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Semantic SEO Guide

Search engines are currently undergoing a significant evolution in the area of artificial intelligence. In contrast to the original keyword search, Google, with the help of RankBrain and Co., gathers the complete contents of a site and discerns the semantic relationships to deliver the relevant search results to users.

In this article, we show you how to optimize your website for semantic searches.

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In order to clarify the concept of the semantic web, we have to take a look at the origins of the "classical web." In 1989, Sir Timothy John Berners-Lee, a British physicist and computer scientist, invented Hypertext Markup Language (HTML) and therefore the World Wide Web. He created the first website online http://info.cern.ch for the European Organization for Nuclear Research CERN.

The classical web includes the following basic standards:

  • URLs as web addresses,

  • HTTP as a protocol to call up these addresses and to be able to edit their content,

  • And HTML as a markup language for documents in text form.

Twelve years later, Tim Berners-Lee explained how the further-developed classical web would become the semantic web:


"The semantic web is an expansion of the traditional web, in which information is provided with clear meanings in order to facilitate work between men and machines."


In order to "simplify" this collaboration, website operators should heed the following tips and prepare their website content in such a way that algorithms can read them correctly.

Development of the Semantic Search

In the semantic search, not only are individual keywords searched, but also the content-related meaning of the entire text. Just as the human brain uses a semantic search term and associations. Website operators should provider their documents with structured data, so that the search engine can correctly evaluate homonyms and synonyms.

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Figure 1: Search for "ball" (2017): relevant results for sports equipment and formal dances

A homonym is a word that has multiple meanings. For example, if the term "ball" appears on a website, it needs to be specified if it means a toy, sports equipment, or a formal dance. The incorporation of synonyms in the search inquiry facilitates the completeness of the search results. In order to provide users with relevant search results, Google uses its own web protocol for semantic analysis.

With the tools "Suggest" and "Autocomplete," Google suggests alternative keyword combinations (keyword phrases) directly upon the entry of the search inquiry.

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Figure 2: Recommendations for "ball" in Google Suggest

A search for the term "ball" from 2015 shows how much Google has improved its search results over the past few years. Here, in addition to article pages, search results that were not directly associated or were less relevant were also displayed.

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Figure 3: Search for "ball" in 2015 resulted in fewer relevant results.

Semantic Analysis in the Context of a Search Inquiry

When linguists scrutinize the meaning of a word, they are speaking of "semantic analysis." Search engines follow these guiding principles: with the help of semantic analysis, search engines such as Google or Bing ascertain what the website is about and suggest relevant results for users. With its Hummingbird update in 2013, Google already laid out the requirements for this specialization.

Semantic analysis improves the search results and is goal-oriented. Google thereby does not only look for a technically perfect optimization of a website, but also for user-oriented content (texts, images, videos, etc.)

As an example, the search inquiry for the keyword "Jaguar" shows just how important it is to provide Google with the right information. The first pages only list websites that have to do with the car. Content-related sites about the big cat are shown on page four, along with the vehicle of the same name. On the other hand, the image gallery shows only animal photos on the first page.

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Figure 4: Page 1 results for search "Jaguar", only the vehicle brand

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Figure 5: Page 1 results for search "Jaguar", only animal photos in the image gallery

From this perspective, the newly introduced Google function "Similar Products" in mobile browsers and in the Google App on Android devices is very exciting. Thanks to machine recognition, users can now find products that they have seen in photos in the Google image search and can receive recommendations for similar products.

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Figure 6: Google's new function "Similar Searches"

This currently only works for handbags, shoes, and sunglasses, however. Products from clothing and home and garden will be added in the coming months. If you also sell products it makes sense to store the relevant sub-pages with the structured Schema.org product markup.

Google’s Knowledge Graph

Google's Knowledge Graph also falls under semantic analysis in terms of search results. It is a knowledge database in which information about persons, locations, events, and their relation to one another are collected. To compile the data, Google uses an algorithm that crawls through the index according to structured data. Results from Wikipedia are often listed here. Thanks to the Knowledge Graph, things can be found without having to specifically name them.

Thus, in answer to the question, "How tall is Brad Pitt?” Google shows the exact answer to the question as well as the detailed Knowledge Graph with the most important information on the actor Brad Pitt (see Figure 7).

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Figure 7: Combined search result with OneBox and Knowledge Graph

RankBrain and Semantic SEO

RankBrain is an algorithm implemented by Google in 2015, based on machine learning and that incorporates artificial intelligence. By now, Rankbrain has become the third most important ranking factor for Google after links and content. Search engines can correctly arrange ambiguous search terms, understand neologisms and colloquial terms, and deliver better results for voice commands.

