In several cases you might need to mix structured data using different formats like microdata and json-ld; in this article we review the do’s and don’ts for these edge cases.
Can I mix microdata and json-ld?
Yes,it is totally fine to use both syntaxes side by side on the same page but Google will not be able to merge attributes for the same entity using the item ID unless you are using json-ld ONLY.
Let’s get into the details:
I can have on the same page both syntaxes (microdata and json-ld); for instance I might use microdata to render WebPage and use json-ld for Organization;
I can also merge attributes related to the same entity when all the data is available in json-ld but …
I cannot combine information related to the same entity by item ID when this information is written in microdata and json-ld. While this is possible in principle, and a pure RDF application would be able to do it, Google does not support it, which means properties won’t be merged and, most importantly, this won’t satisfy the Rich Snippets‘ requirements.
This topic is particularly relevant as microdata remains today the most widely used format for structured data (see data below collected by Aaron Bradley from the 2019 Common Crawl’s sample) and there is a huge demand to improve structured data to gain additional visibility on Google’s SERP.
To confirm that we cannot mix attributes by item ID when combining microdata and json-ld we asked the help of several SEOs with in-depth knowledge on structured linked data, includingDan Brickley, Jarno van Driel, Jono Alderson, Richard Wallis and Mark and Martha van Berkel.
Before engaging with the community we created two examples HTML pages:
json-ld + microdata: here is the result validated with the Google Structured Data Testing Tool (where you will see the “Unspecified Type” error since GSDTT cannot merge the two syntaxes);
json-ld + json-ld: here we can see that GSDTT supports the merge by type ID when data is written in json-ld
Interesting enough the first example would be properly rendered by the Structured Data Linter: a tool designed to help webmaster validate structured data markup. Here follows the information from the Twitter thread and the messages by Dan Brickley and Jarno van Driel:
in general you can use both syntaxes side by side, but you won’t get the fine-grained merging of triples by ID that a pure RDF application might expect
The way we communicate and interact online is constantly changing. Users have come to expect a much more personal and tailored experience, the type that can’t be provided using traditional ways of interaction.
When looking at the words conversational marketing, some people might be wondering what exactly that is. Well, it basically is a strategy that gives customers the personalized value they are looking for and allows businesses to scale while saving time and resources. We found out that through conversational marketing and therefore through live chats, chatbots, and social monitoring it’s possible to promote genuine conversations and real relationships. The goal here is, of course, to enhance the user’s experience while minimizing friction.
Long gone are the days when consumers were passive recipients of marketing messages who had to be bombarded with a blatantly pushy sales pitch in order to be convinced to make a purchase. New, interactive technologies enabled them to break the fourth wall and have their say about how they feel about brands and what they expect from them. This means that the time has come for brands to learn how to listen actively while their customers do the talking. Marketing is a two-way street, and that’s the essence of conversational marketing.
What’s Conversational Marketing?
Unlike traditional marketing which heavily relied on TV commercials, billboards, newspaper ads, direct mail, and similar methods which customers learned to ignore successfully, conversational marketing enables brands to have relevant, meaningful, one-on-one conversations with their audiences across different channels of communication.
Live chat and chatbots are the first things that come to mind when it comes to conversational marketing. However, this strategy is much more than these two tools, and it can be extended to social media, phone calls, SMS, and IMs – pretty much any channel that your customers prefer.
Some of the benefits of such an approach include:
Being available 24/7. This is something that your customers will appreciate as you’re putting their needs first, and override your regular working hours which are somewhat limiting. AI-powered bots can answer customers’ questions in real time, be it 7 a.m or midnight. No wonder that by 2020, more than 85% of customer support interactions will be handled by chatbots.
Getting to know your audience on a more profound level. These chats and conversations are a gold mine of customer information, and they can help you understand your audience better and start using their language in your messaging.
Humanizing your brand. By combining live chat, bots, and social media, your outreach will be much more natural, and you’ll avoid using generic request forms which your customers don’t consider particularly promising in terms of providing them with timely responses.
