Conversational AI at the center of your content strategy!
2019 will be the year of voice search. This article explores how conversational AI and voice queries are driving the top SEO trends for this year.
What are the top trends for SEO in 2019?
The trends for SEO in 2019, one way or another, are linked with the growth of conversational AI, voice queries and the emergence ofknowledge graphs. Here are the top 5 trends you need to watch in 2019:
We’re already living in a world where 13% of Google searches are voice queries (here is a good article to read by Rebecca Sentance on what the future of voice search holds for us). The very enthusiastic supporters of the voice search bandwagon might even say that by 2020 one every two searches will come from voice but predictions, as we know, are very hard to make especially in the marketing world.
What we have seen for sure in 2018 is that voice search is shaping the entire SEO industry. As SEO Expert Aleyda Solis pointed out recently, voice search is driving “a bigger shift”, from specific “results” to “answers” that become part of a continuous “conversational search journey”.
Artificial Intelligence, though, is the real enabler behind this transition. It was back in December 2016 when, Andrew NG Chief Scientist at Baidu at the time, predicted that speech-recognition accuracy going from 95% to 99%, would have moved the needle in terms of mass adoption of voice interfaces.
As speech-recognition accuracy goes from 95% to 99%, we’ll go from barely using it to using all the time! https://t.co/TfjqJLDTPJ
As of today machine learning and semantic networks are being constantly used to provide a personalised user experience across a multitude of channels, to guide the user across different tasks (from driving directions, to cooking, from podcast discovery to news reading and “listening”) and to help us find what matters the most.
In 2018 we witnessed knowledge graphs entering the Gartner hype cycle as emergent technology forming the bridge between humans, knowledge and conversational AI. In 2018 not only researchers and universities, but also industry companies have been heavily investing in knowledge graphs and not only Amazon with its product graph, Facebook with the Graph API, IBM with Watson, Microsoft with Satori and Google with its own Knowledge Graph but also Internet startups like Airbnb, Zalando and many others have committed resources for the creation of functional knowledge graphs meant to support general-purpose reasoning, inference and above all an improved search experience.
In conclusion, we don’t expect the entire world to shift to voice but we can predict that conversational AI and a combination of voice and touch interactions will drive SEO in 2019.
In 2019 SEOs and marketers have to prepare for a more human-driven and conversational web. Voice search will not disrupt every business but it is a driving force in the entire content marketing sector. The 2019 trends for SEO, one way or another, are linked with the growth of conversational AI and the emergence of knowledge graphs.
1. Conversational user intents and long-tail keywords
Focusing on the user intent is going to be strategic. We expect that the user search intents will be likely expressed in a more advanced range of sophisticated conversational queries. Focusing on long-tail keywords that target a specific user (in a specific context) will be simpler (and wiser in most cases) than going after a broad keyword.
When and if, we decide to go broad and to target a more general intent (ie. “business model“) we shall provide enough structure (and data) to help users (and machines) find the winning answer by further refining the initial request as if they were having a dialogue with the website (“Are you interested in the business model of Apple or of a startup?“).
Imagine preparing content as if the user would be always asking their questions to a Google Home or another voice-first device. We need to prepare all the possible answers that a conversation around that topic might trigger. We need to guide the user from the initial request to a deeper discovery of the available content and we need to match the format the user is looking for (some might like to activate a video, while others might prefer a long-format article).
2. Featured snippets and answer boxes
As a result of the information overload, and due to the growth of queries carried out via smart speakers (statistics talk about 26.4 million daily voice queries) machines will constantly need to sum up a vast amount of information, find what is really relevant for us and provide a decent speakable version of our content. While parsing language remains one of the grand challenges of artificial intelligence good results are today being achieved by Google Featured Snippets, Bing Expanded Answer and the alike. Visibility across the SERP and throughout the AI-first user experience is very much dependent on answer boxes and featured snippets. Once again, this is currently an aspect of SEO that involves mobile as well as the desktop but it is fueled by the growth of conversational AI. We shall prepare content that can be easily summarised and read aloud; we also need to leverage on structured data to help machines disambiguate the context and to support the meaningful summarization of it.
