10 Reasons Why Search Is In Vogue: Hot Trends In Semantic Search
Search is strongly featured in the all-important September issue of Vogue, which includes a 10-page layout of models wearing Google Glass, along with an in-depth feature on Yahoo CEO, Marissa Meyer, looking simply stunning and chic. Google Glass and the latest trends in search are now so hot that they are no longer considered geeky […]
Search is strongly featured in the all-important September issue of Vogue, which includes a 10-page layout of models wearing Google Glass, along with an in-depth feature on Yahoo CEO, Marissa Meyer, looking simply stunning and chic.
Google Glass and the latest trends in search are now so hot that they are no longer considered geeky but rather cool and hip.
Technology (and fashion) are all about providing you with the next thing you can’t live without. If we look to this month’s Vogue as a harbinger of must-have things to come in the world of search, we can deduce that the next generation of search — semantic search — will soon be essential for marketers.
1. Semantic Search = Answer Engines
The Knowledge Graph (or any entity graph) is based on internal, verified and validated structured data that facilitate the existence of answer engines.
Evolving into answer engines is the natural, long-term goal of search engines because they provide a better experience for the user than searching through lists of results. And an answer is better suited for display purposes on alternative devices (like Google Glass or a watch) than a typical computer screen.
How much more convenient would it be to get the right information delivered to you at the right time in the right form? This is provided to you in the form of cards in Google Now and Google Glass — the latter of which is not by a long shot the last form of wearable device you’ll be seeing (as evidenced by the formation of Glassomics and similar related entities).
In the near future, you’ll need to ensure that you (or your clients) exist as an entity in the knowledge graph in order to be “findable” in entity graph search results.
2. Semantic Search = Machine Readable
The Semantic Web, in the form of structured markup embedded in HTML pages, provides machine-readable information to search engine crawlers on specific topics/subjects.
Ensure that you include this markup on your website (check out Schema.org to get started) and make certain that it is geared toward providing your target audience with answers for questions they may ask search engines.
3. Semantic Search = Enhanced SERP Displays & Lift
Search Engines exploit semantic technology to create a better user experience. Google’s rich snippets, Bing Tiles and Yahoo SearchMonkey results are all “enhanced displays” which make SERPs more visually engaging to the audience — which, among other things, leads to a higher click-through rate (CTR). The carousel and knowledge graph results are also examples of enhanced displays which create a better user experience.
The ideal display mechanism is optimized on a per-device basis. These user interfaces can be tested in A/B testing type experiments run in real time (Google typically runs about 24 or so simultaneously) to determine the optimal user experience/response to their GUIs.
Make sure that you are using the latest and greatest (as well as the most accurate/granular) semantic markup possible on your websites. This will enable you to automatically take advantage of any lift when new rich snippets or enhanced structured data are displayed in search results.
4. Semantic Search = Validation Of Web Pages
By extracting pertinent structured data, search engines can verify that your pages are, in fact, about the topic you are describing on those pages. This verification adds trust to your webpages.
Your page content and structured markup should also match any information you supply via a data feed or API. This not only serves to further validate your content, but also provides an additional data source to enable machine learning/training sets on webpages.
Ensure that Schema.org markup is consistent with what you display to human users and that it matches any information supplied via an API or data feed.
5. Semantic Search = Social Network Adoption
Search engines like Google can leverage semantic search to drive adoption of their Google Plus social network for businesses.
Creating a Google Plus page for your brand or business will increase brand awareness and visibility, and linking your Google Plus page to your website will ensure your business exists as an entity within the Knowledge Graph.
Although no longer strictly necessary, implement rel=publisher on your website and link it to your Google Plus page (specific details can be found here).
6. Semantic Search = Google+ Authorship Rich Snippet
Google+ social network adoption is further driven for personal use by individuals due to the authorship rich snippet.
Not only can use of authorship markup increase visibility for a verified author, it also ensures that original content for an article is attributed directly to the author. The result is that sites which scrape content from other sites will ultimately have their authority reduced (which may in turn impact rankings).
Publishers should take the time to properly implement both authorship markup as well as Schema.org article markup. (Articles can also be further optimized to have a better chance of appearing as an “in-depth article” in SERPs.)
7. Semantic Search = Internal Structured Data
Internal structured data (verified and validated via trusted sources) can be leveraged for many things, such as prediction or recommendation. Google is a master at using this kind of “Big Data.” But remember, the law of all data when utilizing it for results: GIGO (Garbage In, Garbage Out).
So, make sure you do not adopt any spammy techniques or feed Google any invalid or Garbage information. It will decrease Google’s trust in you — and, as SEOs, you know very well what a negative impact that may have. No information is better than bad information.
8. Semantic Search = The Future Of Search
Internal axiomatic facts, along with “context” or “knowledge base partitions” can allow computers (and search engines) to derive new information and can be leveraged along with viable reasoning mechanisms to create the all-intelligent “Star Trek” computer of the future. At a minimum, search engines like Google are already deriving basic associations by traversing a “Semantic network” or Knowledge Graph.
Think future capabilities (things that, in the past, may have been considered science fiction), and you may well be on track to envisioning the future of search.
9. Semantic Search = Schema.org Ontology
When search engines leverage something like a Schema.org ontology (or any vocabulary or representation of concepts within a computer), those concepts are essentially language independent.
Examples that better describe this are projects like the DARPA TIDES program. You can also see that Google supports “rich snippets” in many languages; the languages cited by Google in this link are: Chinese, Czech, Dutch, English, French, German, Hungarian, Italian, Japanese, Korean, Polish, Portuguese, Russian, Spanish, and Turkish.
So, if you are targeting consumers in other languages, be sure to take that into account. (You can implement structured markup in these languages if they are part of your target audience.)
10. Semantic Search = Understanding User Intent
Search engines use Semantic Search to better understand user intent. This is possibly one of the most important aspects to understand.
Leveraging a user’s location, search history, device type, daily habits, etc., are all mechanisms that can be used to help a search engine understand a user’s intent when asking a query.
The more “context” that is added, the better the search engine can refine the query, disambiguate extracted information, narrow the search space for the answer, and, of course, provide the user with the right answer at the right time.
Adding factors such as the emerging Internet of “things,” you can imagine how useful this could be to search engines and how critical it is as a factor in search. However, this is a topic in and of itself.
There are many signals that are considered to better determine user intent. Be aware of these signals (or at least the more obvious ones) and ensure you take them into account in targeting your audience.
In summary, Semantic Search is on the rise and must be understood by anyone wishing to engage in SEO best practices. Presumably, Semantic SEO will become the term used to describe how SEOs can leverage this.
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