Every day, here at WordLift, we spend a great amount of time talking with experts in the digital marketing world and experimenting new ways to stand out on Google and Bing by getting better at organizing knowledge.

To help websites improve their SEO WordLift creates a knowledge graph; this is really a large database that describes the “things” that the website talks about.

Google itself uses a knowledge graph to provide all sort of relevant facts about a topic using its knowledge graph panels. Have a look below at the knowledge graph panel of TheNextWeb and all the information it provides to online users. 

Why creating your own knowledge graph improves SEO?

Imagine the knowledge graph behind your website as the scaffolding that lets crawlers and bots access to your content in a smarter and more efficient way. Much like Google uses the graph, as the engine to power up its search results, a graph that describes the content of a website helps machine understands what this content is really about.

Whether is a featured snippet showing on the SERP of Google or an app providing an answer using the voice like Cortana, Alexa or the Google Assistant, in the back, everything depends on the data that connects articles and facts in a machine-friendly form.

This is why having your own knowledge graph helps you make your content easier to be found and more accessible. Let’s dive into the practice and let’s try to ask the Google Assistant something like “what is Semantic SEO“. You will get as answer a snippet of content taken from this same blog.

What is Semantic SEO - Google Assistant

What is Semantic SEO on the Google Assistant

The more metadata we make available to semantic search engines like the one used by Google Assistant and the easier it gets for these machines to understand the relevancy of our content in relation to a specific intent. Let me give you another example of content findability in the new world of personal assistant search optimization where a knowledge graph comes into play.

Here below the query to trigger is “tell me something about WordLift“. In this specific example, the Google Assistant proposes to the user the invocation of a Google Action called Sir Jason Link that can match this request.

The Google Action – Sir Jason Link – has been created using the graph data behind this website much like in the previous example.

The Google Assistant has analyzed the content of the Google Action (imagine a Google Action much like an app for the Google Assistant or the equivalent of a skill for Amazon Alexa) and probably has seen that the content matches the content on this website. The assistant is therefore suggesting to users, that might not know Sir Jason Link, to invoke it when asking for our product.

You can find out more on how to optimise your content for Google Actions on WooRank’s blog.

There is more SEO value than featured snippets, voice search and personal assistant search optimization in creating a linked graph with the metadata of a website.

In today’s digital world, publisher and readers are overwhelmed with information and it gets increasingly complicated to discover the content we really want. Semantic Technologies, like WordLift, do the magic and help publishers create better content while guiding readers in finding the content they want.

In SEO terms, articles enriched with semantic information, improve their findability by making information extraction more efficient. Concepts mentioned in an article are annotated and linked with extensive knowledge bases (such as DBpedia, Wikidata, Geonames and the Google Knowledge Graph) to provide search engines with key indications on why a specific piece of content can be relevant for a given search intent.

More importantly – all the information is structured in a graph – this means that a search engine can process, all it has to know about an article, much like we do when looking at the nutrition facts label on a pack of spaghetti. All the relevant information is condensed in a label that is easy to read and organized in a standard way.   

OK, so how is WordLift’s Graph getting smarter?

Just like kids, when starting to learn a language start with the names of the things they see around them, the vocabulary that editors could create with WordLift was primarily made of concepts and names.

Just like other major knowledge bases like DBpedia and Wikidata, WordLift‘s Knowledge Graph has been built around concepts (or entities) and the relationships between these concepts.

As we progress, and the use-cases we deal with become more mature, WordLift‘ graph is getting smarter to support new business cases and to help us improve the findability of online content.

Our main goal with WordLift Snowball was really to improve the linked data graph in order to:

  1. Be able to compute and analyze the relationship between entities and articles being annotated. Here, as a side effect, we will have a lot more links from the graph to the articles and this will facilitate the indexation of articles,
  2. Improve how smart agents (or crawlers) access information about entities using the semantic technology language of RDF and SPARQL this basically means, for instance, that we can handle queries to event-related questions like:
  • What are the next events in Paolo Alto?
  • What are the upcoming talks with Gennaro Cuofano?
  • How much does it cost to attend the Meetup on AI & ML for WordPress?

Check out below a sample dialogue that Sir Jason Link (WordLift’s powered Google Action) can support thanks to this new update.

Sir Jason Link answering on events

Asking Sir Jason Link about Gennaro’s upcoming event.

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As we have seen with a smarter knowledge graph publishers can create SEO-friendly content and open up their website to new and engaging ways to connect with their audiences and grow their traffic.

Find below one more example of a query that users can trigger using the query language SPARQL to find out events happening in a specific location.

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