Pro-Tech SEO Checklist For Agencies via @sejournal, @JetOctopus

This post was sponsored by JetOctopus. The opinions expressed in this article are the sponsor’s own.

When you’re taking on large-scale projects or working with extensive websites with hundreds to thousands of pages, you must leverage advanced technical SEO techniques.

Large websites come with challenges such as vast site architectures, dynamic content, and the higher-stakes competition in maintaining rankings.F

Leveling up your team’s technical SEO chops can help you establish a stronger value proposition, ensuring your clients gain that extra initial edge and choose to continue growing with your agency.

With this in mind, here’s a concise checklist covering the most important nuances of advanced technical SEO that can lead your clients to breakthrough performance in the SERPs.

1. Advanced Indexing And Crawl Control

Optimizing search engine crawl and indexation is foundational for effective technical SEO. Managing your crawl budget effectively begins with log file analysis—a technique that offers direct insights into how search engines interact with your clients’ websites.

A log file analysis helps:

• Crawl Budget Management: Essential for ensuring Googlebot crawls and indexes your most valuable pages. Log file analysis indicates how many pages are crawled daily and whether important sections are missed.
• Identifying Non-Crawled Pages: Identifies pages Googlebot misses due to issues like slow loading times, poor internal linking, or unappealing content, giving you clear insights into necessary improvements.
• Understand Googlebot Behavior: Know what Googlebot actually crawls on a daily basis. Spikes in the crawl budget may signal technical issues on your website, like auto-generated thin, trashy pages, etc.

For this, integrating your SEO log analyzer data with GSC crawl data provides a complete view of site functionality and search engine interactions, enhancing your ability to guide crawler behavior.

Next, structure robots.txt to exclude search engines from admin areas or low-value add-ons while ensuring they can access and index primary content. Or, use the x-robots-tag—an HTTP header—to control indexing at a more granular level than robots.txt. It is particularly useful for non-HTML files like images or PDFs, where robot meta tags can’t be used.

For large websites, the approach with sitemaps is different from what you may have experienced. It almost doesn’t make sense to put millions of URLs in the sitemaps and want Googlebot to crawl them. Instead, do this: generate sitemaps with new products, categories, and pages on a daily basis. It will help Googlebot to find new content and make your sitemaps more efficient. For instance, DOM.RIA, a Ukrainian real estate marketplace, implemented a strategy that included creating mini-sitemaps for each city directory to improve indexing. This approach significantly increased Googlebot visits (by over 200% for key pages), leading to enhanced content visibility and click-through rates from the SERPs.

2. Site Architecture And Navigation

An intuitive site structure aids both users and search engine crawlers in navigating the site efficiently, enhancing overall SEO performance.

Specifically, a flat site architecture minimizes the number of clicks required to reach any page on your site, making it easier for search engines to crawl and index your content. It enhances site crawling efficiency by reducing the depth of important content. This improves the visibility of more pages in search engine indexes.

So, organize (or restructure) content with a shallow hierarchy, as this facilitates quicker access and better link equity distribution across your site.

For enterprise eCommerce clients, in particular, ensure proper handling of dynamic parameters in URLs. Use the rel=”canonical” link element to direct search engines to the original page, avoiding parameters that can result in duplicates.

Similarly, product variations (such as color and size) can create multiple URLs with similar content. It depends on the particular case, but the general rule is to apply the canonical tag to the preferred URL version of a product page to ensure all variations point back to the primary URL for indexing. If there is a significant number of such pages where Google ignores non-canonical content and puts them in the index, consider reviewing the canonicalization approach on the website.

3. JavaScript SEO

As you know, JavaScript (JS) is crucial in modern web development, enhancing site interactivity and functionality but introducing unique SEO challenges. Even if you’re not directly involved in development, ensuring effective JavaScript SEO is important.

The foremost consideration in this regard is critical rendering path optimization — wait, what’s that?

The critical rendering path refers to the sequence of steps the browser must take to convert HTML, CSS, and JavaScript into a rendered web page. Optimizing this path is crucial for improving the speed at which a page becomes visible to users.

Here’s how to do it:

• Reduce the number and size of the resources required to display initial content.
• Minify JavaScript files to reduce their load time.
• Prioritize loading of above-the-fold content to speed up page render times.

If you’re dealing with Single Page Applications (SPAs), which rely on JavaScript for dynamic content loading, then you might need to fix:

• Indexing Issues: Since content is loaded dynamically, search engines might see a blank page. Implement Server-Side Rendering (SSR) to ensure content is visible to search engines upon page load.
• Navigation Problems: Traditional link-based navigation is often absent in SPAs, affecting how search engines understand site structure. Use the HTML5 History API to maintain traditional navigation functionality and improve crawlability.

Dynamic rendering is another technique useful for JavaScript-heavy sites, serving static HTML versions to search engines while presenting interactive versions to users.

However, ensure the browser console shows no errors, confirming the page is fully rendered with all necessary content. Also, verify that pages load quickly, ideally under a couple of seconds or so, to prevent user frustration (nobody likes a prolonged loading spinner) and reduce bounce rates.

Employ tools like GSC and Lighthouse to test and monitor your site’s rendering and web vitals performance. Regularly check that the rendered content matches what users see to ensure consistency in what search engines index.

4. Optimizing For Seasonal Trends

In the retail eCommerce space, seasonal trends influence consumer behavior and, consequently, search queries.

So, for these projects, you must routinely adapt your SEO strategies to stay on par with any product line updates.

Seasonal product variations—such as holiday-specific items or summer/winter editions—require special attention to ensure they are visible at the right times:

• Timely Content Updates: Update product descriptions, meta tags, and content with seasonal keywords well before the season begins.
• Seasonal Landing Pages: Create and optimize dedicated landing pages for seasonal products, ensuring they link appropriately to main product categories.
• Ongoing Keyword Research: Continually perform keyword research to capture evolving consumer interests and optimize new product categories accordingly.
• Technical SEO: Regularly check for crawl errors, ensure fast load times, and confirm that new pages are mobile-friendly and accessible.

On the flip side, managing discontinued products or outdated pages is just as crucial in maintaining site quality and retaining SEO value:

• Evaluate Page Value: Conduct regular content audits to assess whether a page still holds value. If a page hasn’t received any traffic or a bot hit in the last half-year, it might not be worth keeping.
• 301 Redirects: Use 301 redirects to transfer SEO value from outdated pages to relevant existing content.
• Prune Content: Remove or consolidate underperforming content to focus authority on more impactful pages, enhancing site structure and UX.
• Informative Out-of-Stock Pages: Keep pages for seasonally unavailable products informative, providing availability dates or links to related products.

Put simply, optimizing for seasonal trends means preparing for high-traffic periods and effectively managing the transition periods. This supports sustained SEO performance and a streamlined site experience for your clients.

5. Structured Data And Schema Implementation

Structured data via schema.org markup is a powerful tool to enhance a site’s SERP visibility and boost CTR through rich snippets.

Advanced schema markup goes beyond basic implementation, allowing you to present more detailed and specific information in SERPs. Consider these schema markups in your next client campaign:

• Nested Schema: Utilize nested schema objects to provide more detailed information. For example, a Product schema can include nested Offer and Review schemas to display prices and reviews in search results.
• Event Schema: For clients promoting events, implementing an Event schema with nested attributes like startDate, endDate, location, and offers can help in displaying rich snippets that show event details directly in SERPs.
• FAQ and How-To Pages: Implement FAQPage and HowTo schemas on relevant pages to provide direct answers in search results.
• Ratings, Reviews, and Prices: Implement the AggregateRating and Review schema on product pages to display star ratings and reviews. Use the Offer schema to specify pricing information, making the listings more attractive to potential buyers.
• Availability Status: Use the ItemAvailability schema to display stock status, which can increase the urgency and likelihood of a purchase from SERPs.
• Blog Enhancements: For content-heavy sites, use Article schema with properties like headline, author, and datePublished to enhance the display of blog articles.

Use Google’s Structured Data Testing Tool tool to test your pages’ structured data and identify any errors/warnings in your schema implementation. Also, use Google’s Rich Results Test to get feedback on how your page may appear in SERPs with the implemented structured data.

Conclusion

Considering their long SEO history and legacy, enterprise-level websites require more profound analysis from different perspectives.

We hope this mini checklist serves as a starting point for your team to take a fresh look into your new and existing customers and help deliver great SEO results.

Image Credits

Featured Image: Image by JetOctopus. Used with permission.

In-Post Images: Image by JetOctopus. Used with permission.

SEO Reinvented: Responding To Algorithm Shifts via @sejournal, @pageonepower

A lot has been said about the remarkable opportunities of Generative AI (GenAI), and some of us have also been extremely vocal about the risks associated with using this transformative technology.

The rise of GenAI presents significant challenges to the quality of information, public discourse, and the general open web. GenAI’s power to predict and personalize content can be easily misused to manipulate what we see and engage with.

Generative AI search engines are contributing to the overall noise, and rather than helping people find the truth and forge unbiased opinions, they tend (at least in their present implementation) to promote efficiency over accuracy, as highlighted by a recent study by Jigsaw, a unit inside Google.

Despite the hype surrounding SEO alligator parties and content goblins, our generation of marketers and SEO professionals has spent years working towards a more positive web environment.

We’ve shifted the marketing focus from manipulating audiences to empowering them with knowledge, ultimately aiding stakeholders in making informed decisions.

Creating an ontology for SEO is a community-led effort that aligns perfectly with our ongoing mission to shape, improve, and provide directions that truly advance human-GenAI interaction while preserving content creators and the Web as a shared resource for knowledge and prosperity.

