How the SEO game has changed — And why you need a paradigm shift

How the SEO game has changed — And why you need a paradigm shift

The SEO game has changed. That’s a fact. Just look at any Google‘s SERP to see how much.

One of the main things you will notice if you compare the same SERP in the last five years is that the first position is continuously shifting down on the SERP, often falling below the folding line.

SERP: 2015-2020 - How the SERP changed in the last 5 Years
The screenshot above shows how a specific SERP evolved in the last 5 years. Andy Crestodina explored this evolution on Orbit Media.

This is not even just Google or Bing. Have a look at what happens on Baidu’s SERP in the Chinese search market.

Here is how a SERP on Baidu looks like today

What does really happen when a SERP is such rich and visual?

The presence of rich snippets, such as a sponsored product carousel, video carousel, featured snippet, a knowledge panel, a PAA, and many others, changes the way a user looks at the SERP. According to a study by the Nielsen Norman Group, 74% of the users look at the rich results.

In other words, the visual impact of SERP features influences the path of the user’s gaze and, since the number of features can vary from query to query, the gaze pattern is nonlinear. It bounces around between visual elements, resembling the path of a pinball.

The Pinball Pattern for the Nielsen Norman Group

A User Centered Search (and Discover) Experience

Another few things that you might notice, is that the SERP is moving in two directions that are complementary.

Once Google was reactive: the user typed a search, it answered to the search with a bunch of results. And those results were common, meaning that every user would have got the same list of links while typing the same phrase.

Nowadays, Google is proactive and the results are personalized and vary by user, location, time in the day, device… and many other factors. In this way you might not have the same SERP twice.

Google Discover is an example on how Google is moving from reactivity to proactivity, offering the users a selection of content based on their previous searches and behaviour.

Which are the winning strategies in SEO today?

Here are some practical tips that could help you get some rich results and therefore the attention of the users.

  • Create an entity in the Knowledge Graph — the best way to start doing this is publishing 5-stars linked open data. And that’s WordLift’s job. 😎
  • Write quality content which will help you build your brand authoritativeness and uplift your rankings.
  • Frequently update your content to stay relevant and useful to your users.
  • Think mobile-first, paying attention to critical technical factors such as speed and performance.
  • Work on a multi-format strategy, producing different kinds of format such as texts, images, videos — possibly around the same content.

Have a look at the video below, to see a practical demonstration of how WordLift can help you get rich results through structured data.

How Google works — and how you can get users’ attention

Learn more

If you want to learn more tips and tricks about SEO, just click on the button below and book a demo with one of our experts.

The Role of Content Structuring in Voice Search and Beyond

The Role of Content Structuring in Voice Search and Beyond

In 1996 Bill Gates wrote “Content is King”, predicting a world where content would have been the main wealth on the Internet. Although this prediction has been a catchphrase in the contest of digital marketing in the 2000s, nowadays it could sound a little naive. It isn’t, if you rethink content separating it from its containers and try to understand and follow its law

Don’t think in terms of pages, think in terms of entities

Pages are just one of a thousand ways in which content can be rendered and displayed to your users. An entity is the real single brick of your content strategy. It can be displayed through a page, but it’s something more. It is a thing (or a person, a place, an event, etc.) that has its own properties and relationships with other things. 

Adding schema.org markup to your content you can define and describe your entities and help search engines better understand your content. Let’s say for example you have a recipe: as an entity, this recipe will have many properties such as recipeCuisine, recipeIngredient, recipeInstructions, recipeYield… and a lot more. All these properties can connect the entity to other entities or just exist as single data points. 

On the left side, you see a recipe on IINH, as users would see it on the web page, while on the right side, you have the same recipe as Google sees it through structured data.

Let’s say I’m looking for an apple pie with one single egg — because I have just one in the fridge, semantic search engines could give me the right recipe thanks to the additional information related to the entity. So, in the end, entities allow you to give a better answer to your potential readers

The same recipe presented on Google’s SERP in the recipe carousel

Why are entities relevant in this context?

Structured content can help you build Actions for the Google Assistant upon some entity types such as recipes, how-tos, news articles and podcasts. And here is how schema.org markup comes handy for voice search

Moving from building pages to creating structured data helps us create relationships between entities that matter. Entities are not isolated items, they are all connected into a cluster which is semantically meaningful.

This means that through entities you can feature different angles of a complex thing. 

For example connecting all information related to a course or a webinar across multiple pages can be strategic to stand out on Google search and is the best way to answer to different user intents. 

Structure your content building your own content model — and stick with that

As I said before, entities are just the first brick of your content strategy. Content modeling is the law that underlies your content. Structuring the content of your website allows you to reuse it in different formats and match different search intents. 

