The global data sphere will grow from 33 zettabytes (each corresponds to one trillion gigabytes) in 2018 to 175 ZB by 2025.

In marketing, too, our role as administrator of much of this data is growing.

According to a report by IDC, more data has been stored in the company's core since last year than on all existing endpoints in the world.

annual size of the global data sphere

The big challenge for marketers and SEO professionals is to activate and use this data.

In 2025, every connected person will have at least one data interaction every 18 seconds, and almost 30% of the world's data must be processed in real time.

Human marketers can never handle this processing alone.

And as our machine learning tools process and analyze search data, they learn more and improve their understanding over time.

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Machine learning in search

Perhaps the most well-known use of machine learning in search is Google's own RankBrain, an algorithm that helps the search engine better understand the relevance and context of words and the relationship between words.

Through machine learning, Google can understand the idea behind the query.

Through machine learning, the algorithm can continuously expand this understanding as new words and queries are introduced.

And if algorithms can determine better Which The content best meets the needs of every seeker that we are challenged to create Content that meets these requirements – and that is optimized so that its relevance is clear.

It is no coincidence that, given this data explosion, interest in SEO is growing.

SEO & Data Science

SEO has developed into a viable, respectable mainstream marketing career.

As of this writing, there are 823,000 people on LinkedIn with “SEO” in their profile and 8,600 on LinkedIn who specifically categorize their core service offerings as SEO.

Globally, these numbers increase to 3.2 million or 25,000.

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However, this is only a small selection from the SEO industry.

There are those in search engine optimization who identify themselves as content marketers, strategists or digital marketing practitioners, website developers, analytics professionals, consultants, consultants and more.

Our industry is huge in size and scope as SEO now touches almost every aspect of the business.

Thanks to the massive increase in data we have to deal with, much more is now required from SEO professionals.

However, according to our research at BrightEdge, only 31.5% of companies have a data scientist in their company.

Do you have a data scientist in your company?

Working with machine learning offers tech-savvy SEO professionals a number of important benefits.

1. Improved performance in your field

Employers and customers are equally result-oriented.

Do you know how to use AI-based tools in your field?

Whether with paid search, technical search engine optimization, content creation and optimization, link building or another facet of search engine optimization – those who can demonstrate superior performance through the use of AI-capable search engine optimization increase their own value.

2. Start ahead and stay ahead

The search is a live auction. If you wait to see what customers think and then prepare to respond, you are already behind.

AI tools enable marketers to activate real-time information, personalize and optimize content right now to adapt it to the individual needs of each user.

3. economies of scale

You are exponentially more valuable as an SEO practitioner and leader when you can demonstrate that you can scale your efforts.

The real strength of machine learning lies in the ability to turn more data than we know into actionable insights and automated actions that marketers can really use to move the needle.

It is difficult to do that.

For example, to create BrightEdge autopilot, we had to process over 345 petabytes of data over many years to help fine-tune machine learning and automated products.

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Machines do not fish after transportation. They have no prejudices and don't care about past mistakes.

They are completely subjective and take opinions, personalities and other potential bottlenecks out of the data evaluation process.

The marketers are left with pure, accurate data output, which can then be activated on a large scale to improve the visibility of the search and the interaction with customers.

4. Room to grow

Once you've mastered your SEO toolset, you'll have more room to grow in your job and as a person who just loves your job.

Machine learning, in particular, enables us to gain insights from larger data sets and gives us access to far more intelligence than if we could only learn from what we ourselves analyzed manually.

It is Your Expertise and industry knowledge that determine which results are useful and how they should be applied.

Machine learning allows you to quickly see how your audience's behavior has changed during a major market disruption, for example based on our recent experience with COVID-19.

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But how you interpret and respond to these changes is still the domain of marketing and SEO professionals.

Through machine learning, you can identify patterns in visitor behavior that indicate opportunities and areas that need improvement.

What technology can not Replace the creative and analytical human thought process and experience that determine the best next steps in response to these insights.

The people of SEO cannot be replaced. In fact, they are more important than ever.

The tools we use can be very sophisticated. AI-enabled tools can even make decisions and implement optimizations.

However, it is the people of SEO who drive the creative and analytical processes that simply cannot replace machines:

  • Creative analysts.
  • Data scientist (who controls the input in machines).
  • Analytics.
  • Content producers.
  • Creators of culture and success evangelists.
  • Experienced users who make sales easier and help customers.
  • Strategic planning across digital channels.

And there are agile marketers who can take any combination of the above.

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They are the key to facilitating collaboration with other digital departments to ensure a truly holistic SEO strategy.

In their HBR article Collaborative Intelligence: Humans and AI merge, H. James Wilson and Paul R. Daugherty explain the three key roles that humans play in every interaction with machine-learning technology:

  • Zug: We have to teach the machine to perform certain tasks.
  • Explain that we need to understand the outcome of the task, especially if it is unexpected or not intuitive.
  • Sustain: It is up to us to ensure that the technology is used logically and responsibly.

When we apply this lens to our SEO technology, we see that these three principles apply.

We have to decide which SEO tasks should be intelligently automated and give our tools the right input.

We need to take the output and make sense of it, and just focus on the insights that have the potential to build business.

It is our responsibility to ensure that the privacy of the seeker is protected, that the value of the technology outweighs the cost and that it is otherwise used well.

You can add value to SEO and learn to work more effectively with machine-learning technology by building these skills:

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  • Data literacy: According to Stanford researchers, the share of AI jobs rose from 0.3% in 2012 to 0.8% of total jobs in the United States in 2019. Demand for AI workers is growing, especially for high-tech Services and in manufacturing.
  • Communication: As a referee for so much customer data, it is important that we communicate important insights and values ​​in a way that other department heads and decision-makers can understand.
  • Agility: Agility is more than a characteristic or a property. It is a skill that has been developed through constant experimentation.

Using machine learning and automation means building synergies with human creativity and skills.

It can make us more creative and effective by uncovering SEO insights and patterns that we would never have recognized otherwise.

It can help us discover new topics, identify content gaps, optimize for certain types of queries and results, and much more.

It can also save important time on tasks that are too time-consuming, repetitive, and tedious, so we can scale performance.

We develop new skills and advances, also in the context of a symbiotic relationship between people and technology.

More resources:

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Image credits

All screenshots from the author, June 2020

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