{"id":27063,"date":"2023-12-24T02:56:47","date_gmt":"2023-12-24T02:56:47","guid":{"rendered":"https:\/\/www.searchenginejournal.com\/entity-seo-festive\/502130\/"},"modified":"2023-12-24T02:56:47","modified_gmt":"2023-12-24T02:56:47","slug":"entities-in-seo-what-are-they-and-why-do-they-matter-festive-flashback-via-sejournal-dixon_jones","status":"publish","type":"post","link":"https:\/\/marketingnewsbox.com\/?p=27063","title":{"rendered":"Entities In SEO: What Are They And Why Do They Matter? (Festive Flashback) via @sejournal, @Dixon_Jones"},"content":{"rendered":"<p><em>Celebrate the Holidays with some of SEJ\u2019s best articles of 2023.<\/em><\/p>\n<p><em>Our Festive Flashback series runs from December 21 \u2013 January 5, featuring daily reads on significant events, fundamentals, actionable strategies, and thought leader opinions.<\/em><\/p>\n<p><em>2023 has been quite eventful in the SEO industry and our contributors produced some outstanding articles to keep pace and reflect these changes.<\/em><\/p>\n<p><em>Catch up on the best reads of 2023 to give you plenty to reflect on as you move into 2024.<\/em><\/p>\n<hr>\n<p>There is a lot of confusion about how SEO pros should both understand and, more importantly, leverage \u201centities\u201d in SEO.<\/p>\n<p>I understand where this comes from, especially with the traditional approach to <a href=\"https:\/\/www.searchenginejournal.com\/seo\/\">SEO<\/a> being around words and phrases.<\/p>\n<p>Indeed, most of the algorithms that the first wave of SEO pros (like me) grew up with had no concept of an \u201centity\u201d in search. <a href=\"https:\/\/www.searchenginejournal.com\/seo\/search-authority\/\">SEO principals<\/a> \u2013 from content writing to anchor text in links to SERPs tracking \u2013 were (and largely still are) keyword-driven, and many people still find it hard to understand what has changed.<\/p>\n<p>But over the last decade, all search has been moving towards understanding the world as a string of words and as a series of interconnected entities.<\/p>\n<p>Working with entities in SEO is the foundation for a <a href=\"https:\/\/www.searchenginejournal.com\/future-proof-seo-strategy-ai\/489457\/\">future-proof search strategy<\/a>.<\/p>\n<p>They are also important for a future with <a href=\"https:\/\/www.searchenginejournal.com\/category\/digital\/generative-ai\/\">generative AI<\/a> and <a href=\"https:\/\/www.searchenginejournal.com\/what-is-chatgpt\/473664\/\">ChatGPT<\/a>.<\/p>\n<p>This article talks about why. It covers:<\/p>\n<ul>\n<li>What are entities?<\/li>\n<li>What is the Knowledge Graph?<\/li>\n<li>A brief history of entities in search: Freebase, Wikidata, and entities.<\/li>\n<li>How entities work and how they are used for ranking.<\/li>\n<li>Examples of entities in Google.<\/li>\n<li>How to optimize for entities.<\/li>\n<li>Using Schema to help define entities.<\/li>\n<\/ul>\n<h2>What Are Entities?<\/h2>\n<p>SEOs often confuse entities with <a href=\"https:\/\/www.searchenginejournal.com\/keyword-research\/\">keywords<\/a>.<\/p>\n<p>An entity (in search terms) is a record in a database. An entity generally has a specific record identify.<\/p>\n<p>In Google, that might be:<\/p>\n<p>\u201cMREID=\/m\/23456\u201d or \u201cKGMID=\/g\/121y50m4.\u201d<\/p>\n<p>It is certainly not a \u201cword\u201d or \u201cphrase.\u201d I believe that the confusion with keywords stems from two root causes:<\/p>\n<ol>\n<li>The first is that SEO pros learned their craft pre-2010 in terms of keywords and phrases. Many still do.<\/li>\n<li>The second is that every entity comes with a label \u2013 which is generally a keyword or descriptor.<\/li>\n<\/ol>\n<p>So while \u201cEiffel Tower\u201d might seem like a perfectly identifiable \u201centity\u201d to us as humans, Google sees it as <a href=\"https:\/\/www.google.com\/search?kgmid=\/m\/02j81\" target=\"_blank\" rel=\"noopener noreferrer\">\u201cKGMID=\/m\/02j81\u201d<\/a> and really doesn\u2019t care if you call it \u201cEiffel Tower,\u201d or \u201c Torre Eiffel,\u201d or \u201c\u0627\u06cc\u0641\u0644 \u0628\u0648\u0631\u062c\u0648\u201d (Which is Azerbaijan for \u201cEiffel Tower\u201d). It knows that you are probably referring to that underlying entity in its Knowledge Graph.