This is especially important for brand new search inquiries, including individual words, phrases, or questions. And each time the search engine must understand user intent: What exactly is the user searching for? With linguistic problems such as synonymity, ambiguity, sense (intention), and meaning (extension), RankBrain is used to better evaluate complex search inquiries.

RankBrain seems to be based on a conversational model that incorporates previous search inquiries in order to guess the next sequence. If the system is running properly, the inferred sequences are incorporated back into the context of the next search inquiry. In the following example, we can clearly see how intelligently Google reacts to seldom-asked questions.

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Figure 8: Search results for the user intent "Food Chain"

The question "What animal is on the highest feeding level?" is directed toward the words "Food chain". Although not explicitly named, Google shows the result with the strongest topical connection. The words animal, ecosystem, consumer, and food are considered. Also, no products are shown, but rather knowledge-focused editorial content.

For unknown words, Rankbrain thus ties together semantic connections to already-known linguistic entities. Of course there are engineers who can teach the system how to handle unknown terms and relate them to one another. In the future, however, the system should learn this by itself. RankBrain is thus more than just an algorithm; it is a learning process. Therefore, it is not possible to directly influence RankBrain. You can, however, take a few things into consideration:

Tips on the Semantic Optimization of Your Website

To be more easily found, you can lay "tracks" for your readers with semantic SEO. Because Google is always getting better at filtering by topic, the quality of your content and whether or not the search engines can capture that context are the determining factors.

Ask yourself the following questions when optimizing your content:

  • Which keywords should your site rank with?

  • Who are your current competitors and how is their content structured?

  • How can your content on this topic outperform them?

  • How do your users currently interact with your content?

  • Are they finding the answers they searched for?

  • How can you use your content to optimize user experience on your site?

  • With which content are you most effectively reaching your target groups?

After you have answered these questions, you can optimize your content in terms of the semantic search using these concrete tips.

  1. Expand your keyword plan: The rule of optimizing each URL for a single keyword is obsolete. Expand your keyword plan to terms that belong to the same topic area.

  2. Gain an advantage over the competition: Distinguish yourself from your competitors with comprehensive, current information that is relevant to your target groups.

  3. Regular monitoring: Regularly research the top 10 results in the SERPs and, based on the changes in ranking, evaluate what can still be improved.

  4. Co-occurrences: Attract links and mentions on other topic-relevant, editorial sites and link to relevant sites yourself. In this way, you can create a closely-networked setting for your site.

  5. Increase authority: Through brand and domain names in suitable thematic environments you strengthen your own name recognition.

  6. . Use owned media: Offer your readers additional value on the topic with your own editorial channels such as corporate blogs, social media, or newsletters.

  7. Use synonyms In creating text, enrich the topic with synonyms instead of always mentioning the same keyword. Don't forget plural forms!

Comprehensively Optimize Texts with WDF*IDF

Unique text content is the basis for successful and sustainably optimized websites. With the help of the term weighting analysis WDF*IDF, you can calculate the weight of keywords within a document with On Page optimization. WDF stands for "within document frequency," IDF for "inverse document frequency."

The WDF*IDF module from OnPage.org supports this analysis, in which the term frequency of the 15 best-placed websites on a desired key term are automatically analyzed. With the help of these graphs, you can not only create unique texts, but you can also supplement existing content with important terms. This is not simply a pure keyword optimization, rather, the tool helps you create content with true added value for the user.

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Figure 9: WDF*IDF analysis with OnPage.org

Featured Snippets and Rich Cards as Semantic Designations

Google's goal is to always deliver the best possible results to its users. So understandable processing of content with so-called semantic designations is decisive for usability.

The products, items, services, or topic areas that are found on the site are stored in the Knowledge Graph, in featured and enhanced snippets, and in Rich Cards. If these are ranked well in the search results, the click rate also increases.

With the use of structured data from schema.org, you can somewhat influence how your websites are presented in SERPs. On the schema.org website, you will find a collection of HTML tags and markups to use with rich snippets for the areas of items, ratings, persons, prices, companies, events, or restaurants, among others.

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Figure 10: Rich snippet with ratings stars and information on baking time

Conclusion and Forecast

The significance of search engine optimization is fundamentally changing. Of course, you still have to make sure that your site is in technically perfect condition. But without a stronger focus on text content, in the long term, you won't be able to keep up if your competitors are doing a better job.

Thanks to the semantic search and the newest search assistants, Google has valuable tools for presenting the right results to the right target groups. Complex questions and sentences are no longer a hindrance, but rather an advantage. Take advantage of this and create your content as attractively and comprehensively as possible.

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Published on May 2, 2017 by Kathrin Schubert