3. Structured data and knowledge graphs
Linked data, knowledge graphs and schema markup helps us connect content with a specific search intent using usage patterns that are now embedded in the search experience. A vast variety of Google SERP features are already dependent on structured data and more will come in 2019. Here below a quick overview highlighting in blue the SERP features that are linked with the use of structured data.
Google Search Features (the original list is from BrightEdge) in blue items that have some connection with schema markup.
Structured data is foundational in the conversational era as it provides well-defined information for a wide range of encoded user intents. Machine learning needs to be trained across a vast amount of semantically relevant datasets. This is true for commercial search engines, for smart assistants and for our own internal user experience – once again our website needs to become capable of answering to specific intents by guiding the user where it matters the most.
Knowledge Graph Entities are being used by the Google Assistant for answering simple questions.
4. Google News optimization and content discovery
Pre-emptive knowledge delivery and content discovery have been a trend for a few years now. This basically means helping users discover content in a serendipitous way and without searching for. In September 2018 Google introduced the Google feed “to surface relevant content […], even when you’re not searching for”.
Being able to predict the information need in a queryless way is a major focus in Google’s future of Search and it will be strategic for all major consumer brands (Amazon, Facebook, Microsoft and Apple). If we focus on Google alone we can see that, content being proposed in Google Discover is made of three types: youtube videos and fresh visual content, evergreen content like recipes and news articles. As we have seen in the checklist to optimize for Google Top Stories being present in Google News has become an important asset since the explosion of the fake news scandal (Google News content represent a selection of somehow validated and authoritative content that Google – and other players – can trust). While not all websites are eligible for Google News, if you are producing fresh content for your industry this is definitely a time to consider Google News as a new distribution channel. This becomes even more strategic these days since Google announced an upcoming voice-driven version of Google News for the Google Assistant.
5. Technical SEO for less complicated and faster websites
In 20 years we failed in building a simpler Web. Websites are becoming more and more complicated with an endless number of (sometimes useless) routines that run every time a browser hits the first page. I am not going to get into the topic but there is a brilliant article that you should read to learn about the importance of simplicity and why (the article is titled The Bullshit Web and is by Nick Heer a front-end developer from Canada) we now have to invest on technical SEO. Once again the key aspect in technical SEO – in relation with the conversation AI – is speed.
As highlighted in a study done this year by Backlinko – content that is brought into the Google Assistant is only the content that renders super fast.
A Voice Search study by Backlinko on the importance of page speed.
Page Speed has effectively become a mobile ranking factor as announced by Google this last July and will continue to impact on SERP features (featured snippets, top stories etc.) and voice search in 2019. Another major aspect that we expect to keep on driving organic growth is the support for Accelerated Mobile Pages.
Search in 2019, besides these key 5 trends, will be once again about building relationships, providing valuable answers to people needs and keeping the audience at the very center of the content strategy.
By creating exceptional content and using artificial intelligence tools for SEO you will keep your website ahead of the curve!
Still have a question? Want to go in-depth with more insights and tips? Book a call with us and get ready to dominate SEO in 2019!
Google Top Stories is a powerful way to boost mobile SEO and CTR of news content. In this article, we describe a real-world implementation, what it takes to be picked up by Google and how to measure the traffic impact.
When Google first introduced the top stories carousel it had an immediate impact on the news and media industry that started to embrace the support for AMP pages. Top Stories are a modern, ultra-performing card-style design to present searchers with featured news stories in Google SERP.
Top Stories Carousel in Google Search
Getting featured is far from being a straightforward process as there are several requirements that need to be fulfilled and these requirements belong to different aspects of modern SEO: from AMP support, to Google News support (not required, while highly recommended), from structured data, to content editing, image preparation and page speed optimisation.
Let’s dive in and look at very basic by analyzing what we have done to bring this ultra-performing search feature to one of our SEO managed service clients. Before doing that, as usual, I like to show you the results of this work.
The effect of the top stories as seen from the Google Search Console.
The top stories news carousel is an ultra-performing SERP feature that strictly depends from your organic rankings.
Here is the checklist you need to follow to grab this mobile SEO opportunity.