<\/p>\n<p>This comes on to the next point:<\/p>\n<h2>What Is \u201cThe Knowledge Graph\u201d?<\/h2>\n<p>There are subtle but important differences between \u201ca knowledge graph,\u201d \u201cThe Knowledge Graph,\u201d and \u201cThe Knowledge Panel.\u201d<\/p>\n<ul>\n<li>A knowledge graph is a semi-structured database containing entities.<\/li>\n<li>The <a href=\"https:\/\/www.searchenginejournal.com\/how-google-knowledge-graph-works\/400485\/\">Knowledge Graph<\/a> is generally the name given to Google\u2019s Knowledge Graph, although thousands of others exist. Wikidata (itself a knowledge graph) attempts to cross-reference identifiers from different reputable data sources.<\/li>\n<li>The <a href=\"https:\/\/www.searchenginejournal.com\/knowledge-panel-for-person\/410337\/\">Knowledge Panel<\/a> is a specific representation of results from Google\u2019s Knowledge Graph. It is the pane often showing on the right of the results (SERPs) in a desktop search, giving more details about a person, place, event, or other entity.<\/li>\n<\/ul>\n<h2>A Brief History Of Entities In Search<\/h2>\n<h3>Metaweb<\/h3>\n<p>In 2005, <a href=\"https:\/\/en.wikipedia.org\/wiki\/Metaweb\" target=\"_blank\" rel=\"noopener noreferrer\">Metaweb<\/a> started to build out a database, then called <a href=\"https:\/\/en.wikipedia.org\/wiki\/Freebase_(database)\" target=\"_blank\" rel=\"noopener noreferrer\">Freebase<\/a>, which it described as an \u201copen, shared database of the world\u2019s knowledge.\u201d<\/p>\n<p>I would describe it as a semi-structured encyclopedia.<\/p>\n<p>It gave every \u201centity\u201d (or article, to extend the metaphor) its own unique ID number \u2013 and from there, instead of a traditional article in words, the system tried to connect articles through their relationships with other ID numbers in the system.<\/p>\n<p>Some $50 million dollars in capital funding, and 5 years later, the project was sold to Google.<\/p>\n<p>No commercial product was ever built, but the foundation was set for a 10-year transition, for Google, from a keyword-based search engine to an entity-based one.<\/p>\n<h2>Wikidata<\/h2>\n<p>In 2016 \u2013 some six years after the purchase \u2013 Google formally closed down Freebase because it had migrated and developed the ideas into its own \u201cknowledge graph,\u201d the modern term for these databases.<\/p>\n<p>At that time, it is useful to note that Google publicly stated that it had synced much of its entity data with <a href=\"https:\/\/www.wikidata.org\/wiki\/Wikidata:Main_Page\" target=\"_blank\" rel=\"noopener noreferrer\">Wikidata<\/a> and that, moving forward, Wikidata (which underpins the data used in Wikipedia) was one way in which Google\u2019s Knowledge Graph could interface with the outside world.<\/p>\n<h2>How Entities Work And How They Are Used For Ranking<\/h2>\n<h3>Entities In The Core Algorithm<\/h3>\n<p>Entities are primarily used to disambiguate ideas, not to rank pages with the same ideas.<\/p>\n<p>That is not to say that clever use of entities can\u2019t help your site\u2019s content rank more effectively. It can. But when Google tries to serve up results to a user search, it aims first and foremost for an <strong>accurate<\/strong> answer.<\/p>\n<p>Not necessarily the most deserving.<\/p>\n<p>Therefore, Google spends considerable time converting text passages into underlying entities. This happens both when indexing your site and when analyzing a user query.<\/p>\n<p>For example, if I type in \u201cThe names of the restaurants underneath the Eiffel Tower,\u201d Google knows that the searcher is not looking for \u201cnames\u201d or the \u201cEiffel Tower.