Google’s next chapter for metrics to focus on clarity once ‘average position’ is removed

Fred Vallaeys explains why advertisers need to rethink bidding strategies and position metrics now that Google has announced it will sunset one of its oldest metrics later this year.

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Average Position was one of the original metrics in Google Ads when they launched their search advertising product called AdWords. But as search advertising has evolved, what used to be a primary metric for making optimization decisions has lost its usefulness and so Google has announced that it will disappear later this year.

This means advertisers will need to rethink some dated bidding strategies, update reports they share with stakeholders and figure out how the new position metrics can replace what is being deprecated. But first, let me share my take on why this change is being made.

Why ‘average position’ is a poor metric to understand position

Historically the average position metric was useful because ads reliably showed up in consistent locations on the page. Knowing the average position of an ad meant you knew where your ad showed on a web page. Its physical “position” on the page correlated to the “average position” in reports.

For example, in the earliest days of AdWords, premium ads that were sold to big companies on a CPM basis were shown above the search results. Ads on the right side were reserved for smaller advertisers who paid on a CPC basis through what was then known as AdWords Select. So if you were an AdWords Select advertiser and your ad was reported as having an average position of 1, you understood it was the first ad on the right side of the SERP.

But then Google realized that the ads they were putting in premium locations on the page from advertisers paying on a CPM basis were making less money than the CPC ads on the right side. So they merged the two advertising programs and made all advertisers compete for all slots on the page based on Ad Rank, a metric comprised of the CPC bid and the CTR. Position still equated to a physical location on the page, except for the fact that Google made one more change in its effort to ensure only the most relevant ads would occupy the top of the page.

The ads with the highest rank would only be shown above the organic results if they met a certain relevance threshold. This was Google’s way of ensuring users would see only the most helpful ads above organic results. Now if your ad was reported as being in position 1, only one thing was certain – your ad was shown before all others (i.e., your ad was the winner of the auction). What was no longer certain is where it showed; it might have appeared at the top of the page, or on the right side if no ads met the top of page promotion threshold.

And this was just the start of the muddling of the meaning of “average position.” Google briefly started showing ads below the search results (and gave these slots to ads ranked above the ones that showed on the right side meaning that ads with lower average positions would be seen before ones with higher positions). Later ads disappeared from the right side, more ads started showing at the top of the page, thresholds and auction rules kept getting updated, new ad formats like shopping started using a different layout and new search syndication partners had their ad slot locations. While average position continued to reflect an ad’s rank compared to all others, it became less and less clear what that position actually equated to in terms of a location on the page.

In essence, “average position” should have been named “auction rank” to better reflect its meaning. The word ‘position’ refers to a relative position compared to other advertisers and has nothing to do with a physical position on the page where the ad is shown. Advertisers often care more about where their ad is shown rather than who they were beating in the auction so the average position metric became less meaningful and it’s no surprise it is being sunset by Google.

Top position metrics bring back clarity

Being the leader in online advertising is a double-edged sword for Google. They got to pick the metrics that we all care about but they’re also locked into supporting those metrics for the long haul or face lots of questions.

Google Ads got started in a world where little could be automated yet Google wanted to give lots of control to its advertisers. So they decided to create structures like ad groups, and share metrics like average position to let advertisers understand what was happening and give control to take action at the same time. A lot of that legacy is difficult to undo, even now that it may simply make more sense to let machine learning handle a lot of the details.

Fortunately, in this case, Google is only sunsetting a metric after they feel they’ve introduced newer metrics that better inform advertisers about what they primarily care about: that their ads are shown in places where they will drive more business. Google has introduced four new metrics:  “Impression (Absolute Top) %,” “Impression (Top) %,” “Search absolute top impression share” and “Search (Top) IS.”

These metrics tell advertisers two things: how often their ads are at the top of the page when they get an impression and what share of all the top of page impressions they’re getting.

Bid-to-position is not a good way to set bids

Advertisers have long used average position as an input to bid management strategies. Remember that until Google introduced automated bidding (e.g., target CPA and target ROAS bid strategies), advertisers had to set their own CPC bids. Many advertisers set their CPCs based on their expectation of how likely clicks were to convert, something they might measure with conversion tracking. But many advertisers without conversion tracking set bids by looking at the average position. Some simply wanted to have their ad always be the “top” ad, so they bid as much as needed to keep an average position of 1. Others argued that clicks in position 1 were too expensive and that they’d rather get fewer but cheaper clicks so they set bids in an attempt to stay at lower positions but still on the first page of results. This is where bid-to-position bid strategies originated.

Nowadays, automated bidding is so ubiquitous and cheap that bid-to-position strategies simply don’t make a lot of sense for the majority of advertisers. They’d do far better by implementing proper conversion tracking so that automated systems can set the right CPC bids for each auction to achieve the target CPA or target ROAS.

Brand advertisers can use the new position metrics instead of ‘Average Position’

One group of advertisers who rightfully care about position are brand advertisers. Even though Google Ads is at heart a direct response advertising platform, there are brand advertisers who want to go beyond the Display Network and Video Ads on YouTube for branding and who want to run brand ads on search. In these cases, bidding to the absolute top of the page is the right strategy. This strategy doesn’t work very well with just the average position metric because that metric only says if the ad is the top-ranked in the auction, but not if it passed all the other criteria needed to be shown above the organic results or at the absolute top of the page. Google’s four new metrics offer far better data to use for advertisers who care about branding.

What we lose with the end of ‘average position’

The vast majority of advertisers will be better off when average position no longer exists and they look at the newly introduced metrics instead. But at my company, Optmyzr, we’ve found there are still some scenarios where average position is helpful, especially when looking at segmented data.

For example, we have a bid optimization tool that recommends geo bid adjustments or validates that automated bidding systems are doing a decent job with geographic differences in performance. Our tool’s recommendations are generated by a machine learning algorithm that looks at many factors, including average position. Specifically, it uses this metric to predict if an increase in geographic bid adjustment is likely to increase volume for that location. After all, there’s no point raising a bid for a location where an advertiser already dominates the auction. And while average position is a metric that is available in a geo report, the new metrics are not. This means that we can no longer as reliably identify opportunities for geo-segmented data.

This specific example won’t cause issues for most advertisers but the point is that there are advanced use cases relying on the average position metric that will be hard to fix until the new metrics are more widely available across all of Google Ads.

Conclusion

There’s never a dull day working in PPC and the sunset of one of the oldest metrics around is another clear illustration of that. As we’ve seen in the past (like with the deprecation of mobile campaigns and the later re-introduction of -100 percent device bid adjustments), Google does respond to the needs of its advertisers so this is a great time to share constructive feedback about how this change will impact you.

While I worked on  Google Ads, I was involved in several updates related to Quality Score. I can tell you we cared a lot about what advertisers said because we couldn’t possibly know every use case. That’s the case here too so I for one really look forward to learning a lot more about how advertisers use average position in unique ways and what sort of workarounds they’ll come up with before it disappears forever.


Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.


About the author

Frederick Vallaeys
Contributor
Frederick (“Fred”) Vallaeys was one of the first 500 employees at Google where he spent 10 years building Google Ads and teaching advertisers how to get the most out of it as the first Google AdWords Evangelist. Today he is the Cofounder and CEO of Optmyzr, a PPC management SaaS company focused on making search, shopping, and display ads easier to manage with rules, scripts, reports, audits, and more. He is a frequent guest speaker at events where he inspires organizations to be more innovative and use AI and Automation Layering to become better marketers. His latest book, Unlevel the Playing Field, follows his best-seller, Digital Marketing in an AI World.

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