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Want to improve your appearance in search results? Then you need to know how to implement schema markup.

Getting started with schema can be confusing – it can be a very technical process.

But any SEO can implement schema correctly without the help of a developer.

Here’s what you’ll need to implement schema microdata:

What You Need To Know About Schema

It’s important to understand where enhancements can be made for your specific industry. Staying focused on what enhancements will actually show up with the search results will help you prioritize what type of markup to concentrate on first.

Don’t get hung up on getting every bit of information that might be listed in the chúng tôi library when doing your research.

While having markup markup on your web page as possible is ideal for all the search engines, it’s also important to understand exactly why you wanted to implement schema in the first place and not lose focus from that primary business objective.

Common enhancements that motivate site managers to implement schema:

Image is shown with my search result

Aggregate ratings shown with my search results

Upcoming events shown with my search results

Address to be known by the search results

There is definitely a lot more that can be done. Keep reading for specific and common enhancements later in this post.

How to Implement Structured Data Using HTML

If you use a content management system (CMS) that allows you the functionality to switch to a text editor then you can easily add in markup tags to give your HTML content. If you’ve never done this before, the process is very simple.

Let’s use Devil’s Teeth Baking Company in San Francisco as an example of a local business to see how to markup the business name, address, and phone number. (Yes, I do eat here.)

There is currently no schema markup for this page, but the address is clearly shown in the hero image on the home page:

The HTML text code displays the following:

We can enhance this homepage content by adding a few HTML tags to tell the search engine the address of this business using the existing content on the page.

This might seem messy, but if you take the time to digest it, we really just added two div tags and a few span tags and put in the properties like a local business, telephone, street address, region, image and postal code names within those tags.

The end result if you put this code snippet into Google’s structured data tool is this:

As you can see my LocalBusiness markup has a warning for the price range. Seeing as I did not have the price range from the hero image I used for this example, I omitted it.

Whenever you implement schema, keep tabs on errors. When the structured data markup tool detects errors the SERPs will not show any of the schema markups with an error. But warnings will still populate the other schema tags you have in place.

Process to Find the Right Markup

The above example had the goal in mind to mark the specific information on the page to have LocalBusiness information that search engines can understand. This markup will help the search engine understand that locality of the business with the intent to hopefully perform better in local search. That is a simple enough business objective.

You can determine what markup is needed for your business by taking into account what your business does, and where your audience is.

If you serve customers from a physical address then a local business markup should be included in your page.

If you sell products online, then your product pages should have the correct product markup.

If you host events then you would want to markup the event information with the correct event markup.

You can markup your entire page and the more your do, the more it will assist the search engine to understand your content better, which is the job of any SEO. Markup is also going to help you stay on top tomorrow’s world of voice search.

You can easily find the specific schema markup you need on chúng tôi and sift through the full list of what you might need and what schema microdata is available.

Copy, Swap, and Paste from chúng tôi Examples

This is a simple method that is easy to use. Look up the markup you need through’s site search. I will show this process with an example of a product markup.

Example: Product

Follow the link above and at the bottom you should find 3 examples of content being marked up on the bottom. They are divided into 4 tabs for each example.

Without Markup




We will look at example 2 because this example is the most in depth for a product markup.

This product markup has everything you would probably need to enhance your search result as it includes the product name, the aggregate rating, the price, and will alert the customer that this product is currently in stock. All of these elements, by the way, will show up in a product image search on a mobile device.

If you run an e-commerce site and want to use this markup, you would simply copy this code and swap out the areas with information related to your product. This is simple enough to do, and you can check your implementation using the structured data testing tool. Run your code implementation through the tool and check for errors.

Tip: Try running the code first and opening up the areas Google has already identified.

So, if you’re confused about how to swap out specific elements, just find the elements that directly apply to what you’re looking for. The tool will split your code into two views: the left side will be for your code, which you are free to edit. The right side is the schema validations that you can use as a guide to toggle through the code. This process is straightforward, find what you need and swap!

This is the simplest method to implementing structured data if you have no technical background in working with HTML.

Using the JSON-LD Examples

I like to use the JSON-LD example because it is less intrusive than the HTML markup.

