By OLIVER ANDREWS
Python For Technical SEO Marketing
Why You Should Switch To Python For Technical SEO Marketing
It didn’t take me long before I started learning how to apply Python’s SEO strategies. As I write this, I must admit that I am delighted with the skills and knowledge I have acquired so far. However, my curiosity for perfection using Python is unquenchable. I feel mutually obliged to help my fellow SEO community members to learn how to use this language in Automating SEO Tasks. You don’t need a computer science background to understand the language and apply the strategies in your content; that’s the beauty of Python SEO. Tag along and learn some new amazing ideas I discovered, which I’m already applying.
What Is Python?
Python is an object-oriented and interactive open-source programming language interpreted line by line. The language supports a huge number of libraries and modules, great readability, user-friendly, and a simple to use syntax.
Python’s great power and performance in SEO automation is recognized by big companies like Netflix, Google, NASA, Google, and Spotify and acknowledged its contribution towards their growth. Key features provided are speed, simplicity, and scalability. Worth noting, Google’s first web-crawler was coded in Python.
How Python Helps With Technical SEO
Without disputing the fact that having an understanding of common program languages such as CSS, JavaScript, and HTML is important, everyone should feel propelled to learn some simple Python language. Unlike the rest of the languages that support our websites, Python provides numerous automation opportunities, thus saving you time when performing low-level tasks.
Not only does Python analyze and extract massive data, but also facilitates automating repetitive tasks on your website. Additionally, SEO professionals are empowered by its prowess and unmatched performance. With the amount of data that SEO content creators work with increasing every day, being able to apply Python to break down the data efficiently is an advantage marketers can’t ignore.
SEO professionals have catalyzed the growth and popularity of Python language. With Python, not only will marketers be able to understand the analyzed data, but also, enable them to make accurate data-driven decisions. In marketing, everyone understands that marketing decisions define your marketing career; they either earn you favor from clients and stakeholders or taint your reputation. Python enables SEO professionals to make rational decisions driven by concrete insights, which boost their confidence.
Automating Your SEO Tasks
Though Python may fail to imitate human feelings, perspectives, and intent strategies, it can handle efficiently a large number of tasks that we spend much time on. Some of the most important tasks that Python automates include:
- Optimizing images.
- Internal link analysis.
- Identifying user intent.
- Performing keyword research
- URL mapping before migration
- Ready To Try Out Python?
Here are some scripts for you to try with a guiding brief of each script and their applicability.
Image Captioning
You will fall in love with Python’s image captioning script without even noticing it. This feature enticed me to explore Python’s applicability in detail. The script auto-generates captions for an image URL, thanks to Pythia’s deep learning framework. The caption is applicable when captioning images that lack alt tags. It enables quick accessibility during an image search.
The script uses top-down and bottom-up mechanism to focus on different elements of an image when calculating results. The number of individual pixels in an image determines where attention should be drawn to generate caption words. The region with maximum attention determines the words generated. Python allows users to run image script without direct coding. After copies of specific codes have been saved to your Google Colab drive, all the cells ran automatically. It performs the rest of the steps for you which would typically require manual undertaking.
SEO Analyzer
SEO analyser script analyses data structure to give a detailed breakdown of basic SEO issues in a website derived through crawling. Once the script has been installed, it crawls a website to display site data. Displayed data include page titles, meta descriptions, and word counts. Also, it gives warnings in case there are missing files, alt text, and meta descriptions.
Image Optimiser
The script reduces the size of an image without losing its quality. However, I would advise that you keep a copy of the image before running the script since the optimisation can be destructive when not well executed.
With Python’s Automation possibilities such as Log file analysis, Internal file analysis, Keyword growth calculation, Competitor analysis, and Collecting GSC data rolling out continuously, it’s important that SEO professionals learn and apply these special automated features.
