Nothing is more critical than having the correct team in place when it comes to successful data science for SEO.

The challenges connected with getting and assuring the consistency of the data, as well as your choice of machine learning models and associated analysis, all benefit from the collaboration of team members with diverse skill sets.

This article discusses the three primary sorts of teams, who make up each one, and how they operate.

Let’s begin with the most lonesome of data science SEO professionals: the team of one. 

The Lone Data Science SEO Expert

In both small and large organizations, the one-person team is frequently the reality.

There are numerous individuals out there that are capable of managing both the SEO and data functions independently.

The lone data science SEO specialist can be broadly defined as an SEO expert who has chosen to pursue advanced computer science studies to concentrate on the more technical aspects of SEO.

They are proficient in at least one programming language (e.g., R or Python) and are proficient in the usage of machine learning methods.

They are actively monitoring Google improvements such as Rankbrain, BERT, and MUM since Google’s algorithms have included an increasing amount of machine learning and artificial intelligence.

These professionals must be proficient in automating SEO operations to grow their efforts.

This may involve the following: Automatic indexing of newly created URLs in Bing.

• Sitemaps with the new URLs created for Google.
• Generating text using GPT models.
• All SEO reports have anomalies.
• Long-tail traffic forecasting.

At my company, we discuss these SEO use examples via a Jupyter Notebook.

However, they can be automated to run every day using Papermill or DeepNote (which now has an automatic mode for launching Jupyter Notebooks).

If you want to diversify your skillset and increase your professional value, there are fantastic training courses available for SEO enthusiasts interested in learning data science – and vice versa, for data scientists interested in learning SEO.

The only constraint is your willingness to master new skills.

Some prefer to work alone; after all, it eliminates any bureaucracy or politics that may exist (but are not required) in larger teams.

However, as the French proverb states, “alone we travel faster; together we travel farther.”

Even if projects are completed fast, they may not be as effective as they could have been with a more diverse set of abilities and expertise.

Now, let’s move on from the lone SEO to two-person teams. 

The MVT for Data Science SEO

You may already be familiar with the term MVP, which stands for Minimum Viable Product.

This style is often used in agile methodologies, where the project begins with a prototype and evolves over one to three weeks.

The MVT is the team’s equivalent.

This team structure can assist in mitigating project risks and expenses while bringing more different perspectives to the table.

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It entails assembling a team of two people with complementary skill sets — typically an SEO specialist who also knows machine learning methods and a developer who tests ideas.

The team is constituted for a specified period, often around six weeks.

Consider content classification for an e-commerce site. Often, one person may evaluate several methods and adopt the most efficient one.

However, an MVT might do more complicated tests concurrently with multiple models — for example, preserving the most often occurring classification while adding image categorization.

This can be accomplished automatically using any of the pre-existing templates.

Current technology enables accurate findings to reach 95% of the time, at which point the granularity of the results becomes relevant.

PapersWithCode.com can assist you in staying current with the state of technology in each field (for example, text generation), while also providing the source code.

For example, OpenAI’s GPT-3 may be used for prescriptive SEO to recommend text summarizing, text production, and picture generating operations that are all of the high quality. 

The Data Science Search Engine Optimization Task Force

For a moment, let’s travel back in time with me and examine one of the greatest partnerships of all time: The A-Team.

Each member of this legendary team played a critical part, and as a result, they excelled at each of their collective assignments.

Regrettably, there were no episodes devoted to SEO.

However, what may the composition of your data science SEO task force look like?

You will undoubtedly require the assistance of an SEO professional, as well as a data scientist and a developer.

This team will manage the project, prepare the data, and apply the machine learning algorithms together.

The SEO specialist is best equipped to act as a project manager and manage communication with management and external stakeholders.

(In larger organizations, the team manager and project leader may have separate duties.)

Several examples of projects for which this type of team might be responsible are as follows:

• Establishing a data warehouse for the enterprise (an out-of-the-box data warehouse that merges business, market share-of-voice, technical, and content data).
• Detection and erasure of “zombie” pages.
• New query detection.
• Forecasting traffic/profits in response to specific activities. 

Compliance with SEO Standards for Data

Naturally, teams want tools to maximize their efforts.

This takes us to the concept of SEO-compliant data management software.

Three criteria, in my opinion, must be strictly followed here to prevent utilising black-box tools that provide results without disclosing their approaches and algorithms.

1. Access to documentation that discusses the machine learning model’s techniques and parameters in detail.

2. The capacity to replicate the results on a different dataset to evaluate the methodology.

This does not imply software emulation; rather, the difficulties are with the performance, security, reliability, and industrialization of machine learning models, not with the model or approach it.

3. The tool must have been developed scientifically, describing the background, the aims, the methods used, and the final results.

Data SEO is a scientific method to search engine optimization that is based on data analysis and the use of data science in decision-making.

It is possible to implement data science methodologies regardless of your budget. The current trend is for data scientists’ notions to become more accessible to anyone interested in the discipline.

It is now up to you to take responsibility for your data science projects by assembling the appropriate team and capabilities.

To the success of your data science SEO efforts! 

Read: What is Off Page SEO and On Page SEO? Know Its working, Importance and Benefits in Detail