Google Updates Report

What is the overall impact of Google’s updates on the visibility of websites?

Key points

• The Core Update is the type of update that shows the greatest variability in the visibility of the sites analysed.
• The sectors analysed and, by extension, the categories into which they have been summarised, maintain their visibility in general, which suggests and demonstrates that Google is a zero-sum game.
• The sites we are interested in analysing are those with extreme change values (positive or negative), which means that 24% of the sites analysed are considered significantly impacted.

Domain extension or age has no correlation with Updates

The domain extension distribution of our panel shows a high concentration of sites in the .com and .es extensions, however, the analysis of this characteristic indicates that there is no correlation between the affectations and the domain extension.

The age distribution of the domains in our panel shows a high concentration of data between 10 and 20 years, which already speaks for the maturity of the sites included in the dataset.

However, the analyses performed with this characteristic indicate that there is no correlation between affectations and domain age.

If we look at the data but aggregating the category that groups the different sectors, we see that there are no appreciable differences, except for a greater maturity in some sectors than in others, which is completely normal due to the speed of adoption of categories such as technology, which presumably started to have websites before other sectors.

We can conclude here that the age of the domain is not an important factor that is affected by Google’s Updates.

The percentage of overall impact tends to be similar depending on the type of update.

One of the first keys when analysing the data and finding out how the different Google updates have impacted the visibility indexes of the websites analysed, is to analyse the outliers of the changes in the visibility index, i.e. the extreme values that have changed most positively or negatively. Here we can see the percentage of outliers for each type of Update:

Thus, we can conclude that between 73% and 75% of the sites have minor or not very extreme impacts.

We can now confirm with this analysis that Core Updates are the updates that stand out as having the greatest impact (even if it is slight).

Google is a zero-sum game

On the other hand, when we look at the average visibility ratios per category before and after updates, we can see that Google is a zero-sum game, meaning that the average visibility of categories hardly varies before and after updates.

This is a demonstration of what has been heard for so long in the SEO community that what one site loses, another gains.

The nature of the organic channel transcends far beyond the top 10 positions, now more than ever. Be selective in choosing the right keywords to focus on and also be prepared to conquer territory that your competitors may end up losing.

How does the impact of Google updates vary between sectors?

Key points

• The “Commercial and Financial Services” category appears to be the most volatile set of industries after more than 30 rollouts.
• However, “Home & Lifestyle” is the most stable category.
• Among the most predictable ones the industries in the “Education and Employment” category show up.

Average absolute variation by category and type of update

Each industry has specific characteristics that, due to the type of content and the needs of the sector, remain constant across all the sites that make up the industry. In this way, we can see how each update affects each of the industries differently.

Absolute average change by category and rollout

There is a remarkable variability in the way different categories respond to Google updates, this can be seen by checking how the average change varies across all or individual updates in the different categories analysed.

The acronyms in the graph stand for:

CU = Core Update

PRU = Product Reviews Update

HCU = Helpful Content Update

SU = Spam Update 

LSU = Link Spam Update

PEU = Page Experience Update

This shows that there are categories with high variability, such as “Commercial and Financial Services” or “Other Specialised Services”.

Other categories remain broadly stable, such as “Home and Lifestyle” or “Motor and Mobility”.

The Basic Update in May and December 2020 have had the most positive and negative impact, respectively.

In general, Core Update has the highest overall impact in all categories.

Learning or confirmation refers to the path Google has taken with its algorithms in terms of user experience, quality of search results and influence on more sensitive sectors such as those where health, safety, money or user welfare is at stake (YMYL industries).

Are there discernible patterns in the response of websites to different types of Google updates?

Key points

• Industries tend towards stability
• The Page Experiencie Update has a different pattern to the rest of the Updates.
• Categories such as “Education and Employment” are among the most predictable and “Home and Lifestyle” among the most stable.

Average absolute change by category and update

Categories tend to be more stable than volatile, suggesting that while Google Updates have a noticeable impact, not all sectors are extremely affected. The almost equal rankings of predictable and surprises indicate that there is a balance between expected and unexpected changes.

The resistance and volatility of SEO depends largely on the nature of each category and its response to Google’s specific update guidelines.

What factors contribute to the success or failure of websites when adapting to Google’s updates?

Key points

• Continuous evolution to learn and adapt to different updates
• A defined strategy will ensure robust traffic acquisition
• YMYL sectors remain the most sensitive to algorithm changes

The multiple factors analysed by Google mean that heterogeneity is the norm in the number of factors that contribute to the success or failure of websites. Looking at the categories with the most extreme movements in each of the updates we can see what these factors are in each of them.

