Google is again modifying both the calculation and impact of their ‘Quality Score’ metric. As with most Google changes, the stated goal is improving search quality and user experience. The coincidental result is that Google will make more money.
There are two changes this time:
- Quality score will now be ‘position adjusted’ to take into account the location of the text-ad when the click-through occurs. This makes it ‘more accurate’. Makes me wonder why this didn’t happen a long time ago. This increases the value of extensive text-ad testing.
- Quality score can now cause an ad to move above another ad it would normally rank below IF this jump pushes the ad to the top of the page (rather than the right edge). (That’s a bad quick summary, read the Google announce for the details.)
Beyond these details what strikes me is how important quality score has become to paid search management and results.
Quality score drives bid requirements, quality score drives ad position, quality score drives impression share, and now quality score drives the chance to leapfrog your way to the top center of search result pages.
What Do We Know About Quality Score?
Although quality score plays a central role in how your money is spent and made in Google Adwords, it is officially a ‘secret formula’.
Like PageRank on the SEO side, Google makes only vague pronouncements while pundits and practitioners share theories and recommendation endlessly – but nobody can tell you definitively how to maximize your quality score.
It still isn’t even that easy to see your quality score, although it is getting easier. Google recently changed the way they display quality score – giving it an integer value – but it’s still under a ‘work for it’ pop-up in the Adwords interface. On the positive front, they have finally added quality score to the API (thank you!) so third-party tools can begin to make use of it.
But also like PageRank the scores tend to clump around certain values, and the distinctions between close numbers aren’t obvious.
Also, and this is just a hunch, I’d bet nearly anything Google doesn’t maintain or use the number as an integer. So two keywords from two different bidders that both show a QS of ’7′ might in fact be one with a 7.0001 and another with a 7.9998.
- Google has an awesome business. They sell a product with secret specifications which are subject to change, and charge whatever they want without even telling anyone why or how. Nobody but the Mafia selling protection services to local merchants ever got away with this before.
- Advertisers have to really play the ‘chase the quality score ghost’ game. Obsess about CTR’s and align as many of the other known factors as possible. Live with the fact that you’ll waste time trying to please the QS algorithm because there’s no published list for how to get into quality-score-heaven.
- Advertisers should continue to clammor for more openness from Google as to what counts, how much, when, and how we’re charged accordingly. Neither #1 or #2 should be true.
- I need to spend a lot more time thinking and writing about Quality Score. It’s a big deal.
One thought I wasn’t able to put in the last post about missing and misleading click data, was about keyword click-through-rates.
Do keywords really have click-through-rates?
Objectively they do because the engines report them. But does that make sense?
If A Keyword Falls In The Forest, And The User Doesn’t See It…
The user doesn’t even know the keyword exists. The user typed a query (which in some small percentage of searches was exactly matched to the keyword, but far more often was only related to the keyword) and was shown (if they even saw it) a text-ad (containing some specific copy) in some position on the page in relation to a number of other text-ads (not to mention the organic search results.)
What portion of the influence in that click, or lack thereof, did the keyword have?
- We know different text-ad copy produces different CTRs.
- We know different positions result in different CTRs.
- We know that the presence or absence of specific competitive adds produce different CTRs.
- We know different queries that may match to the same keyword in broad or phrase match type have different CTRs.
- We can assume that CTRs vary by time and the geography of the user.
- There must be a couple of other factors I’m not thinking of right now… (comments?)
So does the keyword really have a CTR, or do the combinations really have CTRs? Clearly the Keyword CTR is the average of a range of different situations and conditions.
The Average Average is Only So-So
There are a lot of averages presented in search analytics. That’s necessary as we can’t handle all the granules, but close attention must be paid to the composition of these averages, lest they be less than clear or useful.
If the campaign is reasonably constructed in terms of organization and match type application, and are being reasonably run (meaning the text-ads and bids have both logic and dilligence being regularly applied to them), then the average CTR as reported for keywords can be useful. If any of these elements are missing, the utility dwindles rapidly.
As with most averages in PPC reports, if you aren’t sure dive down and look at the components – the more performance diversity you find inside the less weight you should place on the average.
Know Your Metrics
Just another example of the fact that even the simple metrics of paid search have more to or behind them than you might realize, and how some understanding and healthy skepticism can help you get closer to truly understanding what’s happening in your campaigns.