A lot of SEOs are adamant about not using hidden HTML content. The JSON-LD markup allows you to markup your web page without it being seen by the end user as it is done in JSON code and not visible HTML.

With this, you are able to add all the markup needed and not hinder the visual look of your web page with unnecessary text.

Take this code and try editing the existing JSON-LD example within the script tags and pasting it into the text editor of your content management system.

Run the code you have from your text editor into the structured data testing tool and see if any errors occur. If no errors occur then you have readable markup in the form of JavaScript that the search engine will be able to understand this markup (while the user won’t know it’s there).

I prefer this implementation over HTML markup because you won’t stir up the wrath of your web designers with this method.

Learn From Your Competitors

If you notice a competitor having a better search result than you do than analyze what markup they are using by placing their URL into the structured data testing tool.

You can run any page through Google’s Structured Data Tool to see how they are implementing their structured data. If you use the exact same schema markup that your competitors use, then your web page will also get those rich enhancements.

If you can’t tell by now the structured data testing tool is essential to doing any of this correctly.

Common Markup You Should Use

Let’s go through some common markups that will enhance your search results.

Product Markup




Aggregate Rating


In Stock

Recipe Markup



Aggregate Rating

Total Time


Recipe Instructions

Event Markup


Event Name

Event Start Date

Event Location Name

Event Address Locality

Event Address Region

Key Takeaways

Using schema is essential to any successful SEO strategy. Schema is only going to become more important as people increasingly use voice search.

Search engines like Google tell us exactly which bits of information they think is the most important to markup, based on how they design the look of the search results. By seeing what enhancements are made and what exactly will set off an error message we can tell that Google has collected all the data they need to let us know what is commonly being searched for.

Image Credits

Featured Image: Created by Author

In-Post Images: Screenshots by Author taken July 2023

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Local Seo For Beginners: Getting Started

One of the first questions a lot of businesses have about local SEO is: Do I really need it?

And I get it. You’re busy – your time, budget, and energy are precious resources.

Do you really need another thing to keep up with?

If you want to attract in-store traffic, online or phone orders, appointment bookings, clinic visits, or other business from local consumers, the answer is a definitive YES!

Who Benefits From Local SEO And Why?

All types of businesses that interact with and service customers in a specific region can benefit from local SEO.

This includes retail stores, service businesses, restaurants and hotels, hospitals, banks, construction companies, and more.

Here are a few examples.

Lawyers And Law Firms

One of the biggest benefits of local SEO for these clients is that Google shows a call button directly in the local search results on mobile phones.

So when a potential client pulls out their phone and does a search for [(type of) attorney], they will see targeted results for their particular location.

When done right, local SEO will push the attorney to the top of the search results for that location, and the dominant call to action will be the “call us” button.

The reason why this is such a huge benefit is that anyone who has been in an accident or has another issue will be on the phone attempting to find attorneys who offer free consultations.

This one avenue offers a way to get in front of those consumers exactly when they need an attorney.

Doctors And Medical Practices

When someone is searching for a medical professional, they’re often searching for a [doctor nearby] or a [doctor near me].

Most people don’t want to go out of their way or travel several hours to visit a doctor. They want a nearby doctor who can see them regularly.

If you reference the screenshot below, using the search [doctors near me], there are several benefits of this large local pack result.


When someone has an emergency involving plumbing, are they going directly to a store?

No, they usually go to Google to search for [plumber near me].

The Google search results provide an easy way for someone to call a plumber directly, read reviews, and access local plumbers immediately if they have such an emergency.

Who Won’t Benefit From Local SEO?

While we would love to see everyone benefit from local SEO and sell these services to more clients as SEO professionals, the reality is that some businesses just don’t lend themselves well to local SEO efforts.

Businesses like online only ecommerce shops, businesses that don’t want to share their local information, and private online sellers who want to keep their information private are likely not great candidates for local SEO services.

Local Search Still Needs Organic SEO

Local search rankings appear in the form of the Map Pack on Google, but your site’s organic ranking is an important factor, as well. This helps Google understand your overall prominence, which is one of the three main categories of local ranking signals.

SEO tricks and tactics are long gone, and search has evolved exponentially.

Nowadays, user experience signals, E-A-T, high-quality content, high-quality links, and much higher quality UX rule the game.