\u201d<\/p>\n<p>They are looking for restaurants. Not any restaurant, but ones in a specific location. The two relevant entities in this search are \u201crestaurant\u201d in the context of \u201cChamp de Mars, 5 Av. Anatole France, Paris\u201d (The address of the Eiffel Tower).<\/p>\n<p>This helps Google to decide how to blend its various search results \u2013 images, Maps, Google businesses, adverts, and organic web pages, to name a few.<\/p>\n<p>Most importantly, for the SEO pro, it is very important for (say) the Jules Verne restaurant\u2019s site to talk about its spectacular view of the Eiffel Tower if it wants Google to recognize that the page is relevant to this search query.<\/p>\n<p>This might be tricky since the Jules Verne restaurant is inside the Eiffel Tower.<\/p>\n<h3>Language Agnostic<\/h3>\n<p>Entities are great for <a href=\"https:\/\/www.searchenginejournal.com\/search-engines\/\">search engines<\/a> because they are language-agnostic. Moreover, that idea means that an entity can be described through multiple media.<\/p>\n<p>An image would be an obvious way to describe the Eiffel Tower since it is so iconic. It might also be a speech file or the official page for the tower.<\/p>\n<p>These all represent valid labels for the entity and, in some cases, valid identifiers in other knowledge graphs.<\/p>\n<h3>Connections Between Entities<\/h3>\n<p>The interplay <strong>between<\/strong> entities allows an SEO pro to develop coherent strategies for developing relevant <a href=\"https:\/\/www.searchenginejournal.com\/fundamental-seo-tactics-to-grow-traffic\/398958\/\">organic traffic<\/a>.<\/p>\n<p>Naturally, the most \u201c<a href=\"https:\/\/www.searchenginejournal.com\/seo\/search-authority\/\">authoritative<\/a>\u201d page for the Eiffel Tower is likely to be the official page or Wikipedia. Unless you are literally the SEO pro for the Eiffel Tower, there is little that you can do to challenge this fact.<\/p>\n<p>However, the interplay between entities allows you to write content that will rank. We already mentioned \u201crestaurants\u201d and \u201cEiffel Tower\u201d \u2013 but what about \u201cMetro\u201d and \u201cEiffel Tower,\u201d or \u201cDiscounts\u201d and \u201cEiffel Tower\u201d?<\/p>\n<p>As soon as two entities come into play, the number of relevant search results drops dramatically. By the time you get to \u201cDiscounted Eiffel Tower tickets when you travel by Metro,\u201d you become one of just a tiny selection of pages focusing on the juxtaposition between Metro tickets, Eiffel Tower tickets, and discounts.<\/p>\n<p>Many fewer people type in this phrase, but the conversion rate will be much higher.<\/p>\n<p>It may also prove a more monetizable concept for you! (This example is to explain the principle. I do not know if such discounts exist. But they should.)<\/p>\n<p>This concept can be scaled to create exceptionally strong pages by first breaking all the competing pages for a search phrase into a table showing the underlying entities and their relative importance to the main query.<\/p>\n<p>This can then act as a content plan for a writer to build up a new piece of content that is more authoritative than any of the other competing pieces.<\/p>\n<p>So although a search engine may claim that entities are not a ranking factor, the strategy goes to the heart of the philosophy that \u201cIf you write good content, they will come.\u201d<\/p>\n<h2>Examples Of Entities In Google<\/h2>\n<h3>Entities In Image Search<\/h3>\n<div id=\"attachment_493341\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-493341 size-full b-lazy pcimg\" src=\"https:\/\/www.searchenginejournal.com\/wp-content\/uploads\/2023\/08\/screenshot-2023-08-07-at-12.23.39-pm-64d072eb7f82f-sej.png\" alt=\"dog on a skateboard: Google search\" width=\"2116\" height=\"1274\"><span class=\"wp-caption-text\">Screenshot from search for [dog on a skateboard], Google, August 2023<\/span><img decoding=\"async\" src=\"https:\/\/www.searchenginejournal.com\/wp-content\/uploads\/2023\/08\/screenshot-2023-08-07-at-12.23.39-pm-64d072eb7f82f-sej.png\" alt=\"dog on a skateboard: Google search\"><\/div>\n<p>Entities can also be very helpful in <a href=\"https:\/\/www.searchenginejournal.com\/on-page-seo\/image-optimization\/\">optimizing images<\/a>.