In modern day marketing, search engine optimization (SEO) is necessary for success. It is vital to maximizing business visibility and creating an effective user experience, both of which lead to increased profit and brand loyalty. The optimizing of a web page or domain for these purposes is called “technical SEO,” as it often deals with the code or design of the website.
The practice of technical SEO is based on data insights. This scraping, analysis, and interpretation of information is reminiscent of the job done by many data scientists. Of course, data scientists may not consider themselves prime SEO candidates, yet there is a connection between the two that cannot be denied.
This article will show the connection between data science and technical SEO. Hopefully, upon realizing the similarities, professionals from both fields can further their own abilities by borrowing methodology from each other. Whether that means SEO professionals are able to find a wider variety of information relevant to their work or that analysts can learn new ways to manipulate data, it’s clear the two have a lot to gain from each other.
SEOs Can Learn More About Data Analysis
SEOs and data analysts both use similar methods of examining information. Take the concept of data visualization, for instance. The use of visual demonstrations such as charts, scatter plots, and digital models is a regular occurrence in both professional fields. This helps them to communicate with clients or other departments who may not have a technical understanding of data.
However, this is complicated by the tendency of SEO professionals to isolate themselves within their niche and to only use SEO-based software. Doing this forfeits a lot of information that would otherwise be useful to them. Considering that SEO professionals now have free access to data sources from all different kinds of professional fields, this is a major oversight.
Data analysts often work in coding software, and SEO analysts could benefit from using such programs to scrape and organize keyword information from multiple sources. In other words, data science tools offer information that may be better suited to explain why certain SEO methods work and others don’t.
Data Scientists Can Learn More About Data Manipulation
Data scientists work primarily in the interpretation of data. They scrape information and create a report for a firm’s decision-makers, detailing precisely what it means for a business. However, SEO specialists take this data and manipulate it in order to drive engagement. If data scientists learned how to manipulate that data as well, they could further advise digital marketing departments and round out their own skill sets.
This truth is especially relevant when talking about technical SEO. Looking through a technical SEO checklist, many optimization tactics are specifically informed by data. URL structures, site designs, and meta tags, for instance, are formed in response to analytic insights.
Data scientists already have the information necessary for site optimization and technical SEO, but they could take it a step further by learning how to apply it practically. This would allow them to effectively communicate with SEO specialists and take on advisory roles. Their standing in their workplace could grow accordingly, giving them newfound authority.
Examples of SEO/Data Science Overlap
The overlap between SEO and data science already exists to an extent. There are specific tools, primarily those offered by Google, which are heavily used in both fields. Google Search Console and Google Analytics are major examples.
There are other tools that could benefit both fields. For instance, Octoparse has completely automated the jobs of data analysts by compiling large amounts of information. SEO specialists could utilize Octoparse by scraping competitor websites. On the other hand, data scientists may do well to understand how to write schema markup for search rankings.
These examples are only a few of the ways that SEO and data science can overlap for better digital marketing results. Both of them have great potential to benefit the other. It’s important to always be learning more and sharpening your skill set, after all. Further innovation could bring digital marketing methods to great heights and create room for more efficient results in the future.