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3 Data Science Methods For SEO

With the emergence of data science, people are using volumes of data, meticulously collected to make predictions and better serve themselves and their businesses. Perhaps, no industry has capitalized on the countless opportunities that data science provides more like people that work in the world of analytics.

From Google AdSense to Instagram Feed, what we see is largely shaped by data science. With the use of Search Engine Optimization (SEO) to make content on websites more visible in the vast spaces of the world wide web, data science have taken the notch up, to not only predict topics that would trend in the coming days or even months but go as far as creating content for websites. But to plunge into that world we first must get acquainted with the various method that can be used in SEO.

See below 3 common data science methods for SEO as identified by website hoosting company OnCrawl:

1. Prediction

With data science, it is now possible to forecast keyword performance tendencies, future long-tail trends, and even organic traffic. Using the Facebook Prophet algorithm and your Google Search Console data, you can easily build a predictive model to forecast Google hits.

Great for:

  • Reassuring your C-suite of the value of an investment
  • Balancing expenses between organic and paid channels

2. Text Generation

Data science now makes it possible to automatically generate text for a page. Using the deep learning framework PyTorch and GPT-2, you can train this machine learning algorithm to learn your lexical field and writing style and automatically generate content on a given topic.

Great for:

  • Creating anchors for internal linking
  • Mass-creating variants of title tags
  • Mass-creating variants of meta descriptions
  • Building rich product pages

3. Anomaly Detection

Using the Robust Random Cut Forest (RRCF) algorithm, you will be able to detect any change on given KPIs that is unusual and requires your attention. This algorithm will even take seasonal events into account, along with gradual changes to the website over time. Examining anomalies can also reveal whether certain metrics are key to a website’s SEO.

Great for:

  • Knowing if your site is affected by an algorithm update — before a human can identify the change
  • Detecting technical problems before they create a lasting impact
  • Identifying real-world events that have an impact on your site
  • Automating your SEO monitoring
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