Generative AI has completely changed how search works. The old keyword-first model, where pages competed to match exact phrases, no longer applies. In generative search optimization (GEO), also called answer engine optimization (AEO), a query is only the starting point.

AI systems now expand, rewrite, and interpret it through dozens of related intents before building a final answer. Success today depends less on ranking for a single keyword and more on how clear, extractable, and trustworthy your content is when AI decides what to include.

In this new search landscape, authority signals and schema markup shape visibility. Citations, expert quotes, and proprietary data strengthen credibility, while structured data helps AI systems understand and cite your content accurately. When combined, these elements make your work not only readable but machine-trustable, ensuring your expertise stands out in the era of AI-driven search.

Author’s Note:

This article is the sixth entry in my AEO/GEO series, which explores how generative AI is redefining search visibility. If you’re just joining in, start with the earlier pieces to see how AI-driven retrieval and synthesis are reshaping the foundations of SEO.

Catch up on the series:

• How AI Overviews Impact CTR and SEO – How Google’s AI-generated results are changing click behavior and rankings.
• Mapping Content to User Goals – How to align structure and messaging with user intent to improve engagement.
• How Generative AI Is Changing Search Behavior – Why people search differently in the age of AI and what it means for your strategy.
• How Generative AI in Search Works – A breakdown of how large language models retrieve, rank, and synthesize information.
• Structuring Content for AI Extraction – A practical guide on formatting content so AI systems can easily parse and reuse it.

How AI Creates Answers and Chooses Citations in Generative Search

If you’ve noticed that AI results don’t stay still, you’re not imagining it. Ask Google’s AI Overview the same question two days in a row, and you’ll often see a completely different set of cited pages.

Take, for example, the keyword “best places to sightsee in metro manila,” which I asked ChatGPT today:

And now look at the answer it gave me yesterday, when I searched for the same exact keyword:

As you can see, two different answers with different citations. And this doesn’t just happen on ChatGPT. One study from Authoritas found that 70% of the pages ranking in AI Overviews changed over the course of 2 to 3 months. 

This volatility is how generative search is designed to work. Instead of pulling a fixed ranking of web pages (like traditional SEO does), AI systems generate answers by making a series of probabilistic choices at every stage. 

Each prompt is expanded into multiple related versions, routed to different retrieval paths, and matched using semantic embeddings that go beyond literal keyword overlap. The system then scores each piece of retrieved content for authority, clarity, and extractability, before deciding which fragments to cite in the final synthesis. Patents filed by Google show this is the underlying system behind AI search. 

Visibility in AI search isn’t about ranking first anymore. A top organic result might never appear in an AI Overview, while a smaller, well-structured page can surface across many prompts. Success now depends on being selected often, not just ranked once. To do that, SEOs and marketers must understand selection, where content is scored, and synthesis, where chosen pieces are assembled into clear answers.

AI Content Selection Process: How Systems Decide What to Keep

After the retrieval stage, a generative system is left with an enormous volume of material—far more than it can feasibly include in a final response. This is where the selection phase begins. 

The AI now filters through all that gathered content, evaluating each piece to decide which ones are both accurate and structurally suited for integration. Unlike traditional search, where algorithms rank entire pages by relevance, generative engines must determine which individual snippets or data units are clean, factual, and easy to reuse. Only a small fraction of the retrieved material will make it through this stage.

To narrow the field, the model applies a set of filters that determine which content is most suitable for synthesis:

• Extractability – Evaluates how easily a passage can stand on its own. Structured lists, tables, and short, clearly defined sections tend to score higher than long, narrative blocks of text.
• Evidence Density – Rewards passages rich in data, statistics, or citations, rather than general statements or opinion-based writing.
• Authority – Assesses the credibility of the source or author, prioritizing expert voices, institutions, or publications with recognized trust signals.
• Corroboration – Checks whether the information aligns with or is supported by other reliable sources. Consistency across multiple references increases confidence.
• Freshness – Prefers content that reflects up-to-date facts or recent reviews, filtering out outdated or time-sensitive material.

For example, imagine a query like “best places to sightsee in Metro Manila.” A table listing top attractions—complete with locations, entry fees, and visiting hours—would be easy for the model to extract and reuse. A short list of landmarks with brief descriptions and verified sources would likely be kept as well. 

In contrast, a long travel blog that buries sightseeing tips inside personal anecdotes would be difficult for the system to parse, and a photo carousel without captions or alt text would be ignored entirely. By the end of selection, the AI keeps only the clearly formatted, factual, and self-contained snippets, turning hundreds of retrieved fragments into a compact set of trustworthy insights ready for synthesis.

AI Content Synthesis Explained: How Generative Models Build Answers

Once the selection phase trims hundreds of retrieved fragments down to a few usable pieces, the synthesis phase begins. Here, the large language model (LLM) takes those verified, well-structured snippets and reassembles them into a cohesive response. 