Traditional SEO practices in the early 2010s focused heavily on keyword optimization. This included tactics like keyword stuffing, link schemes, and creating low-quality content primarily intended for search engines.

Since then, SEO has shifted towards a more user-centric approach. The Hummingbird update (2013) marked Google’s transition towards semantic search, which aims to understand the context and intent behind search queries rather than just the keywords.

This evolution has led SEO pros to focus more on topic clusters and entities than individual keywords, improving content’s ability to answer multiple user queries.

Entities are distinct items like people, places, or things that search engines recognize and understand as individual concepts.

By building content that clearly defines and relates to these entities, organizations can enhance their visibility across various platforms, not just traditional web searches.

This approach ties into the broader concept of entity-based SEO, which ensures that the entity associated with a business is well-defined across the web.

Fast-forward to today, static content that aims to rank well in search engines is constantly transformed and enriched by semantic data.

This involves structuring information so that it is understandable not only by humans but also by machines.

This transition is crucial for powering Knowledge Graphs and AI-generated responses like those offered by Google’s AIO or Bing Copilot, which provide users with direct answers and links to relevant websites.

As we move forward, the importance of aligning content with semantic search and entity understanding is growing.

Businesses are encouraged to structure their content in ways that are easily understood and indexed by search engines, thus improving visibility across multiple digital surfaces, such as voice and visual searches.

The use of AI and automation in these processes is increasing, enabling more dynamic interactions with content and personalized user experiences.

Whether we like it or not, AI will help us compare options faster, run deep searches effortlessly, and make transactions without passing through a website.

The future of SEO is promising. The SEO service market size is expected to grow from $75.13 billion in 2023 to $88.91 billion in 2024 – a staggering CAGR of 18.3% (according to The Business Research Company) – as it adapts to incorporate reliable AI and semantic technologies.

These innovations support the creation of more dynamic and responsive web environments that adeptly cater to user needs and behaviors.

However, the journey hasn’t been without challenges, especially in large enterprise settings. Implementing AI solutions that are both explainable and strategically aligned with organizational goals has been a complex task.

Building effective AI involves aggregating relevant data and transforming it into actionable knowledge.

This differentiates an organization from competitors using similar language models or development patterns, such as conversational agents or retrieval-augmented generation copilots and enhances its unique value proposition.

Imagine an ontology as a giant instruction manual for describing specific concepts. In the world of SEO, we deal with a lot of jargon, right? Topicality, backlinks, E-E-A-T, structured data – it can get confusing!

An ontology for SEO is a giant agreement on what all those terms mean. It’s like a shared dictionary, but even better. This dictionary doesn’t just define each word. It also shows how they all connect and work together. So, “queries” might be linked to “search intent” and “web pages,” explaining how they all play a role in a successful SEO strategy.

Imagine it as untangling a big knot of SEO practices and terms and turning them into a clear, organized map – that’s the power of ontology!

While Schema.org is a fantastic example of a linked vocabulary, it focuses on defining specific attributes of a web page, like content type or author. It excels at helping search engines understand our content. But what about how we craft links between web pages?

What about the query a web page is most often searched for? These are crucial elements in our day-to-day work, and an ontology can be a shared framework for them as well. Think of it as a playground where everyone is welcome to contribute on GitHub similar to how the Schema.org vocabulary evolves.

The idea of an ontology for SEO is to augment Schema.org with an extension similar to what GS1 did by creating its vocabulary. So, is it a database? A collaboration framework or what? It is all of these things together. SEO ontology operates like a collaborative knowledge base.

It acts as a central hub where everyone can contribute their expertise to define key SEO concepts and how they interrelate. By establishing a shared understanding of these concepts, the SEO community plays a crucial role in shaping the future of human-centered AI experiences.

Screenshot from WebVowl, August 2024SEOntology – a snapshot (see an interactive visualization here).

The Data Interoperability Challenge In The SEO Industry

Let’s start small and review the benefits of a shared ontology with a practical example (here is a slide taken from Emilija Gjorgjevska’s presentation at this year’s ZagrebSEOSummit)

Image from Emilija Gjorgjevska’s, ZagrebSEOSummit, August 2024

Imagine your colleague Valentina uses a Chrome extension to export data from Google Search Console (GSC) into Google Sheets. The data includes columns like “ID,” “Query,” and “Impressions” (as shown on the left). But Valentina collaborates with Jan, who’s building a business layer using the same GSC data. Here’s the problem: Jan uses a different naming convention (“UID,” “Name,” “Impressionen,” and “Klicks”).

Now, scale this scenario up. Imagine working with n different data partners, tools, and team members, all using various languages. The effort to constantly translate and reconcile these different naming conventions becomes a major obstacle to effective data collaboration.

Significant value gets lost in just trying to make everything work together. This is where an SEO ontology comes in. It is a common language, providing a shared name for the same concept across different tools, partners, and languages.

By eliminating the need for constant translation and reconciliation, an SEO ontology streamlines data collaboration and unlocks the true value of your data.

The Genesis Of SEOntology

In the last year, we have witnessed the proliferation of AI Agents and the wide adoption of Retrieval Augmented Generation (RAG) in all its different forms (Modular, Graph RAG, and so on).

RAG represents an important leap forward in AI technology, addressing a key limitation of traditional large language models (LLMs) by letting them access external knowledge.

Traditionally, LLMs are like libraries with one book – limited by their training data. RAG unlocks a vast network of resources, allowing LLMs to provide more comprehensive and accurate responses.

RAGs improve factual accuracy, and context understanding, potentially reducing bias. While promising, RAG faces challenges in data security, accuracy, scalability, and integration, especially in the enterprise sector.

For successful implementation, RAG requires high-quality, structured data that can be easily accessed and scaled.

We’ve been among the first to experiment with AI Agents and RAG powered by the Knowledge Graph in the context of content creation and SEO automation.

Screenshot from Agent WordLift, August 2023

Knowledge Graphs (KGs) Are Indeed Gaining Momentum In RAG Development

Microsoft’s GraphRAG and solutions like LlamaIndex demonstrate this. Baseline RAG struggles to connect information across disparate sources, hindering tasks requiring a holistic understanding of large datasets.

KG-powered RAG approaches like the one offered by LlamaIndex in conjunction with WordLift address this by creating a knowledge graph from website data and using it alongside the LLM to improve response accuracy, particularly for complex questions.

Image from author, August 2024

We have tested workflows with clients in different verticals for over a year.

From keyword research for large editorial teams to the generation of question and answers for ecommerce websites, from content bucketing to drafting the outline of a newsletter or revamping existing articles, we’ve been testing different strategies and learned a few things along the way:

1. RAG Is Overhyped

It is simply one of many development patterns that achieve a goal of higher complexity. A RAG (or Graph RAG) is meant to help you save time finding an answer. It’s brilliant but doesn’t solve any marketing tasks a team must handle daily. You need to focus on the data and the data model.

While there are good RAGs and bad RAGs, the key differentiation is often represented by the “R” part of the equation: the Retrieval. Primarily, the retrieval differentiates a fancy demo from a real-world application, and behind a good RAG, there is always good data. Data, though, is not just any type of data (or graph data).

It is built around a coherent data model that makes sense for your use case. If you build a search engine for wines, you need to get the best dataset and model the data around the features a user will rely on when looking for information.

So, data is important, but the data model is even more important. If you are building an AI Agent that has to do things in your marketing ecosystem, you must model the data accordingly. You want to represent the essence of web pages and content assets.

Image from author, August 2024

2. Not Everyone Is Great At Prompting

Expressing a task in written form is hard. Prompt engineering is going at full speed towards automation (here is my article on going from prompting to prompt programming for SEO) as only a few experts can write the prompt that brings us to the expected outcome.

This poses several challenges for the design of the user experience of autonomous agents. Jakon Nielsen has been very vocal about the negative impact of prompting on the usability of AI applications:

“One major usability downside is that users must be highly articulate to write the required prose text for the prompts.”

Even in rich Western countries, statistics provided by Nielsen tell us that only 10% of the population can fully utilize AI! 

Simple Prompt Using Chain-of-Thought (CoT)

More Sophisticated Prompt Combining Graph-of-Thought (GoT) and Chain-of-Knowledge (CoK)

“Explain step-by-step how to calculate the area of a circle with a radius of 5 units.”

“Using the Graph-of-Thought (GoT) and Chain-of-Knowledge (CoK) techniques, provide a comprehensive explanation of how to calculate the area of a circle with a radius of 5 units. Your response should: Start with a GoT diagram that visually represents the key concepts and their relationships, including: Circle Radius Area Pi (π) Formula for circle area Follow the GoT diagram with a CoK breakdown that: a) Defines each concept in the diagram b) Explains the relationships between these concepts c) Provides the historical context for the development of the circle area formula Present a step-by-step calculation process, including: a) Stating the formula for the area of a circle b) Explaining the role of each component in the formula c) Showing the substitution of values d) Performing the calculation e) Rounding the result to an appropriate number of decimal places Conclude with practical applications of this calculation in real-world scenarios. Throughout your explanation, ensure that each step logically follows the previous one, creating a clear chain of reasoning from basic concepts to the final result.” This improved prompt incorporates GoT by requesting a visual representation of the concepts and their relationships. It also employs CoK by asking for definitions, historical context, and connections between ideas. The step-by-step breakdown and real-world applications further enhance the depth and practicality of the explanation.”

3. You Shall Build Workflows To Guide The User

The lesson learned is that we must build detailed standard operating procedures (SOP) and written protocols that outline the steps and processes to ensure consistency, quality, and efficiency in executing particular optimization tasks.