<\/p>\n<p>Google has worked very hard to analyze images using machine learning. So typically, Google knows the main imagery in most photos.<\/p>\n<p>So take [<a href=\"https:\/\/www.google.com\/search?sca_esv=554340491&amp;q=dog+on+a+skateboard&amp;tbm=isch&amp;source=lnms&amp;sa=X&amp;sqi=2&amp;ved=2ahUKEwjf3qTW2cmAAxXJR2wGHaa_ALgQ0pQJegQIDBAB&amp;biw=1222&amp;bih=779&amp;dpr=1.8\" target=\"_blank\" rel=\"noopener noreferrer\">a dog on a skateboard<\/a>] as a search term\u2026making sure that your content fully supports the image can help your content be more visible, just when the user is searching for it.<\/p>\n<h3>Entities In Google Discover<\/h3>\n<p>One of the most underrated traffic sources for SEO professionals is <a href=\"https:\/\/www.searchenginejournal.com\/google-discover\">Google Discover<\/a>.<\/p>\n<p>Google provides a feed of interesting pages for users, even when they are not actively looking for something.<\/p>\n<p>This happens on Android phones and also in the Google app on iPhones. Whilst news heavily influences this feed, non-news sites can get traffic from \u201cDiscover.\u201d<\/p>\n<p>How? Well \u2013 I believe that entities play a big factor!<\/p>\n<div class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.searchenginejournal.com\/wp-content\/uploads\/2023\/08\/discover-64ca6e07a6b08-sej-480x76.png\" alt=\"Google Discover data in GSC\" width=\"480\" height=\"76\" class=\" b-lazy pcimg\"><span class=\"wp-caption-text\">Screenshot from Google Search Console, August 2023<\/span><img decoding=\"async\" src=\"https:\/\/www.searchenginejournal.com\/wp-content\/uploads\/2023\/08\/discover-64ca6e07a6b08-sej-480x76.png\" alt=\"Google Discover data in GSC\"><\/div>\n<p>Don\u2019t be disheartened if you do not see a \u201cDiscover\u201d tab in your Google Search Console. But when you do, it can be a welcome sign that at least one of your web pages has aligned with entities enough that at least one person\u2019s interests overlap with your content enough to have the page in a feed targeted specifically to the user.<\/p>\n<p>In the example above, even though \u201cDiscover\u201d results are not displayed at the exact time that a user is searching, there is <strong>still<\/strong> a 4.2% click-through rate.<\/p>\n<p>This is because Google can align the interests and habits of many of its users to the content on the Internet by mapping entities.<\/p>\n<p>Where a strong correlation occurs, Google can offer up a page for a user.<\/p>\n<h2>How To Optimize For Entities<\/h2>\n<h3>Some Research From A Googler<\/h3>\n<p>In 2014, <a href=\"https:\/\/research.google\/pubs\/pub42235.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">a paper came out<\/a> that I find quite helpful in demonstrating that Google (or at least, its researchers) were keen to separate out the ideas of using keywords to understand topics vs. using entities.<\/p>\n<p>In this paper, Dunietz and Gillick note how NLP systems moved towards entity-based processing. They highlight how a binary \u201csalience\u201d system can be used on large data sets to define the entities in a document (webpage).<\/p>\n<p>A \u201cbinary scoring system\u201d suggests that Google might decide that a document either IS or ISN\u2019T about any given entity.<\/p>\n<p>Later clues suggest that \u201csalience\u201d is now measured by Google on a sliding scale from 0 to 1 (for example, the scoring given in its NLP API).<\/p>\n<p>Even so, I find this paper really helpful in seeing where Google\u2019s research thinks \u201centities\u201d should appear on a page to \u201ccount\u201d as being salient.<\/p>\n<p>I recommend reading the paper for serious research, but they list how they classified \u201csalience as a study of \u2018New York Times\u2019 articles.\u201d<\/p>\n<p>Specifically, they cited:<\/p>\n<h4>1st-loc<\/h4>\n<p>This was the first sentence in which a mention of an entity first appears.