1. Enable AMP
A top stories carousel is presented in the Google Developers Guide as a Search Feature that requires the implementation of AMP. So you need to support AMP on your website either as native or paired mode. Unless you are starting to develop a new project from scratch you are going to use AMP in paired mode. This basically means that you are reusing the active theme’s templates to display AMP responses. With this configuration, AMP uses a separate URLs, whether the canonical URLs for your site will not have AMP. You can use the AMP Test Tool to make sure that your pages comply with Google Search requirements for AMP.
1a. Comply with AMP logo guidelines
You need to make sure that the logo used to represent the publisher that is used in the structured data from AMP fits in a 60x600px rectangle, and either be exactly 60px high (preferred), or exactly 600px wide. A logo 450x45px would not be acceptable, even though it fits within the 600x60px rectangle.
Remember also when you have a logo with a solid background to include 6px minimum padding around it. Wanna see an example? Here is WordLift Publisher’s logo.
2. Use structured data to markup your articles
Google describes the news carousel as “a container that includes articles, live blogs, and videos” and what helps Google understand the content on the page is the required structured data. So the second step is to make sure that you are supporting one of the following schema types:
2a. When in paired mode, make sure to have the same structured data on both canonical and AMP pages
Depending on how you are generating your AMP you might end-up, as it happened to several of our clients, with a different structured data markup on your canonical and AMP pages. This shall be prevented, it is inconsistent and can’t prevent Google from showing your articles in the top stories carousel (we learned the lesson the hard way). The indication about using the same markup is provided in the Google AMP guide.
WordLift is fully compatible with the AMP Plugin (developed by Google, Automattic, and XWP) and AMP pages can inherit the schema.org markup of the canonical page and share the same JSON-LD. Read all about how to add structured data markup to AMP here.
3. Use multiple large images in your markup
Google in the article schema guide for AMP articles requires to provide, in the structured data markup, images that are at least 1.200 pixels wide and that have 800.000 pixels in total. This is not all – the guides also specifies that for best results publishers shall provide multiple high-resolution images with the following aspect ratios: 16×9, 4×3, and 1×1.
4. Remember that being part of Google News is not required but…it helps a lot!
Google can feature any article matching the above criteria in the top stories carousel based on its organic algorithmic selection but…the reality is slightly different. Let’s see why:
The Top Stories Carousel is indeed a SERP feature that evolved from the Google News box and serves the same goal,
While the main difference of the top stories carousel is that content is NOT restricted to outlets Google News approved in reality, as a result of the “fake news” scandal that exploded in November 2016, less-than-reliable sources (and smaller sites that are not in Google News) have been removed from the top stories carousel (NewsDashboard published data showing more than 99% of desktop news box results and 97% of mobile news box results are from Google News sites).
So unless you have the authority of Reddit, Yoast and alike there are much more chances for you to land in the news box if you are Google News approved. If you want to dig deeper on the relationship between Top Stories and Google News go follow this thread on the Google News Help Forum.
4a. Follow the editorial guidelines of Google News
Google provides news publishers with a set of content policies to ensure a positive experience for the readers. It is not only about being newsworthy and keep on writing fresh new content but it also about limiting advertising, preventing sponsored content, malicious links or anything that can be considered hateful, offensive or dangerous.
Here you can find all the editorial criteria to follow.
4b. Avoid article content errors
In order to be featured in Google News there are few technical aspects to be considered:
Prevent article fragmentation. If you have isolated sentences that are not grouped together into paragraphs you might get an error and your article will be rejected from Google News.
Write articles that are not too short and not too long. This basically means to write more than 80 words and prevent your pages from being too long to read. We usually see that between 600-800 words is a good match for a Google News article.
Make sure to write headlines of maximum 110 characters.
News readers want to be able to find fresh updates as fast as possible — and, especially on mobile people care a lot about the speed of a page. A top story is a mobile SERP feature that ispurely organic-driven. If you get to the top 5 results of Google you can get it and it will be an extra boost for your traffic, if you are not top ranking you will not get your spot in the news carousel (in most cases at least). Starting in July 2018, page speed has become a ranking factor for all mobile searches and this means that your website needs to be blazing fast.