But make no mistake: There are still locally enhanced factors of SEO that you need to get right, including:

Finding the right keywords and topics to target as part of your campaign.

Making sure your technical SEO is top-notch.

Ensuring the highest quality content possible.

Earning links to make your website stand out enough in Google’s eyes.

Double-checking and implementing your NAP (Name, Address, Phone number) information is accurate across many linking sites.

Optimizing for local ranking signals.

With a local focus, many of your standard organic SEO methods may change slightly compared to the more traditional methods that are used for ranking.

Local Search Can Be Voice Search, Too

Now that people have more access to devices like smartphones, Amazon Echo, and Google Home, voice search has become a preferred way for many to find local information.

It’s easier to say “find a doctor near me” or “find a plumber near me” for most people than it is to type.

Thus, it isn’t surprising to see a rise in local queries based on conversational voice search.

If your industry is service-oriented, try out keyword variations that include questions.

Semrush’s topic research tool, chúng tôi and AnswerThePublic all provide ways to see questions people are searching for, along with their search volume.

This is an excellent way to target keywords that have local intent.

If your industry is a local brick-and-mortar, service-related business, like a restaurant or an attorney or lawyer, try keyword variations with a conversational tone and focus.

You may be surprised by the search volume you can achieve when you do keyword research in this way.

Local Search Is Mobile Search

We know that a sizable portion of local searches happen on local devices, and that mobile-friendliness is a Google ranking factor.

What do these facts and the mobile-first index mean for your local SEO strategy?

Google has done the work of optimizing Map Pack listings for mobile searchers. But it’s up to you to create that user-friendly, convenient experience on your website – and to ensure Google understands that via good technical SEO.

Search Engine Journal’s Roger Montti shares an overview of what that entails in ‘7 Ways a Mobile-First Index Impacts SEO,’ part of SEJ’s free Advanced Technical SEO Guide.

Local SEO Needs A Dedicated Strategy

But, that doesn’t mean it needs to take up a lot more of your time.

In the next chapter, you’ll find a nine-step checklist to guide your new or improved local SEO strategy.

Then, we’ll dig into the various aspects of it and you’ll find experts tips and tools to bring it all together.

Download the full guide for free here.

Featured Image: Paulo Bobita/Search Engine Journal

Getting Started With Julia – A High Level, High Performance Language For Computing

Learning new tools and techniques in data science is sort of like running on treadmill – you have to run continuously to stay on top of it. The minute you stop, you start falling behind.

As part of this learning, I continuously look out for new developments happening in new tools and techniques. It was in this desire to continuously learn that I came across Julia about a year back. It was in very early stages then – it still is!

But, there is something special about Julia, which makes it a compelling tool to learn for all future data scientists. So, I thought to write a few articles on it. This is first of these articles, which provides the motivation to learn Julia, its installation, current packages available and ways to become part of Julia community.

What is Julia?

Julia is a high-level, high-performance dynamic programming language for technical computing, with easy to write syntax. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.

Why another programming language?

C compiled by gcc 4.8.2, taking best timing from all optimization levels (-O0 through -O3). C, Fortran and Julia use OpenBLAS v0.2.12. The Python implementations of rand_mat_stat and rand_mat_mul use NumPy (v1.8.2) functions; the rest are pure Python implementations.

A Summary of Features in Julia

Some of the important features to highlight from data science capabilities are:

A more comprehensive list of features can be accessed here

Installation of Julia

Now that you might be raring to give Julia a try for all the promises made above, let me quickly walk through various options to test drive your new sedan (which has sports car like acceleration):

Option 1: Try Juliabox in browser – The simplest of option – no setup required. Just go to Juliabox, sign in using Google (sorry, if you don’t have a Google account – try the next version) and your instance is ready to fire.

Option 2 – Use an IDE – Juno seems to be the best IDE available right now. Sadly, JuliaStudio is no longer supported. The best way to install it is to download the combo package from Julia site itself.

Option 3 – Using Command line – If you are the hardcore programmer, who can’t think of a programming language without a command line, don’t worry! There is an option for you as well. You can download the package here.