We can see empirical evidence of the rise of prompt libraries like the one offered to users of Anthropic models or the incredible success of projects like AIPRM.

In reality, we learned that what creates business value is a series of ci steps that help the user translate the context he/she is navigating in into a consistent task definition.

We can start to envision marketing tasks like conducting keyword research as a Standard Operating Procedure that can guide the user across multiple steps (here is how we intend the SOP for keyword discovery using Agent WordLift)

4. The Great Shift To Just-in-Time UX 

In traditional UX design, information is pre-determined and can be organized in hierarchies, taxonomies, and pre-defined UI patterns. As AI becomes the interface to the complex world of information, we’re witnessing a paradigm shift.

UI topologies tend to disappear, and the interaction between humans and AI remains predominantly dialogic. Just-in-time assisted workflows can help the user contextualize and improve a workflow.

• You need to think in terms of business value creation, focus on the user’s interactive journey, and facilitate the interaction by creating a UX on the fly. Taxonomies remain a strategic asset, but they operate behind the scenes as the user is teleported from one task to another, as recently brilliantly described by Yannis Paniaras from Microsoft.

Image from “The Shift to Just-In-Time UX: How AI is Reshaping User Experiences” by Yannis Paniaras, August 2024

5. From Agents To RAG (And GraphRAG) To Reporting

Because the user needs a business impact and RAG is only part of the solution, the focus quickly shifts from more generic questions and answering user patterns to advanced multi-step workflows.

The biggest issue, though, is what outcome the user needs. If we increase the complexity to capture the highest business goals, it is not enough to, let’s say, “query your data” or “chat with your website.”

A client wants a report, for example, of what is the thematic consistency of content within the entire website (this is a concept that we recently discovered as SiteRadus in Google’s massive data leak), the overview of the seasonal trends across hundreds of paid campaigns, or the ultimate review of the optimization opportunities related to the optimization of Google Merchant Feed.

You must understand how the business operates and what deliverables you will pay for. What concrete actions could boost the business? What questions need to be answered?

This is the start of creating a tremendous AI-assisted reporting tool.

How Can A Knowledge Graph (KG) Be Coupled With An Ontology For AI Alignment, Long-term Memory, And Content Validation?

The three guiding principles behind SEOntology:

• Making SEO data interoperable to facilitate the creation of knowledge graphs while reducing unneeded crawls and vendor locked-in;
• Infusing SEO know-how into AI agents using a domain-specific language.
• Collaboratively sharing knowledge and tactics to improve findability and prevent misuse of Generative AI.

When you deal with at least two data sources in your SEO automation task, you will already see the advantage of using SEOntology.

SEOntology As “The USB-C Of SEO/Crawling Data”

Standardizing data about content assets, products, user search behavior, and SEO insights is strategic. The goal is to have a “shared representation” of the Web as a communication channel.

Let’s take a step backward. How does a Search Engine represent a web page? This is our starting point here. Can we standardize how a crawler would represent data extracted from a website? What are the advantages of adopting standards?

Practical Use Cases

Integration With Botify And Dynamic Internal Linking

Over the past few months, we’ve been working closely with the Botify team to create something exciting: a Knowledge Graph powered by Botify’s crawl data and enhanced by SEOntology. This collaboration is opening up new possibilities for SEO automation and optimization.

Leveraging Existing Data With SEOntology

Here’s the cool part: If you’re already using Botify, we can tap into that goldmine of data you’ve collected. No need for additional crawls or extra work on your part. We use the Botify Query Language (BQL) to extract and transform the needed data using SEOntology.

Think of SEOntology as a universal translator for SEO data. It takes the complex information from Botify and turns it into a format that’s not just machine-readable but machine-understandable. This allows us to create a rich, interconnected Knowledge Graph filled with valuable SEO insights.

What This Means for You

Once we have this Knowledge Graph, we can do some pretty amazing things:

• Automated Structured Data: We can automatically generate structured data markup for your product listing pages (PLPs). This helps search engines better understand your content, potentially improving your visibility in search results.
• Dynamic Internal Linking: This is where things get really interesting. We use the data in the Knowledge Graph to create smart, dynamic internal links across your site. Let me break down how this works and why it’s so powerful.

In the diagram below, we can also see how data from Botify can be blended with data from Google Search Console.

While in most implementations, Botify already imports this data into its crawl projects, when this is not the case, we can trigger a new API request and import clicks, impressions, and positions from GSC into the graph.

Collaboration With Advertools For Data Interoperability

Similarly, we collaborated with the brilliant Elias Dabbas, creator of Advertools — a favorite Python library among marketers – to automate a wide range of marketing tasks.

Our joint efforts aim to enhance data interoperability, allowing for seamless integration and data exchange across different platforms and tools.

In the first Notebook, available in the SEOntology GitHub repository, Elias showcases how we can effortlessly construct attributes for the WebPage class, including title, meta description, images, and links. This foundation enables us to easily model complex elements, such as internal linking strategies. See here the structure:

• Internal_Links

• • anchorTextContent
  • NoFollow
  • Link

We can also add a flag if the page is already using schema markup:

• usesSchema

Formalizing What We Learned From The Analysis Of The Leaked Google Search Documents

While we want to be extremely conscious in deriving tactics or small schemes from Google’s massive leak, and we are well aware that Google will quickly prevent any potential misuse of such information, there is a great level of information that, based on what we learned, can be used to improve how we represent web content and organize marketing data.

Despite these constraints, the leak offers valuable insights into improving web content representation and marketing data organization. To democratize access to these insights, I’ve developed a Google Leak Reporting tool designed to make this information readily available to SEO pros and digital marketers.

For instance, understanding Google’s classification system and its segmentation of websites into various taxonomies has been particularly enlightening. These taxonomies – such as ‘verticals4’, ‘geo’, and ‘products_services’ – play a crucial role in search ranking and relevance, each with unique attributes that influence how websites and content are perceived and ranked in search results.

By leveraging SEOntology, we can adopt some of these attributes to enhance website representation.

Now, pause for a second and imagine transforming the complex SEO data you manage daily through tools like Moz, Ahrefs, Screaming Frog, Semrush, and many others into an interactive graph. Now, envision an Autonomous AI Agent, such as Agent WordLift, at your side.

This agent employs neuro-symbolic AI, a cutting-edge approach that combines neural learning capabilities with symbolic reasoning, to automate SEO tasks like creating and updating internal links. This streamlines your workflow and introduces a level of precision and efficiency previously unattainable.

SEOntology serves as the backbone for this vision, providing a structured framework that enables the seamless exchange and reuse of SEO data across different platforms and tools. By standardizing how SEO data is represented and interconnected, SEOntology ensures that valuable insights derived from one tool can be easily applied and leveraged by others. For instance, data on keyword performance from SEMrush could inform content optimization strategies in WordLift, all within a unified, interoperable environment. This not only maximizes the utility of existing data but also accelerates the automation and optimization processes that are crucial for effective marketing.

Infusing SEO Know-How Into AI Agents

As we develop a new agentic approach to SEO and digital marketing, SEOntology serves as our domain-specific language (DSL) for encoding SEO skills into AI agents. Let’s look at a practical example of how this works.

Screenshot from WordLift, August 2024

We’ve developed a system that makes AI agents aware of a website’s organic search performance, enabling a new kind of interaction between SEO professionals and AI. Here’s how the prototype works:

System Components

• Knowledge Graph: Stores Google Search Console (GSC) data, encoded with SEOntology.
• LLM: Translates natural language queries into GraphQL and analyzes data.
• AI Agent: Provides insights based on the analyzed data.

Human-Agent Interaction

Image from author, August 2024

The diagram illustrates the flow of a typical interaction. Here’s what makes this approach powerful:

• Natural Language Interface: SEO professionals can ask questions in plain language without constructing complex queries.
• Contextual Understanding: The LLM understands SEO concepts, allowing for more nuanced queries and responses.
• Insightful Analysis: The AI agent doesn’t just retrieve data; it provides actionable insights, such as:
  • Identifying top-performing keywords.
  • Highlighting significant performance changes.
  • Suggesting optimization opportunities.
• Interactive Exploration: Users can ask follow-up questions, enabling a dynamic exploration of SEO performance.

By encoding SEO knowledge through SEOntology and integrating performance data, we’re creating AI agents that can provide context-aware, nuanced assistance in SEO tasks. This approach bridges the gap between raw data and actionable insights, making advanced SEO analysis more accessible to professionals at all levels.

This example illustrates how an ontology like SEOntology can empower us to build agentic SEO tools that automate complex tasks while maintaining human oversight and ensuring quality outcomes. It’s a glimpse into the future of SEO, where AI augments human expertise rather than replacing it.

Human-In-The-Loop (HTIL) And Collaborative Knowledge Sharing

Let’s be crystal clear: While AI is revolutionizing SEO and Search, humans are the beating heart of our industry. As we dive deeper into the world of SEOntology and AI-assisted workflows, it’s crucial to understand that Human-in-the-Loop (HITL) isn’t just a fancy add-on—it’s the foundation of everything we’re building.

The essence of creating SEOntology is to transfer our collective SEO expertise to machines while ensuring we, as humans, remain firmly in the driver’s seat. It’s not about handing over the keys to AI; it’s about teaching it to be the ultimate co-pilot in our SEO journey.

Human-Led AI: The Irreplaceable Human Element

SEOntology is more than a technical framework – it’s a catalyst for collaborative knowledge sharing that emphasizes human potential in SEO. Our commitment extends beyond code and algorithms to nurturing skills and expanding the capabilities of new-gen marketers and SEO pros.