Each fragment comes from different sources and formats, yet together they form a single, fluent narrative. The model might open with a brief overview, follow with a data table, add a bullet list of key takeaways, and finish with a concise explanation or cited example. 

The resulting answer feels seamless, but beneath the surface it’s a composite of multiple high-quality information units, each filtered for accuracy and clarity.

What makes this process work is how the LLM prioritizes content that’s easy to extract, interpret, and recombine without breaking context. That’s why clearly scoped and labeled content performs best in synthesis. 

Here’s the content and formatting you should be using:

• Tables
• Bulleted or numbered lists
• Semantically tagged headings

Information marked up in these structured formats gives the AI distinct boundaries for understanding what a section represents, allowing it to lift and merge it cleanly with others.

The model then weighs evidence density, favoring passages that deliver specific, verifiable details supported by data or citations. A short paragraph that cites a credible organization carries more weight than a long anecdote filled with filler text. 

Likewise, authority and corroboration strengthen inclusion: information from named experts or trusted institutions, especially when echoed across multiple sources, is far more likely to be chosen. 

Finally, recency matters. For topics where details evolve—like travel restrictions, product updates, or pricing—content that’s dated and reviewed stands out as more trustworthy and usable.

In short, the synthesis phase rewards clarity, structure, and factual precision. The better your content communicates discrete ideas, the easier it becomes for AI to extract, understand, and reuse it. For content strategists, this means designing every paragraph, list, or data point as a self-contained, authoritative building block—because in the synthesis layer, those are the pieces that make it into the final, AI-generated answer.

Using Authority Signals and Schema Markup to Improve AI Search Visibility

In generative search, authority isn’t just about who you are or how well-known your brand is—it’s about how your content proves what it knows. 

As AI systems sift through thousands of potential sources, they look for signals of credibility that make information safe to reuse: clear citations, expert attribution, original data, and verifiable context.

Using Data Citations to Build Trust and Improve AEO/GEO Visibility

Generative systems reward content that can be traced, verified, and trusted. One of the strongest ways to signal that reliability is through data citations. Anchor your statements in concrete numbers, timestamps, and credible sources. 

When information is supported by verifiable evidence, it becomes easier for AI models to extract, score, and reuse confidently during synthesis. 

Whether you’re referencing third-party research or publishing proprietary data, the goal is to make every claim specific, measurable, and sourced.

To strengthen your content’s credibility and extractability, focus on the following practices:

• Use clear, quantifiable data. Use precise numbers, not estimates. Instead of saying “many visitors,” write “Over 1.2 million travelers visited Intramuros in 2023.” AI models can interpret and reuse hard figures far more reliably than vague descriptors.
• Add full timestamps. Replace generic terms like “recently” with concrete markers such as “as of September 2024.” This helps the model assess freshness and relevance.
• Present data in structured formats. Present information in bullet lists, charts, or tables. For example: Top-rated attractions in Metro Manila (2024): Intramuros – 4.8★; National Museum – 4.7★; Ayala Triangle Gardens – 4.6★. Clean formatting improves the content’s extractability during selection.
• Cite original and authoritative sources. When citing studies or reports, point to the primary publication—such as the Philippine Department of Tourism or UNESCO World Heritage Centre—rather than secondary summaries.

Always pair statements with specific data points and verifiable sources. This will be your anchor of authenticity, which signals to AI that your statements are accurate, current, and safe to present as citations or answers to users.

Adding Expert Quotes to Strengthen Authority in AI Search Results

Generative AI evaluates credibility based on what it can confirm directly. That includes who is speaking, where the information comes from, and whether the expertise is verifiable. Adding expert quotes with clear credentials helps establish that trust.

To make expertise recognizable and easy to parse, keep these practices in mind:

• Identify experts by name and qualification. For example, “According to Dr. Juan De La Cruz, PhD in Urban Planning at the University of the Philippines” provides a concrete identity that the model can associate with authority.
• Use visible attributions and proper markup. Apply <blockquote> tags or structured data like Person or Author schema so AI systems can connect quotes to verified individuals.
• Choose quotes that add factual clarity. Statements such as “Peak visiting hours at Rizal Park are between 4:00 p.m. and 6:00 p.m.,” says tourism researcher Juan De La Cruz, offer specific, verifiable details rather than generic statements.

AI systems weigh named, credentialed experts more heavily during synthesis because their input provides traceable evidence.

Using Proprietary Research to Boost Credibility

First-party data not only strengthens your content’s credibility but also gives it a unique fingerprint in corroboration scoring, the process AI systems use to confirm facts across multiple sources. 

When your content contains findings that can’t be found elsewhere, it signals originality and expertise—qualities that both search engines and readers recognize as trustworthy.

