Hi, I’m Emmanuel Dan
a PPC & SEO Specialist Product Marketer Growth PM

SEO Content Writing: How to optimize for Entity Salience

Entity salience offers a peek into the way Google’s AI appraises content in order to create an objective score for web pages.

Whenever we type in a search, as humans we can easily decide which piece of content is best suited to our needs. On the other hand, Google has to process 2.4 million searches per minute, while matching them to content across a web whose size is tending towards infinity i.e. The web contains trillions of pages, while Google’s index contains only about 50 billion of these pages. So at the speed of thought, Google has to decide which site offers the best content for multiple queries (15% of these searches are unique)

How on earth does Google manage to do this? How can Google manage to consistently serve good results faster than most websites or mobile apps can load content?

We would never really know, however Google gave us a glimpse through the entity salience scores offered in their NLP demo. In this article I will attempt to guide SEO content writers on entity salience as a concept and how to optimize articles against this metric.

What is an entity?

An entity is the noun or set of nouns contained in a text. Anything that has a name in your blog or article is therefore an entity. They are nouns and noun phrases that the AI can identify as a distinct object. Google’s entity categories include people, locations, organizations, numbers, consumer goods and more

What is Entity Salience

The noun “salience” derives from the Latin word saliens – ‘leaping, or bounding’. In modern usage it means “Prominent”, “stand out”.

Entity salience therefore refers to the degree of prominence that’s ascribed to a named object within a piece of text.

The salience score for an entity provides information about the importance or centrality of that entity to the entire document. Below is an example

Scores closer to 0 are less salient, while scores closer to 1.0 are highly salient.

How Content Writers Can Optimize for Entity Salience

Since salience scores are more important than simplistic keyword stuffing, every writer needs to know how these scores are calculated in order to produce content that can rank

How The Salience Score Is Calculated

Based on Google research papers, there are certain textual attributes that determine the scores assigned to each named object within a sentence. The factors are;

1. The entity’s position in the text
2. The entity’s grammatical role
3. The entity’s linguistic links to other parts of the sentence
4. The clarity of the entity
5. Named, nominal and pronominal reference counts of the entity

1. The entity’s position in the text

One of the most basic elements of salience is text position. In general, beginnings are the most prominent positions in a text. Therefore, entities placed closer to the beginning of the text and, to a lesser extent, each paragraph and sentence, are seen as more salient. The end of a sentence is also slightly more prominent than the middle.

Advice To Writers: Position the target keyword towards the start of the text, paragraphs and sentences.

2. The entity’s grammatical role

The grammatical role of the entity is usually contingent on its subject or object relationship with the rest of the text.

The subject (the entity that is doing something) of a sentence is more prominent than the object (the entity to which something is being done).

• Messi Scored the winning goal

• The winning goal was scored by Messi

In the first sentence, “Messi” has a score of 0.7, whereas “goal” has a score of 0.3. In the second sentence, “goal” is more salient, with 0.69, whereas “Messi” has a score of 0.31.

Advice to writers: Reword your write ups  to ensure that the target keyword is the subject of the sentence wherever possible.

3. The entity’s linguistic links to other parts of the sentence

If you use the Syntax tab in Google’s API demo, you’ll actually see a sentence-by-sentence breakdown of which words link to each other, along with a grammatical label.

I plugged this sample sentence in – “France held Argentina to penalties but could not have done it without Mbappe’s hattrick”

We can see how the entity “France” links to so many parts of the sentence through the verb “Held”.

An Entity does not need to be repeated artificially in every clause for it to be seen as prominent. It is more important that the other clauses and entities in the sentence depend on the target keyword for their meaning. This is how the linguistic dependency factors into the entity salience score

Advice for writers: When using target keywords in longer sentences, structure the sentence so that its clauses and other entities depend on your target keyword for sense.