Core Update

A quarter of the sites experienced changes in their visibility that were markedly different from the majority.

The “Commercial and Financial Services” category has the greatest impact, followed by “Media and Entertainment” and “Other Specialised Services”, indicating considerable variability in how these sectors were affected by the update.

In contrast, “Technology and Telecommunications”, “Home and Lifestyle”, “Education and Employment” and “Travel and Recreation” show a more uniform response to the Update.

The Core Update has influenced a large number of sites, with a very varied response between sites, ranging from almost no change to considerable increases.

Although for many sites the change has been minimal, there have been fluctuations in visibility over time, with some peaks and valleys suggesting that the impacts of the different launchs of the Core Update have been mixed.

Unlike other updates, there has been no stabilisation over time.

Some thoughts on CU:

• Expertise, authority and trustworthiness (E-E-A-T): Google values sites that demonstrate expertise, authority and trustworthiness in their topics. This is especially important for “Your Money Your Life” pages, which may affect users’ health, happiness, safety or financial stability.
• User experience: Website usability, including loading speed, ease of navigation, accessibility and mobile experience, is an important factor. Google prefers sites that offer a good user experience.
• Website security: Security is crucial, especially for sites that handle sensitive user information. This includes the use of HTTPS and measures to protect against malware and cyber-attacks.

Helpful Content Update

“Other specialised services” leads the list with the highest percentage of outliers (28.55%), followed by “Motor and Mobility”, “Commercial and Financial Services” and “Media and Entertainment”, indicating that a significant number of sites in these categories deviate from the average visibility change behaviour.

The lowest percentages of outliers are in “Technology and telecommunications” and “Home and lifestyle”, suggesting that sites in these categories have had a more uniform response to the Update.

This is a mixed response, where category sites with high percentages of outliers may need special attention to understand the reasons for these extreme changes and adjust their content strategy accordingly.

The chart for the Helpful Content Update shows that while the overall trend may be one of improved visibility, there is a significant difference in how individual websites have been affected by the update.

The combination of these results suggests that the update has favoured those that were probably already aligned with Google’s Helpful Content guidelines, while others have had to make significant adjustments to adapt to the new rules or have lost visibility and been taken over by competitors.

Some ideas to consider for HCUs:

• The Quality of content: content should be accurate, up-to-date and well-written.
• The Relevance of the content: content should be relevant to the user’s search query.
• The Usefulness of the content: content should provide information or a solution to the user’s problem.

Link Spam Update

“Link Spam Update” had approximately 22.50% outliers, indicating that a significant number of websites experienced changes in visibility that deviated from the norm of the dataset.

Looking at the sectors, “Other Specialised Services” has the highest percentage of outliers (26.74%), suggesting considerable variability.

“Motor and Mobility” and “Media and Entertainment” also show high percentages of outliers indicating that a considerable proportion of sites in these categories experienced changes in visibility that were outliers compared to the overall dataset.

In contrast, “Education and Employment”, “Home and Lifestyle” and “Technology & Telecommunications” have the lowest percentages of outliers, which can be interpreted as a more stable response to the update in these areas, with fewer instances of extreme changes in visibility. In these sectors it is more natural and easier to get links, so it is not necessary to use aggressive link building.

Some thoughts on Link Spam Update:

• Link quality: Links from low-quality websites or websites with a history of spam are more likely to be considered spam.
• Naturalness of links: Links that are created naturally, such as those generated as a result of user engagement, are less likely to be considered spam.
• Link purpose: Links created for the purpose of manipulating search results are more likely to be considered spam.

Product Review Update

“Media and Entertainment” stands out alongside “Other Specialised Services” and “Commercial and Financial Services” with the highest percentage of outliers, suggesting that these categories experienced considerable variability in the face of this Update.

In contrast, the categories “Education and Employment”, “Home and Lifestyle” and “Travel and Recreation” have the lowest percentages of outliers, all below 19%, indicating that sites in these categories had a more homogeneous response to the Update.

This graph provides a visual representation of the variability of the impact of “Product Reviews Update” rollout over time.

While the average change is consistent (blue line), the individual website experience varies considerably (yellow band).