Why? Because AI’s true power in SEO is unlocked by human insight, diverse perspectives, and real-world experience. After years of working with AI workflows, I’ve realized that agentive SEO is fundamentally human-centric. We’re not replacing expertise; we’re amplifying it.

We deliver more efficient and trustworthy results by blending cutting-edge tech with human creativity, intuition, and ethical judgment. This approach builds trust with clients within our industry and across the web.

Here’s where humans remain irreplaceable:

• Understanding Business Needs: AI can crunch numbers but can’t replace the nuanced understanding of business objectives that seasoned SEO professionals bring. We need experts who can translate client goals into actionable SEO strategies.
• Identifying Client Constraints: Every business is unique, with its limitations and opportunities. It takes human insight to navigate these constraints and develop tailored SEO approaches that work within real-world parameters.
• Developing Cutting-Edge Algorithms: The algorithms powering our AI tools don’t materialize out of thin air. We need brilliant minds to develop state-of-the-art algorithms, learn from human input, and continually improve.
• Engineering Robust Systems: Behind every smooth-running AI tool is a team of software engineers who ensure our systems are fast, secure, and reliable. This human expertise keeps our AI assistants running like well-oiled machines.
• Passion for a Better Web: At the heart of SEO is a commitment to making the web a better place. We need people who share Tim Berners’s—Lee’s vision—people who are passionate about developing the web of data and improving the digital ecosystem for everyone.
• Community Alignment and Resilience: We need to unite to analyze the behavior of search giants and develop resilient strategies. It’s about solving our problems innovatively as individuals and as a collective force. This is what I always loved about the SEO industry!

Extending The Reach Of SEOntology

As we continue to develop SEOntology, we’re not operating in isolation. Instead, we’re building upon and extending existing standards, particularly Schema.org, and following the successful model of the GS1 Web Vocabulary.

SEOntology As An Extension Of Schema.org

Schema.org has become the de facto standard for structured data on the web, providing a shared vocabulary that webmasters can use to markup their pages.

However, while Schema.org covers a broad range of concepts, it doesn’t delve deeply into SEO-specific elements. This is where SEOntology comes in.

An extension of Schema.org, like SEOntology, is essentially a complementary vocabulary that adds new types, properties, and relationships to the core Schema.org vocabulary.

This allows us to maintain compatibility with existing Schema.org implementations while introducing SEO-specific concepts not covered in the core vocabulary.

Learning From GS1 Web Vocabulary

The GS1 Web Vocabulary offers a great model for creating a successful extension that interacts seamlessly with Schema.org. GS1, a global organization that develops and maintains supply chain standards, created its Web Vocabulary to extend Schema.org for e-commerce and product information use cases.

The GS1 Web Vocabulary demonstrates, even recently, how industry-specific extensions can influence and interact with schema markup:

• Real-world impact: The https://schema.org/Certification property, now officially embraced by Google, originated from GS1’s https://www.gs1.org/voc/CertificationDetails. This showcases how extensions can drive the evolution of Schema.org and search engine capabilities.

We want to follow a similar approach to extend Schema.org and become the standard vocabulary for SEO-related applications, potentially influencing future search engine capabilities, AI-driven workflows, and SEO practices.

Much like GS1 defined their namespace (gs1:) while referencing schema terms, we have defined our namespace (seovoc:) and are integrating the classes within the Schema.org hierarchy when possible.

The Future Of SEOntology

SEOntology is more than just a theoretical framework; it’s a practical tool designed to empower SEO professionals and tool makers in an increasingly AI-driven ecosystem.

Here’s how you can engage with and benefit from SEOntology.

If you’re developing SEO tools:

• Data Interoperability: Implement SEOntology to export and import data in a standardized format. This ensures your tools can easily interact with other SEOntology-compliant systems.
• AI-Ready Data: By structuring your data according to SEOntology, you’re making it more accessible for AI-driven automations and analyses.

If you’re an SEO professional:

• Contribute to Development: Just like with Schema.org, you can contribute to SEOntology’s evolution. Visit its GitHub repository to:
  • Raise issues for new concepts or properties you think should be included.
  • Propose changes to existing definitions.
  • Participate in discussions about the future direction of SEOntology.
• Implement in Your Work: Start using SEOntology concepts in your structured data.

In Open Source We Trust

SEOntology is an open-source effort, following in the footsteps of successful projects like Schema.org and other shared linked vocabularies.

All discussions and decisions will be public, ensuring the community has a say in SEOntology’s direction. As we gain traction, we’ll establish a committee to steer its development and share regular updates.

Conclusion And Future Work

The future of marketing is human-led, not AI-replaced. SEOntology isn’t just another buzzword – it’s a step towards this future. SEO is strategic for the development of agentive marketing practices.

SEO is no longer about rankings; it’s about creating intelligent, adaptive content and fruitful dialogues with our stakeholders across various channels. Standardizing SEO data and practices is strategic to build a sustainable future and to invest in responsible AI.

Are you ready to join this revolution?

There are three guiding principles behind the work of SEOntology that we need to make clear to the reader:

• As AI needs semantic data, we need to make SEO data interoperable, facilitating the creation of knowledge graphs for everyone. SEOntology is the USB-C of SEO/crawling data. Standardizing data about content assets and products and how people find content, products, and information in general is important. This is the first objective. Here, we have two practical use cases. We have a connector for WordLift that gets crawl data from the Botify crawler and helps you jump-start a KG that uses SEOntology as a data model. We are also working with Advertools, an open-source crawler and SEO tool, to make data interoperable with SEOntology;
• As we progress with the development of a new agentic way of doing SEO and digital marketing, we want to infuse the know-how of SEO using SEOntology, a domain-specific language to infuse the SEO mindset to SEO agents (or multi-agent systems like Agent WordLift). In this context, the skill required to create dynamic internal links is encoded as nodes in a knowledge graph, and opportunities become triggers to activate workflows.
• We expect to work with human-in-the-loop HITL, meaning that the ontology will become a way to collaboratively share knowledge and tactics that help improve findability and prevent the misuse of Generative AI that is polluting the Web today.

Project Overview

This work on SEOntology is the product of collaboration. I extend my sincere thanks to the WordLift team, especially CTO David Riccitelli. I also appreciate our clients for their dedication to innovation in SEO through knowledge graphs. Special thanks to Milos Jovanovik and Emilia Gjorgjevska for their critical expertise. Lastly, I’m grateful to the SEO community and the SEJ editorial team for their support in sharing this work.

More resources: 

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Featured Image: tech_BG/Shutterstock

Is That SEO Course Worth Your Time? How To Tell via @sejournal, @WixStudio

This post was sponsored by Wix. The opinions expressed in this article are the sponsor’s own.

SEO courses seem to be everywhere. In that sense, they’ve become a dime a dozen. That’s generally because they’re both a lead magnet and a solution to a real problem.

To the latter, SEO isn’t an exact science, and it’s not like you can major in SEO at a traditional university. Instead, we have a disparate set of publications (like the one you are reading right now) offering collections of various resources and media from which to learn SEO.

Moreover, most practitioners “somehow” fall into SEO from other disciplines. So you’re really starting from scratch. It’s why a lot of SEOs start off following some pretty bad advice from some pretty questionable (yet highly popular) marketers.

It all makes for a pretty messed up learning curve when trying to “uplevel” (sorry for the marketing buzzword) your SEO know-how.

The solution? A set of organized material from knowledgeable sources built on sound pedagogical tactics—AKA a course.

The problem is, even if a course is free, it’s a serious time commitment. So before you fork over your money and/or your time, how do you know if a course is even worthwhile?

To help answer this question, I am going to take you behind the scenes of how I constructed our SEO course (while of course—pun intended—subtly selling you on the idea of taking our course as this is indeed a sponsored article; I just smashed like three “fourth walls” in one sentence).

Let’s get started. Here’s what I was looking for when I constructed the course and what you should look for when taking or recommending an SEO course.

1. Look For Course Instructors That Align with Specific Expertise

If you see a course and it’s just a bunch of random “big names” you’ve seen all over social media, run.

Yes, you do want a course created by experts in the field. However, it’s not as simple as having a “big name” on board.

To start, popularity on social media doesn’t always equate with actual SEO expertise. What you want to do is sniff out if the course instructors are there for the substance they provide or if this is just some sort of influencer marketing play.

When we went about creating our SEO course, one of the things I was adamant about was that the instructors we hired weren’t just experts in “SEO,” but experts in a specific type of SEO (local SEO, tech SEO, etc.). Meaning, it wasn’t just “Are these folks well-respected,” but are they known in the industry for focusing on that subtopic within wider SEO?

I was also looking for good communicators, not just the folks with the largest social followings. Being a good communicator on social media is different from being able to convey information in a more formal setting that relies on video as the medium.

Aside from areas of specialization, there are all sorts of practitioners who are used to doing SEO in different contexts. There are enterprise SEOs, in-house SEOs, consultants, SEOs who work at agencies, etc.

We thought it was important to have course instructors from all these backgrounds to offer a more complete set of approaches to various SEO considerations.

So if you’re looking into an SEO course, ask yourself:

• Is there something to the instructors beyond their name recognition?
• Do the instructors have strong subtopic alignment with their course sections?
• Are the various subsets of SEO represented? (In-house, agency, etc.)
• Do the instructors have previous presenting experience or just big social media followings?