How to track when you have been featured in the Top Stories
Tracking traffic generated from the Top Stories is not immediate and can only be done by looking at specific queries from the Google Search Console, using third-party tools like Semrush or RankRanger or look for specific patterns in Google Analytics.
The simplest way I found is to start from the Google Search Console by filtering results for Rich Results and AMP Articles.
Google Search Console configuration
When you see a spike, you can look from a mobile device the related keyword and hopefully found the matching article. Remember also that a given result might only occur in a specific country. This article here, for example, was only visible from Google in the US so we could only detect it by changing the territory in the Google Search preferences and using the incognito mode.
From Google Analytics we are also able to spot a top story by looking for a peak like the one below. As you can see that traffic, in most cases is only there for a 48-72 hours maximum.
Google Analytics for the article that entered the carousel.
Given the relationship between Google News and Top Stories you might want to analyze these patterns by filtering top articles in Google News. This can be easily done in Google Analytics by knowing that Incoming readers with referrers of ‘news.google.com’ or ‘news.url.google.com’ are from Google News.
Once again there are plenty of SERP feature optimization chances that we can leverage on when combining structured data with more traditional SEO factors and, they do create an enormous difference for your audience reach.
Did you know that over 3.5 billion searches take place on Google every day? This simply means that to get a piece of traffic and boost conversions, you need to appear on the first page of Google. And, to do so, you need to have an SEO strategy. Well, link prospecting certainly can help identify relevant opportunities for your website.
When implemented properly, SEO can double your site’s visibility in the SERPs, drive more traffic to it, help you address the right customers, boost their conversions and, above all, give you a chance to build a solid brand name.
After all, it’s 2018, and no one trusts businesses that are not online. In other words, SEO has become an obligatory investment for any business that wants to stay relevant.
Now, you don’t have to be a seasoned marketer to know that guest blogging is one of the most significant SEO practices. It’s a powerful way to build links and is basically synonymous with doing off-site SEO.
However, many digital marketing experts claim that this technique is dead. Just remember Google’s Matt Cutts, who claimed that“guest blogging has gotten too spammy” in 2014.
However, his judgment could have been wrong. Maybe guest blogging is still alive and kicking. You just need to know how to implement it properly.
So, what is the idea behind Link Prospecting?
Finding quality guest blogging opportunities may seem simple at the beginning. You run a couple of Google searches and make a list of content-rich sites in your niche, where you can publish your guest articles.
But, this sounds too good to be true. Namely, when you take a closer look at your list, you will understand the challenge you’re facing. Not all the sites on your list are worth connecting with, for instance. No matter if it’s a bad content strategy or low PA or DA, once you spot a poor-quality blog, you should run away screaming.
So, you need to do a more complex, advanced analysis and separate the wheat from the chaff. This is what link prospecting is about – finding quality and relevant sites in your niche that will give your SEO efforts an actual boost.
Why is Finding Quality Link Building Opportunities Important?
The idea behind writing awesome content and publishing it on quality sites is earning quality backlinks. Your backlink portfolio is the decisive factor for Google when assessing your site’s value. If it notices that there are numerous highly authoritative and quality links pointing back to your domain, it will consider it relevant and boost its rankings in the SERPs.
Generating exceptional backlinks can also boost your overall domain authority, expand your target audience, prove your expertise, and help you establish a recognizable brand. This is also an opportunity to build relationships with the influencers in your niche and boost your exposure. Namely, once they see that the top players in your industry share or link to your posts organically, your target audience will trust you more.
How to Know which Sites are Valuable Enough?
To make sure you find the right prospects, you first need to set your objectives clearly. For instance, if you want to boost your authority in your niche via guest posting, you need to become a regular contributor on all major sites in that industry – so, just make an actionable list and go!
On the other hand, if you just want to earn some organic and high-quality links, guest posting will be much simpler for you. Of course, you will have a much longer list of prospects to connect with and publish your work. All you have to do is check the site’s DA, see if they published guest posts before, and reach out to them.
Once you select the right targets, you need to see who their target audience is and what their niche is. You should also check traffic and see if people visit their site, as well as pay attention to their backlink portfolio, the quality of their articles, and engagement metrics like the number of shares, likes, comments. These are all some key performance indicators that tell you whether the site is worth your attention.
