November 12, 2021
Back in the day, SEO (short for search engine optimization) was a matter of producing content and stuffing it with keywords. But, in today’s world, SEO specialists require a whole range of technical skills and tools to boost their site’s rankings. A large portion of their responsibilities includes manual, repetitive work which can get pretty overwhelming and distract them from more complex, strategic tasks.
Fortunately, there are multiple creative solutions to speed up and automate many of these tedious tasks. In today’s guide, you’ll learn what SEO automation is and the importance behind it. We’ll then show you how to have automated search engine optimization processes by building simple scripts and web applications.
SEO automation is a way to automate mundane, repetitive tasks that you would usually do manually, i.e., rank tracking. Typically, it is done via third party tools or custom-built tools.
When we hear about SEO automation, most of us immediately think about tools like Ahrefs, SEMrush, Searchmetrics, or SEOmonitor. Rightfully so – these SEO automation tools can help with competitor analysis, link building, keyword monitoring, and so much more.
But for someone who runs a small business or agency, the company budget likely won't cover high monthly fees, let alone for more than one different tool. Because of it, companies become dependent on a single platform, which may lack some features they need.
As a result, SEO specialists either have to choose one or two tools – and lose out on specific functionalities other tools offer – or do the tasks manually.
However, one simply can't manually do all the work and keep up with the ever-growing competition, making SEO automation a crucial part.
Plus, even if an SEO specialist does have access to (several of) these SEO tools, that's often still not enough. Although these tools help automate a lot, they can't do it all. Here's where custom-made SEO automation solutions like scripts, simple web apps, and Google Advanced Search Operators come in, helping companies automate SEO tasks and save money.
Now, we'll take a look at 6 methods for automatic search engine optimization processes.
There are many ways to have automated SEO processes without the use of expensive third-party tools. In the section below, we will define several solutions that can help to increase automation and save time on manual tasks for free or in a budget-friendly way.
1. Using advanced Google search operators
A good place to start with SEO automation is to master Google's special commands that help to retrieve content and insights more effectively.
Say one wants to analyze the content output around a certain topic by their main competitor. It can help shed light on the competitor's content strategy. For instance, you can see if they have incorporated the use of topic clusters in their strategy.
In this case, the advanced Google search operator "site:example.com keyword" can be of great value. This command triggers Google to search through the selected website (in this case, "example.com") for the selected topic (in this case, "keyword").
Once you have the usage of search operators narrowed down, you can retrieve the data using our Google Search API.
But this is just one example. There are dozens of similar search operators that can help speed up SEO tasks and be useful for site audits, page optimization, and the likes. For more information, below is a table of all Google search operators. Here’s an article that covers what each of them does.
On their own, these operators are already useful for performing some simple SEO tasks. But building them into scripts and web apps can help automate things even further.
2. Building web applications or using a 3rd party tool
How the web app functions and what data it pulls is completely up to the programmer. Through the use of commands (like the search operators explained above), the programmer can create practically anything.
The web app can be instructed to crawl a website and find product details. Or, it can go through Google's search engine results pages (SERPs) to collect data on keyword rankings. However, keep in mind that Google doesn’t appreciate having its SERP pages scraped. To prevent that, Google regularly changes its SERP structure and overall algorithm.
Plus, if Google determines that you’ve been checking rankings or tracking specific keywords too often, it may ban your IP address or flood you in CAPTCHA tests.
To get keyword data, companies typically go for an SEO automation tool like Ahrefs or a data scraper, such as SERPMaster. Below is a table that compares the number of keywords automated SEO services and scraping tools provide for 99 USD a month.
As you can see from the table, web scraping tools provide a significantly bigger number of keywords per month. So, when choosing from automated SEO tools, choosing a web scraper over an SEO giant like Ahrefs will certainly save you money.
As for web applications, they can range from a fairly simple script or web scraper that helps automate a minor task to complete data analysis tools that offer loads of features.
Now, building a detailed web application will be out of scope for most small businesses. However, writing scripts and web scrapers to automate simple SEO tasks luckily doesn't have to be hard or time-intensive.
Either way, to get started, you needs to decide on a programming or scripting language to use. At the moment, the Python programming language is the best option for automating SEO and creating simple web apps.
3. Automation with Python for SEO audits
Python is defined as an open-source, interpreted, object-oriented, high-level programming language with dynamic semantics. The language can be used for all sorts of functions, including rapid prototyping, connecting to database systems, and creating server-based web applications.
