Average Position: A Distracting Lie

A great many folks spend time thinking about position on pages, both for their ads and for their organic listings. People care about position, but it’s really a proxy for what we should pay attention to: traffic volume and quality. Indeed, position itself as a KPI is pretty meaningless, and focusing too much attention on it can lead to mistakes.

Average Position Relates To Impressions, Not Clicks

Most of the traffic on a given ad comes when it is higher up on the page than its average position. That comes as a surprise to many.

Part of the disconnect is simple math. If the impressions are evenly spread by position, the clicks will skew higher on the page because the click-through rate at the top is higher than it is at the bottom.

Let’s take a look at a simple model to see how this works.


Above, you see an ad that has received 10,000 impressions in each position on the page. Because of the click-through rate differential, the average position of ads when clicked is higher than the average position of ads seen.

Now, this is just a model, and a person (Dora, the Paid Search Explora…) might argue “there’s no way my ads are being shown in all those positions!” This isn’t necessarily an invalid complaint — so let’s look at some real data for a single ad.

Sample 1

Dora says: “Holy mackerel! Its average position on my reports is 4.8, but more than 70% of the clicks on that ad happen when it’s in position 1!?!”

Let’s look at that ad (Keyword 1) and some of its cousins:

Cohort 1

This is the norm, not an exception.

Dora says: “Aha! I know what it is! This is a broad matched ad, so it serves higher on some queries than others based on relevance, anticipated CTR, etc.”

Interesting hypothesis, Dora! Let’s then look at some exact match ads to see if we see a tighter distribution:

Sample 2

Dora: “It’s still all over the place! Surely this is an outlier!”

It doesn’t seem to be an outlier, Dora — and don’t call me Shirley!

Cohort 2

Dora: “I bet it’s a product of day parting! We’re bidding more when the traffic is the most valuable, less when it is less valuable, so that’s what’s creating the huge distribution of positions!”

Could be! Let’s look at some exact match ads in a relatively new account for which we haven’t yet applied day parting algorithms:

Sample 3

Cohort 3

Dora: “Okay, okay. So ads are served in a wide variety of positions even when they’re exact match and even when we’re not changing bid strategy intra-day. What gives?”

There are a number of factors:

  • Personalization. Personalized SERPs mean past user behavior, location, device, etc., all play a role in what Google expects user behavior to be in paid search; thus, the rankings vary to best respond to anticipated user desire. The anticipated CTR for each ad varies based on the context of who, when and where the user is.
  • Localization. Local competitors may displace your ads in urban areas, but not in others.
  • Device targeting. Increasing bids for some devices over others can be a factor.
  • Retargeting Lists for Search Ads. While still a small factor, bidding preferentially for users you know like your brand will create a wider distribution.
  • Competitor behavior. Even if you’re not engaging in any of the above activities, if your competitors are, it will knock your ad around the auction.
  • Mobile. You may be higher on the page for tablet and desktop than for smartphones or vice versa. In fact, screen size dictates that very few impressions exist for smartphone ads below the top placements.

Google likely does itself and the advertisers a favor by targeting the selection of ads not just to the query but to the context of the specific user. Serving more relevant ads to this person at this moment in this use case gets us all higher quality impressions and better focused traffic.

As KPIs go, average position clearly doesn’t tell you much about how your ad is served. A great deal depends on which auctions you qualify for and the competitive dynamics of those particular auctions. Indeed, the very fact that your ad isn’t served in every auction demonstrates the inadequacy of average position as a KPI. “My average position for this keyword is 3, so I have a lot of visibility there!” Maybe — but if you only qualify for 1/3 of the auctions, then your average position metric may not mean what you think it does.

It has always been problematic to set bids based on position — an issue I wrote about many years ago on SEL. Position-based bidding algorithms were the norm for the early (bad) bid platforms, but most platforms have evolved since then in favor of more sophisticated, ROI-driven algorithms.

What these data demonstrate quite clearly is that paying much attention to average position is a waste of time. What we need to study is the quantity and quality of the traffic driven as well as the factors that affect those much more meaningful numbers. Understanding the factors that influence an ad’s performance and bidding to the value of that traffic at that time assures efficient advertising. Trying to make decisions based on average position misses all the subtlety that goes into playing in an auction.

Does this same position myopia misguide SEOs? It certainly can and sometimes does, but that’s a subject for the SEO column!

