In recent times we are checking how SEO changes vertiginously at the rate that Google decides to change its algorithm . Long ago those times in which a small adjustment of content or a correct labeling in the title allowed us to be in the top results in the search.

Google’s algorithm is now much harder to decipher than before and you have to always be up to date, since 75% of users say they never pass the first page of results in their searches. This forces us to compete in terms of SEO, to overcome the basic techniques that worked so well in the past. Data Science or data science comes into play.

What is data science?


Data science is an interdisciplinary field includes different scientific methods, processes and systems for better understanding of data in its different forms(structured or unstructured), which is a continuation of some fields of data analysis such as statistics, data mining, machine learning and predictive analytics.

Why do we need it?


According to the University of Maryville, at the end of 2020 each person will generate 1.7 megabytes of information per second. Therefore, knowing big data is going to be fundamental if we want to survive in a world so collapsed with information.

Data science provides valuable information about the performance of a website, information that can help us improve our SEO campaigns. This science is used to make predictions about upcoming trends, to know how the user will behave through machine learning and analysis. For example, analyzing the tastes of its customers, Netflix is ​​able to produce a series knowing of its more than likely future success.

How can you help SEO?

According to Data Science training institute in Bangalore, Data Science helps us make much more concrete decisions, because it allows us to:

  • Visualize which combinations have the potential to have the greatest impact on potential visitors to our website.
  • Create marketing campaigns that are aligned with the tastes and needs of our customers.
  • Understand the preferences of our guests and identify possible weaknesses.
  • Identify the reference sources of conversion traffic, that is, from where users access our website.
  • Check the web load time, indexing, bounce rate, response errors, redirects
  • Verify more and less crawled URLs.
  • Identify the pages that we want crawlers not to index.
  • Identify unusual traffic sources.

But how does this Data Science apply to our SEO data?

Select data sources


We must understand that the quality of our data sources directly impacts the knowledge of that data. We need the right tools to track important metrics more accurately. There are several tools that can help us collect the data correctly to make better decisions. Among them, Google Google Analytics , SEMrush or Ahrefs stand out.

Think of ‘ecosystem’ instead of data and tools


We cannot rely on a single solution if our SEO is complex and integrated into other areas of digital marketing such as content marketing , customer experience management, CRO (Conversion Ratio Optimization) or sales.

The approach that Data Science should take to SEO is based on the inclusion of methods, tools and practices that extract deep and accurate information from the accumulation of data. For example, SEMRush presents statistics assuming that all traffic is good and genuine.

But are you sure there are no bots that are dirtying these results? It is therefore important to incorporate tools to verify the quality of traffic such as Finteza. Thanks to its advanced technology, it is able to detect bots, in addition to providing a complete set of conversion funnel optimization modules, to help make our data more meaningful.

Align SEO with marketing initiatives


Supporting SEO with other marketing initiatives makes it stronger. Sales, IT, designers, web developers, customer experience, customer service … all these teams have to be coordinated to optimize all search factors.

Data science determines which SEO practices are best for each of the company’s teams to achieve their goals. To understand how SEO affects other channels, we have to analyze data from:

  • Main conversion routes.
  • Conversions and assisted conversions .
  • Obtaining a clear understanding of the client’s travel map allows for a stronger alignment between the various marketing activities, as well as attributing the results to what campaigns in a simple way.

Improve data visualization with Data Science


It is very difficult to digest all the numbers stacked on a spreadsheet. Adopting a hierarchical approach to data can cause hidden information to be lost between the lines. Therefore, improving the way data is visualized helps to:

  • Compare and contrast.
  • Process large volumes of data at scale.
  • Accelerate the discovery of knowledge.
  • Reveal hidden questions.
  • Detect common patterns and trends.

According to Freelance SEO expert in Bangalore, taking advantage of data science during a technical SEO audit helps to receive detailed information about the status and performance of our website. We may use that data to know more about the authority of the page, rankings, number of external and incoming links per page, as well as other factors.

However, we will not know why some pages work better than others in search results. Taking into account the internal links of the site and discovering the authority of the domains on a scale of one to ten (as Google does) help us to take proactive measures to improve the positioning of these pages.

SEO optimization on the web itself is just an example of how positioning experts combine data visualization with Data Science to provide better search results.

In conclusion, data science focuses on eliminating conjectures around SEO. Instead of presuming what works and how a specific action affects our goals, we have to start using Data Science to know what gives us those results and how we can quantify our success.