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New Insights Into the Google Auction

My monthly paid search column at SEL in case you missed it there:

Granted, we’re geeks.

We get really excited anytime the engines give us new information to analyze or tools with which we can fine-tune our approach.

Google has just given us a treasure trove of new information: click level data on an ad’s position. In the past we’ve had to rely on observations and average position day to day to get a sense of where an ad is appearing on the page. But we know that averages lie.

By giving us information identifying the position on the page for each click we get a whole new window on auction dynamics.

HOW IT WORKS

Similar to the Google Click id, gclid, by flipping a switch in your adwords account, Google will append an ad position parameter called ‘adpos’ to your destination url. We can then parse this information as it’s passed to our clients’ sites and analyze from there.

The values passed in the adpos parameter reveal the page of the results off of which the ad was clicked, whether the ad appeared on top of the organic listings or to the side, and its overall position rank on that page. All of this is passed in one text string.

1s3 means: page 1, on the side of the page, third position among ads.
2t1 means: page 2, on the top of the organic listings, first position.

WHAT IT REVEALS

Matt Mierzejewski, our VP of Paid Search, flipped that switch immediately for one of our clients to start gathering data, and I couldn’t resist digging in, even though we only had a couple of days worth of data.

To wrap my arms around this, I narrowed my study to 8 ads representing 4 different keywords to reveal among other things what impact match type might have on ad serving.

Pages

Of the 471 clicks in my sample: 97% happened when the ad was on page 1; 2% on page 2 and less than 1% on page 3 or more. The academic in me wonders: if an ad is in position 2 on page 2, how does that figure in the average position calculation at the end of each day? Does that count as position 2, or position 12 or whatever it might be given that the page 1 ads were ‘above it’? I suspect the former, but in truth given that 97% of the time we’re looking at page 1, it probably doesn’t matter.

Position

Fascinating, fascinating, fascinating!

Keyword 1. Adwords reports that Keyword 1 on broad match had an average position of 3.7

But take a look at the positions from the perspective of click traffic:

This is just JAW Dropping imho!

The Average Position reported is 3.7, but the weighted average of the clicks by position is 2.6. Bear in mind, the reported Average Position is based on impressions served, not ads clicked. The click-wise view will always be a lower ordinal number reflecting higher position on the page. This is a product of the higher click-through rates of higher positions.

That said, for a reported average position of 3.7, 67% of the clicks came when the ad was in position 1 or 2!

Boy oh boy do averages not tell the whole story!!!

Let’s take a look at Keyword 2, also on broad match. Average reported position for the days covered: 4.9


These results are so startling to me that I wonder if I’m comparing apples and oranges. The average position data comes in day long chunks, and the click data I’m looking at starts midday and ends midday. I also wonder if Google appends the parameter for network partner clicks…I think the answer is yes, but…Also worth noting that our own day-parting activities could be driving this as much as auction dynamics.

This view of data will have us all scrambling to revisit what we thought were settled questions about paid search. One obvious example: we long ago concluded that conversion rates don’t appear to vary much by position. I’d be surprised if we found variance given the new view. Hal Varian’s study, with the crystal clear view of the auction that only available to Google, suggested that conversion rate is relatively invariant with position, and that’s actually somewhat contrary to Google’s best interest — they’d benefit from saying higher positions on the page convert better. Still, the new visibility means we can and should take another look.

Placement

For ads that are primarily in position 1, what fraction of the clicks come from impressions when the ad is on top of the organic listings versus on the side?

Keyword 3 on broad match had 114 of its 140 clicks placed when the ad was on top of the organic listings. The same keyword on exact match saw all 112 of its clicks on top of the organic listings.

This seems to be the trend. There is somewhat less variance in both position and placement when the ad is on exact match than when it’s on broad match. That makes sense, as the competitive landscape is likely different for every broad match variant.

It’s worth pointing out that we don’t get a perfect view of the page layout from this. We don’t know whether 1s3 means the ad was third from the top on the right, or at the top of the right column with 2 ads served over the organic listings, or whether it was below Product Listing Ads. Nevertheless it gives us much more information at the click level than we’ve had before.

SO WHAT?

Well, that’s a hard question in this case. What are we going to do with this data? I don’t know…yet. Perhaps it will shed light on how national ads compete in various local markets? We may be able to see using geographic overlay data that clicks from certain locales are coming from significantly lower on the page than the national average, indicating stiff competition from local brick and mortar stores. That might suggest creating a geo-targeted campaign for that region with separate bid logic and copy to provide a competitive edge.

That’s just one idea. The point is that every time Google has given us greater visibility and greater flexibility the leaders in the industry have been able to figure out ways to raise the performance bar.

I expect this to be another opportunity for differentiation.

Comments
14 Responses to “New Insights Into the Google Auction”
  1. Michael says:

    It’s amazing that, pretty much no matter what the reported average position is, such a high majority of clicks come in position 1 and 2. It almost makes me wish for AdWords’ position targeting again – why waste tons of impressions that come in positions 3 and below? In many cases, the few clicks you get in those positions may not be worth the negative impact on Quality Score because of a much lower CTR.