Option 4 – Using iJulia notebooks – If you are a Python explorer and have used iPython for your interactive data exploration – here is an awesome news. iJulia notebooks are equally awesome and carry over similar interface. In order to install iJulia, you need to install iPython first, then install Julia 0.3 or later. Next start Julia and add package “IJulia” and start using it. You can find more details here.

A few important packages

There are a total of 610 packages on Julia as on date (9th July 2023). If you filter out packages for which tests have failed or which have not been tested, you are only left with 381 packages. Among these I have filtered out the ones related to data science and have more than 15 stars. That leaves us with the following packages:

Package Description Version Stars

BackpropNeuralNet A neural network in Julia 0.0.3 18


Bokeh Bindings for Julia 0.1.0 26


Restricted Boltzmann Machines in Julia 0.1.0 19


Calculus functions in Julia 0.1.8 46


A Julia package for data clustering 0.4.0 33


A julia package for disciplined convex programming. 0.0.6 108


Utilities for calling C++ from Julia 0.1.0 18

DataArrays Data structures that allow missing values 0.2.16 21


library for working with tabular data in Julia 0.6.7 206


Metaprogramming tools for DataFrames 0.0.1 33


Julia implementation of Data structures 0.3.10 52


Decision Tree Classifier and Regressor 0.3.8 36


A package for evaluating distances(metrics) between vectors. 0.2.0 21


A package for probability distributions & associated functions. 0.7.4 101


Filter design, periodograms, window functions, and other digital signal processing functionality 0.0.8 32


Functional and and persistent data structures for Julia 0.1.2 34


Crafty statistical graphics for Julia. 0.3.13 684


A lightweight framework for writing genetic algorithms in Julia 0.0.3 86


Generalized linear models in Julia 0.4.6 78


Wrapper for fitting Lasso/ElasticNet GLM models using glmnet 0.0.4 23


Working with graphs in Julia 0.5.5 90


Saving and loading Julia variables 0.4.18 65


Hypothesis tests for Julia 0.2.9 16


An image library for Julia 0.4.39 73


Modeling language for Mathematical Programming (linear, mixed-integer, conic, nonlinear) 0.9.2 162


Julia Machine Learning library 0.0.3 37


Markov chain Monte Carlo (MCMC) for Bayesian analysis in julia 0.4.11 44


Markdown parsing for Julia 0.3.0 21


Advanced Pattern Matching for Julia 0.1.3 29


A Julia package for fitting (statistical) mixed-effects models 0.3.22 41


A set of functions to support the development of machine learning algorithms 0.5.1 41


Deep Learning framework for Julia 0.0.8 297


A Julia package for multivariate statistics & data analysis (e.g. dimension reduction) 0.2.1 21


Package to call the NLopt nonlinear-optimization library from the Julia language 0.2.1 31


Julia OpenStreetMap Package 0.8.1 20


Optimization functions for Julia 0.4.2 116


Heterogeneous ensemble learning for Julia. 0.0.5 27


A Julia framework for probabilistic graphical models. 0.0.1 25


Package to call Python functions from the Julia language 0.8.1 183


Embedded R within Julia 0.2.1 16


Julia package for loading many of the data sets available in R 0.1.2 34


Algorithms for regression (e.g. linear / logistic regression) 0.3.2 17


Julia-to-R interface 0.0.12 47


Basic statistics for Julia 0.6.15 57

StreamStats Compute statistics over data streams in pure Julia 0.0.2 27

TimeSeries Time series toolkit for Julia 0.5.10 37

P.S. There is a lot of development happening on the language and the libraries. So this can change very quickly.

A few things to note:

Gadfly looks to be the most popular package. This might well be because it is being used as a showcase library across all the products in the ecosystem

The core data science libraries look more evolved than some of the other libraries. Mocha for DeepLearning, Orchestra for optimization, DataFrames or distributions are all on more evolved version comparatively

How to install & use a package?

Installing and using a package in Julia is dead simple. If you want to install / add a package, simply type this in your programming interface


This will install the package as well as its dependencies.

