Have you heard of Python for SEO Automation?

Vidya Gopinath for keySkillsetVidya Gopinath for keySkillset
Vidya Gopinath for keySkillset
Have you heard of Python for SEO Automation?

If you are an entrepreneur, a startup or a business owner with a website that you want to rank higher, then you know the importance of SEO. And there are some repetitive tasks in SEO which you cannot ignore, if you want your site to rank high. Automating some of these repetitive tasks is clearly the best strategy. But, not many would have thought that it is possible to automate these tasks by implementing Python coding. When you hear the word Python, you know it is a sophisticated programming language used to automate repetitive tasks. But, did you know you could implement Python for SEO as well? 

To begin with, let's discuss why you need to learn Python and how it works for SEO automation. 

3 Reasons to Learn Python for SEO 

Learning Python is sure to make your life easier as an SEO professional. While from the Small website owners to agencies and medium to large sites with over 100k urls can benefit from Python for SEO, it is not necessarily the same thing that all these would learn. While small site owners can benefit from marketing or social media automation, you may also learn web development or build your own SEO tools. With python it will be possible to leverage free SEO tools, as it would be possible for you as a small site owner to build it yourselves. Agencies meanwhile dabble in reporting, some automation and creating scripts or templates that you can reuse from client to client. And for bigger websites, you get into data analysis, build your own tools tailored to your requirements. You will also learn how to leverage API with the help of Python. So, there is no really single path to learning Python. 

Reason #1  Excel 

How excited are you about using Excel for SEO? You would have seen those multiple reports and spreadsheets that SEO managers maintain. Imagine you have this pre-built formula for Excel. Now, you make a one single tiny mistake in that and you are just stuck scrolling through it to find this error so that you can fix it. Formulas can be really long and messy and it can be a bad process to work on if you are not proficient in it. Reports claim that about 90% of spreadsheets have errors that affect the results. Main issues with using Excel are marked here-data volume, syntax errors and security risks. So, what can you then do instead of Excel? Best and most convenient alternative that will make you more efficient is definitely Python.

Python automates mundane tasks more efficiently and it allows better calculation of more complex equations and algorithms. It is an open source programming language, thus enabling the code to be inspected and modified by anyone on the team. Also, the Python libraries have many functions and methods that allow you to perform many actions without writing your code from scratch. So, SEO practitioners can study and adapt existing Python codes to get better results. If you want to collect data from Google Analytics Query Explorer, you should set up an API URL that can fetch data across websites with multiple parameters. Or, for analyzing webpage “winners vs. losers” after a site migration–you can fetch the data from Google Analytics and then use a library such as Pandas, to group the page traffic before and after the drop off date. This will enable you to perform more complex data analysis, such as data blending, to merge the data frames to determine invaluable information for best SEO practices going forward. 

Application of macros to automate tasks makes it more complex to use Excel than the automation of tasks in the Python environment. Python can also be easily integrated with other programs to make it more suitable for data analysis. Python, compatible with SQL syntax, makes it possible to run it within its framework to extract data and tables to its environment. The Python environment also automates tasks such as importing data and writing, analyzing data to Excel or CSV functions for data analysis, quite efficiently. This definitely calls for using Python for automation

Reason #2  APIs 

Those big blocks of codes that people and companies have worked on. That’s how you can easily define APIs. Python can be implemented to use Google search console APIs. Google search consoles are limited as it cannot store everything and provide it for everyone. With the API it is possible to extract about several hundred thousand rows of data daily for a single website. With Python once it's connected to the API, it's very easy to extract the entire data from the API and do an amazing visualization.  

Reason #3 Homemade Tools 

Most SEO tools are very expensive and you really don’t have use for everything in those tools. So, with Python you can start building your own as per your requirements. First thing to learn is web scraping. Screaming Frog does its job brilliantly and it's probably not possible to replace that, but trying to build your own crawler could give you a better understanding of SEO. With Python you could also create your own sitemap. 

Now, have you given any thought to the SEO tasks that you can automate using Python? Check this out to get that information. 

SEO tasks to automate with Python 

Here is a list of some SEO repetitive and time consuming tasks that you can automate to save time. These tasks are made more effective by using Python for automation. 

1) Visibility Benchmarking 

The objective of visibility benchmarking is to review a site's current visibility in comparison to its competitors and identify any gaps in keyword coverage or content coverage. This also identifies where your competitors have visibility over you. You could ideally pull the data using sources such as SemRush or other tools. To do this, you must enter the data into Excel and organize it into branded and non-branded keywords. You may find it difficult if you have many non-branded keywords, business lines, and competitors, as well as multiple categories and subcategories. With Python scripts, capturing untapped audiences and identifying content gaps can be automated using cross-site traffic with overlapping keywords.

2) Response Code Analysis

You find out about a broken page or a 302 redirect after you look at your analytics and notice a drop in traffic and revenue on a critical page on your site. Luckily, there is a Python script called Pylinkvalidator that checks the status codes of your URLs for broken links or redirects.

3) Intent Categorization 

This is a part of visibility benchmarking, which can be time-consuming if it is done manually. For a huge site with thousands of millions of keywords, categorizing them by intent- i.e, see, think and do could take weeks. However, the process can be automated with the help of Deep Learning, which relies on sophisticated neural networks. Due to its extensive library and adoption within the academic community, Python is now the most common language used behind the scenes for this. 


Now, by automating these repetitive and tedious tasks, we save time thus making it possible for us to focus more on our clients’ organic performance. There is a great potential to use Python for SEO as it helps to automate time-consuming tasks. Its speed, versatility, clarity, and ease of learning is what makes this language more popular. And to implement this, there is no need for any programming experience. Meanwhile, as Google develops over time along with Machine learning, it will be possible to automate even more elements. It can also be used for Machine Learning and Deep Learning applications, as well as automating SEO analysis, checking for broken links, among others. So, it definitely becomes a crucial technology or language for SEO professionals to be familiar with. It can help them speed up and be more efficient. 

Now, keySkillset has realized the potential of Python in various sectors and for automating various tasks, and so it came out with its simulation based hands on training program for students to master all the shortcuts/ hack of Python coding. SEO professionals trying to make the transition to Python coding for automating their tasks will benefit from this course. To check out for details of the Python coding program that we offer, you can sign up with keySkillset

Learn more about keySkillset Python course here. 

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