<\/p>\n<p>The suggestion is that mentioning the entity early in your web page might increase the chances of an entity being seen as \u201csalient\u201d to the article.<\/p>\n<h4>Head-count<\/h4>\n<p>This is basically the number of times the \u201chead\u201d word of the entity\u2019s first mention appears.<\/p>\n<p>\u201cHead word\u201d is not specifically defined in the article, but I take it to mean the word concatenated to its simplest form.<\/p>\n<h4>Mentions<\/h4>\n<p>This refers not just to the words\/labels of the entity, but also to other factors, such as referrals of the entity (he\/she\/it)<\/p>\n<h4>Headline<\/h4>\n<p>Where when an entity appears in a headline.<\/p>\n<h4>Head-lex<\/h4>\n<p>Described as the \u201clowercased head word of the first mention.\u201d<\/p>\n<h4>Entity Centrality<\/h4>\n<p>The paper also talks about using a variation of <a href=\"https:\/\/www.searchenginejournal.com\/google-pagerank\/483521\/\">PageRank<\/a> \u2013 where they switched out web pages for Freebase articles!<\/p>\n<p>The example they shared was a Senate floor debate involving FEMA, the Republican Party, (President) Obama, and a Republican senator.<\/p>\n<p>After applying a PageRank-like iterative algorithm to these entities and their proximity to each other in the knowledge graph, they were able to change the weightings of the importance of those entities in the document.<\/p>\n<h2>Putting These Entity Signals Together In SEO<\/h2>\n<p>Without being specific to Google, here, an algorithm would create values for all the above variables <strong>for every entity<\/strong> that an NLP or named entity extraction program (NEEP) finds on a page of text (or, for that matter, all the entities recognized in an image).<\/p>\n<p>Then a weighting would be applied to each variable to give a score. In the paper discussed, this score turns into a 1 or 0 (salient or not salient), but a value from 0-1 is more likely.<\/p>\n<p>Google will never share the details of those weightings, but what the paper also shows is that the weightings are determined only after hundreds of millions of pages are \u201cread.\u201d<\/p>\n<p>This is the nature of large language learning models.<\/p>\n<p>But here are some top tips for SEO pros who want to rank content around two or more entities. Returning to the example \u201crestaurants near the Eiffel Tower\u201d:<\/p>\n<ul>\n<li>Decide on a \u201cdead\u201d term for each entity. I might choose \u201crestaurant,\u201d \u201cEiffel Tower,\u201d and \u201cdistance\u201d because <a href=\"https:\/\/en.wikipedia.org\/wiki\/Distance\" target=\"_blank\" rel=\"noopener noreferrer\">distance has a valid meaning and article in Wikipedia<\/a>. Cafe might be a suitable synonym for restaurant, as might \u201crestaurants\u201d in the plural.<\/li>\n<li>Aim to have all three entities in the header and first sentence. For example: \u201cRestaurants a small distance from the Eiffel Tower.\u201d<\/li>\n<li>Aim in the text to talk about the inter-relationship between these entities. For example: \u201cThe Jules-Verne restaurant is literally inside it.\u201d Assuming \u201cit\u201d clearly refers to the Eiffel Tower in the context of the writing, it does not need to be written out every time. Keep the language natural.<\/li>\n<\/ul>\n<h3>Is This Enough For Entity SEO?<\/h3>\n<p>No. Probably not. (You are welcome to read my book!) However, not all factors are in your control as a writer or website owner.<\/p>\n<p>Two ideas that do seem to have an impact, though, are linking content from other pages in context and adding schema to help with the definitions.<\/p>\n<h2>Using Schema To Help Define Entities<\/h2>\n<p>Further clarity might be given to search engines by using the \u201cabout\u201d and \u201cmentions\u201d schema to help a search engine disambiguate content.<\/p>\n<p>These two <a href=\"https:\/\/www.searchenginejournal.com\/technical-seo\/schema\/\">schema<\/a> types help to describe what a page is talking about.