1. Sephora’s Virtual Artist
The upscale beauty retailer stepped up its marketing game by introducing the Sephora Virtual Artist feature in their Facebook Messenger bot.
This innovative AR functionality allows the brand’s customers to “try on” makeup by uploading their selfies and applying different lipstick shades, eyeshadows, and false lashes.
Besides being fun and making it easy for customers to share their makeover photos with friends in order to get valuable feedback or add them to Facebook Stories, Visual Artist offers something much more important – a try-before-you-buy experience without having to visit a physical store.
What’s even better, once a prospective shopper makes their purchasing decision, they can order the products they want directly from the thread, which additionally streamlines and improves the customer journey. The brand reports that Sephora Assistant, a similar Messenger bot for booking makeovers in one of its stores, accounts for an 11% conversion rate increase.
eBay’s Google Assistant App tremendously facilitates browsing through the company’s vast online shopping inventory and lets customers start their search by saying “Ok, Google, ask eBay to find me…”, and this smart app will ask you additional questions in an attempt to narrow down your search and provide you with the most relevant results. Once it finds the best deal, the chatbot will ask you whether to send the results to your smartphone so that you can complete your purchase.
Given that Siri, Alexa, Amazon Echo, and other voice-based assistants are increasingly popular, it’s clear that implementing such a tool can significantly boost customer engagement.
This widget comes after the online retailer’s Facebook Messenger ShopBot, which uses AI and Machine Learning in order to personalize the shopping experience based on a deeper understanding of customer intent.
Planning and executing such an effective conversational marketing strategy can be a complex endeavor, which is why it’s a good idea to consult experts from digital marketing agencies and see what the best approach will be for your company and how to make it work within your budget.
3. Domino’s AnyWare
Domino’s wants to make the process of ordering pizza as easy as pie.
Back in 2015, the company encouraged its customers to tweet or text a pizza emoji and have a pizza sent their way.
This concept evolved further, so that now with Domino’s AnyWare it’s possible to order your favorite items from their menu through a number of available options – Google Home, Alexa, Slack, Facebook Messenger, Twitter, or even a Smart TV. This versatility and abundance of different channels of communications is something that’s of vital importance to today’s picky customers, and Domino’s does everything g to meet its patrons’ preferences.
Again, personalization and an in-depth understanding of customers needs is exactly what helps Domino’s build loyalty thus making sure that its clients will come back knowing that they can easily reorder their favorite item from the menu with a single click, tweet, or word, as well as track their order and see when it will be delivered.
4. General Motors and Social Media
Although conversational marketing is mostly related to innovative chatbots powered by the latest tech, social media is another tool that can make this strategy work.
One of the best examples of this approach is General Motors and the way it dealt with the 2014 ignition switch recalls, a crisis which threatened to ruin not only the company’s finances but also its reputation.
Over the course of several months, more than 30 million cars worldwide were recalled, while the switch ignition flaw resulted in the deaths of 124 people. G.M. was transparent about the issue and owned it, raising the bar on customer support and experience along the way.
Customers flooded the company’s social media channels with distressed comments and negative feedback, and the auto giant had its customer support reps address each and every individual complaint and offered to help on the spot.
Some customers got loaner cars until their problems were solved while others were given a refund for the travel expenses caused by the malfunction of their vehicles. Instead of trying to hush things up and switching to traditional tactics such as emails, phone calls, and other more private communication channels General Motors chose to listen to their customers, hear their objections, and proactively handle this huge blunder in the public eye.
It’s time to jump on the conversational marketing bandwagon, if you already haven’t, and take a cue from these companies who mastered the art of customer experience and satisfaction with the help of this powerful strategy.
Nina is a technical researcher & writer at DesignRush, a B2B marketplace connecting brands with agencies. She loves to share her experiences and meaningful content that educates and inspires people. Her main interests are web design and marketing. In her free time, when she's away from the computer, she likes to do yoga and ride a bike. You can also find her on Twitter.