Opinions expressed in the article are those of the guest author and not necessarily Search Engine Land.

Related Topics: Channel: SEM | Google: AdWords | Paid Search Column


About The Author: is Co-Founder and Chief Marketing Scientist of RKG, a technology and service leader in paid search, SEO, performance display, social media, and the science of online marketing. He also writes for the RKG Blog. Follow him on Twitter at @georgemichie1.

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  • Ian Leong

    I’m not sure I fully agree. For example, on the PPC side, positions 1-3 will get your ad additional impressions on search partner sites like Ask and AOL and subsequently increase your traffic and revenue (although there is not necessarily any correlation with quality of incremental traffic). On the organic side, there is no question top three positions are the holy grail – at least for most SERPs the way there are currently displayed.

  • http://www.rimmkaufman.com/ George Michie

    It’s a complex topic that deserves more research and explanation than I’ve provided here. The point I didn’t hit hard enough is that your avg position doesn’t necessarily correlate with traffic volume. You can have average position 2 and only qualify for 10% of the auctions, while someone with average position 5 who qualifies for all the auctions gets far more traffic. Moreover, Google is already preferentially serving ads based on how relevant your ad is to the specific person, so pushing Google to serve the ad in higher positions to people Google thinks won’t like you or your ads for some reason (past behavior, perhaps) may be a really bad idea.

  • Martin Röttgerding

    Very cool post, George! Love the story about Dora :)

    I believe that personalized quality score (anticipated CTR or click-through probablilty) plays a big role in this and makes it impossible for us to fully assess where we really stand compared to the competition.

    Two years ago I did a not-at-all scientific experiment and searched for a the same product every day, always clicking on some advertiser on the lower right rail. After a few days I began seeing the ad climbing higher, eventually taking the top spot from Amazon. Another browser (without my personal search history) continued to show the ad on a lower position.

    Another aspect in this is that users often search for the same thing twice or more, sometimes much more often. If there’s an ad in the top spot that the user constantly ignores it makes sense for Google to assume a lower click-through probablilty for that ad in the context of the current user. For the ads at the right hand side this isn’t exactly a vote of confidence either, but while it’s clear that the user has ignored the ad on top, the ads on the right rail may have been overlooked. The assumed click-through probablilty for all ads might go down, but the top ads would take a bigger hit than the others. This could lead to another order for the ads, thus contributing to the phenomenon discussed here.

    By the way – these ever changing ad positions make it impossible to assess an ad’s CTR from the outside. Ad A may have a higher CTR than ad B, but without the context of ad position AND everything else this is meaningless. This renders the impression-based evaluation of A/B tests pointless (even though statistical significance will always be a great thing to impress people).

  • http://www.rimmkaufman.com/ George Michie

    Yes, and the personalization is nothing new. We used to have to explain to clients all the time that the reason they never see their ads show up is because they search all the time and never click on their own ads. Most folks understand that now, yet haven’t connected the dots with the implications for average position.

    Thanks as always for your thoughtful and excellent commentary!

  • Martin Röttgerding

    About that last point (pushing Google to serve the ad to people Google thinks won’t like you or your ads): It’s a problem that we can’t consider this in our bidding – except in rare cases. When you are already bidding to position 1.0 and bid simulator shows minimal gains for huge bid increases, I believe that is because the only thing the higher bid will do is keep the ad in front of people who rarely ever click on it. This eventually leads to a few additional clicks for a high price, but the question is whether these clicks are as valuable as clicks from users who didn’t have to be “forced” to click on your ad. This might throw a monkey wrench into strategies built around incremental CPC…

    However, I don’t see how we could ever validate this theory. Maybe if Googles gives as a click ID and some context some day…

  • Ronnie’s Mustache

    George, thanks for explaining this so well.

    It seems to get more confusing by the day w/ so many different result sets, screens and ad formats.

  • http://www.rimmkaufman.com/ George Michie

    Adriano, you can have Google append a valuetrack parameter to your urls that will pass the page, location (top, side, other), and position for each click through. Parsing the referrer string for this parameter then allows you to do the analysis. We have our own platform at RKG so we’ve built this in to be a relatively easy analysis.

    Good luck!

  • http://www.rimmkaufman.com/ George Michie

    Thanks Ronnie. It is remarkable the sticking power of KPIs; even when they are proved to be invalid and/or not actionable, people insist on watching them. People cling to them as though they are handrails in a turbulent industry. They aren’t.


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