4. The Entity’s Clarity

Google’s NLP tool is good at recognising entities but it’s not perfect. For example, it’s not great at recognising two entities as the same when their capitalisation, pluralisation or acronym changes.

Writers should also be wary of how switching between acronyms and full phrases (“SEO” vs “search engine optimization”) can impact salience scores

Advice To Writers: Refer to your target keyword consistently throughout the text if it is a multi-word phrase.

5. The Named, Nominal And Pronominal Reference Counts Of The Entity

The frequency with which an entity is mentioned in your text is a straightforward but crucial aspect of salience scoring. However, resist the urge to veer into archaic, spammy writing techniques. Increased mentions of your focus entities shouldn’t ever be used as a cover for keyword stuffing.

Note: Google has the ability to recognise different references to the same thing e.g.

• Mo Salah – named
• Striker – nominal
• He – pronominal

Advice To Writers: Increase mentions of your focus entities by using a mixture of named, nominal and pronominal references, don’t just repeat the named phrase every time it comes up.

Limitations of Google’s NLP Demo Tool

The natural language processing API demo is best used for product pages, short service, category pages, meta descriptions and ad copy. However, for long form content, its usefulness diminishes the longer the text you input. There is no way for it to process all the signals given across multiple sections of text.

Hence for longer pages, you may want to analyze single sections bit by bit rather than at once.

Conclusion

Google’s natural language API demo gives content writers a tool to help them craft their writing in a more structured way. If you are a writer and are looking to improve your SEO skillset, then you should integrate entity salience analytics into your practice.

How To Use Google BERT Scores In SEO Content Writing

• The Query = How SEO Content Writers Can optimize BERT Scores?
• Top Ranked Page = https://www.webfx.com/blog/internet/google-bert/
• BERT Score of the top page = 0.9767347251 (98%)

As you can see, all the top ranking pages in this sheet have a BERT score that’s above the 80th percentile for the query

Note: the BERT score of a page shows the mathematically derived match between the context and intent of the page in relation to the search query

I believe that BERT score optimization, combined with Higher Entity Salience Scores, can help SEO content writers to achieve first page ranking for their articles

Python Script For Calculating Google BERT Scores

Here is a python script you can use to scrape the web and compare how competitor sites score against yours for various queries.

Here are the steps for running the script

(1) Install the Dependencies in Google Colab

(2) Choose Your Query or Keyword against which the top Websites will be scored

(3) Scrape Google to extract web pages, their ranking position, and the search date

The above is a clear guide on how to calculate BERT scores by yourself. But what are BERT scores, what’s their significance and if you know how an article measures against this metric, how can you improve the scores

Introduction

As search engines become more sophisticated in understanding natural language, traditional metrics for evaluating content are evolving. One such metric that has gained prominence is the BERT Score.

BERT (Bidirectional Encoder Representations from Transformers) Score measures the relevance and quality of content based on contextual understanding.

In this blog post, we will provide a step-by-step guide on how to calculate BERT Scores and leverage this metric to improve your content’s performance.

Understanding BERT Score

BERT Score evaluates how well your content matches the context and intent of search queries. Unlike traditional metrics that focus on keyword density or backlinks, BERT Score emphasizes natural language processing and semantic relevance. It takes into account the fine-grained nuances of user queries, enabling search engines to provide more accurate and relevant search results.

Here’s how BERT takes a look at the context of the sentence or search query as a whole:

• BERT takes a query
• Breaks it down word-by-word
• Looks at all the possible relationships between the words
• Builds a bidirectional map outlining the relationship between words in both directions
• Analyzes the contextual meanings behind the words when they are paired with each other.

How Google Utilizes BERT scores

(a) Enhancing Search Relevance: One of the primary ways Google utilizes BERT Scores is by improving search relevance. BERT allows Google to better comprehend the nuances and context of search queries, enabling it to deliver more accurate search results. By considering the BERT Score, Google can identify content that aligns closely with the user’s intent, resulting in a more satisfying search experience.

