Patters of SERP Volatility

A modern understanding of SEO comes with an awareness of the fluidity of ranking signals. The next-level complexity we see in SEO creates ambiguity, in part because Google is constantly testing results against each other. Constant testing doesn't just happen with regular organic results but also SERP features, from featured snippets to local packs.

These dynamics in search create natural ranking volatility in Google Search that we need to embrace. When looking closer, we can identify different volatility patterns that help us better understand when and why rankings fluctuate.

SERP Volatility and User Intent are connected

Google shuffles rankings to find better answers to users' questions. In other words: to better satisfy user intent. I call the shuffling and testing in the search results "SERP volatility."

SEMrush has a tool that can measure SERP Volatility at scale across different devices, SERP Features, sites, and industries called Sensor. You can also use it to track volatility for your own keyword sets and compare it against total volatility or a specific industry, which helps to understand what happens when Google rolls out new updates.

You can also use Ahrefs SERP position chart in the Keyword Explorer for single keyword volatility of the top 5 results.

I identified two patterns of SERP Volatility: stability and instability. The state of SERPs depends on many factors, but we can generally divide the top 10 results into 3 areas: top 3, 4-6, and 7-10 ranks. We can see how Google's understanding changes when we look at the movement of positions of the SERP, e.g., 1-3, 4-6, and 7-10. On stable SERPs, the top 3 positions barely change. They typically satisfy dominant intent, which shouldn't change much, whereas position ranges 4-6 and 7-10 are for common and minor intent.

Unstable SERPs show ranking fluctuation on all positions because Google is trying to figure out the best rank and mix of results. Google's understanding of the optimal SERP mix is not a "one and done" situation. Queries can move from stable to unstable SERPs and vice versa overnight for three reasons.

Change in dominant, common, or minor intent

The dominant, common, and minor intent for a query can change when Google gets smarter about a query or when the world's understanding of it changes (more about the latter in the next section). Google tends to update its understanding of queries and their user intent with core algorithm updates or current events, and it's mainly driven by machine learning (NLU).

That's in part the reason why in some cases, domains are affected by core algorithm updates without prior changes. Google updated its understanding for a set of queries the domain ranked for. The site didn't change anything.

Current events

Google aims to reflect the world's changes in the search results. When the pandemic in Wuhan broke out, Google's understanding of the user intent behind the keyword "Wuhan" needed to change as quickly as news travel around the globe. The applied concept is QDF, query deserves freshness. When Google detects a lot of news around a certain entity, it might be likely to change it accordingly.

Seasonality

Lastly, good old seasonality can drive SERP volatility. Once a year, Google changes the search results for the query "independence day" around July 4th or "black friday" around the end of November. The sites that are most relevant for the holidays are not the same as the ones most relevant throughout the rest of the year.

TL;DR,  Volatility is an opportunity

The point about SERP Volatility is that we can use it to identify opportunities. Unstable SERPs are easier to rank in that stable ones. When Google is trying to find the right mix, more sites are eligible to rank than when Google already set its mind.

We don't have great tools to determine SERP Volatility at scale, yet, but we can understand it at the single keyword level.