According to this data, every 10% increase in wasted budget leads to 44-72% higher cost per conversion.
But how accurate is this model? A little log level regression Australia Physiotherapist Email Lists uncovers that wasted ad spend accounts for about 60% of cost per conversion (R2 = 0.597).
It’s not a perfect model either, but it’s a big enough piece of the pie to be worth your consideration.
Now, in saying that quality score is only 1% of the cost per conversion equation, I don’t mean to imply that it should be ignored entirely.
After all, if you’re wasting most of your budget on the wrong
clicks, spending more or less isn’t really going to affect your cost-per-conversion very much. So, if your account falls into this category, I’d focus on reducing wasted ad spend first.
However, once your accounts have been cleaned up and
you’re looking for additional ways to boost performance, there are a few ways you can use quality score to your advantage.
The first step is to add quality score to your keywords report like so:
Export your results into Excel, which will allow you to do some meaningful analysis on what the quality scores in your account are costing you.
To start analyzing, select all of the data in your new spreadsheet and create a pivot table.
If you set up your pivot table as seen below, you can tell how much you are spending on each quality score integer.
Just getting to this point may reveal some interesting things
about your account. In the case of this client, 12% of their budget was spent on ads with a quality score of 1 (vs. only 9% on those with a quality score of 8).
This doesn’t necessarily mean that these ads are unprofitable,
but their low quality score was costing the company money unnecessarily. If all of this company’s 1-scoring ads could be upgraded only to a score of 2, then it would have saved them over $22,000!
There could be a lot of these quality score 1 keywords and
ads to deal with though, so rather than giving them all attention, it would make more sense to find the top offenders and fix them first.
You can do this by setting up another pivot table to filter for
keywords with both a quality score of 1 and over $500 of cost.