channel
description and trailer is your opportunity to engage your visitors and
keep them interested. SEO is very important, but engagement is critical.
Add a custom URL. Use a keyword if it makes sense.
Your custom URL will help your channel rank, but you don’t have to
over-optimize it. If your brand name or full name feels right, stick
with it.
Let’s look at how HubSpot optimizes its channel.
HubSpot’s channel name may be created with SEO in
mind. It could’ve been “HubSpot,” but they’ve included “CRM,” which
might be an SEO play. It does seem deliberate, as HubSpot is just
“HubSpot” on other channels, including Instagram and Facebook.
Interestingly, HubSpot has another YouTube channel called “HubSpot
marketing.” These channels could be separate for SEO benefits.
It’s worth remembering, however, that HubSpot is one of the largest SaaS companies.
Separate YouTube channels might make sense for multi-faceted companies
like HubSpot, but it won’t be the solution for everyone, especially
smaller businesses. There are downsides to this approach, such as
splitting your brand values across channels, splitting audiences, and
having to grow multiple channels simultaneously.
The channel description is promoting HubSpot’s CRM
with a trending feature, AI. Everyone is talking about AI, and this
description and video are likely to capture attention.
HubSpot’s trailer promotes the AI CRM and shows its functions.
Your channel description and trailer are particularly impactful
for showing your audience they’re in the right place. The trailer and
the description are the first two things your audience will see on your
channel homepage.
Consider SEO and optimizations, but don’t forget to create a trailer
that quickly engages your audience. HubSpot’s format of combining their
offering with a trending feature is a strong example of a trailer done
well.
Steps to optimize your video content on YouTube
With keywords decided, you can optimize your video content on YouTube
to give yourself the best chance of ranking within the YouTube platform
and on search engines.
Here are some top tips.
Understand your audience
Different demographics have preferences for different search
platforms. Knowing your audience is a key step in optimizing your video
content, as it could impact how you prioritize your keywords and video
strategy.
Fairly evenly male (54%) and female (46%), though men do prefer using YouTube
The largest consumer of YouTube content is aged 25-34 (21.50%), followed by 35-44 (17.90%)
In the US, Millennials (born 1981-1996) make up 25.50% of YouTube
users, followed by Gen-Z (born 1997-2012), who make up 25.10% of users
Gen Xers (born 1965-1980) make up 19.90% of users, and Baby Boomers (1946-1964) make up 15%
Video content is growing fast, and consumers use YouTube for more than just cat videos! HubSpot reports that:
People watch videos that have a goal to sell a product or service.
62% of consumers have watched product videos, demos, and reviews in the
form of a video.
38% of those surveyed use YouTube to learn new things. They also
like to explore entertaining content (46%) and find ideas and
inspiration (27%).
Knowing how your demographic uses search and social media can influence your approach to search marketing.
For example, if your audience is Gen Z, you know from the above data
that they’re a significant user base on YouTube. According to findings
by Axios, 27% of 18 to 24-year-olds start search discovery on video platforms like TikTok or YouTube.
Axios says:
Some
users prefer to search on social media to get more authentic answers,
especially as Google and others increasingly promote sponsored results.
For
news and quick answers, Jordan Alperin, 24, says she heads to Google,
but for inspiration and personal stories, she uses social media.
If you know how your audience searches, finds, and engages with
videos, you can plan to meet them on the platforms they frequent.
This doesn’t mean ignoring traditional search engines. We know that Google has the highest share of search.
What it means is that if Gen Z is the audience that converts the most
for your business, you may focus efforts on prioritizing their search
preferences, leaning a little more into YouTube SEO.
Crafting SEO-friendly video titles that attract clicks
SEO-friendly video titles include a focus keyword. But SEO isn’t the
only thing that matters. A good title is compelling and clickable.
Instead of SEO-driven titles like “Google Business Profiles and SEO,”
a more clickable example is featured in the screenshot below: “Google
Business Profile SEO: Rank #1 in 2025.” The title includes a keyword
(Google Business Profile SEO) and promises something that the viewer
wants.
Other tactics for creating SEO-friendly titles that are also
clickable include superlatives such as “The most powerful…,” “The
best…,” etc.