(b) Understanding User Intent: BERT Scores help Google understand user intent more effectively. With the ability to interpret complex search queries, Google can decipher the true meaning behind the words used by users. This allows the search engine to provide more precise answers and relevant content, even when the user’s query is not phrased explicitly.

(c) Contextual Understanding: BERT Scores take into account the context in which words are used. Google’s algorithm analyzes the surrounding words and phrases to grasp the meaning and context of the query. This contextual understanding enables Google to present search results that match the user’s intent, even when keywords alone may not capture the full meaning.

(d) Semantic Relevance: Semantic relevance is another crucial aspect that BERT Scores consider. Instead of relying solely on individual keywords, BERT focuses on the overall meaning and semantics of the content. By understanding the relationships between words, BERT helps Google identify content that provides the most accurate and valuable information to users.

(e) Natural Language Processing: BERT Scores leverage the power of natural language processing (NLP) to enhance search results. With NLP, Google can interpret and process human language more effectively, taking into account factors such as sentence structure, grammar, and context. This enables Google to deliver search results that better match the natural language used by users.

Impact of BERT Scores on Search Rankings

BERT Scores play a significant role in determining search rankings. Websites that optimize their content to align with BERT’s contextual understanding and semantic relevance have a higher chance of ranking well in search results. By creating content that aligns with the user’s intent and addresses their queries comprehensively, website owners can improve their BERT Scores and increase their visibility on search engine results pages.

How To Optimize BERT Scores

(1) Optimize for Featured Snippets: Featured snippets are highly visible and can significantly boost organic traffic. Content writers should aim to provide concise and direct answers to commonly asked questions related to their target keywords. Structuring content in a way that makes it easy for search engines to extract relevant information increases the chances of obtaining a featured snippet.

Featured Snippet Rules For Content Teams

• Rule 1: Use a “What is [Keyword]”Heading
• Rule 2: The First sentence under the heading should use an Ïs” statement
• Rule 3: Always start the first sentence with the core keyword
• Rule 4; The 1st sentence should provide a definition and the second should explain the most important information about the keyword
• Rule 5: Never Use Brand names in portions of text that will be pulled into a featured snippet e.g. Listicles, Tables etc
• Rule 6: Eliminate all first person language in the featured snippet text
• Rule 7: Be as concise as possible
• Rule 8: Refine. If we don’t capture it, then observe the existing snippet and product a content structure that is of superior concise and explicative quality

(2) Enhance Your Content Structure: Organizing your content with clear headings and subheadings helps search engines understand the structure and hierarchy of information. Proper use of H1, H2, and H3 tags signals the importance of specific sections. Aim for a logical flow and readability, incorporating keywords naturally throughout the content.

(3) Focus On Contextual Relevance: Understanding the user’s intent behind search queries is crucial for creating relevant content. Tailor your content to match user expectations, addressing specific pain points and providing valuable solutions. Analyzing search engine result pages (SERPs) can provide insights into the context surrounding the topic.

(4) Optimal Content Length: Long-form content tends to perform better in terms of BERT Score. Aim for comprehensive and in-depth content that covers the topic thoroughly. Strive to strike a balance between quality and quantity, ensuring that each word adds value. Don’t hesitate to update and refresh existing content to maintain relevance.

(5) Prioritize Language and Style: Simplicity and clarity should be the guiding principles of your content. Use plain language and avoid excessive jargon that might confuse readers and search engines alike. Craft clear and concise sentences in active voice, incorporating LSI (Latent Semantic Indexing) keywords to demonstrate a deeper understanding of the topic.

(6) Readability and User Experience: Enhancing the readability and user experience of your content is vital for optimizing BERT Score. Break up the text with bullet points, lists, and subheadings for easy scanning. Keep paragraphs concise and consider incorporating multimedia elements like images and videos where relevant. Ensure your content is mobile-friendly and responsive.

