What was the May Google update of the main Google algorithm – analysis from Moz

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Researcher Moz Peter Meyers (Dr Peter Meyers) has published its analysis of the last renewal of the Google algorithm ( May 2020 the Update Core ), the launch of which was launched on 4 May.

As of May 14, fluctuations in extradition have virtually subsided. Below is an 11-day chart starting April 30:

Google algorithm update May 2020

MozCast maty 2020
MozCast maty 2020

According to MozCast, the highest volatility was observed from May 4 to 6, the peak temperature in the issue was recorded on May 5 – 112.6 °.

The average temperature 30 days before May 4 was also historically very high (89.3 °).

google algorithm update may 2020
  • What was this update compared to the previous ones?

Considering that recent temperatures in the display were significantly higher than historical average values, the May 2020 Core Update was the second most powerful update to the core Google algorithm after Medic Update (August 2018).

Google algorithm
Google algorithm
  • Who benefited from the update?

The industry has already established the practice of naming winners and losers after major Google updates. However, usually, these conclusions cover a very small period of time and are not representative enough, Meyers noted.

“Whenever we compare two fixed points in time, we ignore the natural volatility in ranking and the differences between keywords.”

Therefore, in his last analysis, Meyers decided to minimize these shortcomings to zero and focused on the winners.

Initially, he compiled a list that took into account only the data for the first day of launch – as is customary in the industry:

The final list takes into account the data for the 1st and 2nd day, as well as 7 days before and after the update, is launched:

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It is noteworthy that some of the sites from the first list remained in the second. It also has new resources, including those sites that lost their visibility on the first day, but significantly improved their positions in the analysis of a larger amount of data.