1. There Is No ‘Best’ Course

If a course names itself something like “Best SEO Course”—run. There is no such thing as a “best” SEO course. There is a course that is great at dealing with advanced SEO topics, or courses that are geared towards specializing in something like tech SEO or local SEO, and there are courses that offer a wider breadth, etc.

The right course depends on your needs and objectives and where you are in your SEO journey. As such, the “best SEO course” is a fictitious construct.

To pull the curtain back, we were debating what to do with the term “best” for our course. The query “best SEO course” is certainly a lucrative one. Perhaps it would be strategic for our SEO to include the term “best” in the name of the course.

We decided not to do so even if there was an SEO benefit to it.

We had an idea of who we built the course for: We specifically wanted to help people having a hard time piecing together the topic and who are relying on doing so for their business needs and/or careers. (That’s not to say the course doesn’t apply to other demographics, but rather this is the primary pain point and audience we had in mind when designing the course).

This is basically because when we sat down to discuss the course, we all felt that when we were first starting out in SEO, it was a struggle to piece it all together.

This not only shows why there is no “best” SEO course, it also leads me to my next point.

2. Make Sure The People Behind The Course Are Genuine SEO Experts

Instructors are one thing. The people responsible for developing the course overall are another thing entirely. Now, I am not saying that if the people behind the course are not SEOs, they can’t create a wonderful course. What I am saying is that you better hope they gave creative control to the SEOs involved.

That’s not just for SEO accuracy per se (although that is a big part of it), it’s also because SEOs who have themselves struggled to grasp SEO concepts at some point in their career will better understand what to include in an SEO course.

Then, of course, there is the actual accuracy of the content. While the instructors may be a part of the process, they are far from in control of the course and what it ultimately looks like in post-production.

The question is, how can you tell if SEOs were involved in the backend of the course and to what extent?

There is no 100% tell-tale sign. However, I can say that from my experience working with our course, the way the course is structured might provide hints.

What do I mean?

Usually in an SEO course’s “on-page SEO” section, you would discuss concepts related to all things content, from E-E-A-T to strategy.

In our course, I purposefully did not put this course material under “On-Page SEO.” Rather, the deep dive into content, quality, and algorithms were placed under keyword research.

Why?

I felt that, often, the SEO industry thinks about topics like keyword research a bit too linearly and without enough depth and nuance. I wanted to contextualize keyword research by connecting it to a discussion about what creating quality content for the SERP looks like.

This is what I mean by looking at unique course structuring as a sign that there is real SEO expertise going into the material.

If a course follows an overly generic format, this (combined with other signals might) be a sign that folks without genuine SEO experience have too much input. Which is, obviously, not what you want.

3. Look For Signs of Pedagogy

This has nothing to do with SEO itself, but is purely about what it means to create a good course.

Yes, the curriculum needs to be accurate, but it also has to be delivered in a way that is conducive for learning. Our own process involved a lot of back and forth with our educational team to ensure that we structured everything from the assessments to the course scripts in a way that facilitates learning.

To give some context, we borrowed something that I used to do back in my teaching days—backward planning.

At the start of the process, we developed learning goals within the course section. These goals would form the basis for the assessments that we offer at the end of each course section. All of the course sections were built to fulfill those specific learning goals. In this way, the course itself directly aligns with the assessment, which is only fair.

On top of that, we made sure to use the assessments to extend the learning by mixing in scenario-based questions.

There are millions of ways to go about constructing a course that incorporates sound pedagogy. If you’re looking at a course and it all seems very linear, that might be a good indication that the course lacks pedagogical depth. Which is clearly not what you want, no matter how amazing the instructors listed are.

So when looking at an SEO course and deciding to dive in, don’t just look at it from an SEO perspective. Getting the SEO education right is only half the battle. The course also has to effectively communicate that information to you.

Look for signs of pedagogical life when choosing an SEO course.

Learning SEO can be hard. It can be a very informal process that leaves you wondering what gaps you might have and what you still need to learn.

The need for an SEO course can be real. There are a lot of great SEO courses out there. There are also a heap of “grifters” looking to take advantage of people who need a comprehensive way to learn SEO.

When it comes to signing up for an SEO course, if it feels too “markety” or too “salesy,” it probably is.

• Look past the “certifications” every course offers (ours included). They’re nice, but no one is hiring you or giving you a raise because you have one.

• Look past the big names a course may have procured.

• Look past the overpromising (“Our users have improved their organic traffic by 1000000000000000000000000.9% in just 1 day after completing our course”).

Instead, think about what your specific needs are and if the course is suitable and substantial enough to help you fill those needs.

It pays to dig a bit deeper into a course and pull the curtain back a bit before investing money and in the case of a free course, time.

Ready to start optimizing your website? Sign up for Wix and get the data you need to deliver great user experiences.

Image Credits

Featured Image: Image by Wix. Used with permission.

Four Reasons You Can’t Ignore Branded SEO in 2025

This post was sponsored by Similarweb. The opinions expressed in this article are the sponsor’s own.

According to Rand Fishkin:

‘For most small and medium businesses and newer creators/publishers, SEO is likely to show poor results until you’ve established credibility, navigational demand, and a strong reputation among a sizable audience.’

In other words, if you want to build organic traffic, build your brand.

The question is how do search engines measure brand, and what does that mean to your SEO?

In this post, I’ll dig into what influence SEOs have over brand-building, and show you:

• Why branded SEO is an untapped opportunity you should grab with both hands.
• How brand in SEO differs from traditional brand strategy.
• Ways you can educate Google about your brand.

Branded SEO, An Untapped Opportunity

Branded SEO remains a largely untapped SEO opportunity. It’s untapped because, as SEOs, we’re trained to ignore branded traffic. However, by ignoring branded search, you are potentially missing some big opportunities to move your business forward.

The reason is that users don’t just use search engines to discover information and products. They also use search engines to discover brands. By focusing on how your brand shows up, you have an opportunity to influence how middle-of-the-funnel users perceive your brand. If you get it right, that could turn into a long-term relationship with your brand. Get it wrong, and I’m sure you have a number of competitors that would love to have the business.

This leads us to a crucial question…

Is There An SEO Angle To Brand?

As SEOs, we influence how content appears on search engines. The function of a search engine is to match end users with content. This means as SEOs, we are not just dealing with how users perceive your brand. We are dealing with how search engines understand how users perceive your brand.

The difference is not subtle.

Search engine algorithms measure how strong a brand is and incorporate those signals into the search results. They primarily seem to use three methods:

• Measuring branded search queries
• Measuring brand engagement metrics
• Understanding your brand entity

So, if the search engine incorporates brand signals into how it generates search results, then as SEOs we should be looking for a strategic way to influence these signals.

1. Branded Search Queries

Google’s leaked documents reveal a crucial aspect of branded SEO: the strength of a brand significantly influences its search rankings. This is measured through what we can call the BrandQueryFactor. This metric assesses how frequently users search for a brand by name. The more brand-specific queries a company receives, the higher its likelihood of ranking well in search results.

We understand that branded searches affect your rankings, the question now is, in what way do they affect your rankings?

Perhaps the answer can be found in a Google patent called Ranking Search Results. This patent describes how Google uses branded search queries as a quality factor similar to links. In fact, it describes branded and navigational queries as implied links that demonstrate user trust and intent.

These ‘implied links’ have a slightly different role in establishing a site’s authority than actual links:

• Links act as a vote of confidence from other websites, often indicating external recognition or authority
• Branded queries reflect real-world user interest, signaling how often users search for and interact with a resource through queries

Putting that together with the Google leak metrics above, we see that brand signals include user engagement and branded query analysis. Google uses these signals to see how users engage with your brand.

Increasing brand signals with branded queries and direct traffic

As an SEO can you increase branded traffic? The sad truth is, not directly. When your SEO starts to bring in traffic you will see an increase in branded searches. But this is an indirect benefit rather than a branded search strategy.

Does this mean branded search is out of your hands?

To answer this, it’s important to first understand how to increase brand signals.

A few years ago, when I worked as an SEO manager, I noticed something. Whenever we ran PPC campaigns, we would see increasing amounts of branded search terms in our Search Console accounts.

The reason is pretty simple. People saw our ads and Googled the brand name. Take a look at the Similarweb Channels report below. What do you see? (Hint, the blue line represents organic traffic.)

Screenshot from Similarweb, September 2024

Channel data for greenies.com

 As we see above, organic traffic seems to correlate directly with paid search.

Screenshot from Similarweb, September 2024

Looking at the organic search breakdown for the brand in 2023, we see that 72% of the site’s keywords were branded.

Screenshot from Similarweb, September 2024

Channel data for elorea.com

 What we see above is organic traffic directly correlates with other channels.

Screenshot from Similarweb, September 2024

Looking at the organic search breakdown for the brand in 2023, we see that 81% of the site’s keywords were branded.

The reason for this pattern is that the more your audience sees your brand, the more likely they are to Google your brand.

Another great example of this is monday.com. The brand has doubled down on its brand strategy, focusing primarily on YouTube ads.

Screenshot from Similarweb, September 2024

Its YouTube ads together with its memorable domain name has led to unprecedented levels of direct traffic.

Screenshot from Similarweb, September 2024

Although I haven’t yet seen evidence that Google uses direct traffic as a ranking signal, it stands to reason that it does. What’s more, you can see that Google has taken notice of the brand.

Try Googling the word Monday and then Google the word Tuesday and compare the results. To Google the word Monday refers to a brand.

Screenshot from search for Monday, Google, September 2024

Tuesday, on the other hand, is a day of the week.

Screenshot from search for Tuesday, Google, September 2024

The takeaway: You can increase brand signals like branded keywords and direct traffic by focusing on other channels.