To make your research easy for AI to identify and reuse, focus on clarity and structure:

• Present data visually and accessibly. Use charts, tables, or bullet points to summarize key findings. This improves extractability, allowing AI systems to lift and interpret your insights without confusion.
• Expose your methodology. Add a short section like “How We Researched and Tested This” to explain how your data was collected or validated. Transparency builds trust with both readers and models.
• Make authorship and editorial signals visible. Include bylines, expert bios, publication and modification dates, and linked sources. These cues reinforce E-E-A-T principles (Experience, Expertise, Authoritativeness, and Trustworthiness).
• Use structured data to connect your insights. Implement schema markup for entities such as Person, Organization, and Dataset so your research can be semantically understood and linked across the web.

For content teams managing large datasets or topic clusters, tools such as WordLift can automate AI-powered entity linking, helping create interconnected pages optimized for both users and search engines. This approach strengthens your semantic knowledge graph, enhances internal linking, and increases the likelihood that your proprietary findings will appear in generative search results.

In short, showcasing your own data turns your content from commentary into original evidence—the type of material AI systems prioritize when deciding what to trust and surface.

Using Schema Markup to Make Your Content Easier for AI to Read

Schema markup, also known as structured data, acts as a machine-language layer of trust, giving large language models (LLMs) clear signals about what your page contains, who authored it, and how its information should be interpreted. 

When implemented correctly, schema improves how content is parsed, segmented, and reused, directly influencing whether it appears in generative answers or enhanced search results.

Below are the most impactful schema types for AEO/GEO and how to use them effectively:

• Article Schema – Provides context about the author, publication date, and subject matter. Include properties such as author, datePublished, headline, about, and citation. This markup helps AI systems recognize the source, credibility, and topical relevance of your article.
• FAQPage Schema – Ideal for question-and-answer formatting, allowing search engines and AI systems to extract direct, factual responses. Follow best practices for concise, verified answers and see this guide on adding FAQ schema for implementation details.
• HowTo Schema – Designed for procedural or instructional content. Clearly define each step with name, image, and tool attributes to improve readability and extractability. Learn how to apply it in your writing through this tutorial on using How-To schema in blog content.
• Product and Offer Schema – Crucial for e-commerce and review-based pages. This markup clarifies attributes such as product features, price, availability, and rating, making it easier for AI to differentiate similar listings. You can find a detailed walkthrough in my guide to adding Product + Review schema.

An example of the some of the schema markups I use for my articles:

How to Combine Authority Signals and Structured Data for AEO/GEO Success

Getting cited by AI depends on how well your content balances readability for humans, clarity for machines, and credibility through strong authority signals. 

The most effective strategy combines semantic chunking (structuring content into clear, self-contained sections) with data citations, expert attribution, proprietary insights, and schema markup that make your expertise verifiable. 

How to Use Semantic Chunking with Structured Markup for AEO/GEO

AI models analyze content in pieces, not pages. They extract atomic chunks—short, focused sections that express a complete idea. Divide your content into clear units using descriptive headings (<h2>, <h3>), tables, and bullet lists. Each chunk should deliver a standalone thought that can be lifted without losing meaning. 

For a detailed walkthrough on structuring content this way, see my guide on how to structure content for AI extraction.

How to Add Metadata to Help AI Understand Your Content

Once your structure is in place, reinforce its credibility with rich metadata. Include author, organization, and dateModified fields across your templates to establish transparency and freshness. Use Organization and Person schema types to strengthen entity recognition and link expertise to real people. 

For implementation help, check out my beginner’s guide to schema markup.

How to Validate and Improve Schema Markup

After adding schema, take validation a step further. Don’t stop at the Rich Results Test—use the Schema Markup Validator to ensure accuracy and consistency. Define meaningful entity relationships (for example, Person > worksFor > Organization) and avoid adding schema that doesn’t match visible page content. 

Clean, precise markup improves how AI systems interpret your information and boosts your site’s structured SEO integrity.

Key Takeaway

The SEO hierarchy of signals has flipped—authority now outweighs simple keyword alignment. In generative search, content isn’t ranked by how closely it matches a query but by how well it earns trust. To survive AI selection and synthesis, every piece of information must be structured, cited, and credible.

For AEO/GEO, optimization now happens at the chunk level, not just the page level. Each section of content should be:

• Clearly scoped, stating its purpose and relevance upfront.
• High in evidence density, delivering facts and insights quickly.
• Formatted for easy extraction, using tables, lists, or concise paragraphs under descriptive headings.
• Authored or reviewed by experts, showing verifiable credentials.
• Dated and versioned, proving the information is current.

Next in my AEO/GEO series: How to Structure Content for Multi-Turn AI Retrieval

The post Authority Signals and Schema Markup: How to Build Trustworthy Content for AI Citations appeared first on SEO Services Agency in Manila, Philippines.

Ranking on page one doesn’t cut it anymore. AI platforms and LLMs are taking over the spotlight—pushing traditional organic search results further down the page. If you want your brand to still be seen and trusted online, then your content must be structured in a way that both people and LLMs understand. 

