We are talking about the importance of Topical Hubs because of the Hummingbirds algorithm, that lately has really changed the way Google works, simplifying the way we find results on the SERP.
Not so long ago, working on long-tail keywords was the new SEO trick and a true goldmine, but since the advent of Hummingbird, this is not working anymore.
Now, in order to optimize our website for semantic SEO and conversational queries, we have to think in entities, understanding the connection between the entities, and we have to be really sure about the context we are creating.
This new mindset will guide our keyword research.
Start your research focusing on entities and not on keywords;
The categories on our website are our topical hubs;
Create your content for the audience you’re serving.
Start focusing on entities
First of all, we need to focus on the concept related to the concept we want to explore. Let’s say we’re going to talk about books because we are a bookshop. What kind of books do we deal with? We can explore the history behind each book, their context, everything about the author and about book fairs all around the world.
We can focus on many different facts related to the concept of book.
Also, if we own a bookshop, this means we have a local site. We should also start thinking about entity searches related to our neighborhood. Once we have all these entities, we could start thinking about the ontology we want to use that we can extract from these entities, then deciding how to group them and create our categories for the website.
Our categories on the website are Topical Hubs, basically
On any given website, we usually have the homepage, then the category and product pages. How can we make our category pages rank? Let’s consider them as topical hubs.
Think of your site as if it was a composition of contextually connected microsites. So each category page could be considered as a new site.
So now we can start optimizing our page, our content hub, with the keywords Google itself is extracting from the best SERPs of entities. We are creating a well-optimized page not only in terms of keywords but also in relation to entities.
When we talk about topical hubs, we talk about the context, and the context is not just related to old classic SEO. Focusing on the context means giving value to the category page.
Create content for the audience you’re serving
The third step would be to do a good audience analysis, in order to understand that in our area we might have a certain demographic, so we can organize the content on the hub page focusing on that demographic. We can add some sort of values for our audience so that all our content could add some contextual and semantic value for Google too.
Now we can start focusing on the content we can create, in order for it to be contextually relevant both for our entity search and for our audience.
So, back to our bookshop, we can start adding a category for Recipes, extracting recipes from famous and not-so-famous books and tag them with schema.org/Recipe markup. We can record videos and mark them with schema.org/VideoObject. We can start writing guides, or submitting Q&A.
We could especially start to leverage events about the location we’re in, which is the neighborhood our bookshop is set.
By doing all these things we are creating something truly relevant about in a semantic way because we are really targeting our site to all of the entities related to our micro-topic. Having optimized it both on a keyword level and on a semantic search level we have created content which is relevant and responding both to our audience and Google.
Structured data is data created using a predefined (fixed) schema and is typically organized in a tabular format. Think of a table where each cell contains a discrete value. The schema represents the blueprint of how the data is organized, the heading row of the table used to describe the value and the format of each column. The schema also imposes the constraints required to make the data consistent and computable.
A relational database is an example of structured data: tables are linked using unique IDs and a query language like SQL is used to interact with the data.
Structured data is the best way for computers to interact with information. As opposed to semi-structured and unstructured data.
Semi-structured data is characterized by the lack of rigid, formal structure. Typically, it contains tags or other types of markup to separate textual content from semantic elements. Semi-structured data is “self-describing” (tags are a good example, the schema is part of the data and the data evolves with the content but lacks consistency)
Unstructured data can be found in different forms: from web pages to emails, from blogs to social media posts etc. 80% of the data we have is known to be unstructured. Regardless of the format used for storing the data, we are talking, in most cases, about textual documents made of sequences of words.
Structured data on the web
Structured data is a standardized format for providing information about a page and classifying that content on the page; for example, on a recipe page, what are the ingredients, the cooking time, the temperature, the calories, and so on.
Imagine a book supported in three different formats: ebook, paperback, and hardcover. Each has different weights, sizes and so on. So does Schema.org.
The Semantic Web movement, the creation of the Schema.org vocabulary and the importance that these technologies have on semantic search engines like Google, Bing, and Yandex have resulted in publishing online structured data on a previously unprecedented scale.
A knowledge graph acquires and integrates information into an ontology and applies a reasoner to derive new knowledge.
(Lisa Ehrlinger and Wolfram Wöß – University of Linz in Austria)
The term knowledge graph has been frequently used in research and business, in close association with Semantic Web technologies, linked data, web-scale data analytics, and cloud computing. At SEMANTiCS, a few years ago, a research paper titled “Towards a Definition of Knowledge Graphs” by the Institute for Application Oriented Knowledge Processing of the University of Linz was presented to propose a definition of the knowledge graph that focuses on data modeling and reasoning.
“Towards a definition of a Knowledge Graph”
The popularity of the term is strictly connected with the launch of Google’s Knowledge Graph in 2012, and by introduction of other large databases by major tech companies, such as Yahoo, Microsoft, AirBnB and Facebook, that have created their own “knowledge graphs” to power semantic searches and enable smarter processing of data.
In the context of Semantic Web, a knowledge graph is a way of representing knowledge. In short, you start from a few triples and those triples are put in relationship to build a graph. For instance, let’s have a closer look – using Semantic Web technologies – at the Apology of Socrates entity on this blog:
As you can see we have a set of triples that tell us a story: The Apology of Socrates, also known as Apology of Socrates is about Socrates, has been written by Plato and mentions the concepts of Daemon and Socratic Dialogue.
A knowledge graph doesn’t speak any particular language. Language is human; a knowledge graph gets expressed in open linked data, which is the language of machines.
Imagine your entire website built upon a large knowledge graph made of all the metadata that describes the thing that you write about. That knowledge graph becomes part of a larger graph that comprises the new web. That is the power of Semantic Web.