So where does this leave you as an SEO?

You have the data to assess branded keywords and direct traffic, putting you in a unique position to partner with marketing leaders to work on big-picture marketing strategies designed to increase branded keywords.

2. Brand Engagement Metrics

Looking at the Google leak we can also see that Google measures user engagement as a signal of brand strength.

Brand Engagement Metrics includes user engagement factors such as click-through rates (CTR) and user interactions with the brand’s content. Higher engagement can positively influence rankings.

This means focusing on improving user engagement is a crucial aspect of brand SEO.

The best way to evaluate user engagement on your site is to compare your engagement metrics with that of your competitors.

For instance I’m analyzing toyota.com and four of its competitors with the Similarweb Website Performance report. Looking at the Engagement metrics we see that ford.com is getting more engagement in almost all metrics.

Screenshot from Similarweb, September 2024

One of the best ways to improve user engagement is to focus on site navigation. This means figuring out the flow of information on your site and including it in your:

• URL structure
• Bread crumbs
• Top level menu

Also make sure that the top of the fold section of every piece of content directly answers the user intent directly.

3. Creating content For [Brand] + Modifier Keywords

You have direct influence over how your brand appears when users search for it on Google. While you might assume all your branded traffic goes to your homepage, there are actually other ways to capture this traffic.

What’s more, your branded traffic can help you discover customer sticking points or even areas where you are potentially losing customers to your competitors.

Want to see how? Try digging through your branded keywords. You are looking for keyword modifiers that either represent issues to resolve or opportunities to be won.

Keyword modifiers might be:

• [brand] pricing
• [brand] reviews
• [brand] alternative
• Where is [brand] located
• [brand] alternative

By looking through your branded keywords, you can quickly see how users are interacting with your brand by seeing the questions they are asking. Make sure you have content that answers all of these questions. If you find long-tail queries it might be a good idea to create an FAQ on your site.

If you don’t do this you might see your branded traffic go to sites like YouTube or worse, your competitors.

For instance using the Similarweb SERP Players report below, we see a large portion of branded clicks for Ninja Creamy going to YouTube.

Screenshot from Similarweb, September 2024

What’s fascinating about this is that YouTube is not above the fold. This means that users often have more than one search intent and are willing to scroll to find what they are looking for. Can you afford to lose traffic for YouTube?

Screenshot from search for Ninja Creami, Google, September 2024

In a case like this depending on which videos users are clicking on, it might make sense for the brand to create video content designed to feature on the SERP.

A great example of a brand that got this right is wildgrain.com. In 2023, the keyword ‘wildgrain reviews’ was trending. Fortunately for the brand they already included a page on their site featuring reviews.

Googling the keyword, users were faced with Wildgrain’s own reviews page ranking in position #1. What’s more the rich result included a review rating of 4.7 out of five. It also listed the amount of reviews (which currently stands at 31040.)

Screenshot from search for Wildgrain reviews, Google, September 2024

Our data shows that 72% of searches were zero-click. That means the vast majority of users were satisfied with what they saw in the search results.

What’s interesting is of the remaining 28% of users, 57% clicked on the Wildgrain’s own result.

Screenshot from Similarweb, September 2024

The takeaway is with the right content, you can directly influence how users interact with your brand, even on things like reviews.

4. Educating Search Engines About Your Brand Entity

Another aspect of how Google evaluates your brand is through your brand entity. Google’s machine learning allows the search engine to understand real-world entities. It does this by gathering information about entities mentioned around the web and arranging that information in a similar way to how a human brain arranges information.

The purpose of this is to understand the relationships between people, places, and things so that Google can deliver more relevant and contextual information in the SERPs.

Google’s knowledge is constantly expanding and updating as new information becomes available.

How does Google understand your brand?

To find out, just Google it. If there are strong signals around the web, Google will present you with things like a Knowledge Panel, Twitter (X) boxes, image boxes and more.

Screenshot from search for Mr Beast, Google, September 2024

If you don’t see anything, you have work to do, as I mentioned above, a large portion of users hear about your brand and then Google you. What they see when they arrive on your brand SERP is up to you.

The great news is you can educate Google about your brand entity. When you do that, you’ll not only improve your brand SERP, but you might see your brand popping up in other strategic places.

For instance, below, I’ve searched for Fandango, a company that sells movie tickets. If you look at the bottom of the Knowledge Panel on the right, you’ll see Fandango’s direct competitors including:

• AMC Theatres
• Regal Cinemas
• Cinemark Theatres

Screenshot from search for Fandango, Google, September 2024

How did a site’s competitors make it into the site’s Knowledge Panel? Google doesn’t only rank content for keywords any more. It understands what the brand entity is and what it relates to. The result is you might find your brand mentioned appearing on your competitor’s brand SERP or in other relevant places on the web.

How do you educate Google about your brand entity?

There is a clear method to educate Google about your brand entity.

1. Establish an entity home page: Create a dedicated page that describes your entity. This page should clearly outline what your business does and who it serves. Although this can be any page on the web, the best place to do this is on your ‘About Us’ page.

2. Build entity citations: Mentions of your brand across the web will reinforce the information provided on your brand homepage. It’s important to keep your brand description consistent around the web so that Google can match each citation with your entity’s home page. Citations can appear on pages you control, such as social media profiles but citations on pages you don’t control often carry more weight and provide the most benefit.

3. Link from your entity homepage to your entity citations: This could mean including links to your social media profiles as well as any guest posts, videos, or podcasts your brand is featured on.

Far From The Final Word On Brand SEO

As an SEO, if you prioritize branded SEO, you are not just a technical specialist. You have access to data to shape the business’s digital identity, which can drive tangible and sometimes immediate results. This paradigm shift allows you to directly impact revenue streams, aligning SEO efforts more closely with overarching business objectives.

If branded SEO is a paradigm shift for you, consider this.

Branded SEO is only one ranking factor in Google’s complex maze of ranking systems. You can read more about it in our latest ebook: Google’s Ranking Anatomy: Dissecting 90+ Ranking Signals.

Image Credits

Featured Image: Image by Similarweb. Used with permission.

In-Post Image: Images by Similarweb. Used with permission.

Page Speed Insights: 6 Powerful Tips To Optimize Your Website via @sejournal, @DebugBear

This post was sponsored by DebugBear. The opinions expressed in this article are the sponsor’s own.

Having a fast website is important not just to provide a great experience for visitors, but also as an SEO ranking factor.

You’ve probably heard of Google’s PageSpeed Insights tool before.

But do you know how to get the most out of PageSpeed Insights? We’ll look at 6 key tips to help you optimize your website performance.

What Is PageSpeed Insights (PSI)?

Website performance has long impacted Google rankings. Accordingly, Google first launched its free PageSpeed Insights tool back in 2010.

PSI is built to help website operators check how fast their website is as well as provide recommendations for how to improve it.

Why Does Page Speed Matter For SEO?

In 2021, Google introduced a new set of website performance metrics, called the Core Web Vitals. The three metrics are:

• Largest Contentful Paint: how fast does your website load?
• Cumulative Layout Shift: do page elements move around unexpectedly?
• Interaction to Next Paint: does the page respond to user input quickly?

A good page experience is rewarded in Google rankings. There’s a “Good” rating threshold for each metric that you need to reach.

Graphic showing Core Web Vitals rating thresholds, September 2024

How To Test Your Website With PageSpeed Insights

Running a performance test with PageSpeed Insights is easy:

1. Open PageSpeed Insights
2. Enter your website URL
3. Click “Analyze”

Test results will appear in just a few seconds. There’s a lot of data, but we’ll explain what it all means next.

Screenshot of test result on PageSpeed Insights, September 2024

1. Understand Where PageSpeed Insights Data Comes From

Each test result on PageSpeed Insights consists of two key sections: “Discover what real users are experiencing” and “Diagnose performance issues”. Each section shows a different type of page speed data.

What Is The Real User Data In PageSpeed Insights?

The real user data in PSI comes from the Chrome User Experience Report (CrUX).

This data is collected from Chrome users on desktop devices and on mobile devices running Android. To contribute to the CrUX report, users need to:

• Be logged into their Google account
• Have opted into browser history synchronization
• Have enabled usage statistics reporting

Wondering if your experiences are included in this real user data? Open the chrome://ukm URL in your Chrome browser and check if metrics collection is enabled.

The real user tells you how fast your website is for actual visitors and how it’s impacting your SEO.

However, the CrUX report also comes with some limitations:

• Data is always aggregated over a 28-day period, so you won’t immediately see if your website is getting worse
• You can see how fast your website is, but CrUX does not tell give you any diagnostic data to speed it up
• Not every page on your website will have CrUX data, as a minimum number of recorded visits has to be reached before Google publishes the data.

You can use a real user monitoring (RUM) tool to get around these limitations. RUM data has several advantages over CrUX data, like instant updates and detailed diagnostics.

Screenshot of a Core Web Vitals trendline in DebugBear real user monitoring, September 2024

What Is The Diagnostic Data In PageSpeed Insights?

While the real user data tells you how well your site is doing, the diagnostic data gives you insight into how to optimize it.

PageSpeed Insights uses Google’s open source Lighthouse tool to test your website and provide a detailed analysis. A Lighthouse test is run in a controlled lab environment, which can means that a lot more information information can be collected compared to real user data.

The lab-test is also run on-demand, and is not subject to the 28-day delay that applies to CrUX data.

At the top of the Lighthouse report Google’s shows an overall Performance score between 0 and 100. This score does not directly impact rankings – Google uses CrUX data for that. However, a good Lighthouse score usually means that your website is also loading quickly for real users.