Finding Quality Link Prospects
Once you set your goals, understand the metric you need to track, and what sort of sites you should be looking for, you can start your search. Here are a few most effective link prospecting ideas you should keep in mind:
Automate your link prospecting efforts using link building tools. These tools will analyze and choose only quality link building opportunities for you, give you invaluable data about your prospects, show their contact emails, helping you find the right sites and connect with them much faster.
Conduct competitor analysis to monitor and replicate their most effective link building strategies.
Take the time to produce original images and include them in your piece – that can become an effective SEO strategy to bring traffic back to your site!
Look for influencers to boost your authority. To do so effectively, you can use Twitter search or its advanced options or simply use a link prospecting tool.
Back to Us
Link prospecting is an immensely important part of building valuable backlinks. It helps you publish your content on quality sites that will really bring value to your SEO. Most importantly, it helps you improve your visibility, expand your target audience, and position yourself as authoritative. And, these are just some of a myriad of practices you may use to find relevant link building opportunities.
Emma Miller is a digital marketer and blogger from Sydney. After getting a marketing degree she started working with Australian startups on business and marketing development. Emma writes for many relevant, industry related online publications and does a job of an Executive Editor at Bizzmark blog and a guest lecturer at Melbourne University. Interested in marketing, startups and the latest business trends.
As search engines move toward voice search, mobile personal assistants adoption is growing at a fast rate. While the transition is already happening, there is another interesting phenomenon to notice. The SERP has changed substantially in the last couple of years. As Google rolls out new features that appear on the “above the fold” (featured snippets, knowledge panels and featured snippets filter bubbles) those allow us to understand how voice search might look like.
In this article, we’ll focus mainly on the knowledge panel, why it is critical and how you can get it too.
The Knowledge Panel: The Google’s above the fold worth billions
The knowledge panel is a feature that Google uses to provide quick and reliable information about brands (be them personal or company brands). For instance, in the case above you can see that for the query “who’s Gennaro Cuofano” on the US search results Google is giving both a featured snippet (on the left) and a knowledge panel (on the right).
While the featured snippet aim is to provide a practical answer, fast; the knowledge panel aim is to provide a reliable answer (coming from a more authoritative source) and additional information about that brand. In many cases, the knowledge panel is also a “commercial feature” that allows brands to monetize on their products. For instance, you can see how my knowledge panel points toward books on Amazon that could be purchased in the past.
This space on the SERP, which I like to call “above the fold” has become the most important asset on the web. While Google first page remains an objective for most businesses, it is also true, that going toward voice search traffic will be eaten more and more by those features that appear on the search results pages, even before you get to the first position.
How does Google create knowledge panels? And how do you get one?
Knowledge panel: the key ingredient is Google’s knowledge vault
When people search for a business on Google, they may see information about that business in a box that appears to the right of their search results. The information in that box, called the knowledge panel, can help customers discover and contact your business.
In most cases, you’ll notice two main kinds of knowledge panels:
While brand panels provide generic information about a person or company’s brand, local panels offer instead information that is local. In the example above, you can see how the local panel provides the address, hours and phone of the local business. In short, that is a touch point provided by Google between the user and the local business.
Where does Google get the information from the knowledge panel? Google itself specifies that “Knowledge panels are powered by information in the Knowledge Graph.”
What is a knowledge graph?
Back in 2012 Google started to build a “massive Semantics Index” of the web called knowledge graph. In short, a knowledge graph is a logical way to organize information on the web. While in the past Google could not rely on the direct meaning of words on a web page, the knowledge graph instead allows the search engine to collect information on the web and organize it around simple logical phrases, called triples (for ex. “I am Gennaro” and “Gennaro knows Jason”).
Those triples are combined according to logical relationships, and those relationships are built on top of a vocabulary called Schema.org. In short, Schema.org defines the possible relationships available among things on the web.
Thus, two people that in Schema are defined as entity type “person” can be associated via a property called “knows.” That is how we might make clear to Google the two people know each other.
