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3 Stages and Tools for SEO Automation

3 Stages and Tools for SEO Automation

SEO automation is a process of systemizing and optimizing SEO tasks with the help of SEO automation tools and software to simplify campaigns. 


The principle of automatic implies the utilization of software to perform tasks swiftly. With SEO automation, you can update the information to your team members with just one click by using one dashboard. It also reduces the period and resources spent on various SEO activities.


The Problem Faced by SEOs


The SEO industry is plagued by a severe shortage of resources and available talent. This is especially evident at the enterprise level, where data sets are vast, dense, and complex, making it difficult to make sense of and act on the data. 


Not to mention that while the various SEO tools are advanced and excellent at pointing out issues to SEOs, they cannot actually "do SEO."


Meanwhile, Google is becoming increasingly intelligent, employing machine learning and artificial intelligence to provide users with the most relevant information in the most efficient manner. The SERPs are more complex than ever, with Google entities competing directly. 


There is far too much data to act on for any human agent to handle alone. On the other hand, automation works around the clock and can produce insights that would otherwise take hours to obtain. SEOs are naturally limited by their ability to sort through data and act on insights at the level required today — AI and machine learning can fill the gaps and accelerate execution. 


It is critical, to begin with, the fundamentals before progressing to automated insights and, finally, automated execution. Automation has changed and evolved, so let's compare what SEO automation looked like in the past to what it looks like now.

What are the Stages of SEO Automation?

Three stages of SEO automation are:


1. Beginner (Data Collection)

2. Intermediate (Automated Insights)

3. Advanced (Execution and implantation)


Beginner- Data Collection


If you are newly introduced to automation, you need to start with data collection, as you cannot benefit from it unless you start with the basics. Data collection and aggregation are very valued. It is one of the first steps in SEO automation. 


It is one of the most time consuming processes and at the same time, it is necessary to do so. It is also a bit of an expensive developmental process in SEO automation. Data collection and aggregation shows how good you are at SEO since it is one of the most basic steps of SEO. 


There are two ways to collect data,

a) DIY (do it yourself)

b) API (application programming interface)


DIY (Do it yourself) for SEO Automation


In this, you have to deal with web crawling and parsing, structuring the data and rewriting it into a convenient format and storing the data in a database, and many more. Using DIY tips is recommended especially if you are short on financial support since it helps with the overall improvement of the SEO process.

  

To get results with DIY SEO, you should have to,


  • Set your organic search baseline
  • Keyword research and relevant search queries
  • Create and publish optimized content
  • Fix site issues and technical issues
  • Build links
  • Stay informed

API (Application programming interface) for Automating SEO Processes

api for seo automation

Getting data through an application programming interface is a very convenient way in SEO and marketing software development. SEO tools are available to choose relevant keywords, creating high-level content, formatting content, responsive design, localization, SEM, and other SEO essentials, which are often accessible by several APIs which are:


  • Google PageSpeed Insight API
  • DataforSEO API
  • Alexa Top Sites API
  • SEO Content Analysis
  • Google Analytics API
  • Google AdWords API
  • Google My Business API
  • Bright Edge API
  • Geo Ranker Tracking API
  • Serpstat API
  • Mozscape Rest API
  • Website Worth API
  • SEO Explorer API


Data obtained by DIY is complex, time and resources consuming and challenging to scale. Moreover, data obtained by API is at affordable pricing, ready-to-use.


Data collection and aggregation is one of the basic steps of SEO software development.

There are many ways to collect it, but the choice of path relies on you. When you decide which one is the jewel for your case, always consider the number of resources you can devote to the task.


Intermediate- Automated Insights


automated insights


As automation advances, SEOs will be able to focus their efforts where they are most needed, allowing the technology to surface site-specific, actionable insights for them. This starts with AI-based alerts: receiving a notification if the AI detects a significant rank change or a critical page element is modified or deleted. 


In this case, automation plays a role as a member of your team, monitoring thousands of pages continuously, so you may not have to perform such a problematic and gruesome task.

Once alerts are automated, SEOs can focus on the advanced and customized insights provided by the AI. These insights assist in the identification of opportunities and issues, allowing you to prioritize strategy and execution.


A few examples of this include recommendations and actions within:


  • Technical audits
  • Content analysis
  • Log-file analysis
  • Backlink analysis (identify link partners, quality backlinks, toxic links)
  • Keyword research (analyze competitors, identify keyword patterns and topics)
  • Page and rank change alerts


Marketers must understand that the sophistication of automation varies significantly in terms of what SEO software brings to the table. To surface and customize those insights based on your site's ranking, crawl, and link data, advanced AI and machine learning are required. Not just the generic and basic on-page SEO provided by most tools.


SeoClarity's Actionable Insights analyses data in real-time to reveal custom, site-specific opportunities and issues for content, page speed, indexability, schema, internal links, and more. These insights are based on data from your site's ranking, crawl, and links, so the technology analyses your site as if it were a member of your in-house SEO team.

Advanced- Execution and Implementation

The advanced steps of SEO automation are execution, implementation, and testing.

Enterprise SEO sets up automation, templates, the proper process, and system and process to increase output successfully. The biggest challenge in enterprise SEO is the speed of execution and implementation at scale.


advanced seo automation


We mostly heard from SEO teams that their technology stacks do not allow them to implement desired changes; they are strapped for resources and cannot take action on the insights even if they are not able to prioritize SEO projects. Thus, SEOs cannot implement critical fixes, deploy new enhancements, and conduct any form of testing to improve results.


Whether it comes to implementing minor briefs or working on a forecast to prioritize a plan, it reduces what we know and should be implemented while Google speeds ahead. You need to keep in mind that you will not meet the results you are looking for unless Google can see the changes on your site.


The development in automation empowers SEO teams to overcome the difficulties that are standing in their way and deploy changes on-site without the need for developers, UX teams, and other stakeholders.


Many companies and their SEO team have not yet implemented this level of automation in SEO. It may be because it is too complicated for them or it is not yet accessible to them.

Although it is the top compliant and roadblock we hear from SEO and their team, enterprises and companies still struggle to scale execution.


Manno Notermans

Manno is a wanderer of the world looking to make an impact and change the world for the better. He has over 10 years of experience working in various marketing positions. Manno’s main focus the past few years has been accelerating the growth of businesses, increasing revenue, and profit with out-of-box creative ideas and implementations.