For example, the content model of the WordLift Academy allows us to repurpose our content in different formats. Each main content is a webinar which is connected to different data points such as creation date and duration, other entities such as the topics covered during the webinar and the main speaker, and media such as the cover image, the profile picture of the speaker, and the video recording. 

The Entity-based content model of the WordLift Academy

All this information can answer to different search intents and function as different entry points to the main content. 

Experiment new formats starting from your content wealth  💎

Now, let me tell you a story. 

Recently, we’ve joined Google’s Mini Apps Early Access Pilot. The idea was to offer to the user an app experience built into the SERP to navigate into the Academy content. 

I won’t enter into the details of the technological stack used to create this Mini App prototype through Google’s console. What matters here is that, having a structured content we have refined the search for WordLift courses allowing the users to navigate through them by selecting one or more topics of interest and/or a speaker. 

A preview of the WordLift Mini App and some query examples

As the pilot has been shut down due to COVID-19, you won’t see it on the SERP anytime soon. 😭 But… we are planning the same structure — well, with a few changes in terms of technology – to build an Assistant App for Google. 🚀

So users will be able, for example, to look for all the webinars about SEO by Jason Barnard on our Academy just invoking the App.  

What’s the take-away of this story? 

Formats may change and evolve, experiments come and go… but a strong content model allows you to reuse your content in different environments.

Is Voice Search Here to Stay? It is now 2020

If you want to learn more about how voice search is evolving in 2020, have a look at the webinar below, with me and Georgie Kemp getting deeper into this topic.

Is Voice Here to Stay? It is now 2020 — Streamed live on May 22, 2020 by Authoritas
How to turn your content model into a powerful marketing and SEO weapon

How to turn your content model into a powerful marketing and SEO weapon

Providing your website with a structured content model is not only the best solution to better organize your content, but also a powerful strategy to improve the SEO of your website and increase organic traffic.

In this article, we’ll explain how the WordLift entity-based model, coupled with the new feature WL Mappings, will allow you to add a more specific markup to your content and to obtain a Knowledge Graph capable of communicating to search engines in a more effective way.

Why is the content model becoming a key tool for SEO?

During his webinar on content modeling for SEO in the WordLift Academy, Cruce Saunders highlights some of the main features that make the content model an indispensable tool for managing and enhancing online content.

In fact, the content model:

  • Specifies how information is organized on your website
  • Makes content more visible to search engines
  • Allows you to reuse content through different channels

Structured content model, in short, not only allows you to better organize data and information but to do it within a malleable structure capable of communicating:

  • to search engines through the use of structured data
  • to users through the enhancement of the user experience and the possibility of reusing the content by presenting it in the form of different layouts both on the site and in the SERP to respond to specific search intents (the same article, for example, may appear in the form of a snippet, of blue link, promotion, etc.)

Structuring your content model means creating a three-dimensional identity capable of highlighting your content and the relationships underlying it. This allows search engines to recognize you among hundreds of pieces of information, making you more visible to users who correspond to the search intent related to your business.

The more the content model is rich in structured data, the more chances you’ll have to meet exactly the users interested in you. That’s why we created WordLift Mappings, a new feature that allows you to select the information and connections that are truly relevant for your business and to create an increasingly specific and refined Knowledge Graph to highlight only the most relevant facets that make your identity more authoritative. 

Through our entity-based model and WordLift Mappings, your content model becomes a powerful SEO weapon and a valuable resource to increase the value of your online data.

WordLift Mappings helps you create a custom Knowledge Graph and increase your online authority

WordLift creates a personalized and highly performing Knowledge Graph through the schema.org markup and the creation of a customized entity-based vocabulary containing the most relevant data to help Google better understand your online content.

Remember that Google uses entities to satisfy users’ search intent and allow them to find the best results. For this reason, an increasingly refined entity-based model such as WordLift is key to increase the visibility of your content for search engines.

WordLift Mappings increases the accuracy of this process and allows you to take greater care of your content and your Knowledge Graph.

Advanced Custom Field for Schema.org: how the new WordLift extension works

By connecting to ACF (Advanced Custom Field), a WordPress plugin that allows you to create advanced fields to specify the attributes that characterize your content, WordLift Mappings allows you to structure your data starting from the fields that you have already configured with ACF or from new fields based on the schema.org taxonomy.

This means having more and more structured content, which can be used to add relevant details to your Knowledge Graph and shaped in different configurations to improve the user experience.

In this webinar, Andrea Volpini and Jason Barnard explain how they used WordLift Mappings to improve Jason’s content model and Knowledge Graph. Jason shows how he obtains a Knowledge Graph in which only the most relevant data to create an authoritarian and coherent Brand SERP are structured to stand out in the search results.