Once the package is installed, you can load it simply by calling “using”

using Gadfly


The Julia ecosystem:

Julia is supported by a close knit community of developers. Here are a few mailing lists, you can be a part of:

julia-news – for important announcements, such as new releases.

julia-users – discussion around the usage of Julia. New users of Julia can ask their questions here.

julia-stats – special purpose mailing list for discussions related to statistical programming with Julia. Topics of interest include DataFrame support, GLM modeling, and automatic generation of MCMC code for Bayesian models.

julia-opt – discussions related to numerical optimization in julia. This includes Mathematical Programming (linear, mixed-integer, conic, semi-definite, etc.), constrained and unconstrained gradient-based and gradient-free optimization, and related topics.

In addition to these newsletter, you can also look at chúng tôi . The site looks like a developing ecosystem as of now though.

End Notes

I hope that you have got a good overview of this powerful language under development. I was pretty excited when I saw it first and I continue to check this language for new developments closely. In the next articles to come, we will understand the data structured available in Julia, its interface with other languages e.g. Python and solve one of the case studies using Julia to understand its power.

If you like what you just read & want to continue your analytics learning, subscribe to our emails, follow us on twitter or like our facebook page.


What Is Workforce Transformation? Why It Matters And Getting Started

blog / General What Is Workforce Transformation? Why It Matters and Getting Started

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The way we work is changing–fast. And many companies are struggling to keep up with the pace of that evolution. 

Updating processes, technologies, and business practices takes significant time and investment. But keeping employees at the top of their game is most critical of all. A company’s workforce failing to keep up with changes to business operations creates an opening for competitors to get ahead.

That’s where workforce transformation comes in. 

What Is Workforce Transformation


Workforce transformation refers to the process of realigning a company’s employee base to ensure that their skills match the company’s strategic needs. Essentially, a company undergoing workforce transformation assesses its existing skills, identifies the skills needed to meet future goals, and maps out any skills gaps. 

Once you identify those gaps, you can embark on closing them through targeted reskilling, upskilling, and hiring. 

Why Is

Workforce Transformation


According to a Newsweek survey, during the COVID-19 pandemic, the rate at which certain workplace skills become obsolete increased by more than 70%. In many industries, technological shifts that were expected to take place years into the future came rapidly in response to our new reality. For example, B2B organizations that traditionally relied on in-person sales visits suddenly needed to shift to digital strategies. 

Companies have always needed to be able to pivot rapidly to avoid falling behind. However, as the pace of technological change increases, these transformations are necessary more often and need to be done on a shorter time scale. Organizations, therefore, need effective workforce transformation programs to ensure they can align their skills base with the company’s future goals and needs. 

How to Launch a Workforce Transformation

Effectively launching a workforce transformation requires careful planning. Consider the following steps.

1. Conduct a skills assessment.

Without knowing what skills you have in your workforce, it’s impossible to know what gaps exist. Consider using a multi-faceted approach to measuring employee skills, including looking at existing job descriptions and performance reviews, talking to managers, and surveying employees themselves. It’s important to regularly reassess skills, as they can change rapidly with employee turnover and as employees grow and develop.

2. Identify critical needs and goals.

While some specific technical skills may receive a lot of buzz, a company’s actual workforce needs are highly dependent upon its organizational goals. Before embarking on a workforce transformation initiative, company leaders should identify and prioritize the most critical skills to fulfill those goals. 

3. Create a plan for skills development.

External online training programs (like those offered by



Company-led (internal) training programs 

Mentorship opportunities

Temporary or “stretch” assignments in different departments

Traditional degree programs

4. Measure and adapt.

Like with any organizational effort, it’s essential to set and track success metrics. Regularly check in to ensure your transformation strategies are effectively deliver new skills and meet company needs. Since workforce transformation aims to adapt to new demands, regularly reassessing the match between employee skills and company needs is essential. 

Addressing Challenges of

Workforce Transformation

While workforce transformation is imperative, it also poses many challenges, which can include the following.

1. The overwhelming scale of the project

Overhauling an entire company’s workforce can be a massive challenge. That’s why it’s recommended to break it into small pieces and identify replicable processes to reduce the scale of the work. 

Starting by identifying specific skills or business units to transform and carefully tracking and measuring the process and results throughout can help build the business case for a broader transformation. Plus, it provides an opportunity to identify company-specific challenges and best practices.

