We are in a world where technology is truly evolving in every aspect of our lives. In Search Engine Optimization, it involves making it simple to automate various tasks that would have taken days, weeks or months. And this is the reason why more and more SEO professionals are utilizing automation to boost boring and repetitive tasks using Python.
In this blog, we have discussed the boring and repetitive tasks using Python. However, let us first discuss what is Python.
Boring and Repetitive SEO Tasks Automated using Python
What do you mean by Python?
Python is an object-oriented, open-source programming language.
As per Python.org, it is easy-to-learn, simple syntax, which encourages readability and so it reduces the expense of program maintenance. Professionals use Python in NLP (Natural Programming Language), crawl/search data analysis and SEO tool automation.
Now, let’s move on to the six SEO boring and repetitive automation tasks using Python.
One of the most usual frustrations SEO consultants and agencies face is their clients not implementing the given recommendations even if it is very crucial to improve the organic performance.
The reasons change from client to client, but one general cause is that they lack the resources or expertise to implement the suggestions. And this is true if they got a challenging content management system.
Fortunately, there are solutions to for help such as SEO automation form RankSense that enables the users to implement almost three priority recommendations like robots.txt or title tags and descriptions every day or once in a week in CDN (Content Delivery Network) Cloudflare. While RankSense is only working with Cloudflare right now, but they are also working to add new CDNs soon.
With this, SEO recommendations are now implemented within days instead of several months. Along with this, the developers are only human that states they can at times commit mistakes that makes a great impact on Search Engine Optimization. It involves blocking the complete site as they pushed a brand new staging website into production without altering the robots.txt.
However, RankSense alerts the users to these errors and corrects it right away. This way it doesn’t affect organic traffic.
2. Visibility Benchmarking
Visibility benchmarking analyzes a site’s present visibility against its competitors and recognizes the gaps in content coverage/current keyword. It also finds where competitors have visibility, which is not seen by your website.
To be brief, you can extract data using BrightEdge, SEMrush and different data sources.
To carry out this process, you need to enter the data into MS Excel and arrange it non-branded and branded keywords and in various visibility zones. If you have got of business lines, non-branded keywords and competitors, it gets very challenging. Especially multiple subcategories and categories.
With Python scripts, you can easily automate the analyze and process cross-site traffic using overlapping keywords to captured far off audiences and find the content gaps. It is a faster process, which takes only a few hours to complete
3. Intent Categorization
A section of the visibility benchmarking process includes intent categorization. It is an exhausting process that was once done manually.
For a massive website having thousands or millions of target keywords that categorizes keywords through intent, it could even take weeks.
However, in the present scenario it has become possible to perform automated intent classification with deep learning.
Deep learning is dependent on sophisticated neural networks. Python is the most used language behind the scene for its extensive adoption and library in the academic community.
4. XML Sitemaps
XML Sitemaps nothing but the actual maps of a website, which allows Google to know about the most significant pages, along with the pages it should be crawling.
In case you own a dynamic site with thousands or millions of web pages, it could get difficult to identify the indexed pages, mainly when all the web URLs are put in one huge XML file.
Now, suppose that you have got crucially significant web pages that Google must crawl and index at all costs. Take an example of the best sellers on your eCommerce website or the most reputed destinations on a travel website.
If you are mixing the most significant pages of your website with your less important pages in the XML sitemaps, you will fail to realize when a few of the best web pages encounter indexing and crawling issues.
With Python scripts, it gets easier to develop custom XML sitemaps including only the pages you want to track to deploy on the server and submit on Google Search Console.
5. SEO Analysis
SEO tools providing an instant analysis of a web page to identify any kind of SEO problem is something we all love. Some of those problems include:
- When the page have a nice title tag or if it even has a title tag
- The meta description is missing or helpful enough to attract clicks
- In case the page is created with proper structured data
- When the page has an ideal word count
- If there common phrases included on the web page
Using a Python SEO analyzer helps you detect issues on every web page that you easily prioritize and fix to boost the organic performance of your website.
6. Response Code Analysis
Experts use links as an important signal by Google and various search engines and remain significant to improve your organic visibility.
Quality matters more than quantity.
You should make sure to earn links through great content on your website and how the content enables people to solving problems or how it provides products that help solving problems.
You can imagine having a critical page on your website, a page that contains a lot of links and ranks using thousands of target keywords. Eventually, it encounters 302 redirect or broken and you do not realize it until you look at the analytics and identify the traffic and revenue drop.
Thankfully, we have Python script named Pylinkvalidator that helps checking all the URL status codes in order to ensure you don’t have pages redirecting to a different URL or any broken pages.
In this case, you might encounter an issue when you have a massive website as it takes time for the completion of this process unless you have some optional libraries downloaded.
In a nutshell
Today, automation using Python is helping SEO professionals and agencies to save time and become more efficient so you can focus on the strategies to improve the organic performance of your client’s website.
Python is one of the most appealing programming language, which helps in automating the time-taking SEO tasks. It helps in completion of the tasks in lesser time without almost no programming experience needed.
With Google evolving with advancements in ML (Machine Learning) over a period time, increased elements will get automated. Thus, getting familiar with Python and other similar programming languages fro SEO pros can help give them a benefit in efficiency and time.