With over 100 podcasts made in collaboration with some of the greatest SEO experts on the planet, Kalicube – Jason Barnard‘s website – has an enviable wealth of content, relevant to the entire digital marketing sector. Thanks to WordLift Mappings, we helped Jason structure this content by following a model that focuses on content, events and people. Thus, each guest of Jason’s podcast has his own page connected with the podcasts in which he participated and with the events in which the podcasts were recorded.

In this way, the architecture of the Knowledge Graph is customized on the basis of the content model and the “network” of the links between the contents becomes the bearer of meanings and allows you to predict further connections. Below you can see the entity-based content model applied to Kalicube through WordLift Mappings.

What can you realistically expect in terms of traffic? How long does it take?

In recent weeks, our SEO team has implemented a new content model on the site of an American customer who deals with the dismantling and re-evaluation of used hardware on a large scale.

The results? After the first week, traffic increased by 14.6% and the growth curve does not seem to stop. To analyze the impact, isolating other factors that may influence the SEO of the site, we have developed a predictive model based on Bayesian networks which, analyzing the traffic in the month preceding the introduction of the WordLift Mappings, allowed us to isolate the benefit to the net of other ranking factors (it’s called causal inference analysis).

Here we see the real clicks in black and the traffic we would have had in blue (that is, the traffic predicted by the mathematical model), then in the following chart the difference between the real traffic and the estimated traffic and finally the delta of increase. In this way, we can be sure that, as analyzed, it has statistical relevance and is related to the introduction of the new content model. 💪

Data source: Google Search Console

In summary, WordLift Mappings allows you to:

  • Build a Custom Knowledge Graph based on your content model
  • Improve the SEO of your website through structured data
  • Shape the structure of your content to improve the user experience
  • Reuse chunks of content through different configurations to respond to different research purposes
  • Enhance any type of content composed of reusable elements (articles, courses, events, How-Tos etc.)

The implementation of a custom Knowledge Graph through WordLift Mappings has a positive and measurable impact on traffic.

Drew Gula is the copywriter at Soundstripe, a company that creates royalty free music to help businesses produce better video content.

Drew Gula

Copywriter, Soundstripe

SERP Analysis with the help of AI

SERP Analysis with the help of AI

SERP analysis is an essential step in the process of content optimization to outrank the competition on Google. In this blog post I will share a new way to run SERP analysis using machine learning and a simple python program that you can run on Google Colab. 

Jump directly to the code: Google SERP Analysis using Natural Language Processing

SERP (Search Engine Result Page) analysis is part of keyword research and helps you understand if the query that you identified is relevant for your business goals. More importantly by analyzing how results are organized we can understand how Google is interpreting a specific query. 

What is the intention of the user making that search?

What search intent Google is associating with that particular query?

The investigative work required to analyze the top results provide an answer to these questions and guide us to improve (or create) the content that best fit the searcher. 

While there is an abundance of keyword research tools that provide SERP analysis functionalities, my particular interest lies in understanding the semantic data layer that Google uses to rank results and what can be inferred using natural language understanding from the corpus of results behind a query. This might also shed some light on how Google does fact extraction and verification for its own knowledge graph starting from the content we write on webpages. 

Falling down the rabbit hole

It all started when Jason Barnard and I started to chat about E-A-T and what technique marketers could use to “read and visualize” Brand SERPs. Jason is a brilliant mind and has a profound understanding of Google’s algorithms, he has been studying, tracking and analyzing Brand SERPs since 2013. While Brand SERPs are a category on their own the process of interpreting search results remains the same whether you are comparing the personal brands of “Andrea Volpini” and “Jason Barnard” or analyzing the different shades of meaning between “making homemade pizza” and “make pizza at home”. 

Hands-on with SERP analysis

In this pytude (simple python program) as Peter Norvig would call it, the plan goes as follow:

  • we will crawl Google’s top (10-15-20) results and extract the text behind each webpage
  • we will look at the terms and the concepts of the corpus of text resulting from the download, parsing, and scraping of web page data (main body text) of all the results together, 
  • we will then compare two queriesJason Barnard” and “Andrea Volpini” in our example and we will visualize the most frequent terms for each query within the same semantic space, 
  • After that we  will focus onJason Barnard” in order to understand the terms that make the top 3 results unique from all the other results, 
  • Finally using a sequence-to-sequence model we will summarize all the top results for Jason in a featured snippet like text (this is indeed impressive),
  • At last we will build a question-answering model on top of the corpus of text related toJason Barnard” to see what facts we can extract from these pages that can extend or validate information in Google’s knowledge graph.

Text mining Google’s SERP

Our text data (Web corpus) is the result of two queries made on Google.com (you can change this parameter in the Notebook) and of the extraction of all the text behind these webpages. Depending on the website we might or might not be able to collect the text. The two queries I worked with are “Jason Barnard” and “Andrea Volpini” but you can query of course whatever you like.   