From those relationships among things (which can be people, organizations, events or any other thing on the web) a knowledge graph is born:
Example of a knowledge graph shaped on a web page from FourWeekMBA that answers the query “Who’s Gennaro Cuofano”
Where does Google get the information to comprise in its knowledge graph? As pointed out on Go Fish Digital, some of the sources are:
In short, there isn’t a single source from where Google mines the information to include in its knowledge panels.
Is a knowledge panel worth your time and effort?
Is it worth it to gain a knowledge panel?
A knowledge panel isn’t only the avenue toward voice search but also an organic traffic hack. It’s interesting to see how a good chunk of Wikipedia traffic comes from Google’s knowledge panels. Of course, Wikipedia is a trusted and authoritative website. Also, one consequence of knowledge panels might be the so-called no-clicks searches (those who don’t necessarily produce a click through from the search results pages).
Yet, as of now, a knowledge panel is an excellent opportunity to gain qualified traffic from search and get ready for voice search.
As search is evolving toward AEO, it also changes the way you need to look at content structuring. As Google SERP adds features, such as featured snippets and knowledge panels, those end up capturing a good part of the traffic. Thus, as a company, person or business you need to understand how to gain traction via knowledge panels. The key is Google’s knowledge graph, which leverages on Google knowledge vault.
It is your turn now to start experimenting to get your knowledge panel!
DBpedia has served as a Unified Access Platform for the data in Wikipedia for over a decade. During that time DBpedia has established many of the best practices for publishing data on the web. In fact, that is the project that hosted a knowledge graph even before Google coined the term. For the past 10 years, they were “extracting and refining useful information from Wikipedia”, and are expert in that field. However, there was always a motivation to extend this with other data and allow users unified access. The community, the board, and the DBpedia Association felt an urge to innovate the project. They were re-envisioning DBpedia’s strategy in a vital discussion for the past two years resulting in new mission statement: “global and unified access to knowledge graphs”.
Last September, during the SEMANTiCS Conference in Vienna, Andrea Volpini and David Riccitelli had a very interesting meeting with Dr. Ing. Sebastian Hellmann from the University of Leipzig, who sits on the board of DBpedia. The main topic of that meeting was the DBpedia Databus since we at WordLift are participating as early adopters. It is a great opportunity to add links from DBpedia to our knowledge graph. On that occasion, Andrea asked Sebastian Hellmann to participate in an interview, and he kindly accepted the call. These are the questions we asked him.
Sebastian Hellmann is head of the “Knowledge Integration and Language Technologies (KILT)” Competence Center at InfAI. He also is the executive director and board member of the non-profit DBpedia Association. Additionally, he is a senior member of the “Agile Knowledge Engineering and Semantic Web” AKSW research center, focusing on semantic technology research – often in combination with other areas such as machine learning, databases, and natural language processing. Sebastian is a contributor to various open-source projects and communities such as DBpedia, NLP2RDF, DL-Learner and OWLG, and has been involved in numerous EU research projects.
Head of the “Knowledge Integration and Language Technologies (KILT)" Competence Center at InfAI, DBpedia
How DBpedia and the Databus are planning to transform linked data in a networked data economy?
We have published data regularly and already achieved a high level of connectivity in the data network. Now, we plan a hub, where everybody uploads data. In that hub, useful operations like versioning, cleaning, transformation, mapping, linking, merging, hosting are done automatically and then again dispersed in a decentral network to the consumers and applications. Our mission incorporates two major innovations that will have an impact on the data economy.
Providing global access That mission follows the agreement of the community to include their data sources into the unified access as well as any other source. DBpedia has always accepted contributions in an ad-hoc manner, and now we have established a clear process for outside contributions.
Incorporating “knowledge graphs” into the unified access That means we will reach out to create an access platform not only to Wikipedia (DBpedia Core) but also Wikidata and then to all other knowledge graphs and databases that are available.
The result will be a network of data sources that focus on the discovery of data and also tackles the heterogeneity (or in Big Data terms Variety) of data.
What is DBpedia Databus?
The DBpedia Databus is part of a larger strategy following the mission to provide “Global and Unified Access to knowledge”. The DBpedia Databus is a decentralized data publication, integration, and subscription platform.
Publication: Free tools enable you to create your own Databus-stop on your web space with standard-compliance metadata and clear provenance (private key signature).