The Lighthouse score itself determined based on 5 performance metrics:

• First Contentful Paint: how quickly does the page start loading?
• Largest Contentful Paint: when does the main page content show up?
• Total Blocking Time: are user interactions blocked by CPU processing?
• Cumulative Layout Shift: does content move around after it appears?
• Speed Index: how quickly does the page content render overall?

Screenshot of performance metrics in PageSpeed Insights, September 2024

Below the overall Lighthouse assessment you can find diagnostic insight that suggests concrete changes you can make to optimize your website.

Each row audits one particular aspect of your performance. For example, if you eliminate render-blocking resources then it will take less time for page content on your website to become visible.

Screenshot of performance diagnostics in PageSpeed Insights, September 2024

2. Use The Score Calculator To See What’s Dragging Your Score Down

If you want to improve your Performance score on PageSpeed Insights, where do you start?

Every Lighthouse report includes a “View Calculator” link that takes you to the Lighthouse Scoring Calculator. This tool tells you how much of the five metrics that Google has measured is contributing to the overall score.

For example, here we can see that the page we’ve tested has a good Cumulative Layout Shift score, while the Largest Contentful Paint receives a poor rating.

We can also see that each metric is assigned a weight. For example, 30% of the Performance score is determined by the subscore for the Total Blocking Time metric.

Screenshot of the Lighthouse Scoring Calculator, September 2024

3. Review Phase Data For The Largest Contentful Paint (LCP) Metric

One of the most insightful audits is often the “Largest Contentful Paint element.”

This audit shows you the largest content element on the page. The LCP metric measures how long it takes after opening the page for this element to become visible. The largest content element can be any type of page content, for example, a heading or an image.

That’s very useful, but Lighthouse actually provides additional insight by breaking the LCP metric down into four phases (also called subparts):

• Time to First Byte (TTFB): how quickly does the website server provide the HTML document?
• Load Delay: How soon after loading the document does the LCP image start downloading
• Load Time: How long does it take to download the LCP image?
• Render Delay: How soon after loading the LCP resource does the LCP element become visible?

This information will tell you where you need to focus on your optimization.

For example, in the screenshot below, we can see that the LCP image loaded quickly but then wasn’t rendered right away by the browser. That could be because other resources on the page were blocking the page from rendering.

Screenshot of the Lighthouse Largest Contentful Paint element audit, September 2024

Google recently ran an analysis to find out what LCP subparts contribute the most to the overall metric value. They found that server response time and image load delay are the biggest factors in LCP optimization for most websites.

While many website performance recommendations have focused on using compact modern image formats, image load time was found to be a minor factor on most slow websites.

However, you should still check the data for your website to see what optimizations can have the most impact.

4. Performance Score Variability Between Tests: What Does It Mean?

We’ve already seen that the real user CrUX data is aggregated over a 28-day period. Accordingly, its value is stable and only changes very gradually.

But the same can’t be said about the Performance score and other metrics measured in the lab. Testing the same page twice will rarely result in the exact same measurements, and often will show high variation. And if you run Lighthouse with other tools like Chrome DevTools you’re likely to see even bigger differences.

There are many reasons for differences between Lighthouse tests, for example:

• Differences in server response time
• Variation in content, for example due to A/B tests or advertisements
• Differences across test devices and test locations
• Inaccuracies during data collection

Google has written a detailed guide on Lighthouse variability. You can run tests several times and look at the average to get a more consistent assessment.

Data Accuracy: Observed Vs Simulated Data

One common reason for discrepancies between page speed testing tools is the way the data is collected. In a lab test the network is throttled to a fixed speed, typically to match a slower mobile data connection. The way this throttling is achieved can impact your measurements.

PageSpeed Insights uses an approach called simulated throttling. Measurements are collected on a fast network connection. After that, a simulation of a slow 4G connection is applied to estimate how the page might have loaded on a mobile device.

You can install the Site Speed Chrome extension to view the original observed metrics when running a test on PageSpeed Insights.

Screenshot of Lighthouse reported and observed metrics, September 2024

Simulated data can sometimes be unreliable, as the Lighthouse simulation doesn’t handle all real life edge cases that can happen when opening a website.

For example, in this test we can see that the Largest Contentful Paint metric is reported as one second worse than the values observed when opening the page in Chrome.

However, the original values for the First Continental Paint and for the Largest Contentful Paint metrics were identical. This suggests that the simulated metrics could potentially not match what real users experience.

You can check the settings section of the Lighthouse report to see if the metrics were measured as reported or if a simulation has been applied.

Screenshot of Lighthouse settings, September 2024

If you want to get reliable page speed data, the free DebugBear page speed test is built to provide the most accurate insight. Collecting real measurements takes a bit longer than running a simulation, but it will also help you make the best decisions when optimizing your website speed.

Why Des The Real User Data Not Match The Lighthouse Test Rresults?

When testing your website on PageSpeed Insights you’ll often find that the real user metrics are much better than those reported by the synthetic Lighthouse test. Why is that?

That’s because the Lighthouse test uses a very slow network connection. The CrUX Core Web Vitals data looks at the slowest 25% of user experiences on your website, but typically, even those visits come from a device that has a decent network connection.

So, a bad Lighthouse performance score doesn’t necessarily mean that you’ll fail Google’s Core Web Vitals assessment. But it can indicate that some users are having a poor experience and that there’s more room for improvement.

Screenshot of real user and lab-based performance metrics in PageSpeed Insights, September 2024

5. Use The PSI API To Automate Performance Testing

Got a lot of pages on your website you want to test? You can use the PageSpeed Insights API to automatically run website tests in bulk.

The API provides more detailed performance metrics and details on each Lighthouse audit. For example, you can use the API to see the most common performance recommendations across your website.

There’s even a way to access PageSpeed Insights data directly in Google Sheets.

JSON page speed data reported by the PageSpeed Insights API, September 2024

6. Know When To Reach For A Different Tool

PageSpeed Insights is a great tool to run a quick performance for a specific URL on your website. However, as we’ve seen above, this data comes with some limitations.

If you just want to get a site-wide overview of Core Web Vitals on your website, the quickest way to find this data is using Google Search Console.

Search Console will show you exactly how many pages on your website are slow or need to be improved.

Screenshot of Core Web Vitals data in Google Search Console, September 2024

Need to dive deep into CPU performance, for example to optimize the new Interaction to Next Paint metric?

The Performance tab in Chrome’s developer tools provides a detailed analysis of all kinds of CPU processing that happens on your website.

Screenshot of a website performance profile in Chrome DevTools, September 2024

Finally, if you want to optimize how different resources are loaded on your website, the DebugBear website speed test can be invaluable.

This test can provide a detailed report on what resources are loaded by your website, when they load, and how they impact rendering.

Screenshot of a website request waterfall in DebugBear, September 2024

How To Always Stay Ahead Of Your Website Speed

PageSpeed Insights and other performance tests are a great starting point for optimizing your website. However, without continuous monitoring, you risk reintroducing problems without noticing.

DebugBear is a monitoring platform for Core Web Vitals that lets you continuously test both your own website and those of your competitors.

Screenshot of the DebugBear performance dashboard, September 2024

In addition to scheduled lab testing, DebugBear also keeps track of Google CrUX data and collects real user analytics directly on your website.

The real user data provides a wide range of insight to not just help you keep track of performance but actively improve it:

• See what LCP subpart is causing the biggest delay for your visitors
• Find specific interactions and scripts that cause a poor Interaction to Next Paint score
• Identify specific countries or devices where performance is worse than usual

Screenshot of real user monitoring data in DebugBear, September 2024

Deliver A Great User Experience

PageSpeed Insights is a helpful tool for any website owner, not just telling you how fast your website is in the real world, but also giving you concrete advice on how to optimize it.

However, if you’d like to go beyond the data PSI provides and test your website continuously, you can sign up for a free 14-day DebugBear trial.

This article has been sponsored by DebugBear, and the views presented herein represent the sponsor’s perspective.

Ready to start optimizing your website? Sign up for DebugBear and get the data you need to deliver great user experiences.

Image Credits

Featured Image: Image by DebugBear. Used with permission.

International SEO Expansion: Best Practices Guide

Getting your international SEO strategy right can be an elusive feat.

There are a lot more factors at play than people give credit for, and it’s often a thankless job.

A successful international SEO strategy requires a deep knowledge of your company’s commercial strategy as well as technical SEO knowledge, cultural sensitivity, and excellent data skills.

Yet the industry often regards international SEO as just your hreflang setup.

In this article, I will distill the complexities of international SEO success into an actionable step-by-step list that will take you from beginner to advanced practitioner. Let’s begin!

Part I: Be Commercially Aware

1. Understand Why Your Company Is Going International

Companies can grow by expanding their products and services, focusing on gaining market penetration or expanding into new markets.

While your team’s goal might be traffic, leads, or revenue, the leadership team is likely working under a different set of parameters. Most of the time, leadership’s ultimate goal is to maximize shareholder value.

• In founder-owned companies, growth goals might be slower and more sustainable, usually aimed at maintaining and growing profitability.
• VC-owned companies have high growth goals because they must provide their investors with a return that’s higher than the stock market. This is what is known as the alpha, or your company’s ability to beat the market in growth.
• Publicly traded companies are likely aiming to grow their share value.
• Startups, depending on their maturity stage, are likely looking to prove product-market fit or expand their reach fast to show that their operations are scalable and have the potential to be profitable in the future. The goal of this is to aid in raising further capital from investors.

