Skip to Content

The author

Steve Baker

Chief Analyst

Improving your click through rate improves your Quality Score. This you probably already know. But how high is a high click through rate? What is a decent click through rate for a given position? How do you know if your Quality Score is being dragged down by the Account Quality Score or your adverts?

Improving your click through rate improves your Quality Score. This you probably already know. But how high is a high click through rate? What is a decent click through rate for a given position? How do you know if your Quality Score is being dragged down by the Account Quality Score or your adverts?

These are questions that everyone that manages an Adwords account has asked at some point. So I decided to find out. As a large agency, we are in the position of having far more data to analyse than most people, and by manipulating this data, we’ve found some very clear and consistent trends, that have given us unique insights into what click through rate Google are looking for in order to consider you ‘relevant’, and how they take your position into account. So here’s what I did. I pulled out the data for the last 30 days for every keyword, in every Ad Group, in every campaign, in every account that we manage. I stripped out any Phrase and Broad Match keywords (since QS is calculated on Exact Match), Google’s Search Partners data (since this is ignored in the calculation) and brand terms (which would skew the click through rate analysis significantly – more about this later). I then looked at the average click through rate in each position from 1 – 8 (in increments of 0.1), for each keyword Quality Score. By graphing the results, it wasn’t hard to detect a pattern. Here’s the CTR’s by position for keywords with a QS of 10: Note that I took the total impressions and clicks for each position, effectively weighting the CTR for each keyword by the number of impressions, so that low volume keywords didn’t have an exaggerated impact on the performance. You can also see why I removed brand names from the above analysis – the position 1 CTR would have been influenced excessively… From the above graph, it’s possible to get some sense of what click through rate Google expects from a keyword in order to give it a QS of 10. And by fitting a curve through the data, it’s possible to get a reasonable indication of where you should be in order to pick up a Quality Score of 10: Based on this line, it appears that Google expect the click through rate in any position to be about 65% of the next position up. So where position 1.0 has an average click through rate of 34%, position 2 has an average click through rate of 22.1%. Whilst this line fits nicely through this data, what happens if you look at other Quality Scores? Will Google expect a similar drop-off in click through rate? If not, then this number is just a convenient fit for this data. Here’s the graph for Quality Scores of 9: And 7: And 6: The same decay of 0.65 has been drawn on each, and in all cases, it appears to fit well. So this appears to be Google’s estimate of what ‘should’ happen to your click through rate every time you drop a position – you lose just over 1/3 of your clicks. Of course, this doesn’t really work once you drop below about 8th, but it’s certainly a useful thing to know. Indeed, the line fits just as well with a Quality Score of 5, 4 or 3 as well. Based on these fitted lines, you can estimate the following average click through rates by position, and how they are converted into Quality Scores: Using this, you can potentially ‘health check’ your account. If you have a click through rate of 4.5% in position 4, you should have a Quality Score of around 7 or so. If you are getting less than the predicted Quality Score across the bulk of your keywords (excluding brand, on Google only, on Exact Match), then it’s a sign that your account has other issues, possibly with the landing page, keyword relevance or the overall account quality. I tried to take this analysis to the next level, by calculating the predicted Quality Score for each keyword, based on its click through rate and average position. Unfortunately, whilst the fits are very good looking at large amounts of data, on a keyword-by-keyword basis, the results can be quite inaccurate, underlining the fact that advert relevance, landing page relevance and account quality also have a significant bearing. One final point worth noting is that the overall figures for the Quality Score of 7 are a little misleading. Most keywords seem to be given a Quality Score of 7 initially, until Google calculates a value based on their performance. Because far more of our keywords get Quality Scores higher than 7 than get less than 7, the effect of new keywords on the ‘7’ performance is pushing up the click through rate significantly. Realistically, none of this has any bearing on the way that you manage your account. Regardless of your click through rate, you should always be looking to improve it (though obviously not to the detriment of your conversion rate), and the Quality Scores that Google quotes in the data are only indicative – the true Quality Score figure is probably much more precise, and keywords that appear to have the same Quality Score could actually have quite different values (6.6 and 7.4 could both round to 7). But in terms of offering insight into what may happen to your traffic volumes if your position were to change, it’s very interesting. If one of the advertisers above you were to drop out, you could potentially be looking at a 50% uplift in clicks. If you’ve got a restrictive budget, this could cause problems. Similarly, a new competitor appearing above you could cost you 1/3 of your clicks…