(Credit where it’s due: The idea of questioning KW CTRs, and many other ideas you’ll find in this blog from time to time, was first suggested by Bruce Ernst)
(Upcoming Events: I’ll be at the Semphonic XChange Conference in San Francisco on Aug 17-19, and am Speaking on “Identify, Analyze, Act: SEM by the Numbers” at Search Engine Strategies in San Jose on August 19th)
Paid Search Managers spend a lot of time analyzing clicks.
Which keywords got them? Did they convert? How much did they cost?
But how much time is spent thinking about the clicks you didn’t get? How much information do you have about those clicks anyway?
Earlier in this series I’ve discussed the idea that paid search marketers have a tough time getting a full and clear picture of what’s really going on in their accounts with the information currently provided by the engines, analytics programs, and PPC tools.
The last few posts discussed the lack of search query details as one example. Gaining insight into missing clicks is another.
Two Ways To Lose
There are two types of clicks you didn’t get. The first are those reflected in your click-through-rate; clicks that didn’t happen when your ad was shown. The count of these can be easily seen by comparing your impression count with the click count for any keyword.
The second type of missed click are those where the query was relevant (or interesting) to you but your ad wasn’t displayed. As Steve Forbert once said: (although I don’t think he was the first) you cannot win if you do not play.
Tracking Missed Impressions
Google has provided a series of Impression Share Metrics for over a year now, which provide important insights into the click missed because ad weren’t even displayed.
- Impression Share (IS): The percentage of times your ads were shown out of the total available impressions in the market you were targeting. This metric is available at the campaign and account level for search.
- Impression Share Exact Match. Impression Share Exact Match reports the impression share of your campaigns as if your keywords were set to ExactMatch.
- Lost IS. Your impression share + Lost IS (Budget) + Lost IS (Rank) = 100%.
- Lost IS (Rank): The percentage of impressions lost due to low Ad Rank (cost-per-click bid x Quality Score).
- Lost IS (Budget): The percentage of impressions lost due to budget constraints.
These are informative and critical reports. You should always know the IS numbers for your campaigns. There are times you can accept a low Impression Share, and times when you cannot.
It’s too bad it takes a trip into the reporting environment (or setting up an email report) to get them rather than having them ‘in line’ with other reporting metrics.
More importantly, this data is only available at the Campaign level, and we could really use it at the Ad-Group level. When you have a large campaign with many Ad-Groups is very possible that some have great Impression Share and a few have lousy Impression Share (or that the reasons why the number is what it is differ between Ad-Groups) and the Campaign-level roll up is of limited use.
In a future post we’ll dig deeper into the meaning and applications of these numbers.
Tracking Missed Clicks
There is less information, ironically, delivered about the clicks you miss when your ads do appear.
There are many reasons people don’t click (see this post for a good list). Many could not be translated into paid search metrics without qualitative research. But there more information that could be shared about these lost clicks.
For example, average click-through rates and various positions are known, both in absolute and relative terms. Given your position of your ads, how many more or less clicks occurred than should have been expected at that position?
And exactly how many clicks would each higher position garner, or lower position lose? This could be predicted with some degree of accuracy.
Since text-ads have their own click-through-rates, which have a massive effect on the CTR’s of keywords, another option is to look at which text-ads were displayed and calculate the number of clicks a keyword would have received if the best of them (CTR-wise) had run all the time.
So with a little work doing some calculations around the position and text-ad running for a keyword, we could start to know what our potential keyword CTR could be, if we just improved our position performance and text-ad copy.
Not Perfectly Clear
Paid search is the pursuit of clicks. The right clicks at the right price.
A clear picture of a paid search campaign would therefore tell us a lot about the clicks we got, and the clicks we didn’t get. Google’s Impression Share is a great start – it delivers actionable information and with the sub-metrics starts to break the main one apart so we can see how different factors are contributing to the remaining click opportunity.
Impression share needs to go mainstream – into the normal dynamic Adwords reports and the API.
And a comparable level of visibility should be given to the clicks we get and don’t get once our ad has been displayed.
- How much better could our CTR have been?
- How many clicks were missed because we under-performed our position?
- How many more were available at higher positions?
- How many were missed because text-ads were under-performing? (Within the text-ad itself, was it the headline or target URL that dragged us down?).
- Was there a specific competitor who took more share from us than another, over time?
These are just some of the things we should be able to know about our clicks.