Have you ever had a song stuck in your head but you can’t remember the name of the song? Or remember that day when you just couldn’t recall the name of a certain character from your favorite movie? These are the times we quickly whip out our phones and google it all.
See how Google interpreted your intent and got you the exact results you were looking for? This is a classic Semantic Search example. Without providing Google with more details on your search query, it still manages to give you the correct answers. This is how semantic search works.
In this blog post, you will learn:
- What is semantic search?
- Why Google implemented Semantic Search?
- Semantic Search Technology
- Semantic Mapping
- Semantic Coding
- Semantic Search Algorithms
- How to use Semantic Search to boost your SEO
What is semantic search?
First, let’s understand what the word ‘semantic’ actually means.
‘Semantic’ is an adjective that carries the concepts, contexts, or ideas of words or phrases. A connotation of sorts. For example, the semantics of the word “home” can be “a place of warmth and comfort”.
Using this semantic relation of words and its concepts, it’s easier for the search engine to understand natural language and it can then use said semantic relation to returning relevant pages to a user’s ambiguous search query.
Remember that search engines are run by algorithms. They don’t understand human conversational language unless the algorithms have been educated about it.
To make machines understand and interpret words and phrases just like humans is an enormous challenge, but Google has consistently made major improvements towards providing this technology which falls under Artificial intelligence and machine learning.
Along with understanding keywords, their context, and intent, semantic search also is able to distinguish between entities (person, place, and thing, etc).
Not only that, but the semantic search takes into account the user’s local and global search history, location, and spelling variations in order to deliver more personalized results.
For example, an Animal Photographer that almost always looks up animal pictures, searches “Jaguar”, most certainly, the results that appear will be about the animal and not the marvelous Land Rover vehicle.
|Semantic Search is a system used by search engines to enhance search accuracy by interpreting the user’s search intent and the contextual meaning of the search terms to return relevant results.|
Why Google implemented Semantic Search?
Semantic search engines have very complex functioning with numerous variables at play. It includes having an organized, connected data structure leading to a deeper understanding of the user’s intent which in turn results in better user experience.
Back in 2010, SEO was mostly centric towards ‘Keywords’. A lot of websites stuffed keywords in their content, there was spamming, and really low-quality content would show up in the web pages. Most of the time the keywords people type in the search bar are mostly unclear and vague. Many of these search terms can have multiple meanings. Because of the lack of context, the search engines were struggling to return relevant pages.
We all are aware of Google’s consistent need to satisfy its users. Search queries are ambiguous and it’s the search engine’s job to make sense of the query. To do this, the search engines need proper management of the big data they hold and make the Semantic connections to the search terms. Thus arose the need for semantic search.
The first step was taken by Google back in 2012, commencing with Knowledge Graph that made the semantic search possible and Google became the first Semantic Search engine.
Let me, briefly, break it down further how this technology works.
Semantic Search Technology
Semantic search holds two main concepts:
- Semantic Mapping
- Semantic Coding
This process associates properties with their respective entities. Entities being People, Places or Things. The relationship between these properties and entities need to be organized and connected to each other in an organized manner for search engines to understand a search query and it’s intent.
These images are taken from Google’s Ramanathan Guha’s paper on ‘Semantic Search’, creator of the Schema Project. These images show the process of mapping of information to an entity. In this case, the entity is Eric Miller, one of the co-authors of the paper.
For a more recent example of semantic search augmentation, let’s take a look at the boxed section or “Knowledge Graph”. The generic information provided about Lamborghini is a result of the mapping process.
Semantic coding is a process of encoding the meaning of something (a word, phrase, picture, event, etc). For example, in HTML (a markup language used to convey information) code such as “<em>” stands for emphasis, and “<cite>” stands for citation, these are also known as semantic tags.
Google can identify and use importation information from a page with help of semantic markup. Search engines understand the purpose and content of a website better when they use semantic markup (Schema.org) which will assist Google in providing a more detailed solution to a query.
Back in 2011, schema.org enabled the website to add more sections to their pages and so the search crawlers were able to analyze and understand the authors of the posts, the type of content, the review, FAQ, or other such sections. This is a part of Structured data, where you can display information on a page in a more organized manner. This helps the search engines trust your content and you end up on the top of the results. For the following sections, it is imperative that you optimize your content accordingly.
Semantic Search Algorithms
Google has always been consistent with upgrading its technology. And so, to further improve semantic search, Google introduced the following algorithm updates.
- Knowledge Graph
Knowledge graph is a combination of semantic mapping and coding. Introduced in 2012, it was the very first step in semantic search technology, a knowledge base that lets the search engine know what properties to display to which keyword.
This was the beginning of the importance of ‘context of keywords’ over a ‘string of keywords’. As Google calls it “things, not strings”. Knowledge graph is a knowledge base that collects information of entities and their respective properties. This is what kickstarted the semantic search era.
This algorithm update was launched in 2013, with the purpose of making sure that the results match with the meaning and context of the search words and not just the keywords.
