Picture the scene: you just sent a keyword ranking report to your client and he gets back to you with:

Your report says I'm 24 on "best smoothie" but when I check on Google I'm actually 32 !!

And you might say something along the lines of "did you check in incognito? from this location? with those parameters and this device?" and checking that everything influencing the SERP is the same setup as your checker.

It will explain some of the differences... but not all of them.

Even for SEOs themselves keyword rankings are not always straightforward.
And you end up with questions like this on Reddit:

Example of question asked on Reddit (/r/bigseo)

Then they either:

  • A) Ignore that volatility
  • B) Consider keyword rankings as an irrelevant KPI (because they're hard to measure accurately and all)

which are 2 viewpoints that lack the nuances associated with keyword rankings.

What if instead we could have a better understanding of how to use them correctly?

That's a quick dive I want to look into today.

Ranking probabilities

Some might shiver when seeing the word "probabilities", but that's really what a keyword ranking is: a probability.

It is not a "hard fact", a fixed number that tells the current truth about your ranking.

Yet it is always represented as such in tools and reports (SEOwl included) because it's easy to grasp.

I'm 7 on the keyword "best smoothie"

yup, got it.

The probability distribution of your ranking tells us that on the keyword "best smoothie" you rank 90% of the time, 75% of the time you rank 7th. In the worst case you're 10 and in the best case you're 6th.

*confused client look*

This can also make you look a lot smarter

The first version is simpler but it's the second one that's actually closer to the "truth" (whatever that is).

I wouldn't explain that to the end client though (except if they're really savvy).

But I do believe it is useful for SEO to understand this topic and be able to use this tool / data to diagnose some situations.

Such analysis can drive lots of interesting insights as we will see.

Keyword ranking = a probability?

If keyword position is not a fixed fact, what is it then?

It's a probability.

For each position.

If you check your position many times during the same minute, how likely it is that you're ranking at position X?

If you had to bet on your ranking in the casino, what would you play?

You would like to play on the most likely position, the most frequent position displayed.

Is that position the one recorded by your favorite rank tracking tool?


Maybe not.

They will most probably pick the first one they find, which can or cannot be the most frequent one.

Testing the volatility

So how do you find the most frequent position?

Simple: check your ranking many times in one minute and record each result. From that you can derive the most frequent position.

This is exactly what I've done with my keyword volatility checker.

The tool checks a keyword SERP 20 times under a minute and reports back the positions displayed and how they are distributed.

This is surprisingly very interesting and in my opinion, an underrated insight.

Here's how it looks for the keyword "best smoothie":

Extract from a volatility report for the keyword "best smoothie" (US)

Charts are not very visible in the screenshot so let's pick one URL (prevention.com) and explain what's going on:

Volatility chart for prevention.com on "best smoothie" (US)

Here are the 20 positions recorded by the tool for this URL: [27,27,27,28,27,31,28,31,27,27,31,27,27,31,29,31,28,24,27,27]

From this we can see:

  • The URL is present 100% of the time (we got 20 positions)
  • Most frequent position is 27 (happens 50% of the time)
  • Worst position is 31 (happens 25% of the time)
  • Best position is 24 (happens 5% of the time)

This is summarized by the chart above that displays what's happening in a visual manner :

  • colors gradients start at the most frequent position
  • if sometimes the URL appears at a better position than the most frequent one, it's in the green region
  • if sometimes the URL appears at a worse position than the most frequent one, it's in the red region
  • bar heights represent the relative frequency of each position (eg. 24 happens only once thus the bar is tiny, the biggest bar is at the most frequent position)

That's all good and all but how do you read that data?

Let's see different patterns you can find and how to interpret them.

Page volatility

One thing that will strike you after a few tests but should not come as a surprise to most SEOs is how the volatily increases the further you go.

Page 1 often looks like this:

Exemple of page 1: not volatile at all !

No volatility at all: we get the same position each time.

But page 6 for the same SERP looks like this:

Page 6: more volatile

More volatile: each URL get a slightly different position between checks.

This is a typical SERP volatility layout.

It becomes interesting when it is not following that layout. For example, if page 1 is highly volatile you might have an SEO card to play as it could mean no competition. But more on that later.

Position testing

A pattern you will spot often is position testing. It's when Google puts you at another position than your most frequent one every once in a while.

Google uses that as a kind of A/B test to see how the SERP (and users) react. If the test is conclusive, it might decide to move you up or down more permanently.