<\/p>\n<p>By making a page \u201cabout\u201d one or two entities and \u201cmentions\u201d of maybe a few more, an SEO professional can quickly summarize a long piece of content into its key areas in a way that is ready-made for knowledge graphs to consume.<\/p>\n<p>It should be noted, though, that Google has not expressly stated one way or another whether it uses this schema in its core algorithms.<\/p>\n<p>I would probably add this schema to my article:<\/p>\n<blockquote>\n<p>&lt;script type=\u201dapplication\/ld+json\u201d&gt; {<\/p>\n<p>\u201c@context\u201d: \u201chttps:\/\/schema.org\u201d,<\/p>\n<p>\u201c@type\u201d: \u201cWebPage\u201d,<\/p>\n<p>\u201c@id\u201d: \u201chttps:\/\/www.yoursite.com\/yourURL#ContentSchema\u201d,<\/p>\n<p>\u201cheadline\u201d: \u201cRestaurants a small distance from the Eiffel Tower\u201d,<\/p>\n<p>\u201curl\u201d: \u201chttps:\/\/www.yoursite.com\/yourURL\u201d,<\/p>\n<p>\u201cabout\u201d: [<\/p>\n<p id=\"sc_350895_666159\">&nbsp;&nbsp;&nbsp;{\u201c@type\u201d:&nbsp;\u201cThing\u201d,&nbsp;\u201cname\u201d: \u201cRestaurant\u201d,&nbsp;\u201csameAs\u201d: \u201chttps:\/\/en.wikipedia.org\/wiki\/Restaurant\u201d},<\/p>\n<p id=\"sc_sk_27364_666159\">&nbsp;&nbsp;&nbsp;{\u201c@type\u201d:&nbsp;\u201cPlace\u201d,&nbsp;\u201cname\u201d: \u201cEiffel Tower\u201d,&nbsp;\u201csameAs\u201d: \u201chttps:\/\/en.wikipedia.org\/wiki\/Eiffel_Tower\u201d}<\/p>\n<p>],<\/p>\n<p>\u201cmentions\u201d: [<\/p>\n<p id=\"sc_sk_27365_666159\">&nbsp;&nbsp;&nbsp;{\u201c@type\u201d:&nbsp;\u201cThing\u201d,&nbsp;\u201cname\u201d: \u201cdistance\u201d,&nbsp;\u201csameAs\u201d: \u201chttps:\/\/en.wikipedia.org\/wiki\/Distance\u201d},<\/p>\n<p id=\"sc_sk_27366_666159\">&nbsp;&nbsp;&nbsp;{\u201c@type\u201d:&nbsp;\u201cPlace\u201d,&nbsp;\u201cname\u201d: \u201cParis\u201d,&nbsp;\u201csameAs\u201d: \u201chttps:\/\/en.wikipedia.org\/wiki\/Paris\u201d}<\/p>\n<p>]<\/p>\n<p>} &lt;\/script&gt;<\/p>\n<\/blockquote>\n<p>The exact choice of schema is as much a philosophical question as an SEO question.<\/p>\n<p>But think of the schema you use as \u201cdisambiguating\u201d your content rather than \u201coptimizing your content,\u201d and you will hopefully end up with more targeted search traffic.<\/p>\n<p><em>Editor\u2019s note: Dixon Jones is the author of <a href=\"https:\/\/dixonjones.com\/seo-book\/\" target=\"_blank\" rel=\"noopener noreferrer\">Entity SEO: Moving from Strings to Things<\/a>.<\/em><\/p>\n<p><strong>More resources:<\/strong><\/p>\n<hr>\n<p><em>Featured Image: optimarc\/Shutterstock<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Celebrate the Holidays with some of SEJ\u2019s best articles of 2023. Our Festive Flashback series runs from December 21 \u2013 January 5, featuring daily reads on significant events, fundamentals, actionable strategies, and thought leader opinions. 2023 has been quite eventful in the SEO industry and our contributors produced some outstanding articles to keep pace and&#8230; <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-27063","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/marketingnewsbox.com\/index.php?rest_route=\/wp\/v2\/posts\/27063","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/marketingnewsbox.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/marketingnewsbox.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/marketingnewsbox.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/marketingnewsbox.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=27063"}],"version-history":[{"count":0,"href":"https:\/\/marketingnewsbox.com\/index.php?rest_route=\/wp\/v2\/posts\/27063\/revisions"}],"wp:attachment":[{"href":"https:\/\/marketingnewsbox.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=27063"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/marketingnewsbox.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=27063"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/marketingnewsbox.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=27063"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}