2. Lack of relevant data

Many organizations lack robust data on their own employees. Without that information, it’s impossible to know how to focus your skill-building efforts. Companies without strong metrics in place should consider investing in people analytics capabilities such as surveys and related tools. For Philip Morris International, detailed online assessments (especially for key leaders) were central to a successful transformation effort. 

“It’s recommended to break it into small pieces and identify replicable processes to reduce the scale of the work.”

3. Need for organizational buy-in

Any large-scale transformation efforts can understandably cause employees anxiety. That’s why you should prioritize strong leadership and clear communication. This will ensure your workforce understands that these development efforts are meant for growth rather than to become a threat to their employment. Most employees are eager to develop their own skills; it’s simply a matter of effectively sharing goals and processes so that they understand what’s to come. 

Workforce Transformation Examples

It’s always helpful to look at companies that have successfully completed comparable workforce transformations for inspiration. Notable examples in recent years include:


In 2023, Unilever embarked on an ambitious effort to prepare its 155,000 employees for the future of work. Their program aims to create a “future-fit plan” for every employee. They name employees’ goals, consider how their specific roles might change or disappear in the future, and identify the skills they need to gain to adapt to new positions. These efforts are combined with a broader initiative within Unilever to help employees find a sense of purpose in their work and build engagement and satisfaction. 


L’Oreal knew it couldn’t rely on its reputation alone to compete in a crowded cosmetics marketplace. It embarked on an ambitious digital transformation plan to reduce time to market from 18 to 6 months, in part by upskilling and reskilling workers to enhance their digital capabilities. L’Oreal has invested in training offerings to power this transformation. This includes virtual courses and a broad online learning platform available to all employees. In fact, in 2023, every L’Oreal employee worldwide received training.


At Allstate, like many insurance companies, the impact of technologies like AI is rapidly changing business operations. While the use of new technologies varies significantly based on employees’ roles, the company has made a concerted effort to roll out new people analytics technology and has invested in training. In 2023, Allstate employees completed 139,000 hours of formal training, and 7,000 attended the company’s Global Learning Week focused on development.

Workforce transformation is a complex undertaking, but experts say it’s well worth the effort. Companies that invest in adapting and staying nimble before the market forces them to will see improved performance and employee engagement–and be better positioned to tackle future challenges.

Ready to embark on your workforce transformation journey? Learn more about how Emeritus Enterprise can help you build a custom plan to upskill and reskill employees through online employee training programs.

Seo Trends For 2023 And Beyond: Interviews With Two Leading Experts

At Pubcon 2014 in Las Vegas the SEJ team had the opportunity to catch up with Jake Bohall of Virante, and Joe Youngblood of Winner Winner Chicken Dinner, about SEO trends.

Jake discusses how he’s starting to see a shift towards SEO being integrated into all company practices, while Joe discusses some interesting new ways to build links.

Hear them explain more about this in the videos and recaps below:

SEOs Tools: An Interview with Jake Bohall

Here are some key takeaways from the video:

Jake believes the future of SEO is shifting more towards using tools and having people on your team who are capable of using those tools, instead of some of the more specialty skill sets people have.

Technical SEO will always be there, says Jake, but certain aspects are becoming more integrated within other business units in a company. For example, link building has become more of a PR strategy with a growing focus on outreach and relationship building.

Jake thinks the days of writing content by following an SEO on-page checklist are going away in favor of using tools like nTopic to help you create authoritative content.

To clarify, SEOs will never be replaced. SEOs bring a very valuable skill set to the technical side, whereas developers don’t have that strong marketing sense when they’re building a site. Adhering to Google’s guidelines is not as much of a concern for developers as it is for SEOs.

Jake says our role as SEOs is going to be more based on the technical side, and then taking that technical expertise and building innovative tools that companies can use in house.

As SEO becomes more and more complex you’re starting to see more SEOs specializing in individual areas, like keyword research, or local search, etc.

Jake says the biggest thing an SEO can do right now is identify what their core competency is and focus on that. For a company, the best thing you can do is find a way to educate your staff about SEO practices so you can integrate it throughout your organization.

Quality Link Building: An Interview with Joe Youngblood

Here are some key takeaways from the video:

Stop being so afraid of building links, Joe says. A lot of site owners try to take the shortcut of buying links due to the instant gratification, rather than putting in the work to try to earn links.