You want something enticing that draws the viewer in. “Effective
content marketing strategies” is better than “Content marketing
strategies,” and “How to do…faster with AI” is better than “How to do…”
YouTube metadata: Writing descriptions that enhance SEO
Your YouTube video description allows you to mention your focus and supporting keywords.
But it’s more than that.
Your video description is most effective if it also includes:
A description of what the video is about and what viewers will get out of it. Try bullet points of key discussion areas for skimmable reading.
Chapters and timestamps so viewers can skip to sections most interesting to them.
Social media and website links so your audience can find you elsewhere.
Links to related products or services if they’re relevant.
A call to action asking for viewer engagement, such as “like,” “comment,” and “subscribe,” or “visit my website to find out more.”
Here’s an example of a YouTube video that includes all of these elements.
Optimizing video metadata and tags
YouTube tags (video tags) are descriptive words or phrases that you
can add to videos to help YouTube understand what a video is about.
They’re similar to keywords, but you mustn’t stuff keywords in tags.
YouTube says:
Your
video’s title, thumbnail and description are more important pieces of
metadata for your video’s discovery. These main pieces of info help
viewers decide which videos to watch.
Tags
can be useful if the content of your video is commonly misspelled.
Otherwise, tags play a minimal role in your video’s discovery.
Adding excessive tags to your video description is against our policies on spam, deceptive practices and scams.
Add tags when uploading your video to help contextualize it or to
catch misspellings. You can also edit and add tags to published videos.
Here’s an example: the video pictured below is titled “The Future of
Marketing & AI Search.” The tags are relevant and have search volume
within YouTube:
Marketing and AI (390 searches)
SEO and AI (3,200 searches)
Future of marketing (159 searches)
Future of SEO (65 searches)
Creating engaging, SEO-aligned videos
When your videos are SEO-aligned, you know people are searching for
them. If you execute the video production well, there’s every reason to
believe you’ll create an engaging video that your audience watches until
the end.
An engaging video will have a long watch time and high retention
rates, as well as good engagement signals such as likes and comments.
These positive user signals will influence the YouTube algorithm to
recommend your video to similar audiences.
These user signals are also great for traditional SEO on Google. An
embedded video on your site might encourage people to stay on your
website longer as they watch it. (We’ll cover more about video analysis later.)
Implementing clickable title tags, engaging thumbnails, and knowing
your audience is a great place to start. But now it’s time to focus on
the actual content of your video.
Let’s take it from the top, starting with a good hook. A hook is the
opening sentence designed to grab the audience’s attention and make them
want to keep watching.
PlayPlay shares nine hooks with examples for social media videos:
Call out a common mistake that you know your
audience is making and encourage them to listen to the video for the
solution. “If you’re doing X, you need this video.”
State the pain point or problem that you know your
audience experiences, and encourage them to listen to the video for the
solution. “Sending emails to 10,000 recipients, but not getting
conversions? This video is for you.”
Start with a surprising fact related to the theme
or solution in your video. For example, “YouTube is the second-most
visited website in the world. Do you know how to get visibility there?”
Ask a question that your audience is asking (the
one they want the response to in the video). “How do you convert people
who watch your videos?”
Give an urgent warning and follow up with the
consequences if the viewer keeps doing the thing you’re warning against.
“If you keep doing X, you’re only going to end up with Y.”
Share secrets and reveals, such as unheard-of tips
or things that experts aren’t making public knowledge (but you’re about
to!). “This is the best-kept YouTube secret in history.”
Test and document experiments in a way that shares an experience. “I tried X for 15 days and Y happened!”
Interrupt the pattern by starting with a random
scene that may not have anything to do with the video. Common pattern
interruption beginnings can be intriguing or strange.
Tease the outcome by sharing what could happen if the viewer finishes the video. “I generated 50,000 leads with…”
Other tactics to create engaging videos include:
Incorporating visuals to support the script and aid viewer understanding
Adding captions so people can watch the video with the sound off
Using on-screen text to reinforce your video’s core messaging
Playing with pacing and cuts keeps the video visually interesting—try varying the speed, using jump cuts, or switching angles
Brian Dean does all of these things in the first three seconds of his video:
Importantly, in Dean’s video (and any video that’s SEO-aligned), the searcher’s intent is at the core.