You can be tested below your current position ...

Exemple of negative position testing


Exemple of positive position testing

or both at the same time.

Exemple of balanced position testing

In the first scenario, it doesn't look good for that URL. Google seems actively looking to push it down.

If that's a position you actually care for and is worth $$$ for you, it might be interesting to act before losing the position by improving the page (eg. getting some more links to it).

On the contrary, if you're position tested positively as in the second picture that looks good for you. There's a chance that your ranking will increase soon.

But if that's a competitor, that's not good. That means they may outrank you soon. You will want to find out if they've done something on that page recently to get that boost or look at ways to boost your own page before getting outranked.

That's pro-active SEO as opposed to reactive SEO where you wait for the fact to happen (ie. them outranking you) before doing something about it.

It's still something to do manually as I don't know any tools doing that analysis automatically (let me know if that's something you would like to see in SEOwl !). It's worth doing on your most important keywords, where one position down for a week can cost $$$$ to the business.

Time sharing

Another pattern you can see is time sharing.

Sometimes you're looking at the SERP 20 times in a row... but your URL is only there 40% of the time.

When you're there, you're at position 12 but sometimes you're just out of the SERP and another URL is at position 12.

That's time sharing.

It looks like this:

Time sharing exemple

For the keyword "google", the URL "safety.google/privacy/data" appeared only 5 times out of 20. When it's there, it's at position 17 ... but it's not always there !

Time sharing makes sense intuitively. On some keywords, there are billions of documents competing for less than 100 organic spots.
So to display artificially more than 100 documents or do some testing (or both) Google is sometimes giving the spot of a document to another one.

And it has consequences for you because if that happens to your URL, you are potentially missing out on 75% of your traffic !

Luckily it doesn't seem to happen a lot on page 1 so it usually doesn't have a massive impact on traffic but that's still something you would like to improve (ie. get a more permanent position for your URL).
Speaking of that ...

The 3 secret ways to improve your ranking

From the considerations above, we can see there's 4 different ways to improve your ranking and get more traffic.

The first and most obvious one is the usual way: simply improve your most frequent position. That's probably what you're already doing and measuring with your usual rank tracking.

But there's more than that:

1) Improve your worst case

Let's say you're ranking 50% at position 54 (most frequent) and your worst position is 80 (10% of the time).

If you take that 80 to a 60 (so you're now 50% at 54 and 10% at 60), that's a great increase in your SEO ranking (that would have not been picked up by the rank tracker).

2) Improve your % frequency of good position

Let's say you're ranking 50% at position 54 (most frequent) and you're also 70 20% of the time and 80 10% of the time.

If you take that 70 to a 60, that's again a nice increase that can be missed by your rank tracker if it only reports the most frequent one.

3) Improve your % presence

Finally a third way to improve your ranking is to improve your % of presence when you're time sharing.

If instead of appearing 30% of the time you appear 80% of the time, that's a good improvement even though your actual position may not have changed.

Those 3 ways to improve your ranking without having the position changed are important because they show that the needle has moved.

And that's the main reason why you track keyword rankings in the first place: to see if your SEO actions are moving the needle in the right direction or not.

So studying those patterns can help you see if you're on the right track or not, especially on keywords where it's difficult to move (eg. with a tough competition).

For example if you're positioned #3 on a difficult keyword, you will want to measure your SEO impact before moving permanently #2 as it could take you months + a lot of resources to get there.

How volatility can help gauging SEO competition

Another interesting aspect of SERP volatility is that it can help check keyword difficulty.

Competitive keywords tend to be less volatile than easy keywords.
Highly volatile SERP can mean that Google is not satisfied with the results and is still testing a lot.

It means you can come with an appropriate document and rank somewhat easily.

Lots of time sharing tend to appear when a lot of optimized documents are competing for those little 100 available spots (eg. "google", "payday loans" are such terms)

"payday loans" (US). Heavy time sharing (5% presence) until the end of the SERP ... probably very hard to get a permanent position in the top 100 there !

And that's it for now, I hope you enjoyed that topic introduction ! I believe there's even more to learn about this so I might do more testing and write a part 2 to this. I'd love to hear your thoughts !

Want access to the volatility checker tool?

Signup below and I will send you the link by email. I'd love to hear your feedback !

The tool is also accessible to all paid customers of SEOwl.

Special thanks to Ted Kubaitis that inspired this tool.