The Future Of Video SEO Is Schema Markup. Here’s Why.

Table of contents:

1. Unlocking the Power of Video SEO through Schema Markup
2. The Evolution of Video SEO
3. SORA, OpenAI text-to-video model entered the conversation
4. The curse of factually incorrect videos: deep fakes are the new negative SEO
5. How to assess the upcoming video landscape as an experienced SEO engineer
6. How to troubleshoot schema markup for video SEO?
7. Schema markup for video SEO is here to stay

Unlocking the Power of Video SEO through Schema Markup: A Game-Changer for SEO

In the ever-evolving landscape of digital marketing, video content reigns supreme. From captivating product demos to engaging tutorials, videos have become the go-to medium for businesses to connect with their audiences. But amidst this visual revolution, there’s a critical element that often goes unnoticed: schema markup.

Imagine if search engines could not only understand the words on your webpage but also decipher the context, structure, and intent behind your videos. That’s precisely what video schema markup accomplishes. By establishing a rigorous quality assurance process to add this metadata to your site’s backend, you can unlock a treasure trove of benefits that will revolutionize your video SEO strategy.

In this article, I’ll delve into the world of video schema markup, exploring its significance, implementation, and best practices. Whether you’re a seasoned marketer or just dipping your toes into the SEO waters, understanding video schema markup is essential. Let’s embark on this enlightening journey together! 

The Evolution of Video SEO

Video SEO didn’t hold much significance until recently. If we delve into its historical development and observe how the data landscape evolved, we can conclude that video SEO changed and it will be even more challenging to do it with video content creation at scale:

Early Days (Pre-2010): Keyword Kingdom

• Imagine stuffing titles and descriptions with relevant (and irrelevant) keywords.
• Focus was on ranking rather than user experience.
• YouTube was young, and the competition wasn’t fierce.

Rise of User Engagement (2010-2015): Quality Takes Center Stage

• Google started paying attention to watch time, click-through rates, and audience retention.
• High-quality, engaging content became king (or queen).
• Video thumbnails and channel branding gained importance.

Mobile First, Voice Search Boom (2015-2020): Adapting to New Habits

• Mobile viewing exploded, demanding responsive video formats.
• Voice search prioritized natural language and semantic understanding.
• Structured data and optimizing for long-tail keywords became crucial.

AI & Personalization Era (2020-Present): Understanding Intent & Context

• AI analyzes viewing patterns and personalized search results.
• Video transcripts and closed captions improve accessibility and SEO.
• Focus is on user intent and providing the most relevant video for each search.

Video SEO in 2024: It’s All About Value & Trust

So, why is video content integral to SEO strategies now? Here’s the scoop:

• Engagement Powerhouse: Videos capture attention better than text, leading to higher rankings and traffic.
• Accessibility & Inclusivity: Transcripts and closed captions cater to diverse audiences, boosting reach and trust.
• Visual storytelling: Videos convey emotions and concepts effectively, building stronger connections with viewers.
• Local SEO Advantage: Localized video content with geo-targeting improves local search rankings.
• Authority & Expertise: High-quality videos establish you as a thought leader in your niche.

But are we conveying the complete narrative? What about generative AI, and what implications does its widespread adoption hold for video SEO as a whole?

I was recently invited to participate in a debate covering a segment of this topic. As I prepared my material and arguments to illustrate the trajectory of all this, I came to the realization that video SEO is a much more intricate subject than I initially perceived.

SORA, OpenAI Text-To-Video Model Entered The Conversation

While headlines trumpet the latest advancements in AI-powered video generation tools like OpenAI’s SORA and Runway, their impact on video SEO might not be as immediate as one might think. However, this doesn’t negate the vital role another approach currently holds in shaping the future of video SEO: schema markup.

But before diving deep, let’s address the AI elephant in the room

OpenAI’s SORA and Runway’s video creation tools represent exciting steps towards democratizing video production. By lowering barriers to entry, they could lead to an explosion of video content. 

Here’s the official video by OpenAI:

However, for this content to be discoverable, it needs to be understood by search engines. This is where schema markup comes in.

Schema markup acts as a translator, giving search engines a deeper understanding of your video content. Think of it like tagging a box with its contents instead of just the word “box.” With schema markup, you can specify details like video title, duration, transcript, speaker information, and even the video’s key themes and concepts. But I bet you already knew this.

What we need to factor in generative AI and ask ourselves:

1. How do we generate realistic video content?
2. What labeling methods can be employed to distinguish between AI-created and human-made videos?
3. How do we conduct fact-checking on content, considering the reduced entry barrier for video production?

Imagine a world where anyone can become a Spielberg overnight. Where AI tools craft compelling visuals and narrate captivating stories, churning out videos faster than popcorn at a movie theater. This future, driven by generative AI, is closer than you think, and it poses a fascinating question: how does one stand out in a sea of content created with minimal effort? The answer lies not in resisting the wave, but in riding it with two powerful allies: data labeling and fact-checking.