In this blog-post we will discuss how the semantic web has changed our experience on the internet, both as users and editors, and why building a vocabulary of concepts for your website can be essential for your business and very easy to do, with one single WordPress plug-in: WordLift.
Semantic What? What’s In It For Me
The semantic web can be defined as a web of data. It originates from the transformation of the Web into an environment in which published documents carry a “hidden side”, an inner layer of data commonly known as metadata: It was 2009 when the inventor of the web, Tim-Berners Lee asked everyone to introduce the semantic information needed to help machine understand information being published.
The context around each set of metadata is what reveals to search engines the intent of the users. The same word can mean different things to different people or at different times: for example, typing french fries at 8am on a laptop can load different results than if searched at 8 pm from a smartphone. The context gives the hint of a clear intent: in the morning you might just be curious about the word itself, why it is called french etc. whereas in the evening you might want to look for the place that serves the best french fries in your town or order them online. The metadata structure behind both pages allows search engines to match the contextualized users’ intent with the most useful results.
The semantic web significantly increased the possibilities offered by the online world, making it easier for software to organize and classify content. Search engines are a perfect example as they leverage metadata to provide results from the most relevant onwards: relevance is now chosen according to the metadata that each page embodies, so you must structure your page correctly if you want to rank on Google, with the right information and the perfect connection to other pages’ themes.
In 2001 Tim-Berners Lee expected the web to become semantic soon; 15 years later we are testifying the change that semantic web is imposing and enjoying the benefits. The content of your website must follow this new concept of an organized web as well; properly organized content provides a better navigation experience, higher search engine rankings and readers’ engagement. But how to do it and how can it be useful to a website’s target audience?
Here is where WordLift comes at hand. WordLift is a plug-in for WordPress that helps you create, organize and beautify the content of your websites, blogs and any digital editorial products. The plug-in takes you by the hand during the whole process of creating, writing and publishing your content, and the metadata attached to it.
While you are writing, WordLift analyses the terms used and identifies the most meaningful ones based on the context of the post; these key-words are suggested in the form of entities, concepts you should focus on that are crucial for your target audience. For each entity you select, a specific page with text and images is created, so that readers can deepen the matter; the plug-in draws this material from the universal encyclopedia that is the web, more precisely from the wealth of open data available, and structures it in the form of web pages enriched with Schema.org markups, the classification system used by Google and all other search engines in the world. WordLift adds the schema.org markup to the page to make it SEO-friendly and readable by computers.
The sum of all the entity pages you create, forms the vocabulary of your website, already linked to open data vocabularies in the web.
The aim of the vocabulary is to organize content for a referring audience which is composed of personas; to connect each content to the other depending on the context; to optimize it for search engines in order to rank to interested readers, or more precisely, to the target audience of the page.
How to Create a Vocabulary
A good vocabulary should contain 70-80 entities to start with, but where to extract it from? Which entities or keywords should be part of the vocabulary?
Think about your audience first – performing a good old basic keyword research can help you understand your readers; analyzing patterns and identifying the intents of searches on Google, can help you identify not only your targets, but the 10 or 100 or 1000 readers a month you need to make a difference in your business (find out more on this subject in this article from our consultancy blog and the work we did in the travel industry for the Salzburg State Board of Tourism.) Once the right audience is targeted, it is easy to build a set of recurring concepts that should eventually become entities in your vocabulary.
The devil is in the details – Look closely at your business model and at what really makes a difference. A real estate agent working in a fancy neighborhood must know not only the properties’ value or the crime rate in the area but also the mood of the little café down the street or the teachers’ skills in the local high school – these details help potential clients understanding your offer; turning these details into entity pages create context and context builds trust.
The vocabulary is your content hub – Think of each entity as a hub around which should revolve a set of content on your site – if you have enough material on a specific concept or if you plan to add this content to your editorial plan – then start with an entity that describes it. These pages can become search magnets and in some cases they can also be designed as clear answers to specific questions and enter the realm of Rank #0.
You are what you share – Entities are a great mean to explain a complex topic to your audience – when doing so you are also creating great content to promote your business on social networks.
Moreover when creating a vocabulary remember that:
We are all in the relationship business – Each entity should be connected to blog-posts and to other entities in the same knowledge domain – we always recommend our users to link each entity at least to another one. These relationships amongst entities translate into specific links in your graph and can be used to discover more content on your website. When linking data, be careful and follow a strategy, with the most value for your users in mind.
The real value is the “hidden side” – Curating the metadata box behind each entity is good for humans as well as machines –
Example: the entity of Rudolph Schindler (an Austrian modernist architect) should be linked to Frank Lloyd Wright’s, who in 1918 asked him to work on a project in L.A. together; this can be done by filling up the schema-org:knows property in the metadata box of Schindler’s entity page, providing new ways to discover content you might have on both Schindler and Frank Lloyd Wright.
Be the Wikipedia of your niche – Always curate your entities and customize their content to fit your offers and your targets. If you decide to create an entity just to add the schema.org markup to your page, you should add a no-index on the entity page to avoid any SEO issue with content duplication.
Keep it super simple – Use your properly structured vocabulary to affect the architecture of your website, to make sure that your reader have quick access to the information they need. Entities can be grouped in your navigation by types (i.e. all schema-org:places) or using custom WordPress taxonomies to fit your needs.
Why Should You Care?
Organizing and enriching content is becoming more and more of a necessity in what has been called the birth of Web 3.0. Users are no longer searching for queries on the web but finding answers. At this point only the linked will survive! Connect your website to the rest of the web, within itself and with your target audience. It is very easy to do it, and you only need one single plug-in: WordLift.
What if I already have pillar articles that could become entities?
Yes, you can now convert your existing articles or pages into entities with a simple click. This helps you reuse your pillar content to reorganize your website and improve the search rankings of these pages.