Instead of asking “What if I do this content marketing thing and I don’t get any links out of it?”, site owners should be more concerned about angering Google by taking the easy way out, and having your site buried in the search results.

Link building takes time, but you have to stop being afraid to do it.

One of the biggest concerns Joe sees from site owners is the thought that they might invest a lot of money into creating content that doesn’t gain any traction.

Instead of second guessing yourself, just start putting in the work. You’ll never see if it works if you don’t do it

Something Joe pushes a lot is a tactic called “scholarship link building.” You can do a scholarship for as little as a few thousand a year and hand over the management to an entirely separate company, then you’ll get a number of high authority links from universities.

Please visit SEJ’s YouTube page for more video interviews.

Pc Specialist Vulcan S2 Review: Getting More For Less?

Elsewhere, the Core i7 CPU is reliably quick, the rest of the components are fine, and the case is compact and smart. It’s not the best for upgrades, but this rig is impressively quick and affordable.

The PC Specialist Vulcan S2 is a superb gaming system on paper, with better components and a lower price than its main rival. But have corners been cut in order to bring this system in under budget, or is a true mid-range marvel that can handle 1440p gaming for less cash than the competition?


This £1,394 machine is built around two key components: an Intel Core i7-9700 processor and an Nvidia GeForce RTX 2070 graphics card. You’ll need to buy it direct from PC Specialist.

That’s a lot of power for this price, and it squares up well against its key rival. The Overclockers Hoplite originally arrived at £1,479, but now it costs £1,299 – so it’s £100 cheaper than the PC Specialist machine. That rig relies on an AMD Ryzen 7 2700X CPU and RTX 2060 graphics.

The Vulcan S2 is protected by the standard PC Specialist deal, which is a three-year labour deal with one year of parts protection and one month of collection coverage.

Check out our  best gaming PC chart.

Design & Build

PC Specialist has used one of its own enclosures for this machine. It’s called the PCS P209, and it nails most of the current trends. There’s a tempered glass side panel, a magnetic dust filter on top, and a slab of metal at the front.

The P209 is 455mm tall and 390mm deep, so it’s smaller than the Kolink – that unit is 510mm talk and 445mm deep. That bodes well for fitting the Vulcan into smaller spaces. Build quality is impressive, too – the steel used throughout is sturdy, so we have no concerns there.

There are slim air intake vents at the front, and at the rear there’s a 120mm exhaust. Air intake is handled by two 120mm fans that are attached to the Cooler Master MasterLiquid Lite 240 processor cooler. That’s a slight concern – because it means that cool air coming in will immediately be heated. This shouldn’t be a huge problem due to the Vulcan’s mid-range components, but the Overclockers is better-equipped due to its trio of intake fans.

The top of the P209 only has two USB 2.0 ports and one USB 3.0 connection – there’s no faster USB 3.1 port. It’s the same as the Kolink case, but it’s not particularly good for fast data transfers.

On the inside the P209 remains conventional. A PSU shroud hides the Corsair power supply, and PC Specialist has done a good job of keeping cables neat – so airflow isn’t disrupted and internal access is easy. Lighting is handled by a patterned strip of RGB LEDs down the front panel and a strip of lights to illuminate the hardware inside.

However, in some areas the P209 is basic. Behind the motherboard there’s only room to add single 2.5- and 3.5in hard disks, and the hard disk option is poor – there’s no dedicated bay and no tool-free installation.

The Hoplite’s Kolink case is better here, with pairs of 2.5- and 3.5in hard disk bays. That case also has 370mm of graphics card clearance – 50mm more than the PCS P209.

The Vulcan’s case is smart, sturdy, small and accessible, and it has RGB LEDs. But it doesn’t have the best port selection, and the slightly cheaper Overclockers has more room to grow – as well as more extravagant design.

Specs & Performance

The Nvidia GeForce RTX 2070 sits in the middle of Nvidia’s latest range. It uses the Turing architecture, which means you get the latest architectural improvements – as well as ray-tracing and DLSS.

The Vulcan’s RTX 2070 is made by Palit, and it uses the GPU’s stock configuration with no overclocking. That means you get 2,304 stream processors, 8GB of memory and a boost clock of 1,620MHz.

