In such circumstances, SEO has to be one of the biggest priorities of a webmaster, especially because Google changes its search engine algorithm roughly 500 to 600 times a year. If you administer a website and want to ensure a higher ranking in Google searches, then you should conduct a thorough SEO audit to eliminate bugs and make improvements.

Our post will show you seven ways to run an SEO audit and boost your ranking relatively quickly. Let’s begin!

1. Choose the Right Tools

You don’t start an SEO audit without the right tools. Doing all the work manually would make the job extremely difficult – if not impossible – so it would be wise to test some of the best SEO platforms and use them in the process. Our recommendation is to consider the following tools:

• Google Analytics: This platform is Google’s native tool and it will tell you everything you need to know about website performance.
• SEO Site Checkup: Just like the name suggests, SEO Site Checkup helps webmasters to conduct thorough audits and eliminate optimization blunders.
• NinjaEssays: Most websites outsource content creation to ensure the highest quality of their posts. If you are looking for a professional paper writing service, try NinjaEssays.
• Screaming Frog: It’s a website crawler that explores every single page and the corresponding URL.

2. Fix Broken Links

Not too many things can ruin the user experience and jeopardize ranking as fiercely as broken links. Fortunately, you can remove broken links quickly using almost any SEO audit tools, but we will stick to Google Analytics because it’s free and widespread.

You just need to open the main dashboard, set the timeframe of your analysis, and create a search filter containing the “404 error” notification. Google Analytics will display all broken links and you’ll know the magnitude of the problem.

The next step is to redirect broken links through your content management system. The way it works depends on your system, but most platforms contain the redirect option where you can create new redirects and take visitors to functional pages.

3. Create Keyword-Rich Content

Another important task is to reevaluate your content and make it keyword-rich. This is where you’ll have to be patient and improve articles to match the search intent of the target audience.

Keep in mind that you shouldn’t compete for simple keywords only. On the contrary, it is also important to target longtail keywords and common search phrases. For instance, content creation services rely heavily on word of mouth marketing, which is why they highlight keyword phrases such as Essay Shark reviews, Superior Papers reviews, or GradeMiners review.

You should follow the same pattern – understand the needs of your audience, come up with the corresponding keywords, and revise the content in a way that makes it highly relevant and keyword-rich.

4. Optimize Metadata

Metadata optimization represents a big part of the SEO audit. It’s not a complex process, but it is incredibly significant for your ranking. Generally speaking, you need to focus on three elements:

• Title tags: Title tags are the first thing users see in Google search results, so you have to make them relevant and easily discoverable.
• Description: Meta descriptions don’t influence ranking directly, but these short paragraphs reveal the nature of your content and inspire searchers to click your link instead of someone else’s.
• Image tags: Users also look for images. It means you’ll need to mark each photo correctly so that Google can display it in related searches.

5. Eliminate Duplicate Content

If you find large portions of the same content across various pages, then you are facing the issue of duplicate content. Google is not exactly thrilled about duplicate content and might even penalize you for it, so you should try to remove such elements as soon as possible. A simple tool like Copyscape will help you to discover duplicates and remove them from your website, thus preventing ranking downfalls.

6. Improve Page Load Speed

Google and users appreciate speedy websites and hate slowly-running pages. For instance, if you search for the best resume writing services and learn that VelvetJobs takes more than a few seconds to load, you would probably consider it irrelevant.

Now, if you don’t want the same thing to happen to your website, you need to increase page load speed using tools such as Pingdom. It’s a simple platform that scans your site, assesses its performance, and gives you suggestions on how to improve. The process is smooth and simple, so you better get it done quickly.

7. Optimize for Mobile Experience

The year is 2019 and we should not talk about mobile optimization, but lots of websites and their HR software still don’t pay attention to it the way there are supposed to. All you have to do is test your pages via Google Search Console to measure the mobile-friendliness of the website in general. Just copy/paste the URL and Search Console will tell you whether the content is mobile-friendly or not.

Conclusion

Ranking in the first page of Google search results sounds like a dream come true for every webmaster, but earning this position is out of reach for most of them. It takes a lot of work and optimization efforts to boost the ranking of your site, so you’ll have to do the homework and begin with an SEO audit.