SEO relies on your video meeting search intent because people are
looking for solutions. They search on YouTube or in Google, and the
platform algorithms deliver the best piece of content based on how
closely aligned it is with the searcher’s query and intent.
Sticking with Dean’s video, people searching for “SEO for beginners”
are looking for beginner tips to do SEO well. SEO done well ranks videos
on page one, which is the ultimate and aspirational goal for any new
SEO. Dean addresses how to do this in a comprehensive video guide.
It’s no surprise that Dean’s video is the top recommended video in Google.
Adding chapters and timestamps for key moments
Chapters and timestamps improve video UX within YouTube and Google
SERPs. With chapters, users can skip through sections of the video to
get to the parts that are most important to them.
Here’s what video chapters look like on YouTube:
You can find video chapters at the bottom of the YouTube description.
Creators also often cite the chapters in the video description.
If you add a timestamp on YouTube, it becomes a clickable link.
Descriptions and comments that reference timestamps in the video can
also result in the timestamp becoming a link that takes you to the
referenced moment when clicked.
Here’s what video chapters look like on Google. They’re called “key
moments” and are highlighted in a highly desirable video SERP feature at
the top of Google search results:
Create as many chapters as needed, but ensure the chapters align with
keywords and topics. Use keywords in the chapter title if you can.
Suppose chapters align with subtopics in a written guide on your site
(like the headings and sections within the guide). In that case, you
can use your video multiple times across one page, referencing specific
chapters and embedding them within the most relevant section.
Creating custom thumbnails
Engaging, custom thumbnails are your best chance of improving CTR and creating a visual brand that people remember.
Source thumbnail inspiration from large YouTube channels in any
industry, particularly channels with budgets and dedicated research into
what works on YouTube.
Diary of a CEO (DOAC) is a popular YouTube channel where host Stephen
Barlett interviews celebrities and subject matter experts. The channel
is known for taking an analytical approach to YouTube. The DOAC team A/B
split tests a whopping 100 thumbnails per episode to see what gets the
most engagement.
Their thumbnails are pictured below. Common elements include:
Close-ups of people’s faces, (sometimes two faces, the host and a guest)
A range of emotions and facial expressions
Bold text and text overlays with high-contrast colors, such as white, yellow, and red against black
The most important topics in the text (refer to trending data discovered in the keyword research phase to see what trends you can attach to videos)
Consistent stylings for all videos, which build a memorable brand identity
Enhancing engagement signals
One thing that YouTube does better than Google is personalized
results. Google and YouTube both incorporate behavioral signals in their
algorithms, but YouTube leans heavily into it and recommends content based on a range of behavioral signals, such as:
User viewing history (videos watched and ignored)
Video engagement metrics such as likes, comments, and shares
Videos watched consecutively
Your YouTube strategy should work toward increasing engagement.
YouTube chapters, custom thumbnails, and calls to action in video descriptions all enhance engagement, but what else can you do?
Ask for likes, comments, and subscriptions
Earlier, we mentioned the Diary of a CEO channel and its dedication
to YouTube research; any decision made likely has data supporting it.
The channel grows by 10k subscribers a day, so clearly it’s doing something right with its growth marketing tactics.
The host, Steven Bartlett, reminds users to subscribe to his channel in every video he publishes.
Here’s the exact transcript Barlett used in his most recent video:
This
has always blown my mind a little bit. 53% of you that listen to this
show regularly haven’t yet subscribed to the show, so could I ask you
for a favor before we start? If you like the show and you like what we
do here, and you want to support us for free, a simple way that you can
do just that is by hitting the subscribe button.
And
my commitment to you is that if you do that, I’ll do everything in my
power, me and my team, to make sure that this show is better for you
every single week.
We’ll
listen to your feedback, we’ll find the guests that you want me to
speak to, and we’ll continue to do what we do. Thank you so much.
This is effective because:
It’s data-driven (53% of people listen but don’t subscribe)
Barlett asks for something from listeners (for them to subscribe)
Bartlett promises something in return (he and the team will make the show better)
He says thank you (a little gratitude goes a long way)
Keep viewer engagement with clickable links and end screens
Once you’ve got an engaged viewer, the goal is to keep them on your
channel. You can do this by adding the following elements throughout
your video at key sections.