One of the most crucial work, once the Web corpus has been created, in the text mining field is to present data visually. Using natural language processing (NLP) we can explore these SERPs from different angles and levels of detail. Using Scattertext  we’re immediately able to see what terms (from the combination of the two queries) differentiate the corpus from a general English corpus. What are, in other words, the most characteristic keywords of the corpus. 

The most characteristics terms in the corpus.

And you can see here besides the names (volpini, jasonbarnard, cyberandy) other relevant  terms that characterize both Jason and myself. Boowa a blue dog and Kwala a yellow koala will guide us throughout this investigation so let me first introduce them: they are two cartoon characters that Jason and his wife created back in the nineties. They are still prominent as they appear on Jason’s article on a Wikipedia as part of his career as cartoon maker.

Boowa and Kwala

Visualizing term associations in two Brand SERPs

In  the scatter plot below we have on the y-axis the categoryJason Barnard” (our first query), and on the x-axis the category for “Andrea Volpini”. On the top right corner of the chart we can see the most frequent terms on both SERPs – the semantic junctions between Jason and myself according to Google.

Not surprisingly there you will find terms like: Google, Knowledge, Twitter and SEO. On the top left side we can spot Boowa and Kwala for Jason and on the bottom right corner AI, WordLift and knowledge graph for myself.  

To extract the entities we use spaCy and an extraordinary library Jason Kassler called Scattertext.

Visualizing the terms related to “Jason Barnard” (y-axis) and “Andrea Volpini” (x-asix). The visualization is interactive and allows us to zoom on a specific term like “seo”. Try it.

Comparing the terms that make the top 3 results unique

When analyzing the SERP our goal is to understand how Google is interpreting the intent of the user and what terms Google considers relevant for that query. To do so, in the experiment, we split the corpus of the results related to Jason between the content that ranks in position 1, 2 and 3 and everything else.

On the top the terms extracted from the top 3 results and below everything else. Open the chart on a separate tab from here.

Summarizing Google’s Search Results

When creating well-optimized content professional SEOs analyze the top results in order to analyze the search intent and to get an overview of the competition. As Gianluca Fiorelli, whom I personally admire a lot, would say; it is vital to look at it directly.

Since we now have the web corpus of all the results I decided to let the AI do the hard work in order to “read” all the content related to Jason and to create an easy to read summary. I’ve experimented quite a lot lately with both extractive and abstractive summarization techniques and I found that, when dealing with an heterogeneous multi-genre corpus like the one we get from scraping web results, BART (a sequence-to-sequence text model) does an excellent job in understanding the text and generating abstractive summaries (for English).

Let’s it in action on Jason’s results. Here is where the fun begins. Since I was working with Jason Barnard a.k.a the Brand SERP Guy, Jason was able to update his own Brand SERP as if Google was his own CMS 😜and we could immediately see from the summary how these changes where impacting what Google was indexing.

Here below the transition from Jason marketer, musicians and cartoon maker to Jason full-time digital marketer.

Can we reverse-engineer Google’s answer box?

As Jason and I were progressing with the experiment I also decided to see how close a Question Answering System running Google , pre-trained models of BERT, could get to Google’s answer box for the Jason-related question below.

Quite impressively, as the web corpus was indeed, the same that Google uses, I could get exactly the same result.

A fine-tuning task on SQuAD for the corpus of result of “Jason Barnard”

This is interesting as it tells us that we can use question-answering systems to validate if the content that we’re producing responds to the question that we’re targeting.

Ready to transform your marketing strategy with AI? Let's talk!

Lesson we learned

We can produce semantically organized knowledge from raw unstructured content much like a modern search engine would do. By reverse engineering the semantic extraction layer using NER from Google’s top results we can “see” the unique terms that make web documents stand out on a given query.

We can also analyze the evolution over time and space (the same query in a different region can have a different set of results) of these terms.

While with keyword research tools we always see a ‘static’ representation of the SERP by running our own analysis pipeline we realize that these results are constantly changing as new content surfaces the index and as Google’s neural mind improves its understanding of the world and of the person making the query.

By comparing different queries we can find aspects in common and uniqueness that can help us inform the content strategy (and the content model behind the strategy). 

Are you ready to run your first SERP Analysis using Natural Language Processing?

Get in contact with our SEO management service team now!

Credits

All of this wouldn’t happen without Jason’s challenge of “visualizing” E-A-T and brand serps and this work is dedicated to him and to the wonderful community of marketers, SEOs, clients and partners that are supporting WordLift. A big thank you also goes to the open-source technologies used in this experiment:

5 Best Chatbot Examples to Significantly Improve Your User Experience

5 Best Chatbot Examples to Significantly Improve Your User Experience

Imagine your online shopping experience.