But unlike traditional search engine crawlers that depend on markup, metadata, and link structures, LLMs understand content in a completely different way. In SEO, we often focus on structured data (like Schema markups) to help search engines read our pages. While that layer of markup is still useful, structuring content for AI extraction (and AEO in general) goes far beyond adding tags.

The good news? This is something you can control. Understanding how LLMs see and digest content is key to increasing your chances of appearing in AI Overviews, Perplexity summaries, or ChatGPT citations. This guide will show you how to do just that. 

Author’s Note:

This article is the fifth entry in my ongoing AI + SEO (AEO) series. If you want the full picture of how search is evolving, I recommend starting with the earlier parts—they lay the groundwork for understanding how AI is reshaping content and visibility.

Catch up on the series:

• How AI Overviews Impact CTR and SEO – How Google’s AI results are changing clicks and rankings.
• Mapping Content to User Goals – Structure content around intent to drive engagement.
• How Generative AI Is Changing Search Behavior – Why AI is transforming how people find and trust information.
• How Generative AI in Search Works – The mechanics behind how LLMs interpret and rank content.

Read the series in order to understand what’s changing, and how to create content that wins in both human and AI search.

Why AI Extraction Matters

Let’s face it, most users don’t click through as much anymore. They read summaries from Google or AI chatbots, then move on. That means if your content isn’t the one being quoted, you’re invisible.

Here’s why structuring your content for AI matters:

• More Visibility: Even if you’re not ranking #1, you can still get quoted.
• Authority Positioning: AI is presenting you as the “trusted source.” That builds your reputation fast.
• Higher CTR: People are more likely to click when they see you in the summary.
• Trust and Recall: Being mentioned in AI-generated answers makes your brand stick in people’s minds.

Think about it. Two businesses write about the same topic. One writes in big paragraphs without structure. The other uses clear answers, lists, and tables. Which one do you think the AI will choose?

How LLMs Look at Content

Large language models (LLMs) like GPT-4 and Gemini process content very differently from traditional search crawlers. Instead of scanning markup, metadata, and links, they ingest the text, break it into tokens, and analyze the relationships between words, sentences, and ideas using advanced attention mechanisms.

When evaluating content, LLMs consider factors such as:

• Information order: how ideas flow from one point to the next.
• Concept hierarchy: the use of clear headings and subheadings to show structure.
• Formatting signals: elements like bullet points, tables, and bold summaries that highlight key insights.
• Repetition and reinforcement: consistent emphasis on important points that help AI models determine what matters most.

By understanding how LLMs process and prioritize information, you can format your content in ways that make it more discoverable, quotable, and AI-friendly.

How LLMs Create Responses

When a language model builds a response, it doesn’t pull a full page. It pieces together sentences and sections it understands best. To be part of that mix, your content must be easy for AI to read and interpret.

That means writing content that is:

• Organized logically, with each section focused on one idea.
• Consistent in tone and language, so nothing feels disconnected.
• Formatted for quick scanning, using FAQs, step-by-step lists, or definition-style intros.
• Clear and straightforward, prioritizing understanding over clever phrasing.

In short, AI rewards clarity, structure, and intent. The better your content communicates ideas at a glance, the more likely it is to be quoted, shared, and remembered.

The AEO/GEO and Content Engineering Mindset

If you want to get serious about structuring content for AI, then you need to stop thinking like in terms of traditional SEO, and start thinking like a content engineer. This is where AEO, also known as GEO, comes in.

Here are the key principles:

• Semantic Chunking: Break your content into small, focused parts. Each section should answer one idea clearly. Remember, AI doesn’t read your article as one long essay. It retrieves and quotes chunks.
• Clear Sentences: Write in subject–predicate–object format. Example: “An HRIS manages payroll for employees.” This removes ambiguity and makes it easier for machines to parse.
• Entity Context: Use related terms together so AI systems understand the connections. For example, if you’re writing about SEO, mention ranking, backlinks, content, and indexing in the right context.
• Structured Data: Knowing how to add schema markups is a must. But you’ll also benefit by going beyond that. Map your own internal knowledge. Use categories and ontologies to make your content more machine-friendly.
• Unique Insights: Don’t just repeat what’s already out there. Add your own case studies, data, or experiences. AI prefers fresh information that adds value.

This isn’t about gaming the system. Structing content for AI extraction is about clarity, precision, and creating content that works for both people and machines.

Best Practices for Structuring Content

Headings and Hierarchy

Headings are not just for design. They signal to both readers and AI what the section is about.

What to do:

• Use H1, H2, and H3 tags to establish a logical content hierarchy.
• Add keywords and entities naturally in your headers.
• Keep each section focused on a single point.

Example:

• Bad: “Tips and Tricks”
• Good: “Best Practices for AI Optimized Headings”

When AI scans your content, it uses your headers as landmarks. Don’t make them vague. Make them count.