Video prompts are calls to action spoken within the video (e.g., “comment down below for the guide and I’ll send you the link”)
Cards are interactive pop-ups that appear within
the video. They usually link to other videos at the moment the other
video topics are mentioned. (For example, in a video about YouTube SEO,
you might mention “YouTube strategy” and use the card to link users
directly to that video for more information.)
End screens are the final screen of a video,
usually lasting a few seconds at the end. They use visual overlays and
prompt a desired call to action, such as watching a second related
video.
YouTube is still social media: Engage with your community
YouTube is a social media channel, and video is one of the most engaged and connected marketing formats.
Engage with your community by replying to comments promptly. The
quicker you are at replying, the more encouraged users will feel to
leave a comment because they’ll have some assurance that they’ll get a
reply and aren’t wasting their time.
Replying to comments with questions or further prompts for engagement
might encourage commenters to reply again. All of these actions
increase engagement. Brian Dean credits comments for growing his channel to 189,000 views per month.
You can use pinned comments that contain calls to action, or pin the best comments to encourage viewer engagement.
Here’s an example of TubeBuddy’s YouTube using pinned comments to remind viewers to take action.
And here’s an example of how Mr. Beast, the biggest channel on
YouTube with 403 million subscribers, uses pinned comments to encourage
engagement.
Leverage playlists
Playlists on YouTube are helpful for users because they contextualize
content and allow them to view a range of videos on a topic they’re
most interested in.
This is what playlists look like on YouTube:
Users can click the thumbnail to watch the entire playlist, or click
“View full playlist” to select a specific video within a playlist.
When users start watching a playlist, videos from the playlist will
automatically play when the initial video finishes. This auto-play
feature can help improve watch time and user engagement. Plus, it gives
YouTube a signal about how videos are related.
For example, if you’ve got seven videos in a playlist called “2025
SEO and Digital Marketing Strategies,” YouTube may show these videos to
lookalike audiences (audiences that look and behave like your channel’s
audience and engage in similar content).
You can create playlists using a bit of common sense (like “This
multi-part series should be grouped together under a single playlist”).
That’s a good start, but you should also refer to your original keyword
research.
We searched “YouTube SEO,” a short-tail, head keyword. The tool provided related keywords.
It would make sense to title a YouTube playlist “YouTube SEO,” then add related subjects such as:
The only YouTube SEO video course you’ll ever need
YouTube SEO changed in 2025: What’s new?
Free YouTube tools we can’t stop using
Monitoring performance and refining
Video marketing is a learning curve. You can read all the best
practice tips and learn from the experts, but your audience is unique.
The only way to understand what works for your audience is monitoring
video performance, refining and testing strategies, and learning from
previous successes (or failures!).
Here are some things to consider when reviewing video performance:
Watch time: the total amount of time people have
spent watching your video. Higher watch time signals valuable content to
YouTube’s algorithm.
Retention: the percentage of the video viewers watch before clicking away. This shows how engaging your video is from start to finish.
Click-through rate: the percentage of people who
clicked on your video after seeing the thumbnail or title. A high CTR
suggests your video is compelling at first glance.
Impressions: how many times your video thumbnail
was shown to viewers on YouTube. More impressions increase your chances
of getting clicks, but CTR tells you if those impressions are
converting.
Subscriber gain: the number of new subscribers gained from a video. This helps measure how well your content builds a loyal audience.
If any of these metrics increase, you’re doing something right. And
when you’re not, you can make changes to your videos to see if they
positively impact the metrics.
The great thing about YouTube is that it’s a search engine. Once a
video is live, even if it’s not performing brilliantly in search, you
can optimize it later. For instance, you can optimize your metadata,
including titles, descriptions, and thumbnails.
You might choose to edit videos when you produce new, relevant
videos. Go back to old videos and add links to newer content. Or add
links to your best-performing videos to see if you can funnel that
traffic to other videos.
To edit published videos:
Go to YouTube Studio > In the left-hand menu, click “Content” > Find the video you want to edit > Click “Details,” which is represented by a pencil.