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!
Bing is starting to provide, across the world, a brand new Intelligent Search features for its SERP, powered by AI, to provide immediate answers with a new and comprehensive look and feel. In this article we’re presenting few tests of the new search capabilities and some guidelines on how to improve the visibility of your content on Bing.
Bing, with the help of machine reading-comprehension and deep neural networks, is aggregating facts from well-known data sources to provide end-users with enough confidence on the information being displayed on its search results.
Let’s start with an example based on a super simple Ego Search about myself. This panel has been around for sometimes in the US but it is now richer and it can be accessed also (when the language is set to English) from other countries.
In this specific example, the data is sourced from LinkedIn, Crunchbase and the good old Freebase. Now these are exactly the same webpages (and the datasets in the case of Freebase) that I reference in the entity about myself that is used to annotate articles on this blog. This is why, I assume that Bing, is using structured data to detect relevant data sources around entities.
Knowledge Panels
Here is how Bing can help you boost your personal branding
Here is how Bing can help your customers find out more about your company
Below the knowledge panel that Bing has created around the entity WordLift.
Instant Answers
Bing is using a machine reading comprehension technology, backed by what they call Project Brainwave, to generate the equivalent of Google’s Featured Snippets by analyzing billions of web pages to provide users with the answer they are looking for.
Let’s try with a couple of queries to see what Bing knows about WordLift. Let’s ask in the first place – “What is WordLift?”
Instant Answer on Bing for “What is WordLift?”
…and then let’s get even more specific with a query like “What is an entity in WordLift?” As you can see, results – on these very narrow queries – are indeed very impressive!
Instant Answer on Bing for “What is an entity in WordLift?“
More helpful in understanding facts about the world
Bing is also providing more ways to read facts about the world. We saw in December last year the new Perspectives Answer Box around highly debated topics like Coffee as well the new Question & Answer panel.
Now, as announced by Bing a few days ago, answer boxes also feature a descriptive tooltip for complex terms that appear in the text of the answer. Have a look at the example below where the term “Liter” is explained when highlighting the word “microliter”.
Intelligent image search
A lot has been done also to improve the image search of Bing that now uses a built-in object detection algorithm or let the user pick up a specific detail of the image with a manual crop. This really makes images way more interactive. See below an example of a photo where Bing is highlighting the two subjects.
The automatic object detection of Bing for images
2018 is definitely the year when publishing data becomes a business imperative as search engines become truly capable of providing direct answers rather than a set of web results. In this context, Bing is bringing significant innovations in the search industry by leveraging on machine reading-comprehension and deep neural networks.
Needless to say we’re particularly keen on following how search engines are starting to use artificial intelligence and how semantic rich structured data help them improve their services and in return, can help publishers improve their online visibility.
Read the full history of the SERP to learn how search engines had become capable of answering questions using natural language.
How to optimize your content for Bing’s Intelligent Search Features
Now let’s have a look at what we learned from these experiments to help you get the best out of Bing’s latest update.
1. Start using Bing Webmaster tool
It has been significantly improved and there is a lot that you can do to ensure proper indexation from Bing, to measure search traffic and even to improve the user experience on your website by using Bing-powered interactive widgets. Bing, with these widgets, works quite similarly like WordLift. It uses NLP to analyze the content of your webpage and adds an interactive widget using data from its graph. It’s a ground breaking feature and I’ll get deeper on it in the next blog post. For the time being you can preview it by visiting this example webpage.
2. Curate your entities
In the web of data, information is scattered across multiple websites and it can be analyzed and reconciled to provide a more comprehensive overview of a person, a company or a product. By curating your profile on LinkedIn, for instance, or on trusted websites like Crunchbase, GitHub or Stackoverflow you are actually publishing relevant data that Bing can effectively re-use in its knowledge panel.