Integration: DBpedia will aggregate the metadata and index all entities and connect them to clusters.
Subscription: Metadata about releases are subscribable via RSS and SPARQL. Entities are connected to Global DBpedia Identifiers and are discoverable via HTML, Linked Data, SPARQL, DBpedia releases and services.
DBpedia is a giant graph and the result of an amazing community effort – how is the work being organized these days?
DBpedia’s community has two orthogonal, but synergetic motivations:
Build a public information infrastructure for greater societal value and access to knowledge;
Business development around this infrastructure to drive growth and quality of data and services in the network.
The main motivation is to be finally able to discover and use data easily. Therefore, we are switching to the Databus platform. The DBpedia Core releases (Extraction from Wikidata and Wikipedia) are just one of many datasets that are published via the Databus platform in the future. One of the many innovations here is that DBpedia Core releases are more frequent and more reliable. Any data provider can benefit from the experience we gained in the last decade by publishing data like DBpedia does and connect better to users.
We’re planning to give our WordLift users the option to join the DBpedia Databus. What are the main benefits of doing so?
The new infrastructure allows third parties to publish data in the same way as DBpedia does. As a data provider, you can submit your data to DBpedia and DBpedia will build an entity index over your data. The main benefit of this index is that your data becomes discoverable. DBpedia acts as a transparent middle-layer. Users can query DBpedia and create a collection of entities they are interested in. For these sets, we will provide links to your data, so that users can access them at the source.
For data providers our new system has three clear-cut benefits:
Their data is advertised and receives more attention and traffic redirects;
Once indexed, DBpedia will be able to send linking updates to data providers, therefore aiding in data integration;
The links to the data will disseminate in the data network and generate network-wide integration and backlinks.
Publishing data with us means connecting and comparing your data to the network. In the end, DBpedia is the only database you need to connect with to in order to get global and unified access to knowledge graphs.
DBpedia and Wikidata both publish entities based on Wikipedia and both use RDF and the semantic web stack. They do fulfill quite different tasks though. Can you tell us more about how DBpedia is different from Wikidata and how these two will co-evolve in the next future?
As a knowledge engineer, I have learned a lot by analyzing the data acquisition processes of Wikidata. In the beginning, the DBpedia community was quite enthusiastic to submit DBpedia’s data back to Wikimedia via Wikidata. After trying for several years, we had to find out that it is not as easy to contribute data in bulk directly to Wikidata as the processes are volunteer-driven and allow only small-scale edits or bots. Only a small percentage of Freebase’s data was ingested. They follow a collect and copy approach, which ultimately inspired the sync-and-compare approach of the Databus.
Data quality and curation follow the Law of Diminishing Returns in a very unforgiving curve. In my opinion, Wikidata will struggle with this in the future. Doubling the volunteer manpower will improve quantity and quality of data by dwindling, marginal percentages. My fellow DBpedians and I have always been working with other people’s data and we have consulted hundreds of organizations in small and large projects. The main conclusion here is that we are all sitting in the same boat with the same problem. The Databus allows every organization to act as a node in the data network (Wikidata is also one node thereof). By improving the accessibility of data, we open the door to fight the law of diminishing returns. Commercial data providers can sell their data and increase quality with income; public data curators can sync, reuse and compare data and collaborate on the same data across organizations and effectively pool manpower.
If you are a web content writer, there is no need to remind you all the struggle you have to face to distribute your content. Maybe you spend hours – or even days! – of hard work writing awesome content, but once your article is done, you know that your job has just begun. Now it’s time to fine-tune your content for SEO purposes, share it on several channels, monitor search keywords for your next article… Wouldn’t be wonderful to just focus on writing and nothing more?
Semantic markup is the key to success. Schema markup can really help your pages get the traffic they deserve. How? To explain it, we need to do a few steps back: first of all, you need to know what schema.org is.
What is schema.org markup
Schema.org is an initiative launched in 2011 by the world’s largest search engines (Bing, Google, and Yahoo!) to implement a shared vocabulary and adopt standard formats to structure data on web pages.
Schema.org markup helps machines understand your content, without fail or ambiguity.