In the past, customers would browse endlessly to find a product that they like. They scour customer testimonials, product information and referrals to assess their purchasing decision. If they have more questions, then they would schedule a live chat or online call with customer service. 

Today, chatbots are expected to automate these processes. Unlike conversing with customer support staff, chatbots can communicate through a conversational messaging interface. 

It works by letting users choose and tap several options. They can ask for product recommendations, make requests and receive personalized responses from a bot powered by AI

For instance, eBay’s chatbot lets customers send details of the products that they’re looking for like “women’s hiking shoes under $75”. In return, they receive recommendations with their ideal prices and shoe size. 

…and the bot can guide customers along the purchasing process too. It’s designed to collect information on a customer’s needs and intent, so they can seamlessly move across the sales funnel. 

Benefits of Chatbots 

Still not convinced? Let’s take a look at some of the benefits of leveraging chatbot solutions. 

Faster Service

The shift to chatbots is part of an attempt to meet customer demands. As brands grow their customer base, support teams struggle to resolve every complaint and respond to every query. 

In contrast, chatbots can communicate with hundreds of customers at the same time and work 24/7 to boot. Hence, customers can shop conveniently through their smartphones and tablets.

According to Hubspot, 71% of customers use messaging apps to get in touch with customer service so their problems are resolved fast. Additionally,  90% of businesses also claim quicker complaint resolution through chatbots.

Non-Intrusive 

You’ve probably heard this benefit parroted by marketers and businesses who have reaped the benefits from chatbot automation.

Compared to email marketing and social media marketing, chatbots are a non-intrusive means of communicating with customers. The users initiate the conversation with chatbots, not the other way around. Customers can also control whether or not they’ll receive brand-related messages. If they don’t want to continue communication, they can mute the conversation.

Gain Customer Insights 

By asking questions and assessing shopping behavior, chatbots can generate personalized product offerings for their customers. They can determine the products to upsell, redevelop and market based on a user’s data. It’s eerily similar to communicating with a staff that knows all your likes, dislikes and preferences. 

How Chatbots Can Improve User Experience

Chatbots can significantly boost a businesses’ user experience by providing faster and personalized service. 

How can your business leverage chatbots? Here’s a list of companies that have upgraded their sales funnel through chatbots. 

1. Sephora 

Sephora maintains its status as a leading beauty brand by being an early adopter of chatbots. 

Let’s take a look at the several bots they’ve launched in recent years:

Sephora Reservation Assistant

The company launched the Sephora Reservation Assistant—an appointment booking bot for scheduling makeovers at Sephora stores. Users can specify their desired services, determine potential dates, and find the nearest in-store outlet. Rather than hiring an employee for the job, a chatbot is a cost-effective means of providing service to customers. 

Sephora Virtual Artist

Sephora Virtual Artist is a groundbreaking app that offers 3D live product experiences for users. 

Fashionistas can try products virtually and find the perfect shade with a few taps on their smartphones. Some looks are created by Sephora experts so you can get inspiration for your future look. Plus, there are beauty tips and tricks users can learn to look their best while wearing Sephora’s products. 

Kik Bot 

The popular Kik platform on Sephora offers make-up tips, style inspiration, custom content and how-to videos aimed at teens and young adults. 

To become relevant for their consumers, Sephora collaborated with Helen Phillips—a Sephora Collection National Artist—to create prom makeup tutorials and conduct Q&A sessions. The community submitted a total of 1,500 questions featuring tips on covering their acne and maintaining their look during the dance. Not surprisingly, the campaign got more than 600,000 Kik bot interactions and 132,000 views per month on Sephora’s Facebook Live. 

2. HelloFresh

HelloFresh is the largest meal kit delivery service in the United States.

Prior to adopting a chatbot solution, their customer support team struggled with a large number of customer messages. Each member took six to twelve hours to help users resolve their issues. 

The solution? Freddy – the HelloFresh chatbot – was born. 

Freddy is a convenient tool for addressing inquiries and cutting wait times. The bot can determine a customer’s intent and attempt to resolve their issues, before contacting a customer support representative. 

In recent years, Freddy’s responsibilities have expanded to include:

  • Providing HelloFresh blog content and news;
  • Providing Spotify playlist recommendations so customers can enjoy good music while cooking;
  • Offering reminders so customers can remember their weekly food orders;
  • Reaching out via messenger to online users that commented on their Facebook page; and
  • Engaging users through breakfast quizzes to promote HelloFresh products. 

In 2018, HelloFresh had an average response time of 5 hours. In 2019, this dramatically decreased to 1 hour and 11 minutes in spite of a 47% boost in messages! Freddy also achieved a 56% chatbot conversion rate which means more sales for their business.