In this article, we showed you seven ways to conduct a basic SEO check of your website. Remember our tips and leave a comment if you have any questions – we will be glad to answer you quickly!

The post SEO Audit to Get Higher Ranking on Google appeared first on Tricky Enough.

But the sheer number of options is enough to make a lot of webmasters dazed and confused. They have a hard time distinguishing between important and irrelevant metrics, which often leads to time-waste and “off the point” reports.

My goal is to help you get around simply and effortlessly, so keep reading to learn 10 ways to use Google Analytics like a boss.

How to Master the Art to use Google Analytics

The 10 functions of Google Analytics that I am about to discuss here follow a logical pattern. Firstly, I want to introduce you to the basic reporting sections. Secondly, you will learn about dashboards and key performance indicators (KPIs). After that, I will describe metrics I believe to be fundamental for the vast majority of websites. Without further ado, let’s take a look!

1. Audience reports

The first reporting section is crucial because it provides you with audience-related insights. The whole unit is divided into multiple categories in order to analyze website visitors from all angles. Using this feature, you can learn all about:

• Demographics: It includes general data like age or gender.

• Location: You can see where the audience comes from.

• Interests: The metric shows you what your visitors are interested in.

• Behavior: Google Analytics also reveals the behavior of site visitors and shows the number of recurring visitors.

• Devices: You get to learn about different browsers and devices used to access your website.

• Users flow: It’s a graph that visualizes user experience.

• Custom: Finally, you are free to tailor audience reports and focus on what you consider most relevant.

2. Acquisition reports

If you want to figure out where the audience comes from (and who doesn’t?), then you must go to acquisition reports. It’s a critical segment of Google Analytics because we all want to find a way to attract more visitors to the website.

The section gives you a general overview of all traffic sources combined. This is a good starting point, but you will have to dig deeper in order to find more accurate information. As always, you can keep an eye on various parameters:

• Channels: It reveals whether something came from paid or organic search, social media, etc.

• Referrals: Discovers third parties that redirected users to your site.

• Campaigns: This feature analyzes the performance of your campaigns.

• SEO: It gives an overview of your optimization efforts.

Besides these variables, you can also check out additional features such as keywords or social impacts.

3. Behavior reports

Just like the name says, behavior reports show you how users behave when they land on your pages. Of course, it all begins with an overview section and then gradually unfolds to give you more comprehensive feedback.

This section reveals the pages people visited and search terms and phrases they looked for on your website. You can also see “Event Categories” to know if someone actually clicked a certain link on your site. With all those details at your disposal, it is much easier to understand what users want to see and consume online.

4. Conversion reports

Converting visitors is a dream come true for every website administrator. After all, the ultimate purpose of your online business is to attract new customers and grow revenue.

Conversion reports are focused on this part of the business because they explain actions taken by the website visitors. Needless to say, you can discover various details:

• Goals: It analyzes website performance according to the goals you’ve defined.

• E-Commerce: This unit is dedicated to financial results.

• Multichannel funnels: Shows the step-by-step process users go through before completing purchases.

• Attribution: This one measures the ROI of each traffic source separately.

5. Determine Objectives

Now that you understand the fundaments of Google Analytics, it is time to move on and define your objectives. This is very important because you might get lost in the abundance of information otherwise.

Think about your digital business and ask yourself: What do I want to achieve? Paper writing help agencies need websites to raise brand awareness and attract more visitors, but your goal might be to sell more products through the website or something completely different. The way you answer these questions will give you a general idea on how to plan and define your KPIs.

6. Create a dashboard

Dashboard creation is the next step in solving the Google Analytics puzzle. It’s an intuitive and user-friendly process since the New Dashboard button is the first thing you’ll see on the menu. The platform allows you to launch a simple Google Starter Dashboard, which is a convenient option for beginner-level administrators.

Once you’re done with the dashboard creation, you must tailor it so as to match your KPIs. Each dashboard offers you a number of widgets where you can find different metrics and set up filters. That way, you are free to define objectives, timeframes, specific pages, and many more.