Here’s how I structured this article with H2s and H3s:

Bullet and Numbered Lists

Bullets make information scannable. They also make it easier for AI to extract key points.

What to do:

• Keep bullets short and punchy.
• Start each with a strong word: a verb, a noun, or an entity.
• Use lists for benefits, steps, or comparisons.

Example:

• Define semantic chunks clearly
• Use schema markup in FAQs
• Limit lists to 5 to 7 items

If you want your content to be quoted by AI systems, lists are one of your best tools. Just remember—bullet points only work when readers and search engines understand them. Always include a short introduction that explains what the list is about and why it matters.

Tables

Tables are gold for AI extraction because they show relationships clearly.

What to do:

• Use descriptive headers.
• Keep your data clean and simple.
• Don’t overload tables with fluff.

Example:

The simpler your table, the more likely AI will pick it up.

Here’s an example of one I made in a previous article:

Use Question-Style or Search Query Phrasing in Headings

Headings don’t just help section content, they act like anchors that help LLMs understand how topics relate to one another. I recommend using question-style phrasing for your H2s and H3s for this reason.

When you write H2 and H3 headings in the form of search queries, you’re doing two things at once:

1. Helping AI recognize intent and match your content to specific user questions.
2. Making it easier for people to scan and find the exact information they came for.

Good headings mirror the exact phrases your audience types into search engines. For example:

• “How does an HRIS improve employee management?”
• “What are the benefits of automating payroll with an HRIS?”
• “Best practices for implementing an HRIS system”

Avoid vague headers like “Smarter HR Tools” or “Why It Matters.” They don’t communicate a clear question or intent, which makes it harder for both humans and AI to understand the relevance of your content.

Answer-First Introductions

Never bury the lead. AI is looking for direct answers.

Formula:
Answer first → Explanation → Example

Example:

• Good: “An HRIS is a digital system that manages payroll, employee data, and compliance. It helps HR teams streamline operations and reduce errors.”
• Bad: “In today’s business environment, HR processes are evolving…”

When you start with the answer, you’re not only helping AI. You’re helping readers too.

Demonstration: Before and After

Before (Unstructured):
“Semantic chunking is important in AI SEO. It involves splitting ideas into parts, but some writers don’t use it. This can confuse retrieval systems, and your content may not show up in results.”

After (Optimized):

What Is Semantic Chunking?

Semantic chunking is the practice of breaking content into focused sections so AI can retrieve them more accurately.

• One idea per section
• Uses clear entities like “AI” and “retrieval systems”
• The answer is in the first sentence

The second version wins because it’s clear, concise, and structured.

Advanced Tips for AEO/GEO

Once you master the basics, take it to the next level:

• Build Content Clusters: Group related articles and interlink them. This strengthens your topical authority.
• Create Entity Maps: Show how terms and ideas connect across your site. This helps AI understand context.
• Use Custom Ontologies: If your niche uses specialized terms, define them clearly and consistently.
• Be Consistent Across Channels: If you share a fact on your blog, repeat it on your socials and guest posts. AI looks for corroboration.
• Publish Original Research: Data, surveys, and unique case studies give AI something new to cite.

These are the strategies that separate generic content from AI-optimized content. If you want to appear in AI-generated summaries, then you need to format your content as something worth quoting. Answer questions directly, keep your layout clean, and make sure every section delivers standalone value.

Key Takeaway

AI is reshaping search. If you want to get quoted in AI Overviews or chat engines, you need to make you’re structuring content for AI extraction. That means clear headings, answer-first intros, bullet lists, and tables. It also means breaking down your content into chunks, adding unique insights, and thinking like a content engineer.

Remember this, you’re not just writing for people anymore. You’re writing for people and for AI. The businesses that adapt to this will dominate the future of AEO and SEO.

Next in my AEO/GEO series: Authority Signals for AI Citations

The post Structuring Content for AI Extraction: How to Get Seen, Picked, and Quoted appeared first on SEO Services Agency in Manila, Philippines.

One of the most basic aspects of content writing is crafting the perfect meta tag to go with it. In an earlier post, we discussed that meta tags are one of the most basic elements of SEO and that they have been around for a really long time. A lot of people feel that meta tags are complicated and some might even argue an altogether different language like computer code.

The Significance of Meta Tags

In reality, meta tags are essentially 150 to 160 words that describe what your website is, what it does and for whom. According to Moz.com, “Meta descriptions are HTML attributes that provide concise explanations of the contents of web pages. Meta descriptions are commonly used on search engine result pages (SERPs) to display preview snippets for a given page.”

We discussed in an earlier post that meta tags aren’t as powerful and useful as they once were, however, applications for meta tags are still many and relevant. The gist of what I’m saying is that meta tags might not have much of an impact on search engine optimization anymore but if you craft your meta tag for people then that’s an altogether different ball game.