The big hypothesis here is to confirm 2 aspects that Google has told us:

• The Spanish market is most impacted from February 2023 onwards, when these rollouts expand to the Spanish language.
• The level of impact is broader as the Update moves from being called Product Reviews, to simply Reviews, as it includes not only product reviews, but also reviews of services and companies, destinations, media and other review content.

Although the graph shows a broadening of the overall effect in the last 3 rollouts, it is not sufficient to confirm with certainty the hypotheses outlined above.

Some ideas or lessons that can be applied to PRU:

• The quality of the review: The review should be accurate, up-to-date and well written.
• The relevance of the review: The review should be relevant to the user’s query.
• The usefulness of the review: The review should provide information or a solution to the user’s problem.

Spam Update

The category with the highest percentage of outliers is “Commercial and Financial Services”, closely followed by “Other Specialised Services”. At the other extreme, the category “Technology and Telecommunications” has the lowest percentage of outliers.

Earlier rollouts had a more considerable overall impact than more recent rollouts, as the graph shows.

This may give rise to several theories:

• Higher intensity in different rollouts depending on the state of search results at a given time and the need to correct poorer quality results or results that incur prohibited practices in the guidelines.
• There is a “learning effect” from the first rolllout to subsequent rollouts, as Google shares information related to the specific Update and the SEO community provides feedback, experiences and advice to resolve negative impacts or anticipate future impacts.

Some ideas for this Update:

• Compliance with Google’s policies: All content on the web (pages, images and videos), must respect Google’s spam policies in order to be included or remain in search results. Google uses both automated systems and human review to identify and penalise offenders.
• Understand the different types of spam: Google’s policies address various forms of spam, such as cloaking (showing different content to users and search engines), doorway pages (pages created to manipulate search results), improper use of text, hidden links, and keyword stuffing, among others. We need to be aware if we are slipping into them, even if it is unintentional.
• Spam Actions and Prevention: Google can take action against sites that violate its policies (lower rankings or removal from search results). Avoid being vulnerable to malicious attacks and deceptive practices by applying prevention measures.

Page Experience Update

The median percentage of outliers across all categories is 23.33%, which means that, in half of the categories, about a quarter of the observations deviate significantly from the central tendency. This implies that the impact of the “Page Experience Update” was significant enough to influence the visibility of a considerable number of pages in several categories in a non-standard way.

Focusing on the categories reveals considerable differences in the variability of the changes in the visibility index. The category “Commercial and Financial Services” leads with 26.00% of outliers, indicating a higher propensity for changes in visibility.

In contrast, “Technology and Telecommunications” shows the lowest proportion of outliers with 13.89%, suggesting relative stability in visibility changes.

To dig deeper into the “Page Experience Update” rollouts and their level of impact, we can see how the mobile-focused rollout (June 2021) had a much more widespread impact than the desktop-focused one (February 2022).

This may underline the great weight Google places on mobile experience, with other initiatives such as the Mobile First Index and in line with the trends it has observed in the context of more organic search from mobile devices than desktop.

Some ideas for dealing with such Updates, even though they are one-off rollouts and have already happened:

• Page load speed: Pages that load quickly are more likely to deliver a good user experience.
• Page interactivity: Pages that are easy to use and navigate are more likely to provide a good user experience.
• Page security: Pages that are secure are more likely to provide a good user experience.

Volatility index: how to identify sites sensitive to Google Updates

The volatility index is a metric designed to assess the extent to which Google algorithm updates affect a website’s visibility in search results.

It is based on two main indicators:

• First, it indicates whether a website has experienced atypical changes in its visibility within its specific category in relation to an algorithm update. A value of 1 means that the site is an outlier (i.e. its visibility change is atypical), and a value of 0 indicates the opposite.
• Second, it reflects whether a website has experienced outlier changes in its overall visibility, regardless of its category, also in relation to an algorithm update. As above, a value of 1 indicates that it is atypical, and 0 indicates that it is not.

The volatility index is calculated by adding the values of the two indicators for each algorithm update released-combination for a website, and then dividing this sum by the total number of possible combinations multiplied by two (since we use two indicators). This result is expressed as a percentage, providing a measure of the website’s volatility.

A higher value on the volatility index suggests a greater susceptibility of the website to fluctuations caused by Google algorithm updates, indicating more volatility in its visibility. A lower value indicates greater stability, suggesting that the website has maintained more consistent visibility throughout the algorithm updates.

This index is valuable for identifying websites that require strategies to manage search algorithm volatility. However, it is specific to Google updates and does not take into account other external factors that may influence website visibility.