7. Analyze the audience

Now I want to concentrate on four elements of Google Analytics that might as well be the most significant for newbie analysts. The first one is audience analysis, with a focus on technology and mobile usage.

The technology feature reveals browsers your visitors are using, while the mobile section highlights visitors coming from smartphone devices. This information is critical to the success of your website because it helps you to optimize for each device individually.

For instance, you can almost entirely focus on mobile experience if you conclude that the majority of visitors use smartphones. That way, you can build a fully responsive site and take mobile experience to the whole new level.

8. Traffic

My fellow colleagues at EssayWritingLab believe website traffic is only important if you are selling advertising space on a website. While the metric is indeed crucial for online advertisers, I believe it has the same level of importance for other websites, too. After all, how can you expect to generate new leads and drive conversions if you cannot attract enough users to your site?

However, you shouldn’t analyze the number of sessions separately, but rather try to combine it with additional KPIs. The final objective is to increase traffic by attracting users who are really interested in your content, products, or services.

9. Bounce rate

If you want to understand how your homepage or landing page is performing, you better analyze bounce rate. This KPI shows you how quickly a visitor leaves your site upon landing. Of course, lower bounce rate suggests that your website is doing well. But if you notice that people abandon your website very quickly, you definitely need to consider rearranging the entire homepage or specific elements such as colors, calls to action, images, and so on.

10. Website content

For me as a content creator, this is by far the most interesting metric. If your traffic and conversions depend on content quality, you definitely need to identify the most popular pages and the ones that chase visitors away.

Authors at Australianwritings.net and Edugeeksclub use this metric to learn which topics perform well and also to figure out what needs to be eliminated from their content creation strategy. After that, they can create more well-performing articles and stop writing posts that don’t contribute to the popularity of their sites.

Conclusion

It’s impossible to run a successful website without quality reporting. Google Analytics gives you all the tools you need to identify both the pros and cons of your site, but you have to figure out the key metrics that explain your online business.

I showed you here 10 ways to use Google Analytics like a boss. While these aren’t the only useful features, they are definitely critical to the overall functioning of your website, so make sure to use them and improve performance in the long-term perspective.

The post 10 Ways to Use Google Analytics Like a Boss appeared first on Tricky Enough.

On average, data scientists earn almost $140K on a yearly basis. Money surely is a factor of motivation. But if money is your sole interest in getting into data science, you’re already making a big mistake. Without passion for numbers and statistics, you’ll quickly be bored. Data science requires a deep mathematical background and an ongoing process of learning.

But even if you enter this career with great passion, you might still make mistakes. All beginners are amateurs. But there’s a difference between those who rise above the rookie stage and those who fail to make progress.

If you’re aware of the common mistakes that data scientists make, you might recognize some of them in your own practices. When you recognize the flaws, it will be easy for you to fix them.

Are you ready?

We’ll list the 7 most common mistakes that amateur data scientists make.

1. Too Much Focus on Theory

Before you can get into the practices of data science, you’ll need some theory to provide a good foundation. This is often where beginners make a big mistake. Yes; the theory is very important in this niche. If you don’t apply that theory, however, you’ll end up with a huge database of information in your mind that serves no purpose. You’ll bury yourself in online courses and books, but you’ll struggle to apply that knowledge into a reality that requires a problem-solving approach.

How do you avoid this mistake?

Never divide the processes of learning and practice. These are not separate stages in your growth as a data scientist. You learn and practice continuously, at the same time. Whenever you’re focused on learning a new aspect of data science, you should work on datasets or problems where you can implement that knowledge.

2. Jumping into Practice Without the Needed Knowledge Base

This is the other extreme. Many people are inspired by the trend of data science… well mostly, they are inspired by the high salary. They did well with math and statistics at high school and college, so they assume they can master data science on the go. Instead of investing in proper education, they want to jump into problem-solving tasks right away.

That’s not how this works.

You can’t become a data scientist unless you master concepts of calculus, linear algebra, probability, and statistics. Maybe you don’t need too advanced knowledge to start, but you have to get above the basics. What you learned in high school is not enough.