3. Aerie by American Eagle 

Aerie—a sub-brand of American Eagle Outfitters—offers lingerie, swimsuits, and apparel for women. The brand owns a Facebook Messenger Bot aimed for its Gen Z target customers. 

The bot finds users’ needs with a simple  ‘this or that’ game. From the start, users can choose from two product images, and their answers enable the bot to determine their body type and needs. After choosing from several options, the bot can deliver personalized products tailored to their personal style. They can even shop based on an occasion like date nights and hangouts.  

What makes Aerie stand out from other online retailers, is that customers can shop with an image in mind. All they need to do is snap a pic with their camera. In return, they’ll get similar styles from the brand. If customers find an item in-store, Aerie’s chatbot can also suggest additional products so they can build an outfit. 

Aerie’s early adoption of chatbots paid off. Their business gained more than double the average number of monthly users across the brand’s social media channels.

4. Booking.com

Booking.com is a metasearch engine for hotels and accommodations. 

They launched a Booking Messages interface which enabled accommodation providers to communicate with customers through an app and web-based chatbot.

Right from the start, the bot connects users with hotel and accommodation staff.

There’s no need to micromanage interested tourists because the bot comes with pre-translated templates and predefined requests so users can make requests and reservations with just a few taps. The chatbot can also manage inquiries related to payment, check-in and check-out times, bed preferences, parking preferences, date adjustments, and WiFi availability. 

For example, users making a booking request can receive a confirmation text from messenger to verify the transaction.  Users can easily communicate with the bot to address their inquiries before, during and after their stay. 

Unlike most companies, this chatbot was developed in-house. The team claims that their bot can handle 50% of a customers’ post-booking accommodation inquiries. 

5. Amtrak

Amtrak is one of the largest passenger railroad services in the United States.  

By launching their “Ask Julie” chatbot and virtual assistant, the company saved $1 million on customer service. 

Julie is an advanced chatbot that can answer customer queries through natural language so it feels like you’re communicating with another person. If you have questions regarding your booking, the chatbot can quickly provide answers and relevant information.

According to Amtrak’s website, here’s a list of services that Julie can provide:

  • Planning a vacation
  • Navigating Amtrak.com
  • Amtrak Guest Rewards program
  • Booking reservations
  • Station and route information
  • Frequently Asked Questions
  • Policies

While Julie has so many responsibilities, it can answer an average of 50,000 calls per day and about 20 million calls per year. These capabilities are nothing compared to a human employee.

As a result, Amtrak was able to increase their booking rate by 25% and boost user engagement by 50%. Interestingly, bookings made via Julie led to more than 30% of revenue as compared to bookings made through other platforms. 

Conclusion 

Chatbots can significantly improve the user experience of customers. 

They can be automated to provide customers with answers, personalized recommendations, and relevant advice for every issue that could pop up. This fast and efficient response eventually leads to more conversions in the long-run. 

We hope that the tips in this article inspired you to jump in the bandwagon and launch your own chatbot. 

How will your business use chatbots to improve the customer experience? Let us know in the comments below.


Emil Kristensen is the CMO and co-founder of Sleeknote: a company that helps e-commerce brands engage their site visitors—without hurting the user experience.

Emil Kristensen

CMO and co-founder, Sleeknote

How To Build A High-Converting Video Website That Ranks

How To Build A High-Converting Video Website That Ranks

Effectively ranking a video-on-demand website in search engines is a challenge many content creators and businesses face.

And with the ongoing global pandemic and current landscape, many have started looking into taking their businesses, events, and organization online by launching a video-on-demand site to host/monetize their content and have it globally accessible.

When the majority of your content is video-based and hidden behind a paywall, it can make on-page SEO feel like a constant uphill battle. But it doesn’t need to be. 

By learning how to build your video website the correct way, you can create a platform that ranks well for your target keywords and also outranks YouTube, like this one.

In this guide, I’m going to show you how our best Uscreen clients have optimized their video websites to rank high on SERPs and convert.

How To Build A High-Ranking Video Website In 7 Steps

Step 1: Perform A “Netflix Audit”

The first step is to perform what I call a “Netflix Audit.”

This involves going through your website and stripping it of any elements that make the logged-out view of your website look like Netflix’s logged-in dashboard. That’s this page here:

converting video website

Video websites often try to emulate Netflix’s design because it looks aesthetically brilliant, showcases the depth of their video database, and has a familiar feel to their target customers.

As you can see from the design below on Magic Stream’s website, it looks and feels just like Netflix:

But this type of theme design on your website’s customer-facing website pages comes at a high cost to both SEO and conversions, because it:

  • Decreases your website’s speed
  • Limits the amount of text (and keywords) which feature on a page
  • Doesn’t provide enough context for semantic search
  • Doesn’t contain elements needed to convert a customer (like CTAs or product info)

Combined, these elements can have a negative impact on your website’s rankings. If nothing else, the layout is complex for Google’s crawlers to work their way through, and filled with information they struggle to interpret.