    I look forward to being able to see the data from this new parameter. Thanks for the post!

  2. Mike Stewart says:

    Just as we predicted… best performing sports are the top ones and although the lower positions are cheaper, the lack of volume in the lower positions is why good ppc management is crucial. Thank you for sharing.

  3. Barry says:

    So how do we turn adpos on?
    You say: “by flipping a switch in your adwords account”… but you don’t say where ot find it, and I don’t see a checkbox anywhere… Do we have to add parameters manually to each ad we want to track?

  4. Michael and Mike, thanks for your comments. I wouldn’t jump to too many conclusions based on this preliminary data. I looked at a few ads from one client over two days. It also isn’t clear to me how much of this variance is being produced by our own day-parting efforts. Bidding more during the highest converting periods of the day and less at others may exaggerate the effect for us more than most folks would see.

    Barry, it’s a fine point! I’ve gotten far enough from the trenches that I don’t know where the switches are myself. I’ll ask Matt!

  5. Matthew Mierzejewski Matthew says:

    Barry,

    There isn’t a “switch” to turn this on in the interface, and you’re correct in assuming that you have to add the parameters manually to all URLs. For most, the easiest way to do this is through a nifty AdWords Editor feature called Advanced URL Changes that makes this as easy as a flipping the switch.

    On the Keywords or Ads tab of AdWords Editor, look to the bottom-center of the window for “Advanced URL Changes”. After selecting it, check the second option “Append this text to each URL:”. Here, you’ll easily be able to add Google’s {adposition} valuetrack parameter as defined on these two Google pages to all of your URLs

    http://adwords.blogspot.com/2011/08/tracking-your-ad-position-with.html
    http://adwords.google.com/support/aw/bin/answer.py?hl=en&answer=178482

    Michael,

    Don’t worry about the impressions received in various ad position having differences in CTR as an impact on QS. Google normalizes QS based on ad position, and accounts for / expects CTR figures to be lower for lower ad positions.

    For more details about this notion, check out Slide 3 of this fantastic presentation given by Frederick Vallaeys @ Google – https://docs.google.com/present/view?id=dgccfxwp_1061fd6x32hn&pli=1

  6. Ron Clabo says:

    George,

    Thanks for sharing this info about ad position. I hadn’t realized that it was possible to get the ad position to show up in the referring url.

    Great post!

    -Ron

  7. Very cool, Ron. Let us know if you find anything interesting!

    George

  8. Hey George,

    Killer post. Have you had any success applying this in combination with Omniture or Channel Advisor appendages? Any hiccups to be concerned with?

  9. Jeff Crist says:

    I’m wondering what is accounting for such a large spread of positions for a given keyword? For a keyword to span between position 1 and all the way down to 9 there has to be some significant and frequent changes happening in the auction. Most CPC bidders (not all) are not going to be changing their CPC frequently. So my best guess is either you or several of your PPC competitors for the same keywords are using automated bid management software that is changing your bidding frequently, are day-parting, or are letting Google change the bid via CPA bid or conversion-optimizer turned on. Still, a range of 1-9 is quite wide. We don’t use CPA because you are telling Google to essentially up your bids to the maximum you can afford when there is better ‘value’ positions if you do your own CPA analysis a different positions and adjust bids as necessary. But we’ve never seen our ads vary by more than 3 positions in the short term when we are not changing bid values and we bid on some fairly competitive keywords which says our competitors bids are fairly static also. So the wide 1-9 impression position range you are inferring on your graphs is quite puzzling.

  10. JP, the additional parameters don’t interfere with other tracking parameters, so no issues.

    Jeff,

    Thanks for your observations. As I mentioned in the post, our dayparting efforts could absolutely be responsible for the degree of spread we saw here. Taking advantage of measured traffic quality variations dynamically is a wise practice but does make these assessments more difficult. I also mentioned that we could be seeing a syndication effect, where an ad in position 3 most of the time on Google.com might be in position 6 on a syndication partner, if that partner has its own ads served over the Adwords listings.

    Mark Ballard will likely do a more comprehensive study down the road looking at a bit more data than I had at the time this was written.

    Thanks for your comment!

  11. Scott says:

    Would be very interesting to pull the CTR and CPC of the ad at each position, then tie those clicks to conversions to shed some insight on over all ad-copy performance by position. Also, would be interesting to tie those metrics with website behavior. (i.e. does this keyword, with this ad, at the number 1 position produce “happy clickers” who browse more then purchase). In theory, you could optimize ads that focus on specific things (leads, conversions, ect) then set budgets and projections accordingly.

    I wonder how much keyword momentum effects position. If a keyword just started out of the gate with zero history, how would ad position vary from the same ad for the same keyword that has history?

    What about time of day? Or Demographics?

    If an ad performed better by a particular gender by position, then maybe it would be worth targeting that gender to build CTR and QS.

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