Google, Meta, OpenAI, and Adobe already started putting some watermarks on their AI-generated image content. See some examples below:

Source

Source

While this is good news and encouraging for creators, it’s still yet to be seen how we can unify these efforts or even better, agree on a standardized approach. This is super important for accessibility, user experience and interoperability of data across systems.

The Curse Of Factually Incorrect Videos: Deep Fakes Are The New Negative SEO

Let’s take a concrete example. See the video below:

This is a brief yet insightful video showcasing how deep fake videos can be swiftly created on a single, more powerful computer. Now, consider the potential of using these deepfake versions to disseminate misinformation on the Internet for various reasons:

1. Deepfakes gain momentum rapidly and spread swiftly.
2. A significant portion of the population lacks digital literacy, making it difficult to distinguish between genuine and deepfaked videos.
3. Videos manipulated through image, audio, or speech extraction have the ability to shape the opinions of the masses and influence public sentiment negatively.
4. Deepfaked videos can be likened to a new form of negative SEO: they pose a threat to national security, undermine leaders, or damage the reputation of brands operating in both the offline and online space.

How To Assess The Upcoming Video Landscape As An Experienced SEO Engineer

Think of the upcoming video landscape as a bustling marketplace. Everyone’s a vendor, hawking their wares (videos) to eager consumers (search engines and viewers). But with so many stalls, competition becomes fierce. While some might struggle to create compelling content, others will produce masterpieces, saturating specific niches. How do you ensure your video doesn’t get lost in the shuffle?

This is where data labeling steps in, acting as your digital megaphone. Remember the old adage, “a picture is worth a thousand words”? Well, imagine each “word” being a relevant keyword, topic, or entity embedded within your video. By meticulously labeling your content, you’re essentially whispering to search engines, “Hey, look at me! I’m about X, Y, and Z!” This empowers them to understand your video’s context, matching it to user queries with laser-sharp precision. Suddenly, your video isn’t just another face in the crowd; it’s the one offering exactly what someone’s looking for.

But wait, there’s more! In this marketplace of trust, viewers become discerning shoppers. They want reliable information, not just flashy visuals. This is where fact-checking becomes your shining knight. Imagine a badge of honor emblazoned on your video, proclaiming, “Verified! Facts checked and double-checked!” This instills confidence in viewers, separating you from the potentially unverified masses. They’ll appreciate your commitment to accuracy, making them more likely to engage, share, and become loyal customers (viewers).

But don’t stop there! Remember, the future of search is about understanding, not just keywords. Imagine your video labeled so meticulously that it anticipates the questions viewers haven’t even asked yet. This granular level of data, fueled by AI-powered tools and even crowdsourced community feedback, creates content that transcends trends and algorithms. It becomes future-proof, ready to adapt and remain relevant as the search landscape evolves.

How To Troubleshoot Schema Markup For Video SEO?

Google Search Console, Schema.org Validator, and the Rich Results Test are excellent tools for beginners. However, their drawback lies in the absence of built-in fact-checking or data labeling capabilities. They cannot even discern whether your content was generated by AI unless explicitly indicated in your schema markup.

This is precisely why having a dependable digital partner to implement supplementary QA processes on your behalf is crucial. This way, you can concentrate on what truly matters: creating value for both potential and existing customers.

Schema Markup For Video SEO Is Here To Stay

Given the exponential growth of content, I view schema markup as the optimal approach for crafting well-optimized videos. I also see schema markup as a means to enhance accessibility and elevate customer experiences through rich snippets. Considering the challenge of watermarking generated video content, schema markup stands out as the ultimate solution for establishing a strong presence in the SEO landscape.

More Frequently Asked Questions

How do you optimize video content for SEO?

Optimizing video content for SEO involves keyword research, using a keyword-rich title, writing a detailed description, adding relevant tags, providing transcriptions or closed captions, optimizing thumbnails, submitting a video sitemap, promoting on social media, encouraging user engagement, and using a reliable video hosting platform.

Why is SEO for video content important?

SEO for video content is important because it enhances the visibility of your videos in search engine results, increases organic traffic, improves user engagement, and contributes to a higher ranking on search engine result pages. It helps your videos reach a larger audience and can positively impact your overall online presence and brand visibility.

What are some tools for optimizing video content?

Tools for optimizing video content include Google Keyword Planner, YouTube Analytics, TubeBuddy, Yoast Video SEO, Moz Keyword Explorer, Rev.com, Canva or Adobe Spark, social media platform analytics, and video hosting platforms like Wistia or Vimeo.

Discover how WordLift can transform your video content for better visibility and engagement. Start leveraging the power of AI to enhance your website’s SEO today. Try WordLift Now!

How can I improve the ranking of my videos on YouTube?

To improve YouTube video rankings: Optimize with keywords, use engaging thumbnails, create high-quality content, write detailed descriptions, include transcriptions, promote on social media, organize into playlists, maintain a consistent schedule, encourage audience engagement, and monitor analytics for adjustments.

How does video schema markup impact SEO?

Video schema markup positively impacts SEO by providing structured data to search engines. It enhances visibility through rich snippets, improves indexing, and contributes to a better presence in search engine result pages by making your video content more understandable and appealing to search algorithms.