3. Use structured data to help Bing reconcile content with data
As seen in these initial experiments we’re conquering a significant estate on personal keywords, branded keywords as well as questions related to our product. As algorithms start to analyze more in details the content that you have published using linked metadata and the schema.org vocabulary you can help search engines properly disambiguate these entities to find relevant information across multiple data sources and websites. By publishing articles under my name with a direct reference – in the metadata of these articles – to my LinkedIn profile I am helping Bing (and the other semantic search engines) reconcile and connect the content I write with the data that describes me.
they are using JSON-LD to interpret and analyze web pages
they are preparing a verification tool to help webmasters check the schema.org markup that will also support the JSON-LD format
Bing has been a founding member of the schema.org initiative along with Google, Yandex, and Yahoo! to help webmaster markup their content using a shared data schema.
We’ve been intercepting and sharing, along with other Semantic SEO lovers, the following tweet from Jon Henshaw, Senior SEO analyst for CBS Interactive:
? @bing just confirmed to me that they now support https://t.co/HxXsuIYRgo formatted in JSON-LD. You no longer have to use microdata!!! ?
Schema markup is metadata that you add to your website to help search engines provide more informative results for their users.
Before the arrival of schema.org back in 2011 (the initiative started in June and Yandex joined in November of the same year), there were way too many standards for marking up different types of content on web pages. While the variety of different vocabulary still exists and it is of a great value for the scientific, the academic and the librarian communities it was of little or no help for commercial search engines.
As a result of the diversity of languages, it was difficult for webmasters to decide on the most relevant and supported markup standards to use.
Creating a schema shared and supported by all the major search engines made it very easy for webmasters to add markup, and in return made it easier for search engines to create a better user experience for their users (with all different sort of enriched results, knowledge panels and other semantic powered goodies of the SERP).
In late 2014, Amazon launched Amazon Echo, a voice-activated speaker powered by the artificial intelligence of Alexa. With this move, the e-commerce giant launched a brand new category of products, the smart speakers.
It took two years to Google to follow Amazon, releasing Google Home in October 2016.
Two more years later, in 2018, the market of smart speakers is growing fast and many new players have entered the market. Just to name a few, Soros launched One, powered by Alexa, and Apple launched the Siri controlled Homepad.
Nowadays, according to a study by NPR and Edison Research, 16 percent of Americans own a smart speaker. We are talking about around 39 million people in the USA only. A recent study from Juniper Research forecasts that voice-activated speakers will be installed in over 70 million U.S. households by 2022, reaching 55% of all homes.
How you can use voice-activated speakers
From playing a playlist to more complicated tasks such as setting an alarm or a timer or even booking an Uber ride, smart speakers entered into our homes and offices as digital butlers, ready to assist us in – almost – everything we need.
They can be extremely functional when they help us interact with smart home devices and appliances, but they can also become funny, telling a joke on command and challenging the entire family with games.
Their main purpose is to assist you with voice search and help you access to many kinds of content from websites to audio books and music. Each smart speaker has slightly different functions and can interact with a certain range of third-party applications.
Are smart speakers becoming a habit?
Smart speakers are replacing traditional media for family entertainment. 30% of users say that they spent less time in front of the tv and more time playing with their favorite voice-activated artificial intelligence.
Moreover, as people get used to the robotic voices of smart speakers, they interact more often with their voice assistants in their smartphones. For 44% of the users interviewed by NPR and Edison Research, smart speakers trigger the use of other voice-activated assistants.
People are becoming accustomed to smart speakers, putting them in the very heart of their homes.
In the infographic below, based on Google‘s data, you are going to find out how smart speakers are used, how this technology affects online shopping and consumes, and what kind of relation do users have with this technology.
It’s not a surprise that voice search queries resemble natural language more than web search queries, but you may find intriguing that so many people feel like they are talking with a friend.
Is Gartner research rightwhen it states that in 2020 we are going to talk more often with virtual assistants than with our partners?
Content writing and voice-activated devices
If you are a web writer and you are trying to figure out how voice technologies are going to impact on your content follow Teodora Petkova’s webinar on how you can engage your readers on screenless devices. Enjoy!