So how do you solve this issue? If you’re still at college, it’s important to start taking the right courses. Focus on calculus and statistics and make sure to include probability in the mix. If you’re looking for an alternative to traditional education, you can always explore online courses. Coursera offers great courses and specializations.

3. Preferring Complex over Simple Solutions

A data scientist is a genius. This is a person who can do advanced math and statistics but can also code. At the same time, they understand how businesses work. When you have that many tricks up your sleeve, you want to impress clients. Thus, you might think that it’s always necessary for you to apply the most complex computer science and statistical methods.

No.

This is a very costly mistake. It will cost you time, effort, energy, and nerves.

The main tools for a data scientist are data exploration and visualization. You will and you should be spending most of your time exploring data. That’s what clients are hiring for. Unless you’re specifically hired to write an in-depth analysis of a basic business issue, don’t do it. Focus on what your job description says: discover actionable indicators and recommend specific steps for your clients.

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4. Using Data Science Slang in Your Resume

Have you ever wondered why so many data scientists decide to hire a writer for their resumes? They already have the knowledge and skills needed for this kind of profession. So why don’t they just list those qualifications and get the resume done?

Many job applicants do that, and they make a huge mistake. They list a plethora of tools they know how to use, and the techniques they implement in their practices. Do you know what that means to a hiring manager? Absolutely nothing!

Recruiters, hiring managers, and business owners are not data scientists. They want to know what you can help them achieve. Yes; they want to see what you’re skilled at. But you can’t list terms like classification, regression, and clustering without explaining what they are important for the employer.

The best way to avoid this mistake is to write the resume for a beginner reader. Consider the fact that the person who will read this has no idea about data science terms. They want to know how you’ll help them improve their practices, so that’s what you should focus on. If you’re looking for a quick solution, you can rely on the best essay writing service. You can go to a writing service that’s specifically focused on delivering resumes, but academic writing agencies like Best Dissertation will also do a great job for you.

5. Procrastinating the Work on Simple Requests

“It’s just a few lines of SQL code… I’ll just do it next week.” When the client requires a simple task from the data scientists, the procrastination habit kicks in. You tend to think like an advanced engineer, so you like building scalable architectures for long-term results. But guess what: the client usually needs quick steps and actionable insights from you. If you can’t provide such solutions, you’re won’t be successful at completing tasks.

Keep this to mind at all times: your clients care about sales. When you can provide insights through very simple tasks, you’ll be doing your job well.

Do not neglect the simple requests. In fact, you should turn them into a priority. Instead of being focused on implementing all tools and the entire knowledge you have, just focus on solving business problems.

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6. Ignoring the Need for Communication Skills

“Just trust me on this one. I’m an engineer. I know what I’m doing.”

Data scientists love that. Clients hate it. No; they are not going to trust you just because you have the education and skills to be a data scientist. They will trust you only if you manage to communicate your ideas. If you stop the communication channels, you’ll fail to convince the clients that you’re doing your job. You’ll leave them hesitant and stressed out.

Communication skills are essential for building a successful career in data science. The communication should flow along the analysis. As you make progress with the analysis, you’ll communicate the steps and you’ll explain the recommendations on the go. Don’t wait to deliver an entire report of several pages. You’ll surely do that as the final point, but prepare the client well through gradual information.

7. Jumping into a Project without Developing a Plan

When data is easily available for a particular project, a beginner data scientist usually jumps in without defining questions and a plan. That’s a recipe for a disaster.

Never forget what a real professional knows: data science is a very structured process. It must start with specific objectives and questions. Without such structure, you’ll easily get lost in a huge volume of data without a purpose.

Start by setting hypotheses that help you achieve the final objective. Plan how you’ll test the hypotheses. That’s always the starting point.

Also, read:

Better tricks to safeguard your company’s database.

It’s Okay to Be a Beginner; Just Be a Good One!

Well you can’t become an advanced data scientist out of the blue, can you? You have to start somewhere, so you can’t skip the beginner stage.

But it’s still important to be a great beginner. When you avoid the seven amateur mistakes we listed above, you’ll think and act like a true professional. That’s what sets the way to career success.

The post 7 Common Mistakes the Amateur Data Scientists Are Always Doing appeared first on Tricky Enough.