Let’s explore how to use the Schema markup, the benefits of using it and how it can be implemented on your WordPress website.
How to add Schema.org markup to WordPress
To use schema markup on your pages, you can either use a tool like WordLift or do it manually. WordLift plugin enables you to add Schema markup on WordPress without writing a single line of code. Once you configured the plugin, a new menu will appear on the right side of your article in the WordPress editor: it will allow you to annotate your content and, by doing so, to create an internal vocabulary to your website or blog.
WordLift uses JSON-LD to inject schema.org markup in your web pages. Click here to see the magic: it’s a gif which shows you the data representation of this article with JSON-LD!
Imagine you have published an event on your website: once you completed creating your specific content, the final step will be to add a normal meta description, which will appear on the search page as plain text. But, by adding Schema markup to the page, you can really help your content stand out by transforming it into a rich snippet and therefore getting a lot more clicks 😉
There are several types of schema you can use to mark your content, and by using the event schema markup is possible to show dates, locations and any other detail related to a specific event to help people easily get access to all the information they might need:
Once the purpose of adding structured data is clear – that is to provide accurate information about what your content’s website is about, you could also see that adding Schema markup to your site really is a highly-customizable process.
How to increase your traffic with semantic markup
While crawling the web looking for some specific content to be served to users, search engines will unquestionably identify the context your articles belong to. Nowadays this is the most effective and affordable way to distribute your content and made it “findable” to those who are looking for it through Search Engines.
The example above shows the results of a long-tail search about the upcoming Salzburgerland Party Meeting event. As you can see, the first result is a rich snippetwith 2 links and allows you to skip directly to the next events. All that is made possible by the markup, which helps search engines detect the structured data matching the user’s answer inside the whole website. It’s been proven that rich snippets increase the Click Trough Rate: so, more qualified traffic for you, here!
Salzburgland.com uses WordLift to structure its content.
Moreover, you can explore new ways to disseminate your content based on chatbots, which can serve your just-baked articles to your readers depending on their interests.
In the image on the right side, you can see how Intelligent Agents such as Google Allo can answer your voice search questions with appropriate content if they are correctly structured.
Assess markup quality with Google’s Structured Data Testing Tool
Once you added your schema markup to WordPress, it’s easy to determine that everything was done right, simply by using the Structured Data Testing Tool made available by Google. Just enter the URL you need to analyze and let the tool verify your content.
Let’s see, as an example, the markup of the SEMANTiCS 2018 Conference on our blog:
As we can see, everything worked just fine, there’s only 1 warning about the field Offer that in this case has no value added.
The first rule while adding schema markup is to be clear. Google will know! Also, remember that adding schema markup to your page might as well not guarantee any result at first. But it’s always recommended to do it because it can definitely give you the best chance for success in SERPs, and help increase your CTR.
Automating structured data markup with WordLift
While developing WordLift plugin, we focused on making more accurate than ever our schema.org markup.
Now we can say – without fear of contradiction – that our Plugin offers you one of the most extended sets of markup to structure data on a WordPress website… without writing a single line of code!
Here is a list of improvements on the markup that SEO specialists are going to appreciate:
ARTICLE: we’ve added the markup schema.org:Article for each article/blog post, publishing it with the property Main Entity of Page. Simply put: we say to Google and to the other search engines that this web page is an article. To know more about this property, read this how-to by Jarno Van Driel.
PUBLISHER: we also communicate the publisher’s information related to each article as structured data. The publisher can be an individual with his/her proper name or an organization with a brand name and a logo.
ID: with WordLift we also made available the Publisher ID. What is an ID, and why it is so important? For each entity, article, and publisher, we generate a permanent ID: a unique identifier which is fundamental in the context of 5 stars Linked Data because it allows the connections between data on the web. Each entity, article, and publisher can be connected to other data, hosted – for example – in WikiData, with the “same as” property and each of them can also be decoded with a JSON-LD data representation.
RELATED ENTITIES: we used the meta tag “mentions” to say which entities are mentioned. In this way, you’ll have a hierarchy or entities where the main one defines the article itself and the other ones are recognized as mentioned on it.
To play around with JSON-LD markup that WordLift created for this article head straight to the JSON-LD Playground.