Understanding why businesses go international is essential for informing your SEO decisions. What’s best practice for SEO isn’t always what’s best for business.

You must adapt your strategy to your company’s growth model.

• Companies choosing to grow sustainably and maintain profitability will likely expand more slowly to a market that resembles their core market.
• VC-owned companies will be able to invest in a wider range of countries, with a smaller concern for providing their users with an experience on par with that of their core markets.
• Startups can try to beat their competitors to market by expanding quickly and throwing a lot of money at the project, or they might be concerned with cash flow and try to expand fast but cut corners by using automatic translation.

2. Stack Rank Your Target Markets To Prioritize Your Investment

I promise I’ll get to hreflang implementation soon, but so much about international SEO has to do with commercial awareness – so bear with me; this will make you a better professional.

Many companies have different market tiers to reflect how much of a priority each market is. Market prioritization can happen using many different metrics, such as:

• Average order value or lifetime customer value.
• Amount of investment required.
• Market size.
• And market similarity.

American companies often prioritize developed English-speaking countries such as the UK, Canada, or Australia. These are most similar to their core market, and most of their market knowledge will be transferable.

After that, companies are likely to target large European economies, such as Germany and France. They might also target the LatAm market and Spain in the same effort.

The last prioritization tier can vary widely among companies, with a focus on the Nordic, Brazilian, or Asian markets.

Part II: Know Your Tech

3. Define Your International URL Structure

When doing international SEO, there are 4 different possible URL structures, each with its pros and cons.

ccTLD Structure

A ccTLD structure is set up to target different countries based on the domain type.

This structure is not ideal for companies that target different languages rather than different countries. For example, a .es website is targeting Spain, not the Spanish language.

An advantage to this kind of structure is that the ccTLD sends a very strong localization signal to search engines as to what market they are targeting, and they can lead to improved trust and CTR in your core country.

On the other hand, ccTLDs can dilute your site’s authority, as links will be spread across domains rather than concentrated on the .com.

gTLD With Subdirectories

This is my personal favorite when it comes to international SEO.

These URL structures can look like website.com/en if they’re targeting languages or website.com/en-gb if they’re targeting countries.

This configuration aggregates the authority you gain across your different territories into a single domain, it’s cheaper to maintain, and the .com TLD is widely recognizable by users worldwide.

On the other hand, this setup can look less personalized to people outside the US, who might wonder if you can service their markets.

gTLD With Subdomains

This setup involves placing international content on a subdomain like us.website.com. While once popular, it’s slipping in favor because it doesn’t bring anything unique to the table anymore.

This setup offers a clear signal to users and search engines about the intended audience of a specific subdomain.

However, subdomains often face issues with SEO, as Google tends to view them as separate entities. This separation can dilute link, similar to the ccTLD approach but without the geo-targeting advantages.

gTLD With Parameters

This is the setup where you add parameters at the end of the URL to indicate the language of the page, such as website.com/?lang=en.

I strongly advise against this setup, as it can present multiple technical SEO challenges and trust issues.

4. Understand Your Hreflang Setup

In the words of John Mueller: hreflang can be one of the most complex aspects of SEO.

Screenshot from Twitter, May 2024

Hreflang reminds me of a multilingual form of a canonical tag, where we tell search engines that one document is a version of the other and explain the relationship between them.

I find hreflang implementation very interesting from a technical point of view. Because development teams mostly manage it, and it can be very much hit or miss.

Often, hreflang is constructed from existing fields in your content management system (CMS) or content database.

You might find that your development team is pulling the HTML lang tag, which follows a different ISO standard than hreflang, leading to a broken implementation.

Other times, there is a field in your CMS that your development team pulls from to build your hreflang setup.

Finding out how your hreflang tags are generated can be extremely helpful in identifying the sources of different issues or mitigating potential risks.

So speak to your engineering team and ask them how you’re currently generating hreflang.

5. Implement Hreflang Without Errors

There are three ways to implement hreflang on your site:

• On your sitemap.
• Through your HTTP header.
• On your HTML head.

The method most of us are most familiar with is the HTML head. And while you can use more than one method, they should match each other perfectly. Otherwise, you risk confusing search engines.

Here are some basic rules for getting it done correctly:

• In your hreflang implementation, the URL must include domain and protocol.
• You must follow the ISO 639-1 language codes – don’t go around making up your own.
• Hreflang tags must be reciprocal. If the page you’re listing as a language alternative does not list you back, your implementation won’t work.
• Audit your hreflang regularly. My favorite tool for this, since it added the hreflang cluster analysis and link graphs, is Ahrefs. For the record, Ahrefs is not paying me to say this; it’s a genuine recommendation and has helped me a lot in my work.
• You should only have one page per language.
• Your hreflang URLs should be self-canonicalizing and respond with a 200 code.

Follow the above rules, and you’ll avoid the most common hreflang mistakes that SEO pros make.

And if you’re interested in the technical SEO aspect beyond hreflang, I recommend reading Mind your language by Rob Owen.

Part III: Invest In Content Incrementally

6. Translate Your Top-performing Content Topics

Now that you have the basic commercial and technical knowledge covered, you’re ready to start creating a content strategy.

You likely have a wealth of content in your core market that can be recycled. But you want to focus on translating high-converting topics, not just any topic; otherwise, you might be wasting your budget!

Let’s go step by step.

Cluster Your Website’s Content By Topic

• Crawl your site using your favorite SEO tool and extract the URL and H1.
• Use ChatGPT to classify that list of URLs into topics. You might already know what you usually write about, so include those topics in your prompt. You don’t want to have a classification that’s too granular, so you can prompt chatGPT to only create groups with a minimum of 10 URLs (adjust this to reflect the size of your website) and class everything else as other. This is an example of what your prompt might look like: “I will provide you with a list of article titles and their corresponding URL. Classify this list into the following topics: survey best practices, research and analysis, employee surveys, market research and others. Return this in a table format with the URL, title and group name.”
• Start a spreadsheet with all your URLs in the first column, titles in the second column, and the group they belong to in the third column.

Measure Your Performance By Topic

• Export your GSC data and use a =VLOOKUP formula to match your clicks to your URLs.
• Export your conversion data and use a =VLOOKUP formula to match your conversions (leads, sales, sign-ups, or revenue) to the right URL.
• You can then copy your topics column onto a new sheet. Remove duplicates and use the =SUMIF formula to aggregate your click data and conversion data by topic.

Choose What Topics You’ll Be Translating First

Using this data, you can now choose what topics are most likely to drive conversions based on your core market data. Choose how many topics or pieces of content you’ll be translating based on your budget.

Personally, I like translating one topic at a time because I’ve found that generating topical authority on one specific topic makes it easier for me to rank on an adjacent topic that I write about next.

7. Localize Your English Content

Once you’re set up with all your key pages and a few content topics, it’s time to evaluate your investment and see where you could be getting a bigger return.

At this stage, many companies have translated their content into a few different languages and likely copied the US content into their UK and Australian sites. Now that you’ve done some translation, it’s time to work on localization.

If you’ve just copied your US content into your UK and Australian sites, your Google Search Console indexing report might be screaming at you, “Duplicate, Google selected a different canonical than the user.”

A very easy fix that could yield great returns is to localize your English content to the nuances of those English-speaking markets.

You will want to instruct your translation and localization providers to adapt the spellings of certain words, change the choice of words, introduce local expressions, and update any cited statistic for the US with their local equivalent.

For example, if I’m targeting a British audience, “analyze” becomes “analyse,” a “stroller” becomes a “pram,” and “soccer” becomes “football.”

8. Invest In In-market Content

Once you’ve got the basics in place, you can start tackling the specific needs of other markets. This strategy is expensive, and you should only use it in your priority markets, but it can really set you apart from your competitors.

For this, you will need to work with a local linguist to identify pain points, use cases, or needs exclusive to your target market.

For example, if France suddenly made it mandatory to run a diversity and inclusion study for companies with over 250 employees, I’d want to know this and create some content on DEI surveys at SurveyMonkey.

9. Integrate With Other Content Workflows

In step six, we evaluated our top-performing content, chose the best articles to translate, and got it all down. But wait. Some of these source articles have been updated. And there is even more content now!

To run a successful international SEO campaign you must integrate with all the other teams publishing content within your organization.

Usually, the teams creating content in an organization are SEO, content, PR, product marketing, demand generation, customer marketing, customer service, customer education, or solutions engineering.

That’s a lot, and you won’t be able to integrate with everyone all at once. Prioritize the teams that create the most revenue-generating content, such as SEO, content, or product marketing.

Working with these teams, you will have to establish a process for what happens when they create a new piece, update some content, or remove an existing piece.

These processes can differ for everyone, but I can tell you what I do with my team and hope it inspires you.

• When a piece of content that’s already been localized into international markets is updated, we get the content in a queue to be re-localized the next quarter.
• When they create a new piece of content, we evaluate its performance, and if it’s performing above average, we add it to a localization queue for the next quarter.
• When they change the URL of a piece of content or delete it, all international sites must follow suit at the same time, since due to some technical limitations, not making the change globally would create some hreflang issues.

Wrapping Up

International SEO is vast and complex, and no article can cover it all, but many interesting resources have been created by SEO pros across the community for those who want to learn more.

Navigating the complexities of international SEO is no small feat. It’s an intricate dance of aligning commercial strategies with technical precision, cultural insights, and data-driven decisions.

From understanding your company’s core motives for global expansion to meticulously implementing hreflang tags and localizing content, every step plays a crucial role in building a successful international presence.

More resources: 

Featured Image: BritCats Studio/Shutterstock