Python's syntax is considered straightforward compared to other programming languages, making it relatively easy to learn and build. Sites like W3Schools offer free online Python introduction courses to help new coders get started.
SEO experts can benefit from Python in several areas, including analysis of search and crawl data, natural language processing (NLP), and SEO tool automation.
Here are a few examples of how SEO specialists can automate daily with Python scripts, turning them into simple web apps.
One of the most common SEO routines is auditing a website to analyze each page for potential technical issues. With Python, a portion of this process can be automated easily.
Take this Python SEO Analyzer script for example. It allows the user to quickly analyze a site's structure and spot potential issues or opportunities by crawling the site.
It can identify broken links, missing markup, incorrect metadata, or similar technical problems in no time. The tool also counts the words on every page and analyzes common keyword usage on-site to highlight keyword stuffing or a lack of keyword usage on a page.
A great added benefit is that SEO specialists can use this script on both their competitor's website and their own. From the number of blog posts and the average word count to keyword frequency inside their article – this script allows the user to analyze the competitor's content at scale. Doing this for several competitors within a niche allows the SEO agent to benchmark their site against the rest of the landscape. This way, they can identify all the gaps in their own content marketing.
Regularly performing a content gap analysis is a crucial part of SEO strategy. Automating this process with scripts and simple web apps not only saves a lot of time-intensive manual work but also allows them to identify gaps in their own content strategy.
4. Automation with Python for image optimization
In June of 2021, Google launched their new Core Web Vitals update. The Core Web Vitals includes a set of measures like loading speed, interactivity, and visual content stability. Although load time has been a Google ranking factor for quite a while already, the introduction of Core Web Vitals will make it a crucial factor to show up in the SERPs.
As every SEO specialist knows, unoptimized images are one of the prime causes of poor loading speed. Specialists at SEO agencies often come across clients with websites packed with thousands of large, unoptimized images.
Now going through the entire site to compress and optimize all of them can take hours. Luckily, a simple Python script can help automate this task.
Take this Python image optimization script. It can go through the entire image directory of a website and compress and optimize the images according to the programmer's guidelines. This fully automated way to optimize images can make one of the most mind-numbing tasks a whole lot easier.
5. Automation with Python for site speed optimization
While on the topic of site speed (again, its importance for SEO can't be overstated), there is another way Python can help speed things up. After all, images aren't the only culprits that cause poor page speed. Think about content-heavy plugins, for example.
Now an SEO expert could go through every single page of a website, throw each separate page in Google Pagespeed Insights, and check each one's performance. If their client's website has thousands of URLs, this task will take days.
With the help of Python, one can create a simple web app (like this Pagespeed-Insights-API) that first crawls the entire website to extract all URLs and then automatically connects with Google Pagespeed Insights to analyze every page's performance.
This method allows for checking the speed of web pages in bulk. Since it pulls data from Google's own Pagespeed Insights tool, the user gets all the same valuable data as when running the tool manually, but in a much quicker, automated fashion.
When auditing a site, this can save the user hours of valuable time, which they can then use to fix any speed issues they encounter.
6. Automation with Python for link validation
As a website ages, new pages are created, old ones are deleted, and 301 redirects or 410 content deleted headers are put in place. Unfortunately, when multiple people (especially non-SEO experts) are deleting and adding content to the site, links can get broken, and 404 errors will pop up.
Poor link structure like that can harm a site's organic performance or cause temporary losses in traffic due to accidentally broken links.
For important pages, one might not notice the link is broken until they see a significant drop in traffic in their Google Analytics – at which point damage has already been done. For less important pages, broken links might go undetected for months, harming a website's performance without anyone knowing.
This is where a Python script such as Pylinkvalidator can come in handy. This script automatically runs through an entire website to check the URL status code for each page. If a page is broken or if a redirect is in place, the script will detect it.
This automated way of checking for link issues not only saves time but can help detect them before they result in loss of traffic (and thus revenue).
In most cases, a custom-built solution won't be as powerful as an industry-leading SEO tool, like MOZ or SEMrush. Yet, it can save the user a lot of money and still provide equally effective solutions to some of the simpler tasks and problems SEOs face.
Utilizing the power of advanced Google search operators, writing basic Python scripts, and building custom web applications requires a bit of technical know-how and the help of publicly available, open-source solutions. But it's all worth it in the end – SEO automation for mundane tasks allows specialists to focus on more complex, strategic parts of their job.
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