When it’s a battle between Semantic search vs Keyword search, semantic search is given the edge. The pages that match the intent more accurately rank higher.
RankBrain came around in 2015. It is a machine learning system that helps with the ranking factor and smart query analysis AI.
Though hummingbird and RankBrain have similar purposes, the AI and machine learning component in RankBrain sets it apart.
It’s RankBrain that’s responsible for judging and deeming a website to be the best result for related queries. It possesses the knowledge of unfamiliar words and their properties by using sophisticated machine learning algorithms. Which makes it a very important factor in the ranking signals.
BERT has the job of understanding and interpreting long, complex sentences or queries which could be quite ambiguous. It has been dealing with 10% of all queries since 2019. BERT stands for Bidirectional Encoder Representations from Transformers.
How to use Semantic Search to boost your SEO
- Develop Content around topics not just keywords
- Prioritize matching Content to Search intent
- Upgrade Technical SEO
- Structured data
- Link building
- Site Structure
- Site Speed
- User Experience
- Leverage Voice search
Develop Content around topics not just keywords
Instead of focusing on keywords and creating content around them, like the old days, it’s time to shift that focus on to potential broad topics and cover them in detail.
By building high quality, relevant and helpful guides, the chances of getting noticed by Google are higher.
If you are used to focusing on keywords, you can use LSI tools that can help in constructing posts providing you with words with the same context or connotations as the keywords.
The more useful, optimized, and comprehensive your content is, the more visible to Google you get.
Prioritize matching Content to Search intent
Analyze what kind of queries or interests will lead your audience to your website. Make a list of possible questions that your users might have and build content around that.
Interpret their intent with every search query and provide them with solutions in a detailed and helpful format.
Remember that keywords are still important. If you forget to use them well, your page might not show up at all.
Having a list of important keywords and then segregating them with the possible intents and context would give you a clear idea.
Make sure you are creating content understanding the intent behind the search queries, giving your user exactly what they asked for. Provide value to your users through your website.
Upgrade Technical SEO
Even with Semantic Search Technologies, the algorithms still don’t fully process natural language completely. That is why, there is still the need for you to optimize your site, your content, your site structure to be a crawlable website.
Keywords: Even though this post emphasizes on search intent, the keywords still hold an important place in the SEO world.
You still need to strategically mention the keywords in your URL, content, headings, header tags, and meta tags, without stuffing them.
Understand different types of keywords (long-tailed keywords, transactional keywords, navigational keywords, informational keywords) their intent, usage, and incorporate them into your content.
Structured Data: Using structured markup enables the search engines to grasp content and deem the site as a provider of rich results.
A structured data showcases organized, high-level content and clarity which builds a sense of confidence in the engine to trust you with your content.
As mentioned in the above examples, rich results featured snippets, and knowledge graph content is a result of using Structured Data. Optimize them all.
Google has some Structured Data policies. You need to abide by those and keep up with the updates Google provides about all the active and in-use structured Data markups.
If you run a Blog you can markup your content with the Article Schema, and if you run a business, you can use Local Business schema. For more, visit the list that Google provides.
Link Building: Build relevancy through link building. Give Google the proof that you use relevant and resourceful links on your sites.
Backlinks, internal links, anchor texts are all important factors in signaling Google that you are a site worth ranking higher in the SERPs.
Site Structure: Optimize your site. Let Google know what your site is about. Strategize mentioning all the important keywords all over, without stuffing.
This majorly helps in indexing your site and also improves UX during the process.
Site Speed: Compress all those images, take advantage of browser caching, avoid adding elements that are heavy to load. Go through Google’s guidelines for site speed optimization.
Site user experience: Make your site attractive, organized, easy to navigate. User experience is a key factor in converting the audience to customers.
People are generally impressed by attractive and unique, never seen before layouts. Speedy sites and mobile-friendly sites are indexed more often after the Mobilegeddon algorithm update. Make sure your user sticks around for a longer time.
Leverage Voice Search
Voice search is becoming more and more common among users. Siri, Alexa or Google are now impressing users with instant verbal search results. According to WordStream, by the end of this year, the percentage of searches via voice technologies will reach 50%, and around 30% of searches will be done without using a screen.
In order to optimize your site for voice search, you need to make use of structured data and incorporate short and direct answers in your content to the possible search query.
For example, if the query reads “how to make spaghetti step by step”, your content must answer precisely.
A decade ago, SEO was a different ball game and I’m sure a decade from now SEO will be a whole lot different.
Though semantic Search has definitely impacted SEO a lot, the main motives remain the same. Google puts the users first. It will always revolve around making it easier for the people.
As Search engines get smarter, mediocre material on websites won’t do you any favors. Semantics is useful for interacting with the user in a more natural way. And it helps semantic search engines understand the intent and needed information from a search query.
To succeed at benefitting from Semantic Search, create content in a way that’s understood by the engines.