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Posted: Sat Feb 01, 2025 4:48 am
So how does Google calculate this magical Quality Score? A simple plot of Quality Score versus CTR for hundreds of campaigns reveals a pretty strong relationship between the two. Quality Score Data Basically the higher your CTR the higher your Quality Score will be. However, there is still some noise due to variance. The reality is that click-through rates vary based on average position. Higher ad rankings are prone to higher click-through rates, while lower ad rankings are equally prone to lower click-through rates.
The same data looks like below when I consider different ad honduras whatsapp list positions Quality Score vs. Position Note that at constant CTR there is a negative relationship between average position and account Quality Score as the regression shifts upward as position increases. This makes sense - if the ad in position 3 has the same click-through rate as the ad in position 3, then the ad in position 3 may be more relevant and therefore get a higher CTR. As before, there is a logarithmic relationship between improvement and diminishing returns; there will be a greater improvement from improvement to than from improvement to or more.
The chart above shows that returns decrease more rapidly the higher the position. So increasing the click-through rate for the third-place ad from 100 to 100 will increase approx. while the same improvement for the 3rd-place ad will only increase approx. For the first four positions the main indicator is that the correlation between the two variables is approx. At lower positions and below this correlation decreases to approximately 100% which suggests that other issues such as landing page relevance or poor ad relevance may have a greater impact on its poorer relevance.
The same data looks like below when I consider different ad honduras whatsapp list positions Quality Score vs. Position Note that at constant CTR there is a negative relationship between average position and account Quality Score as the regression shifts upward as position increases. This makes sense - if the ad in position 3 has the same click-through rate as the ad in position 3, then the ad in position 3 may be more relevant and therefore get a higher CTR. As before, there is a logarithmic relationship between improvement and diminishing returns; there will be a greater improvement from improvement to than from improvement to or more.
The chart above shows that returns decrease more rapidly the higher the position. So increasing the click-through rate for the third-place ad from 100 to 100 will increase approx. while the same improvement for the 3rd-place ad will only increase approx. For the first four positions the main indicator is that the correlation between the two variables is approx. At lower positions and below this correlation decreases to approximately 100% which suggests that other issues such as landing page relevance or poor ad relevance may have a greater impact on its poorer relevance.