YouTube has an algorithm, and the algorithm changes. Performance on
YouTube is a commitment to staying on top of algorithmic changes and
adapting your strategy to keep up with evolving trends and guidelines.
You need to do what’s required by the algorithm to rank. Remember,
you could create the best video in the world, but if the basic elements
that meet the algorithm aren’t included, your video won’t get the
visibility it deserves.
You can also find tips and guides from enthusiastic YouTube creators.
Even the biggest YouTube stars share their tips for succeeding on
YouTube:
Embedding and distributing video
Once a YouTube video is created, there’s no doubt that YouTube SEO
will do a lot to rank on both YouTube and Google. If you never added
your video to your website, it might still rank on search engines via
YouTube’s website.
But wouldn’t it be great if your video bolstered your organic rankings, too?
We think so.
Adding videos to your website has a range of benefits, including:
Increased user signals, such as time spent on the page and engagement rate.
Capturing increased traffic from Google. Content
with video has a better chance of ranking because the page is perceived
to be more helpful, and it might also secure video SERP features.
Improves connection with the website visitors. According to Tavus, 49% of consumers enjoy the human connection of videos.
Build authority with high-quality video, which
offers a new media type for your users (and Google) and showcases
authority through expertise. Videos created by subject matter experts
demonstrate your credibility, helping you build trust with viewers.
How to embed a video into your webpage
Don’t be tempted to just link to your videos—embed videos by following these instructions.
Find the video you want to embed on YouTube > Click “Share” > Click “Embed”
From here, you can copy the embed code and paste it into your
website’s HTML code, and visitors can play the video from the web page.
How to embed a video that starts at a specific timestamp
You can take this further by embedding videos from a starting point.
For example, if there’s a relevant chapter, you can embed the video
starting from that point.
Scroll down past the embed code > Check the box labelled “Start at” > Change the timestamp to the time you want the video to begin playing from > Click “Copy” > Paste the code into the HTML of your website.
Within the HTML, you should see “start=” followed by a number; this
is the number of seconds at which the video starts. If you want to alter
the start point in the code, change the number of seconds to represent
the timestamp. If you started the video after one minute, the code will
read start=60.
Once the video is embedded on your site, you can use Google SEO tactics to bolster both the video and your website even more.
Social mediadistribution
With SEO in place, there’s every chance your audience will share your
video far and wide across social media channels and communities (in
Reddit, for example).
But that doesn’t mean you shouldn’t have your own distribution plan for your video content.
For every video created, share it across relevant channels, including
social media, email newsletters, and communities. Online communities on
Reddit can be particularly impactful at sending the right traffic to
your video.
Steps to optimize your video content on your website
Follow SEO best practices
A page on your website that ranks well gives your video the best
chance of discoverability because a well-ranking page is a page that
Google crawls more regularly. Google bots crawl the website through
links, so it will follow your YouTube link and discover and index the
video.
As expected, SEO best practices are key to ranking pages.
Many SEO best practices are tried and tested methods:
Title tags should be optimized byincluding
focus keywords (ideally the same keyword or a related keyword used in
your video) and by writing a compelling, clickable title
Meta descriptions should encourage someone to click
Content should be well structured with heading tags for easy readability
Internal links build page authority; they should point to the page with the video so Google can find it
Your content should be relevant to both the keyword it’s ranking for, and to the embedded video
URL structure should be neat, succinct, and include the keyword you’re targeting
Optimized content includes your focus and supporting keywords throughout the article
Optimized images include descriptive alt text that contain your target keywords
A positive page UX and a mobile-friendly site are essential for users
When you embed a video on your website, you can provide even more
data to Google through structured data and schema. The schema type you
want is VideoObject.
VideoObject schema makes it easier for Google to find your video.
Here’s what Google says:
While
Google tries to automatically understand details about your video, you
can influence the information that’s shown in video results, such as the
description, thumbnail URL, upload date, and duration, by marking up
your video with VideoObject. Adding video structured data to your watch pages
can also make it easier for Google to find your video. Videos can
appear in several different places on Google, including the main search
results page, Video mode, Google Images, and Google Discover.