Netflix understands the pitfalls of using this dashboard view and, despite not having a search-led marketing campaign, they still opt for a text-based homepage.

If your video website is heavily reliant on this Netflix-style theme, I highly recommend you keep this dashboard-view for the paid (read: logged-in) version of your website and use a more traditional-style landing page for your homepage and subsequent category and taxonomy landing pages.

Step 2: Optimise Your Website’s Homepage

The most important page of any video on demand website is the homepage. It has two crucial jobs:

  1. Ranking: it needs to be well structured to compete for good positions in the SERPs
  2. Converting: it needs to convince visitors to become customers

Your homepage is one of the few pages that will be eligible to rank for search terms because it isn’t behind a paywall, so it’s your chance to shine in the SERPs. It’s also one of the few pages visitors will see before making a purchasing decision.

These factors mean the page will need to be optimized enough to rank for your target keywords but also structured in a way that showcases your product. Basically, it needs to be both a landing page and a sales page rolled into one. 

To help you achieve this, let’s split this step into mini-sections.

Ranking: How To Optimise Your Video Homepage For Search Engines

To create a well-optimized homepage, you will want to rank for two kinds of keywords:

  1. Branded: the keywords you “own” (such as your company or product name) 
  2. Most relevant: a short or medium-tail keyword likely to drive relevant traffic

If you’re already fleshing out your SEO strategy, you will already have these keywords in place. Use this guide to understand how keyword research works and how to get started.

To ensure you have space to naturally include these keywords on your page, follow the 80/20 rule:

  • 80% of your homepage should be made up of keyword optimizable elements (headers, text, images, etc.)
  • 20% of your homepage should be made up of video

In a recent study, we’ve found that your homepage’s length doesn’t play too much of a role in how you rank—our top four ranking Uscreen video websites have less than 500 words on their homepage—but making use of this 80/20 balance does.

Be sure to feature your target keywords in

  • At least one H1 or H2 tag
  • The Alt tags for at least one image
  • Your title tags and meta description

IndieFilmHustle TV, a video website focused on indie filmmakers and screenwriters, is a great example of getting this right with limited text.

Their target keyword is “Indie Film Channel” which they strategically placed in key places for semantic search, namely the page’s header, and title tags:

Doing this has enabled them to have enough information and context for Google to willingly rank them in the second position for their target keyword.

Converting: How To Structure Your Video Homepage For Sales (A 10-Point System)

We find high-converting video homepages all follow a similar structure from the top of their page to the bottom. 

This can be varied depending on your branding and what you feel looks best for your site, but these elements should be present in some way. Here are the 10 points they all hit:

  1. Hero image or carousel: vivid and relevant product or niche imagery
  2. Subscription info: two-to-three sentences about your product and any free trials
  3. Expanded product info: text-based information about your product or page (which can be supported by video or text)
  4. Free trial link: 52% of people who sign up for a free trial convert into paying customers
  5. “How It Works” section: a bullet-point list of how video on demand works (as it relates to your product)
  6. Testimonials: share the views of your fans and customers
  7. Payment and pricing: the cost of your product with a sign-up button
  8. Featured videos: a small catalog section with JPEG images internally linked to video pages
  9. Social media: updates from your latest social media posts (if applicable)
  10.  Free trial link: a final mention of your product’s free trial

A great example of this structure is the video on demand website, Naturally Sassy

If you work your way down the page, the comprehensive home page allows the videos and services as the focus, without compromising on any on-page SEO factors.

Step 03: Make Use Of Strategic Target Keywords

When Google has a limited amount of information to work with, context is everything. 

The more information you can provide in fewer words, the more it will help you set the foundation for a highly rankable website. One way you can provide more context is by using Latent Semantic Indexing (LSI) keywords.

LSI keywords are related to your target keyword or the focus of your website and help Google understand the big picture of what your website is about. And even though Latent Semantic Indexing is old technology, and search engines might not heavily rely on LSI these days, it’s still one of the best SEO practices to make sure that your storefront and other pages are targeting a set of keywords and key phrases relevant to what you represent and what searchers are actively looking for when searching for your content.

Let’s say you run a pop-culture website and you create a video web page talking about “Avatar.” Google would look for these set of keywords to determine if you are referencing:

  • Avatar – The 2009 Film (Film, James Cameron, CGI, etc.)
  • Avatar – The Metal Band (Music, Guitar Solo, Tour Dates, etc.)
  • Avatar – The Anime Cartoon (Aang, Nickelodeon, Waterbending, etc)

These keywords are especially important if your target keyword could be interpreted in multiple ways. Take KweliTV, an independent film streaming platform, for example, whose target keyword is “black streaming service.”

