Natural Language Generation with Python is Changing the SEO GAME!

By Richard A. Rowell, Online Content Strategist at Content Revival

Learn how natural language generation with Python is becoming a must-know subject for those who work in SEO (Search Engine Optimization).

As a digital marketer focused in online content strategy, I know how important it is to create amazing, useful content. Of course, content creation is a very time-consuming process.  While I enjoy writing content for a living, sometimes it’s nice to have a little assistance.

So, you can imagine my excitement when I saw this tweet from Hamlet Batista, CEO of RankSense, on Twitter:

💥Wanna learn to generate quality articles using very little #python code? Check out my @sejournal column tomorrow at 10am EST. You will learn to produce content even when the target pages don’t have any! 🤓

— Hamlet Batista 😷 (@hamletbatista) June 12, 2020

That article went live on June 12, 2020, and you can find it here: How Natural Language Generation Changes the SEO Game

Python is one of the most versatile programming languages out there. In the field of data science, Python is widely used to create deep learning models to parse massive amounts of data.  When it comes to the field of search engine optimization (SEO), this machine learning is being used to assist in creating content that’s well optimized for search. 

Through a process called Natural Language Generation (NLG), there are programs written in Python that can generate text based on context from a webpage and its backlinks. These scripts will read a webpage, then analyze that page’s context, such as anchor text on links, images, and videos. Then, that input uses machine learning models to create text based on the context provided.

Of course, Mr. Hamlet Batista brings up the obvious problem with natural language processing scripts like this. Already, Google has taken steps towards identifying spammy machine-generated content. But, as Mr. Batista points out, this Python code can be used effectively to automate tasks such as creating meta tags such as titles and meta descriptions automatically. 

Yes, it can also be used to produce long-form content that pulls from a variety of sources. The trick is to use these Natural Language Generation tools responsibly, just like anything else automated. We’re not going to see AI-generated content completely take over the world just yet. After all, the deep learning algorithms aren’t yet close to perfect. So, depending on the strength of the dataset used, the deep learning scripts can start to produce some silly strings of words. But, the power of these open source scripts are real.

Being a student of online marketing, I’m definitely going to learn more about Python. If you run any kind of website, you’ll want to learn how it can be used responsibly to make content creation more efficient. I definitely recommend reading Hamlet Batista’s articles and learning all you can when it comes to Python and SEO.

Already, natural language processing and generation is becoming mainstream as a component of many paid SEO tools. Even the free version of one of my favorite SEO tools, SEO Powersuite, has integrated some machine learning into making content template suggestions. And, thanks to the open source nature of the Python programming language, anyone dedicated enough to learning how natural language generation works will be able to benefit from them with some training.

As more people learn how to code in Python, text generation from NLG could well become the new normal for churning out fresh content. Maybe it’ll be a long time before AI is writing bedtime stories for our kids, but it’s already able to save us digital marketers a lot of time creating content here and now.