At the end of the day, one of the best ways your content can help your website is by converting people from passive supporters to active advocates of your cause.  One of the best ways to start converting people is by getting them interested in your content. Meta tags are the starting line in any search related competition. The first very first thing a prospective searcher will find in your website is your meta tag.

The image shows SEO Hacker’s meta tag. It is direct to the point and it tells people exactly what to expect in the website. This is also the very first thing people will see when they look up “SEO Hacker” on their favorite search engine.  Of course, there are many more examples out there which you can see for yourself. Look up any keyword and the most important factor to convince you that this is the article that you want to read is, of course, the meta tag.

Using the Meta Tag

The Meta Tag is widely in use in many applications and websites. Majority, if not all blogs allow its content creators to craft a meta tag for their current post. Meta tags are vital to catching a reader’s attention and popular social media websites such as Facebook understand that.

As you can see in the screenshot provided above, highlighted in red, Facebook appreciates the importance of meta tags as the first real step a person can take before they choose to view your content.

Google constantly monitors the rankings and if no one clicks on a certain link then that link will be bumped down the rankings making them even less visible in search engines. One of the most important things to remember is that creating worthwhile content is important, sure, but getting people to actually read it is a challenge that can be won with meta tags.

Crafting the Perfect Meta Tag

We’ve established that meta tags are important because they are the determining factor for people to either read your content or go for a competitor’s. Creating the perfect meta tag for your post or website isn’t rocket science and anyone can do it with practice and guidance. Here’s are some things to understand in order to start crafting your own meta tag:

1. Limitations – Meta tags are short and concise descriptions about your post and maybe even about your website. While it is tempting to write an impassioned 500 word tell-all about your post, it is best to limit your meta tags to 150 to 160 words. This isn’t entirely because it is better to be short concise, this is because Google will only display the first few hundred words as your meta tag. Any longer and it will simply trail off, leaving an incoherent thought.
2. Stand-out – There are many SEO specialists out there and even seasoned blog writers that have found success in meta tags but not everyone is as fortunate. The best way to get noticed is by standing out. Make your meta tag as unique as possible. Some people tend to stuff keywords in their meta tags but since we’ve established that meta tags don’t help with SEO, then it is a much better practice to write your meta tags for humans.
3. Impact – Contrary to popular belief, it isn’t really considered good practice to write abstract promises on your meta description. The best way to go about things is by using power words. People like confidence and they are more likely to trust your website if it is confident over a website that is unsure of itself.
4. Title – A good supplement for a well written meta tag is the meta title itself. It is an even shorter description of what your post or website is about but it is the very first thing other than the meta tag that people will notice on your website. The impact of titles are so good that some websites now opt for click-bait titles over a more meaningful meta description. The best way to go about this is to create a balance by creating the perfect title to supplement the ideal meta tag.
5. Solve Problems – One of the easiest things to forget about searching stuff up online is the fact that most people do it because they have a problem that needs to be solved. If you offer specific services then let people know about it!
6. Triple Check your Meta Tag – To avoid having a messy or embarrassing looking meta tag then it would be considered good practice for you to triple check what you’re writing. Make sure that your message is coherent and solid.
7. Have fun – Nobody likes boring content. One of the best ways to go about creating the perfect meta tag is by having fun. Let people know that your website is about connecting with them. One of the best ways to attract people to your website is by letting them know that your website is one that inspires happiness or at the very least, customer satisfaction.
8. Be Concise – It is also important to know that the best way to use meta tags is to be concise and straight to the point. Avoid saying too many things and instead, say what you mean to say while maximizing the limits of the meta tags.

There are many ways to write the perfect meta tags and some of them could be done by combining some of the advises that I listed here. Do not be afraid to fail with your first attempts at meta tags. Remember, like anything else worth pursuing in the world, practice makes perfect.

The post Sculpting the Perfect Meta Tag appeared first on SEO Services Agency in Manila, Philippines.

Changes have come and gone over the years and spammers and exploiters who abuse SEO tactics have had their way in stuffing their meta tags with a lot of keywords – even unrelated ones.

Now meta tags have a different use. And it is arguably hardly an effective means to affect your search engine rankings. Aside from the <title> tag, there is not much use for meta tags anymore. So I’ve come up with what little use meta tags still has for your website’s SEO.

This short course has four distinct lessons:

• What are Meta Tags and why are they important?
• What search engine crawlers do with your meta tags
• How Meta Tags should be used for SEO
• What Meta Robots Tag are for

After the course you will have a better uderstanding of:

• What Meta Tags are
• How you can use Meta Tags for SEO
• How search engines values Meta Tags
• What effect Meta Tags have for your website
• What Meta Robots are
• What effects Meta Robots have for your SEO
• How Meta Tags are retrieved from your website
• How Meta Tags affect Search Results Rankings

The post Using Meta Tags for SEO appeared first on SEO Services Agency in Manila, Philippines.

What are robots meta tags for?