Within schema types are properties. Think of properties as details
that you can attach to the type. Properties for VideoObject schema
include the obvious, like “name,” “duration,” “uploadDate,” and more
detailed or nuanced properties like “about” or “associatedArticle.”
You can make VideoObject schema as detailed and as customized as you
like. There are over 100 properties under the VideoObject type.
Don’t let that overwhelm you—many types won’t be relevant, and you can start with a simple implementation.
Here’s a simple implementation of VideoObject schema:
Go to https://videoschema.com/ > Add your YouTube URL to the “Video URL” field > “Click Generate Videoschema”
The tool pulls all the data available on the video on YouTube.
Next:
Edit the output. You don’t want symbols and emojis in the schema; plain text only.
Add content to the schema. Unlike the video
description, users won’t read your schema description, so you can write
more if you think it helps contextualize what the video is about.
This method of creating structured data implementation is easy to do
and will provide more data to Google, increasing its chances of
discovering your video.
But custom schema is even better.
Within your schema you can add “hasPart” properties and “clip” types, which mayhelp
your site achieve the Key Moments feature in search engine results
pages. This schema allows you to assign parts to segments of a video.
Here’s a more detailed Video Object schema with hasPart schema:
{ "@context": "https://schema.org", "@type": "VideoObject", "name": "[Video Title]", "description": "[Video description]", "thumbnailUrl": [ "https://example.com/photo.jpg" ], "uploadDate": "2025-06-01T09:00:00+09:00", "duration": "PT1M54S", "contentUrl": "https://www.example.com/video.mp4", "embedUrl": "https://www.example.com/embed/123", "hasPart": [ { "@type": "Clip", "name": "Introduction", "description": "An overview of the topic and what to expect in the video.", "startOffset": 0, "endOffset": 30 },
{ "@type": "Clip", "name": "Main Topic", "description": "A detailed explanation and demonstration of the main subject.", "startOffset": 31, "endOffset": 90 },
{ "@type": "Clip", "name": "Summary", "description": "Recap of the key points and final thoughts.", "startOffset": 91, "endOffset": 114 } ] }
If you’ve got the resources available, speak to a developer or technical SEO and review the comprehensive VideoObject schema listing to see how much information you can give to Google. Find types that are relevant and work them into your schema.
Go to Google’s Rich Results Test > Click “<> Code” > Paste your structured data and schema code into the text box > “Test Code”
The tool takes a moment to test the code, then directs you here:
If the code is eligible for rich results, you’ll see it in the top
right corner. If there are invalid items, you’ll get a warning about
them in orange or red. You can click through to review the invalid item,
and the tool also provides tooltips on how to solve it.
Always test your code before you add it to the website, and be extra diligent—test the URL once it’s published, too.
Important note:
Google’s Rich Results Test can only test code eligibility and whether
or not it’s one of Google’s supported rich result types. It cannot
verify the quality or accuracy of the content within the schema
framework. Structured data and schema do not guarantee a rich result;
rather, they give you the best chance of winning one.
YouTube content as an authority and entity signal
Experience, expertise, authority, and trust (E-E-A-T) is a framework
that Google Search Quality Raters use to provide feedback on the quality
of websites and search results.
Search Quality Raters are humans who manually review search results and websites to provide feedback on their quality. The Search Quality Rater Guidelines provide a framework for Search Quality Raters when they’re reviewing.
While this framework is not a ranking factor, it’s considered important and a guide for what Google wants to see from websites.
On E-E-A-T, the Search Quality Rater Guidelines say:
In
determining page quality, Raters must consider EEAT: The first-hand
experience of the creator. The expertise of the creator. The
authoritativeness of the creator, the main content itself, and the
website. And trust: the extent to which the page is accurate, honest,
safe, and reliable.
YouTube can serve as an authority and entity signal and, therefore,
may bolster traditional SEO efforts on Google and other search engines
by providing E-E-A-T.
Video demonstrates E-E-A-T in a number of ways:
Videos demonstrate experience and expertise because
they show real people doing things like showcasing a product, answering
questions, or teaching a skill. Videos can feature subject matter
experts answering questions relevant to their industry.