The word “black” makes this keyword unspecific; it could be referring to a brand called Black or an illegal black-market streaming service. 

To ensure their website is recognized as a streaming service for black people, KweliTV uses a range of LSI keywords like:

  • Black community
  • 100% black-owned
  • African descent:
    – Caribbean, 
    – African American
    – Latin American
    – European
  • Diversity
  • Cultural issues.

These keywords will often naturally appear in your website’s copywriting. But, you can also find them suggested using a tool like WooRank’s keyword tool.

Step 04: Hit The “Big Three” Of Video Optimisation

This part is simple. Google is looking for three things when analyzing a video:

  • Title: a descriptive headline for the video 
  • Description: a clear description of what the video is about
  • Thumbnail: an image relevant to the content

These enable Google to determine what your video is about if it’s unique and valuable, and whether it’s worth ranking and are non-negotiables in the eyes of Google’s webmaster guidelines.

Because Google doesn’t “watch” your video in the same way it “reads” a blog post or article, this extra information provides more context and an understanding of how the video will look to the viewer.

Step 05: Build Video Optimised Pages To Attract Traffic

As a video content creator, you are likely to use video to help promote your business. One way to capitalize on this, and to generate more organic search traffic, is to focus on ranking video pages and category pages.

These pages are a great way to add high-value content to your video on demand site, which is also likely to attract links and social signals that can improve your rankings.

The structure of these pages is similar to that of a blog post, which as standard will include:

  • Keywords in your headline tags
  • LSI keywords throughout the page
  • An optimized meta-description
  • Minimum 300 words text
  • Internal links to other website pages

Moz does this brilliantly with their Weekly Whiteboard Friday video posts, like this one on SEO title hacks:

They use a short, keyword-rich introduction to the video, and then follow it up with a blog-post style transcription of the video below.

Video content is well and truly at the core of this content, but these extra touches help to increase the perceived value of the content and have some positive semantic search factors.

Step 06: Use Schema Markup To Add Depth 

Google has a hard time understanding video content. They can glean limited information from the audio and video files but are still heavily reliant on text and users to provide context.

You can make Google’s job much easier by applying schema markup to each of your video and category pages. This allows you to tag elements of your video like:

Adding schema markups to your video and category pages will enable Google to display your pages as rich results. Here you can find the ultimate checklist to rank in the Google Top Stories Carousel.

Source: IMPACT

Although schema markups don’t directly impact rankings, it can help Google understand the information on your pages better. This is super helpful for your video pages and category pages.

You can read the full guide to video schema markup right here.

FAQ Schema for Video and Category Pages

Another great tactic to increase your SERP real estate and drive more clicks is to use FAQ schema markups on your video and category pages.

What is FAQ schema?

“A Frequently Asked Question (FAQ) page contains a list of questions and answers pertaining to a particular topic. Properly marked up FAQ pages may be eligible to have a rich result on Search and an Action on the Google Assistant, which can help your site reach the right users.” -Google

Here’s an example of an FAQ rich result:

Although Google only mentions FAQ schemas for FAQ pages, this doesn’t mean that you can’t leverage this type of schema on other pages.

In fact, adding a FAQ section to your category and video pages, not only will allow you to naturally add context to the pages but also will allow you to answer frequently asked questions, boost your visibility on SERPs and organic traffic.

For example, let’s say you’ve launched an online yoga studio and published a series of yoga workout videos for back pain. By answering several frequently asked questions around the topic (Yoga poses for back pain), and adding FAQ markup to your category page, you can both elevate the user-experience as well as organic traffic. 

In the example below, you can see how this page is using FAQ markup to do exactly that:

Check out this guide to learn more about how you can easily add FAQ markups to your pages using GTM, regardless of your CMS.

Step 07: Make Use Of YouTube

YouTube is the world’s largest video search engine and it should play a part in your website’s overall SEO strategy.
As you can see in this example from TawzerDog, it’s possible to rank first for keywords on both search engines, without negatively impacting your search results:

Uploading your marketing videos to YouTube can provide social signals back to your website, as well as bringing in traffic from people who find you on their platform. 

Wrapping This Up…

Although ranking a video and live streaming website is more challenging than your usual text-based website, I hope you can see it’s not impossible. 

By setting the foundation of good on-page SEO, and focusing on user-experience over video-showcasing, you can build a website framework that ranks well, even with limited content.

Amir is the digital marketing manager at Uscreen, an all-in-one video monetization and OTT platform provider that empowers video entrepreneurs and creators to monetize their content and build thriving businesses around their videos.

Amir Shahzeidi

Digital Marketing Manager, Uscreen

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