The lack of overclocking doesn’t stop the RTX 2070 outstripping the cheaper Overclockers’ RTX 2060. The Gigabyte-made card in that machine has a small overclock, with the 1,680MHz standard turbo speed improved to 1,770MHz, but that GPU only has 1,920 stream processors and 6GB of memory.

In the tougher Ghost Recon: Wildlands, at 1080p and at Ultra settings, the Vulcan still blasted through with an average of 65fps – easily playable.

The Vulcan played games at 1440p, too: in Warhammer and Ghost Recon at maximum settings it averaged 62- and 51fps respectively.

The RTX 2070 can’t handle 4K, though. It only managed good framerates at Medium settings – at Ultra, in both games, minimum framerates dipped below 30fps. You’re either going to get stuttering gameplay or you’ll have to drop the quality levels, and neither is ideal.

The Core i7-9700 CPU is a popular, powerful part. It’s an eight-core chip without Hyper-Threading, and it runs at base and boost speeds of 3GHz and 4.7GHz. On paper, the AMD Ryzen 7 2700X inside the Overclockers is competitive: its eight cores do have multi-threading, and it runs at 3.7GHz and 4.3GHz.

However, benchmarking shows that Intel has a lead. In PC Mark 10 the PC Specialist scored 6,715 points – almost 1,000 points ahead of the Hoplite. The Vulcan’s Geekbench single- and multi-threaded scores of 5,511 and 27,308 were quicker than the 3,806 and 26,785 scored by the Overclockers’ AMD hardware.

You can see benchmark results below compared with the Hoplite and also the  Yoyotech Warbird i7s which also has an RTX 2070.

Both CPUs are fast and versatile, with enough pace for day-to-day work and for gaming. Drill down, though, and those benchmark results create some real-world differences.

The PC Specialist’s Intel chip is better for gaming and for tasks that require single-threaded speed, like mainstream office applications – so it’s well-suited to a wider range of day-to-day tasks. The AMD part will be better in more complicated productivity software, like video tools and photo editing suites, but that’s it.

Elsewhere, the two machines are similar. Both have 16GB of memory at 3,000MHz or beyond – so that’s fine. The PC Specialist has a 512GB Intel 760p SSD, while the Overclockers has a 240GB Gigabyte drive. The former is faster and larger, but neither are bad. Both have secondary 2TB hard disks.

Elsewhere, there are two free memory slots, space for SATA-based storage and plenty of vacant PCI-E x1 slots for smaller expansion cards, but it doesn’t support Nvidia SLI so you can’t add a second graphics card if you were thinking about doing so.

The sole M.2 connector is occupied, the on-board USB 3.1 header uses the slower Gen 1 standard, and at the back there’s no USB 3.1 Gen 2 connectivity and no USB Type-C either.

The PC Specialist had no thermal issues during our testing. The CPU and GPU peaked with normal temperatures of 70- and 59°C – so the potentially problematic air intake wasn’t an issue. The noise was fine, too: the Vulcan produced a low rumble during gaming and work, but it’s easy enough to mask with modest speakers.


There are a couple of areas where the PC Specialist can’t match the cheaper Overclockers machine: that rig is more accommodating for upgrading, and its multi-threaded CPU is better for some work tasks. And, if you don’t want to push your gaming to higher levels, that RTX 2060 machine does the job for less cash

In every other department, though, the £1,399 PC Specialist Vulcan S2 outpaces its £1,299 rival and justifies the extra cost. It’s quicker in gaming and faster in all applications and scenarios beyond some tough work tools. It’s got better storage, and it’s cool, quiet and more compact than its rival.

It’s an excellent, well balanced, mid-range option.

Specs PC Specialist Vulcan S2: Specs

Processor: 3GHz Intel Core i7-9700

Graphics: Palit GeForce RTX 2070 8GB

Memory: 16GB 3,000MHz DDR4

Motherboard: Gigabyte Z390 UD

Storage: 512GB Intel 760p M.2 SSD, 2TB Seagate Barracuda hard disk

Case: PC Specialist PCS P209

Power supply: Corsair TX550m 550W

Warranty: 3yr labour w/ 1yr parts, 1mth C&R

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