I've previously explained how return on ad spend (ROAS) can help indicate how a digital ad campaign contributes to sales. But you will need more than ROAS if you are deciding which other campaigns deserve further investment. Otherwise, you can be shooting blind on what campaigns to improve.
Well, the "more-than-that" metric you need is called a quality score. A quality score is a rating index that reflects how well the digital media for your campaign is being received. Reviewing it alongside ROAS can provide a quick picture of a digital ad group or campaign performance, helping you see where improvements are needed.
How a Quality Score Impacts How You Maintain Your Campaign Strategy
A quality score indexes the likelihood you can improve the digital media for your campaign. An ad with a low-quality score can reflect potential room for improvement. An ad with a high-quality score is performing as best as it possibly can.
Just like ROAS, the quality score appears in the dashboard metrics of the ad managers in any given social media or digital ad platforms. All of the major digital ad platforms index quality score differently and can even use different labels, but the metrics usually contains the same influences: ad copy, its associated landing page, the algorithm that controls when the ad is seen. Google ads look at potential click through rate, landing page and an ad's relevance to the landing page. Twitter examines three factors: resonance (are people clicking?), relevance (does the ad content align with your audience’s interests?) and recency (when did the click occur relative to the ad campaign dates?). Facebook relies on conversion rate, engagement rate and the quality of the ad bidding compared with other ads competing for the same bid. In fact, Facebook identifies five categories for its quality score index.
The way the quality score works with the ROAS is to indicate two complementary aspects of a digital ad campaign. ROAS is meant to answer budgetary concerns, while quality score indicates the bidding performance of an ad on a given referral source — a social media platform or online search via a search engine query. Combined, these two metrics can indicate which campaigns may not be worth your budget and which have the potential opportunity to be improved.
Related Article: How to Use Cohort Analysis in Google Analytics GA4
Where to Incorporate Quality Score in Your Analysis Workflow
If you managing a multitude of campaigns, quality scores can be a good starting point to simplify your workflow decisions on which campaign to improve. To do this analysis, you export ad campaign data into a spreadsheet or table, just like you would for ROAS (I explained how to set up a sheet in the ROAS post).
When you audit the campaigns according to quality score, you have choices on what to highlight. You can sort campaigns according to score, from highest to lowest, to get a sense of the range of scores your campaigns have produced.
A really great workflow tactic is to insert a conditional statement that highlights a table cell when the quality score is below a threshold value. Doing this helps save you time by quickly identifying which campaigns need work. In Excel you would navigate to the conditional format button to add the greater than/less than values. Google Sheets you can access conditional formatting under the Format drop-down menu. Google Data Studio provides a similar conditional formatting feature in its table template.
So far marketers do not agree on one universal threshold value. There are some value averages by specific industry, and some platform-related recommendations — Google considers 80 a good minimum quality score. You can set a value at 60% of a scale as a starting point. Anything below that point is a candidate for improvement. So for your conditional statement settings, set a less-than value to help track the campaigns that need attention.
The chart above shows the quality score of a few shoe campaigns. The ones in red are below a threshold score of 80. Thus these would be candidates for improvements.
Examining quality scores is especially helpful when two or more campaigns return similar ROAS or costs-per-click metrics. If one of these campaigns have a low quality score, it indicates the ad is not as relevant for social media or search queries. Comparing quality score when the ad performance metrics are similar will help you focus on the ad that can be updated by altering the text or evaluating with an A/B test.
Monitoring quality score can be a terrific way to manage marketer workflow when it comes to digital ad campaigns. When you understand the scores, you will get a better view of how to approach your ad campaign spend and see results from your strategy.