Video helps with authoritativeness as an extension
of expertise and experience. Yes, videos with subject matter experts
bring authority. But more than that, video becomes an asset that may be
linked to from other sources or embedded in their website. Your pages
with embedded videos may earn backlinks from relevant, authoritative
sources, which helps Google see your website as an authority.
Trust is demonstrated through experience,
expertise, and authority. We also know that video supports the sales
cycle, and people buy from brands they trust. According to HubSpot, 41% of marketers say that ROI from video is high and 87% say that video increases brand awareness.
Tracking and analyzing the success of video content
Analyzing YouTube metrics
There’s no need to make any guesses about video success on YouTube.
The YouTube Studio tells
you everything you need to know, from video metrics to overall analysis
of subscribers and callouts for your latest achievements.
Here’s what the YouTube Studio dashboard looks like.
You can dig into specific data per video, too.
Navigate to the left-hand menu > Click “Content” > Choose the video you want to analyze > Click “Analytics,” which is represented by the bar graph icon.
You’ll now see analytics for the video selected.
You can see:
Video views: the total number of times the video has been watched
Watch time: the total number of minutes viewers have spent watching the video
Subscribers: the number of subscribers gained or lost from this video
Moments for audience retention: key points where viewer engagement spikes or drops
Average view duration: the average length of time viewers spend watching the video
Average percentage viewed: the average portion of the video that viewers watched, shown as a percentage
Use these metrics to make improvements to your video strategy. For
example, if subscribers are your goal and you have a video that secured a
high number of subscribers, you might want to test a second similar
video or repeat the format.
You can also look for moments of high engagement to see what happened
on screen or what you said that piqued interest. Create similar moments
if you know what they are.
YouTube metrics tell us a lot about the numbers, but growing any
channel and securing high views and datasets large enough to perform
in-depth analysis takes time.
For many creators, especially those more interested in meaningful
engagements, other metrics such as likes, comments, and shares can be
more insightful.
Engagement metrics: Likes and comments
Likes and comment metrics are found within video analysis.
Go to YouTube Studio > Navigate to the left-hand menu > Click “Content”
You can see a breakdown of likes and comments here in terms of quantity.
Quantitative metrics are helpful, but it’s worth reviewing comments
left on the video to determine if you’re capturing the right engagement
from the right people. If your commenters are intrigued by your content,
it’s a good sign. They might ask related questions, which could inspire
a video series.
Loyal fans of your channel may also give you feedback on how they felt about the video.
The comment section on this video is a good example of positive feedback from viewers:
Importantly, nearly every single comment has been responded to by the
creator in the form of a like or reply. Remember, this type of
engagement builds community and viewer loyalty.
Performance tracking across platforms: Tracking the success of YouTube videos on websites
YouTube is one place where your video is viewed and gains traction,
but it’s not the only place. It’s important to look at metrics and tools
associated with your website.
Google rankings
Google Search Console (GSC)
is a tool that measures your website’s rankings. It’s a free tool and a
must-use for all websites. GSC shows precisely what queries people are
typing into Google to find your website, how many impressions you’re
getting (meaning how many times you’re seen in search), and how many
times your website is clicked for a particular search query.
You can filter data to analyze specific:
Queries: the keywords people are typing in and the ones that lead to clicks
Pages: the pages people click from Google
Countries: where users are searching from
Devices: which device people use to search (desktop, mobile, tablet)
Search appearance: featured snippets and rich results, such as review stars
Dates: data filtered by date
In Google Search Console, you can filter rankings in video search results and web (traditional Google search), images, and news.
Here’s how to monitor video performance.
Go to Google Search Console > Navigate to the left-hand menu > Click “Performance” > Click “Search Results”
You’ll see a screen like the one below, detailing clicks and impressions for your website overall.
Next, filter by video:
Navigate to the drop-downs above the graph > Click “Search type: Web” > Select “Video” > “Apply”
Results will filter to video-only results.
Click queries to see which queries led to a click
Click pages to see which page they clicked to
You can toggle average position to see whether the video position is increasing or decreasing.
Google Search Console is excellent if you want a tool that
demonstrates how your site is performing and which video queries bring
clicks.
The limitations of GSC are that it can only display opportunities
based on keywords your site is ranking for and at least getting
visibility for, so GSC is best used with other tools that help identify
opportunities not yet reached.