(7) User Engagement Signals: User engagement signals, such as dwell time and click-through rates (CTR), are closely related to BERT Score. Encourage user interaction by enabling comments and social sharing. Craft engaging headlines and meta descriptions that entice users to click through. Engage your audience with high-quality content that encourages them to spend more time on your page.

(9) Monitoring and Optimization: Regularly monitor your content’s BERT Score using SEO tools to track its performance. Continuously review and update your content to keep it fresh and relevant. Pay attention to user feedback and adjust your content accordingly. Stay informed about search engine algorithm changes that may impact your content’s visibility.

Conclusion

Calculating BERT Scores allows you to measure the relevance and quality of your content in alignment with user queries and intent. By leveraging the power of BERT models and following the steps outlined in this guide, you can gain valuable insights into how well your content matches user expectations. Remember to keep refining and optimizing your content based on the BERT Scores to enhance its visibility and drive organic traffic to your website.

In the ever-evolving landscape of SEO and content optimization, understanding and utilizing metrics like BERT Score is crucial to staying ahead of the competition and delivering valuable content to your audience.

How to Avoid Being a Victim of Domain Squatting & Homograph Attacks

If you had a site that was doing well but suddenly, things just went downhill, it could be worth exploring to see if you have been a victim of a negative SEO attack. Negative SEO attacks are in many forms and each type has a different degree of impact on a website. Of all the negative SEO attacks I’ve experienced, one of the most devastating is a Domain squatting attack. These types of attacks exist in various forms which are:

1. Typo squatting attacks and
2. Homograph attacks

What is domain squatting

This is a family of negative SEO techniques which are deployed in order to harvest web credentials, steal direct traffic, harm an organization’s reputation, achieve affiliate marketing monetization, install adware, transmit malware or to achieve other malicious objectives. 

How these attacks are initiated

These groups of attacks are initiated by registering a variation of a legitimate domain and building a mirror website of that domain. This enables the attacker to deceive people into mistaking the fake domain as the legitimate URL of the website they were trying to visit (which could be a bank, a fintech solutions provider, or an online store)

When this happens, visitors will interact with the fake domain by clicking through or trying to login. This is what enables the attackers to achieve whatever objective they had in mind. The techniques vary which will be discussed individually under their respective classes which are:

a. Typo squatting attacks: An attacker registers a domain similar to the target domain in spelling. They do this based on the likely keyboard typos that can occur whenever the target domain is being typed into a search bar. They also pick variations of the target domain based on TLD’s (replacing abc.com with abc.ng) with the goal of stealing traffic that people accidentally direct to the target domain. For example, the attacker could replace ab.cd.com with abcd.com or biz.com with biiz.com. 

b. IDN homograph attacks: The International Domain Name protocol allows for the display of Tamil, Arabic, Chinese, Amharic, etc. characters in domain names. Some characters, like the Greek “p” (meaning Rho in their language) appear identical to the English “p”, and can resolve to entirely different servers. 

This is what attackers exploit when initiating a homograph attack. For example, websites like “picnic.com” could be registered such that the p in picnic is actually not an English but a Greek or German letter. This will allow two domains called “picnic.com” to be registered for two different but identical sites (one fake and one legitimate) on two different servers. 

How to protect your website

Any domain can be squatted and this is what makes these types of attacks very common and effective. To protect your website, you might consider the proactive registering of similar variations of your domain name. This is usually an expensive option but if you can snatch of the most similar versions of your site, you can reduce the likelihood of a successful domain squatting attack ever being initiated against you. You can also consider other mitigative measures such as:

1. Trademarking your assets
2. Informing your staff, site visitors and other relevant stakeholders
3. By monitoring domain registrations using tools like swimlane or CipherBox
4. Use the Anti-cybersquatting Consumer Protection Act or ICANN’s Uniform Domain-Name Dispute-Resolution Policy (UDRP) to take hold of the domains or have them taken down.