Quick Answer: Robots meta tags are pieces of code that instruct search engine robots. These HTML snippets tell them what they can and cannot do on your page. It’s a way of controlling how your pages are crawled and indexed, and how your content is displayed in the SERPs.

Overview

Have you ever wondered what the robots file in your website is for? Maybe you’re using WordPress and you stumble upon this certain, unfamiliar tag that says <meta name =”robots” content=”index”>.

What the heck is it!? Is it a robot that automates your meta tags? Is it a piece of magical SEO tag? Does it summon the Google robot to your page?

Meta robots tag is a tag that tells search engines what to follow and what not to follow. It is a piece of code in the <head> section of your webpage. It’s a simple code that gives you the power to decide about what pages you want to hide from search engine crawlers and what pages you want them to index and look at.

Another function of the meta robots tag is that it tells search engine crawlers what links to follow and what links to stop with.

When you have a lot of links going out of your website you should know that you lose some Google juice. And as a result, your page rank would lower down.

So what you want to do is to keep that juice to yourself with some of the links—and you tell the search engine crawlers not to follow the links going out of your site because in doing so, they will also take some of your Google juice with them.

If you don’t have a meta robots tag though, don’t panic. By default, the search engine crawlers WILL index your site and WILL follow links.

Let me make it clear that search engine crawlers following your links is not bad at all. Losing some of your juice won’t affect your site much in exchange for getting the attention of other websites you’re linking out to.

In fact I don’t recommend using nofollow at all if you don’t have too much outbound links.

Basically the meta robots tag can be cracked down to four main functions for the search engine crawlers:

• FOLLOW – a command for the search engine crawler to follow the links in that webpage
• INDEX – a command for the search engine crawler  to index that webpage
• NOFOLLOW – a command for the search engine crawler NOT to follow the links in that webpage
• NOINDEX – a command for the search engine crawler NOT to index that webpage

Pretty simple isn’t it? Now you’re telling yourself “Heck is that all? I thought it was some crazy program that takes years and years to study.”

Well there are some more commands for the meta robots tag but these four are the MAIN functions. These four are what meta robots tag are mostly used for.

If you ask me, meta robots tag are little things in your site’s SEO that you can use to control your Google juice. I personally don’t use the noindex but I do sometimes use nofollow. Don’t ask why. It’s personal. Haha!

An example of a meta robots tag code would look like this:

<meta name =”robots” content=”index”>

What this tag does is to index the webpage which it is on. It’s like telling someone who’s going to get a glass of water to get a glass of water. Because again, by default, search engine already indexes your site even if you don’t use this code.

And you can also combine the commands if you so desire:

<meta name=”robots” content=”noindex,nofollow”>

For me, this code is a good thing to keep in mind – especially if you’re trying to save up Google juice by applying nofollow to your outbound links. Other than that, it’s not something you’d want to keep on checking when you’re optimizing your on-site SEO.

Tips for Keeps

We all want to know all the little things about SEO. This is something that might help in the future so try to remember it. This code isn’t developed for nothing. The most skilled SEOs know how to use this best.

For further reading, you can go to the article about meta robots in Search Engine Land.

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Meta tags are words in your code which users will not be able to see. It’s effect on SEO has become less and less over the years due to the abuse of webmasters in stuffing keywords inside the meta tags. It used to affect rankings, now it doesn’t. It used to be a factor in the retrieval of the indexed site, now only 2 search engines are left practicing that. But SEO experts, according to Danny Sullivan still do use it for things we might not have been able to think of. So how does SEO experts use Meta tags?

SEO Experts use Meta tags for Misspellings

Since we already know that Yahoo and Ask uses Meta tags to at least retrieve or recall indexed information, you would want to use your meta tags to target people who might misspell your keywords with their search engine query. Putting misspelled keywords in your site’s visible content would be embarrassing and would look quite unprofessional. Here’s your chance to get those misspellers into your website – put the misspelled keywords in your meta tags.

Misspellers are most probably looking for the right thing any way, it’s just that they didn’t do too well in their english spelling subject. Which means that they are still potential conversions for you! You just need to exert a little extra effort in helping them out with their spelling bee score in Google.

SEO Experts use Meta tags for Synonyms

Using synonyms in your site is something that we all do. But we try to minimize using it because we want to focus on our keywords and try to populate our content with it. SEO experts sometimes leave the synonyms in the meta tags in order for them to get traffic from people who aren’t directly using their keywords but are probably looking for the same thing. Although it would still be much better if you use these words inside the body of your content to enable all search engines to read it.

SEO Experts use Meta tags for textless pages

There are still websites which are design and entertainment oriented. These are the kind of sites which packs a lot of flash and pictures and very few to no text at all. In cases like this, meta tags would be helpful. 2 search engines being able to find you is better than no search engine visibility at all. That is exactly why we want content in a website – although that’s another topic altogether.

So there you have it, these three are some of the ways that an SEO expert uses meta tags. It’s not much, but you’d want every little detail to help in SEO.