SERP feature analysis
One of the main benefits of videos for SEO is that you get enhanced
listings in search engine results pages, which are called SERP
features.
These features are mentioned above with images, and include:
Video listings
Video carousels
Featured videos
Video SERP features might also be complemented with key moments.
SERP features will increase traffic to your video as they’re so prominent in SERPs.
Monitoring your SERP features will help you see how they’re
performing and whether you’ve lost a feature so you can work to get it
back. You can also analyze opportunities for SERP features, which can
influence your video strategy.
If you’ve created and embedded a video on your site, you can monitor how well that page performs for video SERP features.
Here’s how you do it using the position tracking tool,
which only shows data for keywords you’ve specifically input for
analysis. This targeting analysis helps get straight to the data that
matters the most.
First, you must enter the keywords you want to track.
Go to Semrush > Navigate to the left-hand “SEO” section > Click “Position Tracking” > Choose your project > Choose “Overview” > Below the graph, click “Add keywords”
Add your keywords with each keyword on a new line. Optionally, you
can add a tag that will later be filterable. Separate tags from keywords
with a comma. You might add a “video” tag for any keywords you want to
monitor and rank in video results.
For example:
YouTube SEO, video
How to do YouTube SEO, video
You can add global tags at the bottom if all keywords use the same tags.
When you’re done, click “Add keywords.” The system
might take time to analyze keyword positions and populate the report.
This could take minutes or hours, depending on the data.
Once your keywords are added, you can use the “Overview” within the
Position Tracking tool to filter data by video SERP features.
Site engagement metrics
Engagement metrics are tracked as standard in GA4, including video
engagement metrics for videos embedded via YouTube (another benefit to
using YouTube).
You have to turn video engagement metrics on in order to track them in GA4.
Here’s how:
Go to Google Analytics > Click “Admin”, which is represented by a cog (bottom left) > Navigate to “Data streams” > Click the data stream you want to manage.
Once you’ve clicked the data stream to which you’re managing and
uploading videos, check that enhanced measurements are toggled on and
“Video engagement” is present.
Measuring video engagement metrics in GA4
Next, you need to find the video engagement metrics in your report.
In the left-hand menu > “Reports” > “Engagement” > “Events”> In the search bar, type “video” to filter to video events > Press “Enter”
Want to get even more granular data? Find out which page on your site the user is on when they click the video.
Click the “+” next to “Event name” > Start typing “page” to bring the menu items into view > Select “Page path and screen class.”
GA4 adds the page on which the video event took place.
There are three types of video events:
Video start (triggers when the video starts playing)
Video progress (when the video progresses past 10%, 25%, 50%, and 75% duration time)
Video complete (when the video ends)
Important note: Engagement
metrics on your website will also be recorded on YouTube if the video
is embedded using YouTube’s embed code. So, if GA4 says a video was
completed, YouTube Analytics will have this data already. GA4 doesn’t
provide new information about video engagement, but it lets you see how
effectively the website generates video engagements.
One of the limitations of this engagement report is that you
can’t see which video was viewed, though you can work it out if there’s
only one on a page. This video explains how to add video titles to your
GA4 report.
Heat mapping
Heat mapping tools like HotJar or Microsoft Clarity allow you to see where users are clicking and where they’re most engaged.
The screenshot below shows how it works. High click zones have a red
circle, yellow is slightly less clicked, green even less so, and blue
signifies the least-clicked areas.
If a video gets a lot of engagement, you’d see a red circle around the play button.
These tools also offer analysis for scroll depth. Scroll depth is how
far users scroll down a page. If you analyzed scroll depth and found
users weren’t even getting to your video, you might consider moving it
up the page and seeing how it influenced engagement.
Ready to start doing YouTube for SEO?
Do you feel ready to think about SEO holistically?
If so, get started with researching using Keyword Analytics for YouTube
so you can research keywords, identify growth keywords, and review top
videos already performing in the YouTube algorithm. It’s $10/month, but
you can start with a seven-day free trial and cancel any time.
If you’ve already mastered the keyword portion of YouTube SEO, read this guide to high-impact educational video content. It covers everything from defining purpose, scripts, and storyboarding, choosing your video tech stack, and so much more.
