Impression Weighted Quality Score

Quality score is a pretty important metric if you’re trying to get the best efficiency from your Google Ads campaign. Google does give us quite a bit of data in the user interface about quality score and it’s inputs. One pain point for some is that Google Ads does not aggregate quality score at the account, campaign or ad group level. This can make understanding how large changes to an account impacted quality score more difficult. To solve this, I like to do a little spreadsheet gymnastics and generate impression weighted quality score.

Get The Data

I made up a metric and my math process seems to work. Impression weighted quality score is intented to measure the overall quality score for an ad group, campaign or account. To generate the data point at any of those levels you simply need to export a keyword report for the date range you’re interested in and include the columns for impressions, quality score and quality score (hist.) (if analyzing old data).

Pivot Table

Insert a pivot table and select your data. (MS Office or Google Sheets) I like to copy the data to a second tab and delete the top two rows so I can select the data with whole columns. In any case, once you’ve got the pivot table set Quality Score (or QS(hist) whatever you’re analyzing) as the rows. Set Sum of Impressions to the rows.

Calculate % of Impressions (Weight) & Quality Score x Weight Columns

The next two steps can be done by copying the data to a new area of the workbook (I like copy as plain text) then calculating in cells or by creating calculated fields in the pivot table. In any case, to find the weight of each quality score, divide the number of impressions for that quality score by the total number of impressions. Then multiply the % of Impressions (weight) column by the QS column.

Last Step

Finally, simply find the sum of all the values in the Quality Score x Weight column. Now you have your impression weighted quality score.


I find this useful for analyzing keyword quality score performance. You can calculate this metric for any segment of your campaign that you want to by simply filtering the data that you initially download. You can also analyze all of the keywords in your account, which is useful when measuring the impact of large account changes on quality score. So that’s what I use it for. If you find this useful, or come up with a different way to use weighted average to help you understand your Google Ads account, let me know in the comments. Happy pay per clicking!

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