Tips for keeps: Study any possible misspellings with your site’s keywords and try to experiment with the meta keywords and see what happens. It won’t hurt to go the extra mile to get a little more targeted traffic.

This entry is part of the SEO Hacker School series: Using Meta Tags for SEO

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Next Lesson: What Meta Robots Tag are for

The post How Meta Tags should be used for SEO appeared first on SEO Services Agency in Manila, Philippines.

Meta tags are codes in your website’s <head> portion. They are invisible to the users and are by far, the only legal way to have unseen keywords in your website. Don’t you ever wonder what search engines do with your meta tags since we know that it doesn’t affect page ranking anymore? I know I do. So I read some articles about it and found out from Search Engine Land what exactly your meta tags is being used for by the search engine crawlers.

There are three things that a search engine crawler does with your meta tags:

1. Indexing: When a search engine crawls your page, it replicates a copy of your HTML code and stores it in its database. This is called indexing. All your meta keywords are indexed by Google – it is aware of your meta keywords and has stored it up. Even so, it doesn’t mean it uses it in any way else. It just stores it up.

2. Retrieval: Also termed  by information research professionals as “Recall”, is how a search engine reacts to the people surfing the web and looking for something.  The search engine retrieves what it has indexed about your website and will compare it with the search query of the user. It matches if the documents it has indexed are relevant with the search query the user has initiated. While it does look at the sites it has indexed, it does not necessarily mean that it will go through the indexed document completely – meaning that it will not necessarily go through the meta keywords for retrieval and matching with the search query. I know Google doesn’t, although I’ve read that Yahoo does.

3. Ranking: Now this is where it goes down to business. Ranking is also termed as “Precision” because it is all about putting the best, and most accurate and relevant stuff up top. The ranking algorithm between search engines vary. Some say that for Yahoo, meta keywords still hold water albeit very shallowly so. For Google, I’ve heard that meta tags hold no weight at all in their ranking algorithm. Any way you put it, meta tags can do very little to none with your page rankings.

Now that we have that established, what exact uses does meta tags have in your website? What does SEO experts use meta tags for? I’ll be talking about this in my next entry so watch out for it!

Tips for keeps: Don’t focus too much on your meta tags. Yes it does help, but it helps minimally. You should focus on SEO factors with more weight in relation to your site’s page ranking.

This entry is part of the SEO Hacker School series: Using Meta Tags for SEO

Next Lesson: How Meta Tags should be used for SEO

The post What Search Engine Crawlers do with your Meta Tags appeared first on SEO Services Agency in Manila, Philippines.

Meta tags have been around since… Since I can remember. They have been a big part in search engine history. They were valued as a factor in rankings before – until people started abusing their use in getting on top of the SERPs. After that, Google opted for meta tags out of the ranking factors. But that doesn’t mean they’re not important anymore. Meta tags still play quite a big role in your site’s SEO.

Meta tags are the words that are hidden in your code. People browsing your site will just not be able to see them. It is, as Danny Sullivan puts it, a ‘legal’ way of hiding words in your webpages for search engines. The search engines still read them for it to have a simple, summarized idea of what your site is about and what exactly your keywords are.

Meta tags are located inside your html’s head area. These tags are what you should learn about after being well-versed in HTML tags.

<head>Meta tags are located here</head>

There are three important parts of Meta tags that you can use:

1. Title – The title tag is the title text that is shown in search engine listings. I know that this is not necessarily a meta tag, but it similarly functions like one.

<title>Title text here</title>

2. Description – The meta description tag is where you would want to put your site’s summary. This is where you put what your site is all about and what you are offering people. It should not be too long because the search engines only read up to a certain number of words.

<meta name=”description” content=”This is where you put your site’s summary”/>

3. Keywords – The meta keywords tag is where you put all of the keywords you use on your site. This is basically where you want the words which will take you to the top of the SERPs page to be. Your keywords are important – even if you take away all of the other words, the user should be able to know what your site is all about when they read your keywords.

<meta name=”keywords” content=”SEO, Hacker, Google, Search, etc”/>

These three things make up your meta tags.

The importance of meta tags is that the search engines read them in order to compare if these keywords and the description are related to the visible content. Are your keywords present in your webpage? Is your meta description related to your content and your site’s niche? There is a certain weight in your meta tags that the search engines see, that being the reason, wouldn’t you want to do everything in order to bring your page a little bit higher in the SERPs? That’s exactly the reason why meta tags are important.

Tips for Keeps: Even if meta tags do not hold much water when it comes to page ranking, their importance is still present as the search engine robots validate their relativity to your content and site niche.

This entry is part of the SEO Hacker School series: Using Meta Tags for SEO

If you want this tutorial to be sent straight to your email inbox, please subscribe in the text area below

Next Lesson: What Search Engine Crawlers do with your Meta Tags

The post What are Meta Tags and why are they important? appeared first on SEO Services Agency in Manila, Philippines.